Matthew D. Wilkerson

The Cancer Genome Atlas Network recently cataloged recurrent genomic abnormalities in glioblastoma multiforme (GBM). We describe a robust gene expression-based molecular classification of GBM into Proneural, Neural, Classical, and Mesenchymal subtypes and integrate multidimensional genomic data to establish patterns of somatic mutations and DNA copy number. Aberrations and gene expression of EGFR, NF1, and PDGFRA/IDH1 each define the Classical, Mesenchymal, and Proneural subtypes, respectively. Gene signatures of normal brain cell types show a strong relationship between subtypes and different neural lineages. Additionally, response to aggressive therapy differs by subtype, with the greatest benefit in the Classical subtype and no benefit in the Proneural subtype. We provide a framework that unifies transcriptomic and genomic dimensions for GBM molecular stratification with important implications for future studies.

Abstract Summary: Unsupervised class discovery is a highly useful technique in cancer research, where intrinsic groups sharing biological characteristics may exist but are unknown. The consensus clustering (CC) method provides quantitative and visual stability evidence for estimating the number of unsupervised classes in a dataset. ConsensusClusterPlus implements the CC method in R and extends it with new functionality and visualizations including item tracking, item-consensus and cluster-consensus plots. These new features provide users with detailed information that enable more specific decisions in unsupervised class discovery. Availability: ConsensusClusterPlus is open source software, written in R, under GPL-2, and available through the Bioconductor project (http://www.bioconductor.org/). Contact: mwilkers@med.unc.edu Supplementary Information: Supplementary data are available at Bioinformatics online.

Liver cancer has the second highest worldwide cancer mortality rate and has limited therapeutic options. We analyzed 363 hepatocellular carcinoma (HCC) cases by whole-exome sequencing and DNA copy number analyses, and we analyzed 196 HCC cases by DNA methylation, RNA, miRNA, and proteomic expression also. DNA sequencing and mutation analysis identified significantly mutated genes, including LZTR1, EEF1A1, SF3B1, and SMARCA4. Significant alterations by mutation or downregulation by hypermethylation in genes likely to result in HCC metabolic reprogramming (ALB, APOB, and CPS1) were observed. Integrative molecular HCC subtyping incorporating unsupervised clustering of five data platforms identified three subtypes, one of which was associated with poorer prognosis in three HCC cohorts. Integrated analyses enabled development of a p53 target gene expression signature correlating with poor survival. Potential therapeutic targets for which inhibitors exist include WNT signaling, MDM4, MET, VEGFA, MCL1, IDH1, TERT, and immune checkpoint proteins CTLA-4, PD-1, and PD-L1.

Invasive lobular carcinoma (ILC) is the second most prevalent histologic subtype of invasive breast cancer. Here, we comprehensively profiled 817 breast tumors, including 127 ILC, 490 ductal (IDC), and 88 mixed IDC/ILC. Besides E-cadherin loss, the best known ILC genetic hallmark, we identified mutations targeting PTEN, TBX3, and FOXA1 as ILC enriched features. PTEN loss associated with increased AKT phosphorylation, which was highest in ILC among all breast cancer subtypes. Spatially clustered FOXA1 mutations correlated with increased FOXA1 expression and activity. Conversely, GATA3 mutations and high expression characterized luminal A IDC, suggesting differential modulation of ER activity in ILC and IDC. Proliferation and immune-related signatures determined three ILC transcriptional subtypes associated with survival differences. Mixed IDC/ILC cases were molecularly classified as ILC-like and IDC-like revealing no true hybrid features. This multidimensional molecular atlas sheds new light on the genetic bases of ILC and provides potential clinical options.

Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. Here we describe quantitative mass-spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers, of which 77 provided high-quality data. Integrated analyses provided insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. Interrogation of the 5q trans-effects against the Library of Integrated Network-based Cellular Signatures, connected loss of CETN3 and SKP1 to elevated expression of epidermal growth factor receptor (EGFR), and SKP1 loss also to increased SRC tyrosine kinase. Global proteomic data confirmed a stromal-enriched group of proteins in addition to basal and luminal clusters, and pathway analysis of the phosphoproteome identified a G-protein-coupled receptor cluster that was not readily identified at the mRNA level. In addition to ERBB2, other amplicon-associated highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. We demonstrate that proteogenomic analysis of breast cancer elucidates the functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.

Abstract The success in lung cancer therapy with programmed death (PD)-1 blockade suggests that immune escape mechanisms contribute to lung tumor pathogenesis. We identified a correlation between EGF receptor (EGFR) pathway activation and a signature of immunosuppression manifested by upregulation of PD-1, PD-L1, CTL antigen-4 (CTLA-4), and multiple tumor-promoting inflammatory cytokines. We observed decreased CTLs and increased markers of T-cell exhaustion in mouse models of EGFR-driven lung cancer. PD-1 antibody blockade improved the survival of mice with EGFR-driven adenocarcinomas by enhancing effector T-cell function and lowering the levels of tumor-promoting cytokines. Expression of mutant EGFR in bronchial epithelial cells induced PD-L1, and PD-L1 expression was reduced by EGFR inhibitors in non–small cell lung cancer cell lines with activated EGFR. These data suggest that oncogenic EGFR signaling remodels the tumor microenvironment to trigger immune escape and mechanistically link treatment response to PD-1 inhibition. Significance: We show that autochthonous EGFR-driven lung tumors inhibit antitumor immunity by activating the PD-1/PD-L1 pathway to suppress T-cell function and increase levels of proinflammatory cytokines. These findings indicate that EGFR functions as an oncogene through non–cell-autonomous mechanisms and raise the possibility that other oncogenes may drive immune escape. Cancer Discov; 3(12); 1355–63. ©2013 AACR. See related commentary by Rech and Vonderheide, p. 1330 This article is highlighted in the In This Issue feature, p. 1317

In parallel with an ongoing human clinical trial, genetically engineered mouse models of lung cancer with different genetic alterations are treated with chemotherapeutic agents; the results have implications for the clinical trial. The idea of 'co-clinical' trials has been put forward as way of evaluating novel therapies. By testing a drug simultaneously in human clinical and mouse preclinical trials, the thinking is, the two sets of data can be combined to extract extra information. To demonstrate the potential of this approach, genetically engineered mouse models were used to mirror a randomized phase II clinical trial of the chemotherapeutic docetaxel in KRAS-driven lung cancer, comparing its action alone with that in combination with a MEK inhibitor. In the mouse model, tumours with Kras or Kras and p53 mutations were more responsive to the combination than to docetaxel alone, whereas mice carrying a deletion of Lkb1 in addition to activated Kras remained relatively unresponsive. This has important implications for the ongoing clinical trial, suggesting that patients should be tested for LKB1 mutations. Targeted therapies have demonstrated efficacy against specific subsets of molecularly defined cancers1,2,3,4. Although most patients with lung cancer are stratified according to a single oncogenic driver, cancers harbouring identical activating genetic mutations show large variations in their responses to the same targeted therapy1,3. The biology underlying this heterogeneity is not well understood, and the impact of co-existing genetic mutations, especially the loss of tumour suppressors5,6,7,8,9, has not been fully explored. Here we use genetically engineered mouse models to conduct a ‘co-clinical’ trial that mirrors an ongoing human clinical trial in patients with KRAS-mutant lung cancers. This trial aims to determine if the MEK inhibitor selumetinib (AZD6244)10 increases the efficacy of docetaxel, a standard of care chemotherapy. Our studies demonstrate that concomitant loss of either p53 (also known as Tp53) or Lkb1 (also known as Stk11), two clinically relevant tumour suppressors6,9,11,12, markedly impaired the response of Kras-mutant cancers to docetaxel monotherapy. We observed that the addition of selumetinib provided substantial benefit for mice with lung cancer caused by Kras and Kras and p53 mutations, but mice with Kras and Lkb1 mutations had primary resistance to this combination therapy. Pharmacodynamic studies, including positron-emission tomography (PET) and computed tomography (CT), identified biological markers in mice and patients that provide a rationale for the differential efficacy of these therapies in the different genotypes. These co-clinical results identify predictive genetic biomarkers that should be validated by interrogating samples from patients enrolled on the concurrent clinical trial. These studies also highlight the rationale for synchronous co-clinical trials, not only to anticipate the results of ongoing human clinical trials, but also to generate clinically relevant hypotheses that can inform the analysis and design of human studies.

We studied 137 primary testicular germ cell tumors (TGCTs) using high-dimensional assays of genomic, epigenomic, transcriptomic, and proteomic features. These tumors exhibited high aneuploidy and a paucity of somatic mutations. Somatic mutation of only three genes achieved significance-KIT, KRAS, and NRAS-exclusively in samples with seminoma components. Integrated analyses identified distinct molecular patterns that characterized the major recognized histologic subtypes of TGCT: seminoma, embryonal carcinoma, yolk sac tumor, and teratoma. Striking differences in global DNA methylation and microRNA expression between histology subtypes highlight a likely role of epigenomic processes in determining histologic fates in TGCTs. We also identified a subset of pure seminomas defined by KIT mutations, increased immune infiltration, globally demethylated DNA, and decreased KRAS copy number. We report potential biomarkers for risk stratification, such as miRNA specifically expressed in teratoma, and others with molecular diagnostic potential, such as CpH (CpA/CpC/CpT) methylation identifying embryonal carcinomas.

Significance A significant proportion of head and neck cancer is driven by human papillomavirus (HPV) infection, and the expression of viral oncogenes is involved in the development of these tumors. However, the role of HPV integration in primary tumors beyond increasing the expression of viral oncoproteins is not understood. Here, we describe how HPV integration impacts the host genome by amplification of oncogenes and disruption of tumor suppressors as well as driving inter- and intrachromosomal rearrangements. Tumors that do and do not have HPV integrants display distinct gene expression profiles and DNA methylation patterns, which further support the view that the mechanisms by which tumors with integrated and nonintegrated HPV arise are distinct.

Head and neck squamous cell carcinoma (HNSCC) is a frequently fatal heterogeneous disease. Beyond the role of human papilloma virus (HPV), no validated molecular characterization of the disease has been established. Using an integrated genomic analysis and validation methodology we confirm four molecular classes of HNSCC (basal, mesenchymal, atypical, and classical) consistent with signatures established for squamous carcinoma of the lung, including deregulation of the KEAP1/NFE2L2 oxidative stress pathway, differential utilization of the lineage markers SOX2 and TP63, and preference for the oncogenes PIK3CA and EGFR. For potential clinical use the signatures are complimentary to classification by HPV infection status as well as the putative high risk marker CCND1 copy number gain. A molecular etiology for the subtypes is suggested by statistically significant chromosomal gains and losses and differential cell of origin expression patterns. Model systems representative of each of the four subtypes are also presented.

Ovarian clear-cell carcinoma (OCCC) is an aggressive form of ovarian cancer with high ARID1A mutation rates. Here we present a mutant mouse model of OCCC. We find that ARID1A inactivation is not sufficient for tumour formation, but requires concurrent activation of the phosphoinositide 3-kinase catalytic subunit, PIK3CA. Remarkably, the mice develop highly penetrant tumours with OCCC-like histopathology, culminating in haemorrhagic ascites and a median survival period of 7.5 weeks. Therapeutic treatment with the pan-PI3K inhibitor, BKM120, prolongs mouse survival by inhibiting the tumour cell growth. Cross-species gene expression comparisons support a role for IL-6 inflammatory cytokine signalling in OCCC pathogenesis. We further show that ARID1A and PIK3CA mutations cooperate to promote tumour growth through sustained IL-6 overproduction. Our findings establish an epistatic relationship between SWI/SNF chromatin remodelling and PI3K pathway mutations in OCCC and demonstrate that these pathways converge on pro-tumorigenic cytokine signalling. We propose that ARID1A protects against inflammation-driven tumorigenesis. ARID1A is frequently mutated in ovarian clear-cell carcinoma. Here the authors show that ARID1A loss in mice cooperates with PI3K activation to recapitulate the human disease, and implicate IL-6 signalling as the underlying mechanism.

Abstract Pulmonary large-cell neuroendocrine carcinomas (LCNECs) have similarities with other lung cancers, but their precise relationship has remained unclear. Here we perform a comprehensive genomic ( n = 60) and transcriptomic ( n = 69) analysis of 75 LCNECs and identify two molecular subgroups: “type I LCNECs” with bi-allelic TP53 and STK11 / KEAP1 alterations (37%), and “type II LCNECs” enriched for bi-allelic inactivation of TP53 and RB1 (42%). Despite sharing genomic alterations with adenocarcinomas and squamous cell carcinomas, no transcriptional relationship was found; instead LCNECs form distinct transcriptional subgroups with closest similarity to SCLC. While type I LCNECs and SCLCs exhibit a neuroendocrine profile with ASCL1 high / DLL3 high / NOTCH low , type II LCNECs bear TP53 and RB1 alterations and differ from most SCLC tumors with reduced neuroendocrine markers, a pattern of ASCL1 low / DLL3 low / NOTCH high , and an upregulation of immune-related pathways. In conclusion, LCNECs comprise two molecularly defined subgroups, and distinguishing them from SCLC may allow stratified targeted treatment of high-grade neuroendocrine lung tumors.

Lung squamous cell carcinoma (SCC) is clinically and genetically heterogeneous, and current diagnostic practices do not adequately substratify this heterogeneity. A robust, biologically based SCC subclassification may describe this variability and lead to more precise patient prognosis and management. We sought to determine if SCC mRNA expression subtypes exist, are reproducible across multiple patient cohorts, and are clinically relevant.Subtypes were detected by unsupervised consensus clustering in five published discovery cohorts of mRNA microarrays, totaling 382 SCC patients. An independent validation cohort of 56 SCC patients was collected and assayed by microarrays. A nearest-centroid subtype predictor was built using discovery cohorts. Validation cohort subtypes were predicted and evaluated for confirmation. Subtype survival outcome, clinical covariates, and biological processes were compared by statistical and bioinformatic methods.Four lung SCC mRNA expression subtypes, named primitive, classical, secretory, and basal, were detected and independently validated (P < 0.001). The primitive subtype had the worst survival outcome (P < 0.05) and is an independent predictor of survival (P < 0.05). Tumor differentiation and patient sex were associated with subtype. The expression profiles of the subtypes contained distinct biological processes (primitive: proliferation; classical: xenobiotic metabolism; secretory: immune response; basal: cell adhesion) and suggested distinct pharmacologic interventions. Comparison with lung model systems revealed distinct subtype to cell type correspondence.Lung SCC consists of four mRNA expression subtypes that have different survival outcomes, patient populations, and biological processes. The subtypes stratify patients for more precise prognosis and targeted research.

Background Lung adenocarcinoma (LAD) has extreme genetic variation among patients, which is currently not well understood, limiting progress in therapy development and research. LAD intrinsic molecular subtypes are a validated stratification of naturally-occurring gene expression patterns and encompass different functional pathways and patient outcomes. Patients may have incurred different mutations and alterations that led to the different subtypes. We hypothesized that the LAD molecular subtypes co-occur with distinct mutations and alterations in patient tumors. Methodology/Principal Findings The LAD molecular subtypes (Bronchioid, Magnoid, and Squamoid) were tested for association with gene mutations and DNA copy number alterations using statistical methods and published cohorts (n = 504). A novel validation (n = 116) cohort was assayed and interrogated to confirm subtype-alteration associations. Gene mutation rates (EGFR, KRAS, STK11, TP53), chromosomal instability, regional copy number, and genomewide DNA methylation were significantly different among tumors of the molecular subtypes. Secondary analyses compared subtypes by integrated alterations and patient outcomes. Tumors having integrated alterations in the same gene associated with the subtypes, e.g. mutation, deletion and underexpression of STK11 with Magnoid, and mutation, amplification, and overexpression of EGFR with Bronchioid. The subtypes also associated with tumors having concurrent mutant genes, such as KRAS-STK11 with Magnoid. Patient overall survival, cisplatin plus vinorelbine therapy response and predicted gefitinib sensitivity were significantly different among the subtypes. Conclusions/ Significance The lung adenocarcinoma intrinsic molecular subtypes co-occur with grossly distinct genomic alterations and with patient therapy response. These results advance the understanding of lung adenocarcinoma etiology and nominate patient subgroups for future evaluation of treatment response.

The genetic basis of Lewy body dementia (LBD) is not well understood. Here, we performed whole-genome sequencing in large cohorts of LBD cases and neurologically healthy controls to study the genetic architecture of this understudied form of dementia, and to generate a resource for the scientific community. Genome-wide association analysis identified five independent risk loci, whereas genome-wide gene-aggregation tests implicated mutations in the gene GBA. Genetic risk scores demonstrate that LBD shares risk profiles and pathways with Alzheimer's disease and Parkinson's disease, providing a deeper molecular understanding of the complex genetic architecture of this age-related neurodegenerative condition.

Lung squamous cell carcinoma (SCC) is the second most prevalent type of lung cancer. Currently, no targeted therapeutics are approved for treatment of this cancer, largely because of a lack of systematic understanding of the molecular pathogenesis of the disease. To identify therapeutic targets and perform comparative analyses of lung SCC, we probed somatic genome alterations of lung SCC by using samples from Korean patients.We performed whole-exome sequencing of DNA from 104 lung SCC samples from Korean patients and matched normal DNA. In addition, copy-number analysis and transcriptome analysis were conducted for a subset of these samples. Clinical association with cancer-specific somatic alterations was investigated.This cancer cohort is characterized by a high mutational burden with an average of 261 somatic exonic mutations per tumor and a mutational spectrum showing a signature of exposure to cigarette smoke. Seven genes demonstrated statistical enrichment for mutation: TP53, RB1, PTEN, NFE2L2, KEAP1, MLL2, and PIK3CA). Comparative analysis between Korean and North American lung SCC samples demonstrated a similar spectrum of alterations in these two populations in contrast to the differences seen in lung adenocarcinoma. We also uncovered recurrent occurrence of therapeutically actionable FGFR3-TACC3 fusion in lung SCC.These findings provide new steps toward the identification of genomic target candidates for precision medicine in lung SCC, a disease with significant unmet medical needs.

Chemotherapy of a combination of DNA alkylating agents, procarbazine and lomustine (CCNU), and a microtubule poison, vincristine, offers a significant benefit to a subset of glioma patients. The benefit of this regimen, known as PCV, was recently linked to IDH mutation that occurs frequently in glioma and produces D-2-hydroxyglutarate (D-2-HG), a competitive inhibitor of α-ketoglutarate (α-KG). We report here that D-2-HG inhibits the α-KG-dependent alkB homolog (ALKBH) DNA repair enzymes. Cells expressing mutant IDH display reduced repair kinetics, accumulate more DNA damages, and are sensitized to alkylating agents. The observed sensitization to alkylating agents requires the catalytic activity of mutant IDH to produce D-2-HG and can be reversed by the deletion of mutant IDH allele or overexpression of ALKBH2 or AKLBH3. Our results suggest that impairment of DNA repair may contribute to tumorigenesis driven by IDH mutations and that alkylating agents may merit exploration for treating IDH-mutated cancer patients.

As the deficiencies of traditional password-based access systems become increasingly acute, researchers have turned their focus to keystroke biometrics, which seeks to identify individuals by their typing characteristics. However, this field still faces many challenges before it can see full acceptance.

PlantGDB (http://www.plantgdb.org/) is a genomics database encompassing sequence data for green plants (Viridiplantae). PlantGDB provides annotated transcript assemblies for >100 plant species, with transcripts mapped to their cognate genomic context where available, integrated with a variety of sequence analysis tools and web services. For 14 plant species with emerging or complete genome sequence, PlantGDB's genome browsers (xGDB) serve as a graphical interface for viewing, evaluating and annotating transcript and protein alignments to chromosome or bacterial artificial chromosome (BAC)-based genome assemblies. Annotation is facilitated by the integrated yrGATE module for community curation of gene models. Novel web services at PlantGDB include Tracembler, an iterative alignment tool that generates contigs from GenBank trace file data and BioExtract Server, a web-based server for executing custom sequence analysis workflows. PlantGDB also hosts a plant genomics research outreach portal (PGROP) that facilitates access to a large number of resources for research and training.

In mice, Lkb1 deletion and activation of Kras(G12D) results in lung tumors with a high penetrance of lymph node and distant metastases. We analyzed these primary and metastatic de novo lung cancers with integrated genomic and proteomic profiles, and have identified gene and phosphoprotein signatures associated with Lkb1 loss and progression to invasive and metastatic lung tumors. These studies revealed that SRC is activated in Lkb1-deficient primary and metastatic lung tumors, and that the combined inhibition of SRC, PI3K, and MEK1/2 resulted in synergistic tumor regression. These studies demonstrate that integrated genomic and proteomic analyses can be used to identify signaling pathways that may be targeted for treatment.

A comprehensive description of genomic alterations in lung squamous cell carcinoma (lung SCC) has recently been reported, enabling the identification of genomic events that contribute to the oncogenesis of this disease. In lung SCC, one of the most frequently altered receptor tyrosine kinase families is the fibroblast growth factor receptor (FGFR) family, with amplification or mutation observed in all four family members. Here, we describe the oncogenic nature of mutations observed in FGFR2 and FGFR3, each of which are observed in 3% of samples, for a mutation rate of 6% across both genes. Using cell culture and xenograft models, we show that several of these mutations drive cellular transformation. Transformation can be reversed by small-molecule FGFR inhibitors currently being developed for clinical use. We also show that mutations in the extracellular domains of FGFR2 lead to constitutive FGFR dimerization. In addition, we report a patient with an FGFR2-mutated oral SCC who responded to the multitargeted tyrosine kinase inhibitor pazopanib. These findings provide new insights into driving oncogenic events in a subset of lung squamous cancers, and recommend future clinical studies with FGFR inhibitors in patients with lung and head and neck SCC.

Abstract Motivation: Variant detection from next-generation sequencing (NGS) data is an increasingly vital aspect of disease diagnosis, treatment and research. Commonly used NGS-variant analysis tools generally rely on accurately mapped short reads to identify somatic variants and germ-line genotypes. Existing NGS read mappers have difficulty accurately mapping short reads containing complex variation (i.e. more than a single base change), thus making identification of such variants difficult or impossible. Insertions and deletions (indels) in particular have been an area of great difficulty. Indels are frequent and can have substantial impact on function, which makes their detection all the more imperative. Results: We present ABRA, an assembly-based realigner, which uses an efficient and flexible localized de novo assembly followed by global realignment to more accurately remap reads. This results in enhanced performance for indel detection as well as improved accuracy in variant allele frequency estimation. Availability and implementation: ABRA is implemented in a combination of Java and C/C++ and is freely available for download at https://github.com/mozack/abra . Contact: lmose@unc.edu ; parkerjs@email.unc.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Abstract SWI/SNF chromatin remodeling complexes regulate critical cellular processes, including cell-cycle control, programmed cell death, differentiation, genomic instability, and DNA repair. Inactivation of this class of chromatin remodeling complex has been associated with a variety of malignancies, including lung, ovarian, renal, liver, and pediatric cancers. In particular, approximately 10% of primary human lung non–small cell lung cancers (NSCLC) display attenuations in the BRG1 ATPase, a core factor in SWI/SNF complexes. To evaluate the role of BRG1 attenuation in NSCLC development, we examined the effect of BRG1 silencing in primary and established human NSCLC cells. BRG1 loss altered cellular morphology and increased tumorigenic potential. Gene expression analyses showed reduced expression of genes known to be associated with progression of human NSCLC. We demonstrated that BRG1 losses in NSCLC cells were associated with variations in chromatin structure, including differences in nucleosome positioning and occupancy surrounding transcriptional start sites of disease-relevant genes. Our results offer direct evidence that BRG1 attenuation contributes to NSCLC aggressiveness by altering nucleosome positioning at a wide range of genes, including key cancer-associated genes. Cancer Res; 74(22); 6486–98. ©2014 AACR.

Lung cancer is the leading cause of cancer-related deaths worldwide, and lung squamous carcinomas (LUSC) represent about 30% of cases. Molecular aberrations in lung adenocarcinomas have allowed for effective targeted treatments, but corresponding therapeutic advances in LUSC have not materialized. However, immune checkpoint inhibitors in sub-populations of LUSC patients have led to exciting responses. Using computational analyses of The Cancer Genome Atlas, we identified a subset of LUSC tumors characterized by dense infiltration of inflammatory monocytes (IMs) and poor survival. With novel, immunocompetent metastasis models, we demonstrated that tumor cell derived CCL2-mediated recruitment of IMs is necessary and sufficient for LUSC metastasis. Pharmacologic inhibition of IM recruitment had substantial anti-metastatic effects. Notably, we show that IMs highly express Factor XIIIA, which promotes fibrin cross-linking to create a scaffold for LUSC cell invasion and metastases. Consistently, human LUSC samples containing extensive cross-linked fibrin in the microenvironment correlated with poor survival.

<h2>Summary</h2> The diversity and heterogeneity within high-grade serous ovarian cancer (HGSC), which is the most lethal gynecologic malignancy, is not well understood. Here, we perform comprehensive multi-platform omics analyses, including integrated analysis, and immune monitoring on primary and metastatic sites from highly clinically annotated HGSC samples based on a laparoscopic triage algorithm from patients who underwent complete gross resection (R0) or received neoadjuvant chemotherapy (NACT) with excellent or poor response. We identify significant distinct molecular abnormalities and cellular changes and immune cell repertoire alterations between the groups, including a higher rate of <i>NF1</i> copy number loss, and reduced chromothripsis-like patterns, higher levels of strong-binding neoantigens, and a higher number of infiltrated T cells in the R0 versus the NACT groups.

We examined the role of repeat expansions in the pathogenesis of frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) by analyzing whole-genome sequence data from 2,442 FTD/ALS patients, 2,599 Lewy body dementia (LBD) patients, and 3,158 neurologically healthy subjects. Pathogenic expansions (range, 40-64 CAG repeats) in the huntingtin (HTT) gene were found in three (0.12%) patients diagnosed with pure FTD/ALS syndromes but were not present in the LBD or healthy cohorts. We replicated our findings in an independent collection of 3,674 FTD/ALS patients. Postmortem evaluations of two patients revealed the classical TDP-43 pathology of FTD/ALS, as well as huntingtin-positive, ubiquitin-positive aggregates in the frontal cortex. The neostriatal atrophy that pathologically defines Huntington's disease was absent in both cases. Our findings reveal an etiological relationship between HTT repeat expansions and FTD/ALS syndromes and indicate that genetic screening of FTD/ALS patients for HTT repeat expansions should be considered.

Identifying somatic mutations is critical for cancer genome characterization and for prioritizing patient treatment. DNA whole exome sequencing (DNA-WES) is currently the most popular technology; however, this yields low sensitivity in low purity tumors. RNA sequencing (RNA-seq) covers the expressed exome with depth proportional to expression. We hypothesized that integrating DNA-WES and RNA-seq would enable superior mutation detection versus DNA-WES alone. We developed a first-of-its-kind method, called UNCeqR, that detects somatic mutations by integrating patient-matched RNA-seq and DNA-WES. In simulation, the integrated DNA and RNA model outperformed the DNA-WES only model. Validation by patient-matched whole genome sequencing demonstrated superior performance of the integrated model over DNA-WES only models, including a published method and published mutation profiles. Genome-wide mutational analysis of breast and lung cancer cohorts (n = 871) revealed remarkable tumor genomics properties. Low purity tumors experienced the largest gains in mutation detection by integrating RNA-seq and DNA-WES. RNA provided greater mutation signal than DNA in expressed mutations. Compared to earlier studies on this cohort, UNCeqR increased mutation rates of driver and therapeutically targeted genes (e.g. PIK3CA, ERBB2 and FGFR2). In summary, integrating RNA-seq with DNA-WES increases mutation detection performance, especially for low purity tumors.

Background Evidence suggests the incidence of oral tongue squamous cell carcinoma is increasing in young patients, many who have no history of tobacco use. Methods We clinically reviewed 89 patients with oral tongue cancer. Exomic sequencing of tumor DNA from 6 nonsmokers was performed and compared to previously sequenced cases. RNA from 20 tumors was evaluated by massively parallel sequencing to search for potentially oncogenic viruses. Results Non-smokers (53 of 89) were younger than smokers (36 of 89; mean, 50.4 vs 61.9 years; p < .001), and seemed more likely to be women (58.5% vs 38.9%; p = .069). Nonsmokers had fewer TP53 mutations (p = .02) than smokers. No tumor-associated viruses were detected. Conclusion The young age of nonsmoking patients with oral tongue cancer and fewer TP53 mutations suggest a viral role in this disease. Our efforts to identify such a virus were unsuccessful. Further studies are warranted to elucidate the drivers of carcinogenesis in these patients. © 2014 Wiley Periodicals, Inc. Head Neck 37: 1642–1649, 2015

BackgroundBrain metastases are one of the most malignant complications of lung cancer and constitute a significant cause of cancer related morbidity and mortality worldwide. Recent years of investigation suggested a role of LKB1 in NSCLC development and progression, in synergy with KRAS alteration. In this study, we systematically analyzed how LKB1 and KRAS alteration, measured by mutation, gene expression (GE) and copy number (CN), are associated with brain metastasis in NSCLC.Materials and methodsPatients treated at University of North Carolina Hospital from 1990 to 2009 with NSCLC provided frozen, surgically extracted tumors for analysis. GE was measured using Agilent 44,000 custom-designed arrays, CN was assessed by Affymetrix GeneChip Human Mapping 250K Sty Array or the Genome-Wide Human SNP Array 6.0 and gene mutation was detected using ABI sequencing. Integrated analysis was conducted to assess the relationship between these genetic markers and brain metastasis. A model was proposed for brain metastasis prediction using these genetic measurements.Results17 of the 174 patients developed brain metastasis. LKB1 wild type tumors had significantly higher LKB1 CN (p < 0.001) and GE (p = 0.002) than the LKB1 mutant group. KRAS wild type tumors had significantly lower KRAS GE (p < 0.001) and lower CN, although the latter failed to be significant (p = 0.295). Lower LKB1 CN (p = 0.039) and KRAS mutation (p = 0.007) were significantly associated with more brain metastasis. The predictive model based on nodal (N) stage, patient age, LKB1 CN and KRAS mutation had a good prediction accuracy, with area under the ROC curve of 0.832 (p < 0.001).ConclusionLKB1 CN in combination with KRAS mutation predicted brain metastasis in NSCLC.

We present a deep proteogenomic profiling study of 87 lung adenocarcinoma (LUAD) tumors from the United States, integrating whole-genome sequencing, transcriptome sequencing, proteomics and phosphoproteomics by mass spectrometry, and reverse-phase protein arrays. We identify three subtypes from somatic genome signature analysis, including a transition-high subtype enriched with never smokers, a transversion-high subtype enriched with current smokers, and a structurally altered subtype enriched with former smokers, TP53 alterations, and genome-wide structural alterations. We show that within-tumor correlations of RNA and protein expression associate with tumor purity and immune cell profiles. We detect and independently validate expression signatures of RNA and protein that predict patient survival. Additionally, among co-measured genes, we found that protein expression is more often associated with patient survival than RNA. Finally, integrative analysis characterizes three expression subtypes with divergent mutations, proteomic regulatory networks, and therapeutic vulnerabilities. This proteogenomic characterization provides a foundation for molecularly informed medicine in LUAD.

We characterized the role of structural variants, a largely unexplored type of genetic variation, in two non-Alzheimer’s dementias, namely Lewy body dementia (LBD) and frontotemporal dementia (FTD)/amyotrophic lateral sclerosis (ALS). To do this, we applied an advanced structural variant calling pipeline (GATK-SV) to short-read whole-genome sequence data from 5,213 European-ancestry cases and 4,132 controls. We discovered, replicated, and validated a deletion in TPCN1 as a novel risk locus for LBD and detected the known structural variants at the C9orf72 and MAPT loci as associated with FTD/ALS. We also identified rare pathogenic structural variants in both LBD and FTD/ALS. Finally, we assembled a catalog of structural variants that can be mined for new insights into the pathogenesis of these understudied forms of dementia.

Abstract PlantGDB (http://www.plantgdb.org/) is a database of plant molecular sequences. Expressed sequence tag (EST) sequences are assembled into contigs that represent tentative unique genes. EST contigs are functionally annotated with information derived from known protein sequences that are highly similar to the putative translation products. Tentative Gene Ontology terms are assigned to match those of the similar sequences identified. Genome survey sequences are assembled similarly. The resulting genome survey sequence contigs are matched to ESTs and conserved protein homologs to identify putative full-length open reading frame-containing genes, which are subsequently provisionally classified according to established gene family designations. For Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa), the exon-intron boundaries for gene structures are annotated by spliced alignment of ESTs and full-length cDNAs to their respective complete genome sequences. Unique genome browsers have been developed to present all available EST and cDNA evidence for current transcript models (for Arabidopsis, see the AtGDB site at http://www.plantgdb.org/AtGDB/; for rice, see the OsGDB site at http://www.plantgdb.org/OsGDB/). In addition, a number of bioinformatic tools have been integrated at PlantGDB that enable researchers to carry out sequence analyses on-site using both their own data and data residing within the database.

Precise subtype diagnosis of non-small cell lung carcinoma is increasingly relevant, based on the availability of subtype-specific therapies, such as bevacizumab and pemetrexed, and based on the subtype-specific prevalence of activating epidermal growth factor receptor mutations.To establish a baseline measure of interobserver reproducibility for non-small cell lung carcinoma diagnoses with hematoxylin-eosin for the current 2004 World Health Organization classification, to estimate interobserver reproducibility for the therapeutically relevant squamous/nonsquamous subsets, and to examine characteristics that improve interobserver reproducibility.Primary, resected lung cancer specimens were converted to digital (virtual) slides. Based on a single hematoxylin-eosin virtual slide, pathologists were asked to assign a diagnosis using the 2004 World Health Organization classification. Kappa statistics were calculated for each pathologist-pair for each slide and were summarized by classification scheme, pulmonary pathology expertise, diagnostic confidence, and neoplastic grade.The 12 pulmonary pathology experts and the 12 community pathologists each independently diagnosed 48 to 96 single hematoxylin-eosin digital slides derived from 96 cases of non-small cell lung carcinoma resection. Overall agreement improved with simplification from the comprehensive 44 World Health Organization diagnoses (κ = 0.25) to their 10 major header subtypes (κ = 0.48) and improved again with simplification into the therapeutically relevant squamous/nonsquamous dichotomy (κ = 0.55). Multivariate analysis showed that higher diagnostic agreement was associated with better differentiation, better slide quality, higher diagnostic confidence, similar years of pathology experience, and pulmonary pathology expertise.These data define the baseline diagnostic agreement for hematoxylin-eosin diagnosis of non-small cell lung carcinoma, allowing future studies to test for improved diagnostic agreement with reflex ancillary tests.

Esophageal squamous cell carcinoma (ESCC) is endemic in regions of sub-Saharan Africa (SSA), where it is the third most common cancer. Here, we describe whole-exome tumor/normal sequencing and RNA transcriptomic analysis of 59 patients with ESCC in Malawi. We observed similar genetic aberrations as reported in Asian and North American cohorts, including mutations of TP53, CDKN2A, NFE2L2, CHEK2, NOTCH1, FAT1, and FBXW7. Analyses for nonhuman sequences did not reveal evidence for infection with HPV or other occult pathogens. Mutational signature analysis revealed common signatures associated with aging, cytidine deaminase activity (APOBEC), and a third signature of unknown origin, but signatures of inhaled tobacco use, aflatoxin and mismatch repair were notably absent. Based on RNA expression analysis, ESCC could be divided into 3 distinct subtypes, which were distinguished by their expression of cell cycle and neural transcripts. This study demonstrates discrete subtypes of ESCC in SSA, and suggests that the endemic nature of this disease reflects exposure to a carcinogen other than tobacco and oncogenic viruses.

Obesity continues to be one of the most prominent public health dilemmas in the world. The complex interaction among the varied causes of obesity makes it a particularly challenging problem to address. While typical high-fat purified diets successfully induce weight gain in rodents, we have described a more robust model of diet-induced obesity based on feeding rats a diet consisting of highly palatable, energy-dense human junk foods - the "cafeteria" diet (CAF, 45-53% kcal from fat). We previously reported that CAF-fed rats became hyperphagic, gained more weight, and developed more severe hyperinsulinemia, hyperglycemia, and glucose intolerance compared to the lard-based 45% kcal from fat high fat diet-fed group. In addition, the CAF diet-fed group displayed a higher degree of inflammation in adipose and liver, mitochondrial dysfunction, and an increased concentration of lipid-derived, pro-inflammatory mediators. Building upon our previous findings, we aimed to determine mechanisms that underlie physiologic findings in the CAF diet. We investigated the effect of CAF diet-induced obesity on adipose tissue specifically using expression arrays and immunohistochemistry. Genomic evidence indicated the CAF diet induced alterations in the white adipose gene transcriptome, with notable suppression of glutathione-related genes and pathways involved in mitigating oxidative stress. Immunohistochemical analysis indicated a doubling in adipose lipid peroxidation marker 4-HNE levels compared to rats that remained lean on control standard chow diet. Our data indicates that the CAF diet drives an increase in oxidative damage in white adipose tissue that may affect tissue homeostasis. Oxidative stress drives activation of inflammatory kinases that can perturb insulin signaling leading to glucose intolerance and diabetes.

Genetic mutations associated with acute myeloid leukemia (AML) also occur in age-related clonal hematopoiesis, often in the same individual. This makes confident assignment of detected variants to malignancy challenging. The issue is particularly crucial for AML post-treatment measurable residual disease monitoring, where results can be discordant between genetic sequencing and flow cytometry. We show here, that it is possible to distinguish AML from clonal hematopoiesis and to resolve the immunophenotypic identity of clonal architecture. To achieve this, we first design patient-specific DNA probes based on patient's whole-genome sequencing, and then use them for patient-personalized single-cell DNA sequencing with simultaneous single-cell antibody-oligonucleotide sequencing. Examples illustrate AML arising from DNMT3A and TET2 mutated clones as well as independently. The ability to personalize single-cell proteogenomic assessment for individual patients based on leukemia-specific genomic features has implications for ongoing AML precision medicine efforts.

Primary (AL) amyloidosis results from the pathologic deposition of monoclonal light chains as amyloid fibrils. Studies of recombinant-derived variable region (VL) fragments of these proteins have shown an inverse relationship between thermodynamic stability and fibrillogenic potential. Further, ionic interactions within the VL domain were predicted to influence the kinetics of light chain fibrillogenicity, as evidenced from our analyses of a relatively stable Vlambda6 protein (Jto) with a long range electrostatic interaction between Asp and Arg side chains at position 29 and 68, respectively, and an unstable, highly fibrillogenic Vlambda6 protein (Wil) that had neutral amino acids at these locations. To test this hypothesis, we have generated two Jto-related mutants designed to disrupt the interaction between Asp 29 and Arg 68 (JtoD29A and JtoR68S). Although the thermodynamic stabilities of unfolding for these two molecules were identical, they exhibited very different kinetics of fibril formation: the rate of JtoD29A fibrillogenesis was slow and comparable to the parent molecule, whereas that of JtoR68S was significantly faster. High-resolution X-ray diffraction analyses of crystals prepared from the two mutants having the same space group and unit cell dimensions revealed no significant main-chain conformational changes. However, several notable side-chain alterations were observed in JtoR68S, as compared with JtoD29A, that resulted in the solvent exposure of a greater hydrophobic surface and modifications in the electrostatic potential surface. We posit that these differences contributed to the enhanced fibrillogenic potential of the Arg 68 mutant, since both Jto mutants lacked the intrachain ionic interaction and were equivalently unstable. The information gleaned from our studies has provided insight into structural parameters that in addition to overall thermodynamic stability, contribute to the fibril forming propensity of immunoglobulin light chains.

Abstract Purpose: We evaluated X-ray repair complementing defective repair in Chinese hamster cells 1 (XRCC1) protein in head and neck squamous cell carcinoma (HNSCC) patients in association with outcome. Experimental Design: XRCC1 protein expression was assessed by immunohistochemical (IHC) staining of pretreatment tissue samples in 138 consecutive HNSCC patients treated with surgery (n = 31), radiation (15), surgery and radiation (23), surgery and adjuvant chemoradiation (17), primary chemoradiation (51), and palliative measures (1). Results: Patients with high XRCC1 expression by IHC (n = 77) compared with patients with low XRCC1 expression (n = 60) had poorer median overall survival (OS; 41.0 months vs. OS not reached, P = 0.009) and poorer progression-free survival (28.0 months vs. 73.0 months, P = 0.031). This association was primarily due to patients who received chemoradiation (median OS of high- and low-XRCC1 expression patients, 35.5 months and not reached respectively, HR 3.48; 95% CI: 1.44–8.38; P = 0.006). In patients treated with nonchemoradiation modalities, there was no survival difference by XRCC1 expression. In multivariable analysis, high XRCC1 expression and p16INK4a-positive status were independently associated with survival in the overall study population (HR = 2.62; 95% CI: 1.52–4.52; P &amp;lt; 0.001 and HR = 0.21; 95% CI: 0.06–0.71; P = 0.012, respectively) and among chemoradiation patients (HR = 6.02; 95% CI: 2.36–15.37; P &amp;lt; 0.001 and HR = 0.26; 95% CI: 0.08–0.92, respectively; P = 0.037). Conclusions: In HNSCC, high XRCC1 protein expression is associated with poorer survival, particularly in patients receiving chemoradiation. Future validation of these findings may enable identification of HNSCC expressing patients who benefit from chemoradiation treatment. Clin Cancer Res; 17(20); 6542–52. ©2011 AACR.

Recently, the management of head and neck squamous cell carcinoma (HNSCC) has focused considerable attention on biomarkers, which may influence outcomes. Tests for human papilloma infection, including direct assessment of the virus as well as an associated tumour suppressor gene p16, are considered reproducible. Tumours from familial melanoma syndromes have suggested that nuclear localisation of p16 might have a further role in risk stratification. We hypothesised p16 staining that considered nuclear localisation might be informative for predicting outcomes in a broader set of HNSCC tumours not limited to the oropharynx, human papilloma virus (HPV) status or by smoking status.Patients treated for HNSCC from 2002 to 2006 at UNC (University of North Carolina at Chapel Hill) hospitals that had banked tissue available were eligible for this study. Tissue microarrays (TMA) were generated in triplicate. Immunohistochemical (IHC) staining for p16 was performed and scored separately for nuclear and cytoplasmic staining. Human papilloma virus staining was also carried out using monoclonal antibody E6H4. p16 expression, HPV status and other clinical features were correlated with progression-free (PFS) and overall survival (OS).A total of 135 patients had sufficient sample for this analysis. Median age at diagnosis was 57 years (range 20-82), with 68.9% males, 8.9% never smokers and 32.6% never drinkers. Three-year OS rate and PFS rate was 63.0% and 54.1%, respectively. Based on the p16 staining score, patients were divided into three groups: high nuclear, high cytoplasmic staining group (HN), low nuclear, low cytoplasmic staining group (LS) and high cytoplasmic, low nuclear staining group (HC). The HN and the LS groups had significantly better OS than the HC group with hazard ratios of 0.10 and 0.37, respectively, after controlling for other factors, including HPV status. These two groups also had significantly better PFS than the HC staining group. This finding was consistent for sites outside the oropharynx and did not require adjustment for smoking status.Different p16 protein localisation suggested different survival outcomes in a manner that does not require limiting the biomarker to the oropharynx and does not require assessment of smoking status.

The recent FDA approval of the MiSeqDx platform provides a unique opportunity to develop targeted next generation sequencing (NGS) panels for human disease, including cancer. We have developed a scalable, targeted panel-based assay termed UNCseq, which involves a NGS panel of over 200 cancer-associated genes and a standardized downstream bioinformatics pipeline for detection of single nucleotide variations (SNV) as well as small insertions and deletions (indel). In addition, we developed a novel algorithm, NGScopy, designed for samples with sparse sequencing coverage to detect large-scale copy number variations (CNV), similar to human SNP Array 6.0 as well as small-scale intragenic CNV. Overall, we applied this assay to 100 snap-frozen lung cancer specimens lacking same-patient germline DNA (07–0120 tissue cohort) and validated our results against Sanger sequencing, SNP Array, and our recently published integrated DNA-seq/RNA-seq assay, UNCqeR, where RNA-seq of same-patient tumor specimens confirmed SNV detected by DNA-seq, if RNA-seq coverage depth was adequate. In addition, we applied the UNCseq assay on an independent lung cancer tumor tissue collection with available same-patient germline DNA (11–1115 tissue cohort) and confirmed mutations using assays performed in a CLIA-certified laboratory. We conclude that UNCseq can identify SNV, indel, and CNV in tumor specimens lacking germline DNA in a cost-efficient fashion.

“Soldier’s Heart,” is an American Civil War term linking post-traumatic stress disorder (PTSD) with increased propensity for cardiovascular disease (CVD). We have hypothesized that there might be a quantifiable genetic basis for this linkage. To test this hypothesis we identified a comprehensive set of candidate risk genes for PTSD, and tested whether any were also independent risk genes for CVD. A functional analysis algorithm was used to identify associated signaling networks.We identified 106 PTSD studies that report one or more polymorphic variants in 87 candidate genes in 83,463 subjects and controls. The top upstream drivers for these PTSD risk genes are predicted to be the glucocorticoid receptor (NR3C1) and Tumor Necrosis Factor alpha (TNFA). We find that 37 of the PTSD candidate risk genes are also candidate independent risk genes for CVD. The association between PTSD and CVD is significant by Fisher’s Exact Test (P= 3*10-54). We also find 15 PTSD risk genes that are independently associated with Type 2 Diabetes Mellitus (T2DM; also significant by Fisher’s Exact Test (P= 1.8*10-16). Our findings offer quantitative evidence for a genetic link between post-traumatic stress and cardiovascular disease, Computationally, the common mechanism for this linkage between PTSD and CVD is innate immunity and NFκB-mediated inflammation.

Recurrence rates after breast-conserving therapy may depend on genomic characteristics of cancer-adjacent, benign-appearing tissue. Studies have not evaluated recurrence in association with multiple genomic characteristics of cancer-adjacent breast tissue. To estimate the prevalence of DNA defects and RNA expression subtypes in cancer-adjacent, benign-appearing breast tissue at least 2 cm from the tumor margin, cancer-adjacent, pathologically well-characterized, benign-appearing breast tissue specimens from The Cancer Genome Atlas project were analyzed for DNA sequence, copy-number variation, DNA methylation, messenger RNA (mRNA) sequence, and mRNA/microRNA expression. Additional samples were also analyzed by at least one of these genomic data types and associations between genomic characteristics of normal tissue and overall survival were assessed. Approximately 40% of cancer-adjacent, benign-appearing tissues harbored genomic defects in DNA copy number, sequence, methylation, or in RNA sequence, although these defects did not significantly predict 10-year overall survival. Two mRNA/microRNA expression phenotypes were observed, including an active mRNA subtype that was identified in 40% of samples. Controlling for tumor characteristics and the presence of genomic defects, this active subtype was associated with significantly worse 10-year survival among estrogen receptor (ER)-positive cases. This multi-platform analysis of breast cancer-adjacent samples produced genomic findings consistent with current surgical margin guidelines, and provides evidence that extratumoral RNA expression patterns in cancer-adjacent tissue predict overall survival among patients with ER-positive disease.

Traumatic brain injury (TBI) results in complex pathological reactions, where the initial lesion is followed by secondary inflammation and edema. Our laboratory and others have reported that angiotensin receptor blockers (ARBs) have efficacy in improving recovery from traumatic brain injury in mice. Treatment of mice with a subhypotensive dose of the ARB candesartan results in improved functional recovery, and reduced pathology (lesion volume, inflammation and gliosis). In order to gain a better understanding of the molecular mechanisms through which candesartan improves recovery after controlled cortical impact injury (CCI), we performed transcriptomic profiling on brain regions after injury and drug treatment. We examined RNA expression in the ipsilateral hippocampus, thalamus and hypothalamus at 3 or 29 days post injury (dpi) treated with either candesartan (0.1 mg/kg) or vehicle. RNA was isolated and analyzed by bulk mRNA-seq. Gene expression in injured and/or candesartan treated brain region was compared to that in sham vehicle treated mice in the same brain region to identify genes that were differentially expressed (DEGs) between groups. The most DEGs were expressed in the hippocampus at 3 dpi, and the number of DEGs reduced with distance and time from the lesion. Among pathways that were differentially expressed at 3 dpi after CCI, candesartan treatment altered genes involved in angiogenesis, interferon signaling, extracellular matrix regulation including integrins and chromosome maintenance and DNA replication. At 29 dpi, candesartan treatment reduced the expression of genes involved in the inflammatory response. Some changes in gene expression were confirmed in a separate cohort of animals by qPCR. Fewer DEGs were found in the thalamus, and only one in the hypothalamus at 3 dpi. Additionally, in the hippocampi of sham injured mice, 3 days of candesartan treatment led to the differential expression of 384 genes showing that candesartan in the absence of injury had a powerful impact on gene expression specifically in the hippocampus. Our results suggest that candesartan has broad actions in the brain after injury and affects different processes at acute and chronic times after injury. These data should assist in elucidating the beneficial effect of candesartan on recovery from TBI.

Head and neck squamous cell carcinoma (HNSCC) is a frequently fatal heterogeneous disease.Beyond the role of human papilloma virus (HPV), no validated molecular characterization of the disease has been established.Using an integrated genomic analysis and validation methodology we confirm four molecular classes of HNSCC (basal, mesenchymal, atypical, and classical) consistent with signatures established for squamous carcinoma of the lung, including deregulation of the KEAP1/NFE2L2 oxidative stress pathway, differential utilization of the lineage markers SOX2 and TP63, and preference for the oncogenes PIK3CA and EGFR.For potential clinical use the signatures are complimentary to classification by HPV infection status as well as the putative high risk marker CCND1 copy number gain.A molecular etiology for the subtypes is suggested by statistically significant chromosomal gains and losses and differential cell of origin expression patterns.Model systems representative of each of the four subtypes are also presented.

Squamous cell lung cancer (SqCC) is the second most common type of lung cancer in the United States. Previous studies have used gene-expression data to classify SqCC samples into four subtypes, including the primitive, classical, secretory and basal subtypes. These subtypes have different survival outcomes, although it is unknown whether these molecular subtypes predict response to therapy. Here, we analysed RNAseq data of 178 SqCC tumour samples and characterised the features of the different SqCC subtypes to define signature genes and pathway alterations specific to each subtype. Further, we compared the gene-expression features of each molecular subtype to specific time points in models of airway development. We also classified SqCC-derived cell lines and their reported therapeutic vulnerabilities. We found that the primitive subtype may come from a later stage of differentiation, whereas the basal subtype may be from an early time. Most SqCC cell lines responded to one of five anticancer drugs (Panobinostat, 17-AAG, Irinotecan, Topotecan and Paclitaxel), whereas the basal-type cell line EBC-1 was sensitive to three other drugs (PF2341066, AZD6244 and PD-0325901). Compared with the other three subtypes of cell lines, the secretory-type cell lines were significantly less sensitive to the five most effective drugs, possibly because of their low proliferation activity. We provide a bioinformatics framework to explore drug repurposing for cancer subtypes based on the available genomic profiles of tumour samples, normal cell types, cancer cell lines and data of drug sensitivity in cell lines.

Early diagnosis improves melanoma survival, yet the histopathological diagnosis of cutaneous primary melanoma can be challenging, even for expert dermatopathologists. Analysis of epigenetic alterations, such as DNA methylation, that occur in melanoma can aid in its early diagnosis. Using a genome-wide methylation screening, we assessed CpG methylation in a diverse set of 89 primary invasive melanomas, 73 nevi, and 41 melanocytic proliferations of uncertain malignant potential, classified based on interobserver review by dermatopathologists. Melanomas and nevi were split into training and validation sets. Predictive modeling in the training set using ElasticNet identified a 40-CpG classifier distinguishing 60 melanomas from 48 nevi. High diagnostic accuracy (area under the receiver operator characteristic curve = 0.996, sensitivity = 96.6%, and specificity = 100.0%) was independently confirmed in the validation set (29 melanomas, 25 nevi) and other published sample sets. The 40-CpG melanoma classifier included homeobox transcription factors and genes with roles in stem cell pluripotency or the nervous system. Application of the 40-CpG melanoma classifier to the diagnostically uncertain samples assigned melanoma or nevus status, potentially offering a diagnostic tool to assist dermatopathologists. In summary, the robust, accurate 40-CpG melanoma classifier offers a promising assay for improving primary melanoma diagnosis.

Drug resistance is a constant threat to malaria control efforts making it important to maintain a good pipeline of new drug candidates. Of particular need are compounds that also block transmission by targeting sexual stage parasites. Mature sexual stages are relatively resistant to all currently used antimalarials except the 8-aminoquinolines that are not commonly used due to potential side effects. Here, we synthesized a new Torin 2 derivative, NCATS-SM3710 with increased aqueous solubility and specificity for Plasmodium and demonstrate potent in vivo activity against all P. berghei life cycle stages. NCATS-SM3710 also has low nanomolar EC50s against in vitro cultured asexual P. falciparum parasites (0.38 ± 0.04 nM) and late stage gametocytes (5.77 ± 1 nM). Two independent NCATS-SM3710/Torin 2 resistant P. falciparum parasite lines produced by growth in sublethal Torin 2 concentrations both had genetic changes in PF3D7_0509800, annotated as a phosphatidylinositol 4 kinase (Pf PI4KIIIβ). One line had a point mutation in the putative active site (V1357G), and the other line had a duplication of a locus containing Pf PI4KIIIβ. Both lines were also resistant to other Pf PI4K inhibitors. In addition NCATS-SM3710 inhibited purified Pf PI4KIIIβ with an IC50 of 2.0 ± 0.30 nM. Together the results demonstrate that Pf PI4KIIIβ is the target of Torin 2 and NCATS-SM3710 and provide new options for potent multistage drug development.

Not every gene nominated as a cause of human disease stands the test of time. As additional data become available, the evidence supporting the pathogenicity of a particular variant within a gene can be enhanced or diminished.1 The amyotrophic lateral sclerosis (ALS) field, as much as any other, has been hesitant to address these controversies, leading to uncertainty among the research community.

Low dose-rate radiation exposure can occur in medical imaging, as background from environmental or industrial radiation, and is a hazard of space travel. In contrast with high dose-rate radiation exposure that can induce acute life-threatening syndromes, chronic low-dose radiation is associated with Chronic Radiation Syndrome (CRS), which can alter environmental sensitivity. Secondary effects of chronic low dose-rate radiation exposure include circulatory, digestive, cardiovascular, and neurological diseases, as well as cancer. Here, we investigated 1-2 Gy, 0.66 cGy/h, 60Co radiation effects on primary human mesenchymal stem cells (hMSC). There was no significant induction of apoptosis or DNA damage, and cells continued to proliferate. Gene ontology (GO) analysis of transcriptome changes revealed alterations in pathways related to cellular metabolism (cholesterol, fatty acid, and glucose metabolism), extracellular matrix modification and cell adhesion/migration, and regulation of vasoconstriction and inflammation. Interestingly, there was increased hypoxia signaling and increased activation of pathways regulated by iron deficiency, but Nrf2 and related genes were reduced. The data were validated in hMSC and human lung microvascular endothelial cells using targeted qPCR and Western blotting. Notably absent in the GO analysis were alteration pathways for DNA damage response, cell cycle inhibition, senescence, and pro-inflammatory response that we previously observed for high dose-rate radiation exposure. Our findings suggest that cellular gene transcription response to low dose-rate ionizing radiation is fundamentally different compared to high-dose-rate exposure. We hypothesize that cellular response to hypoxia and iron deficiency are driving processes, upstream of the other pathway regulation.

Abstract Human induced pluripotent stem (iPS) cell‐derived neurons and astrocytes are attractive cellular tools for nervous system disease modeling and drug screening. Optimal utilization of these tools requires differentiation protocols that efficiently generate functional cell phenotypes in vitro . As nervous system function is dependent on networked neuronal activity involving both neuronal and astrocytic synaptic functions, we examined astrocyte effects on the functional maturation of neurons from human iPS cell‐derived neural stem cells (NSCs). We first demonstrate human iPS cell‐derived NSCs can be rapidly differentiated in culture to either neurons or astrocytes with characteristic cellular, molecular and physiological features. Although differentiated neurons were capable of firing multiple action potentials (APs), few cells developed spontaneous electrical activity in culture. We show spontaneous electrical activity was significantly increased by neuronal differentiation of human NSCs on feeder layers of neonatal mouse cortical astrocytes. In contrast, co‐culture on feeder layers of isogenic human iPS cell‐derived astrocytes had no positive effect on spontaneous neuronal activity. Spontaneous electrical activity was dependent on glutamate receptor‐channel function and occurred without changes in I Na , I K , V m , and AP properties of iPS cell‐derived neurons. These data demonstrate co‐culture with neonatal mouse cortical astrocytes but not human isogenic iPS cell‐derived astrocytes stimulates glutamatergic synaptic transmission between iPS cell‐derived neurons in culture. We present RNA‐sequencing data for an immature, fetal‐like status of our human iPS cell‐derived astrocytes as one possible explanation for their failure to enhance synaptic activity in our co‐culture system.

The Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) network is implementing a prospective curation and translation of real-world data (RWD) into real-world evidence (RWE) within the learning healthcare environment of the Department of Defense and Department of Veterans Affairs. To support basic, translational, clinical, and epidemiological sciences, APOLLO will release data to public repositories for secondary analysis to assist others in assessing whether similar molecular-driven clinical practice guidelines will improve health outcomes for their relevant cancer populations. In the United States, > 80% of patients with cancer are initially diagnosed and treated in a community hospital setting rather than an academic hospital setting. Despite the increased adoption of electronic health records (EHRs), the lack of interoperable health information systems makes it challenging to aggregate RWD generated from a cancer patient’s journey before diagnosis, during treatment, and throughout survivorship. RWD might include data collected as part of routine health and cancer care delivery or for research (translational, implementation science, and/or epidemiological) efforts. Longitudinal collection of RWD is essential to generating RWE and is often absent when elucidating long-term consequences of care strategies. Recent studies have demonstrated the success of individualized cancer care strategies enabled by molecular profiling and targeted therapies. In the past 2 years, the US Food and Drug Administration (FDA) has approved tumor site–agnostic, biomarker-driven cancer treatments and next-generation sequencing in vitro diagnostic devices.1 A parallel review process by the Center for Medicare & Medicaid Services led to a national coverage determination next-generation sequencing-based in vitro diagnostics. The rapid development and approval of such technologies underscored this widening gap in capturing real-world use of molecular-driven cancer care to generate RWE to help inform regulatory and clinical decisions.2 Conducting valid real-world studies requires data quality assurance through auditable data abstraction methods and incentives to drive electronic capture of data during delivery of care.2 The Department of Veterans Affairs (VA) has the nation's largest integrated healthcare system with over 9 million veterans enrolled and is a high-volume provider of cancer care with nearly 50,000 incident cancer cases reported in 2010.3 The VA Office of Research and Development has as its three major priorities to: (i) enhance veteran access to multisite clinical trials, (ii) make VA data a national resource, and (iii) increase the real-world impact of research findings. The VA Office of Research and Development's national Cooperative Studies Program4 and data resources enable researchers to access and identify initial cohorts for further studies to advance RWD analysis have been leveraged through partnerships with federal collaborators to further a learning health care system within the VA. The Department of Defense (DoD) Military Health System (MHS) is responsible for maintaining the health and readiness of 1.7 million active-duty and reserve service members (SMs) and caring for 9.4 million beneficiaries in TRICARE health benefit plans. The John P. Murtha Cancer Center at Uniformed Services University and Walter Reed National Military Medical Center offers a comprehensive cancer care operational view in 64 capability areas to proactively mitigate and close gaps in cancer care and research in the MHS. The John P. Murtha Cancer Center utilizes agreements with other federal agencies and extramural collaborators to provide return on investment by deploying the most robust and modern molecular technologies under various programs. The administrative and medical care data from both direct and indirect care are stored in the military data repository, which includes detailed information on demographics, diagnoses, diagnostic procedures, prescriptions, ancillary and radiology services, treatments, cost of care, and vital status. The DoD also has a cancer registry that collects detailed data on cancer diagnosis and features, including some cancer biomarkers. These RWD have been widely used for cancer research among DoD beneficiaries.5, 6 Leveraging the two largest nationwide connected healthcare systems, the APOLLO network was launched in 2016 with the intent of curating longitudinal RWD and health outcome data to create and assess adoption of new molecular-driven clinical practice guidelines. By developing, defining, and aligning RWD elements of MHS, patients with cancer from prediagnosis through survivorship among the federal and civilian partners, the APOLLO network is implementing an integrated multifederal network for prospective curation and translation of RWD into RWE in a learning healthcare environment that will assist other payers in assessing whether similar clinical practice guidelines will improve health outcomes for their relevant populations. Previous large-scale tumor characterization projects, such as The Cancer Genome Atlas and the ongoing Clinical Proteomics Tumor Analysis Consortium, focused on analyzing the genomics and proteomics profile of tumors at a single time point.7 The lack of focus on longitudinal RWD collection limits the clinical utilization of these programs’ data.8 APOLLO is distinct from The Cancer Genome Atlas and other previous tumor characterization projects as it was focused on integrated proteogenomic analyses, the collection of longitudinal RWD, and development of a sustainable collection pipeline from its inception. The foundation of the approach is a network of biospecimen collection sites throughout the DoD and VA plus select civilian sites. APOLLO tissue collection is infused into pathology departments to preserve patient care, optimize collections, and control for preanalytic variables while involving the local organizations as true partners. This culture of collaboration also promotes the capture of longitudinal clinical, radiology imaging, and patient data throughout patients’ disease cycles that can otherwise be difficult to obtain. This culture expands to Clinical Laboratory Improvement Amendment (CLIA) laboratories, biobanking, imaging characterization, and proteogenomic analysis centers to form a robust APOLLO ecosystem that will be leveraged to enable additional longitudinal oncology studies of both established and new patients. To maximize longitudinal clinical data collection, APOLLO uniquely designed a combination of disease-specific pilot retrospective studies of hundreds of cases (APOLLOs 1–4) and prospective studies of ~ 8,000 cases (APOLLO 5). Successes and lessons learned during the implementation of these pilot projects, as well as those from past large-scale molecular and clinical studies, are being leveraged to successfully forge the APOLLO ecosystem. Central to generating RWE from RWD in combination with molecular data is the challenge of balancing effective biospecimen matching and integration of data from multiple modalities from the same patient while maintaining accuracy and privacy over time. One way the network tackled this issue was bringing together early stakeholders to develop and adopt a prospectively generated unique APOLLO participant and aliquot identifiers (APOLLO ID; Figure 1). APOLLO ID will also be linked to a 128-byte global unique participant and aliquot identifiers with an “AP-” prefix when data are uploaded to public repositories for secondary analysis. The APOLLO system is electronically supported by an enterprise informatics infrastructure, which includes a Data Tracking System (DTS-APOLLO) for transactional activities, a Data Warehouse for Translational Research for (DW4TR-APOLLO),9 and a network of connected public data repositories to support capturing, management, and delivery of RWD to the study team and the public to enable discovery of RWE. Initial pilot datasets have been successfully uploaded to the National Cancer Institute's Genomic Data Commons and The Cancer Imaging Archive (TCIA) from both VA and DoD studies. The length of patient follow-up time within APOLLO will be pre-estimated for each cancer type using prior literature rather than by duration of a funding cycle, so advanced planning will enable continued capturing of such data from both the regulatory and technical perspectives. The APOLLO program aspires to accelerate the application of next-generation proteogenomic profiling with deep baseline and longitudinal RWD from DoD and VA EHRs and research records into RWE for FDA-approved tests and treatments for development and deployment of tools and strategies used in the prevention, diagnosis, and treatment of cancer. These activities support readiness and health by empowering patients and providers to optimize their care and health through customized and enterprise solutions. The program will deploy both retrospective and prospective observational designs with provisions for clinical trial participation. Select civilian cohorts with aggressive or rare cancers will be incorporated with SMs and veterans to contribute diversity, events, experiences, and outcomes to the disease-oriented and pan-cancer cohorts to learn about, treat, and prevent cancers that develop in warfighters. Types of clinical and research RWD that will be collected by the APOLLO network are listed in Table 1. This program will require and utilize operationalized processes and procedures tracked via a user-friendly APOLLO Dashboard. Integrated analyses will incorporate a deep complement of RWD from medical and research records. Sequencing and proteomic data generated by CLIA facilities and analytical core facilities will not only be analyzed using current clinical databases but will be available for iterative reanalysis over time applying new clinical databases and trusted sources to advance reinterpretation of the patients’ molecular profiling data to determine future access to new FDA-approved drugs and/or clinical trial opportunities. This program will provide data in support studies of basic science, translational medicine, epidemiology, comparative effectiveness, cost-effectiveness, and health disparities. Various data-release provisions were incorporated into the APOLLO framework, including release to repositories for future research, clinical trials, indications and guidelines, dissemination to scientists, healthcare professionals, and the public, release to study doctors when research results meet guidelines for medical consideration for follow-up and clinical assessments, and return to patients when the research results qualifies for release without clinical certification, as recommended recently by the National Academies of Sciences, Engineering, and Medicine.10 Translation of RWD into RWE is a key component of APOLLO with integrated systems for enhancing capabilities across the cancer care continuum, driving efficiencies, and enhancing quality, thereby improving health outcomes and the readiness of warfighters and the operational medical force. The full potential of APOLLO will be realized when interoperable EHRs are readily and securely exchangeable across the DoD and VA with enterprise solutions and clinical decision tools for molecular pathology, clinical imaging, patient-reported outcomes, clinical trials, serious adverse events reporting, prevention clinics, rehabilitative and other supportive services, pain management, survivorship, palliative care, end-of-life care, research, and education. Improvements in readiness, health care, and outcomes for SMs, veterans, health beneficiaries, and civilians will be achieved not only from deliverables generated by the APOLLO network but also from release of RWD and RWE to the public for secondary research. APOLLO patients may also benefit from release of research data that qualify either for clinical certification or direct release based on criteria, such as level and quality of the evidence. Federal agencies may also benefit from the generated agreements, established working groups, and taskforces with representation from the stakeholders and invited nonfederal experts, aligned resources and assets, integrated and expanded infrastructure and workforces, and the capabilities developed for APOLLO and operationalized across the DoD and VA for implementing precision oncology solutions to acquire and translate RWD from APOLLO into RWE for SMs, veterans, and the global cancer ecosystem. The authors would like to thank Joseph Shaw, Sara Sakura, Autumn Beemer Phillips, Gregory Samuel, Olga Castellanos, Jillian Infusino, and Mayada Aljehani for their critical review of the figure and paper. Funding for these efforts was provided from Uniformed Services University of the Health Sciences (USUHS) awards from the Defense Health Program to the Murtha Cancer Center Research Program (HU0001-16-2-0014, C.D. Shriver and J.S.H. Lee), the Gynecologic Cancer Center of Excellence (HU0001-16-2-0006, Y. Casablanca and G. Larry Maxwell), and HU0001-16-2-004 (L. Kvecher and H. Hu) administered by the Henry M. Jackson Foundation for the Advancement of Military Medicine. This project has also been funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. HHSN261200800001E (J.B. Freymann). The authors declared no competing interests for this work. The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views, opinions, or policies of the USUHS, the Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., the Department of Defense (DoD), the Departments of the Army, Navy, or Air Force, Department of Health and Human Services, or Department of Veterans Affairs. Mention of trade names, commercial products, or organization does not imply endorsement by the U.S. Government.

In prostate cancer, emerging data highlight the role of DNA damage repair genes (DDRGs) in aggressive forms of the disease. However, DDRG mutations in African American men are not yet fully defined. Here, we profile germline mutations in all known DDRGs (N = 276) using whole genome sequences from blood DNA of a matched cohort of patients with primary prostate cancer comprising of 300 African American and 300 European Ancestry prostate cancer patients, to determine whether the mutation status can enhance patient stratification for specific targeted therapies. Here, we show that only 13 of the 46 DDRGs identified with pathogenic/likely pathogenic mutations are present in both African American and European ancestry patients. Importantly, RAD family genes (RAD51, RAD54L, RAD54B), which are potentially targetable, as well as PMS2 and BRCA1, are among the most frequently mutated DDRGs in African American, but not in European Ancestry patients.

Contemporary high dimensional biological assays, such as mRNA expression microarrays, regularly involve multiple data processing steps, such as experimental processing, computational processing, sample selection, or feature selection (i.e. gene selection), prior to deriving any biological conclusions. These steps can dramatically change the interpretation of an experiment. Evaluation of processing steps has received limited attention in the literature. It is not straightforward to evaluate different processing methods and investigators are often unsure of the best method. We present a simple statistical tool, Standardized WithIn class Sum of Squares (SWISS), that allows investigators to compare alternate data processing methods, such as different experimental methods, normalizations, or technologies, on a dataset in terms of how well they cluster a priori biological classes. SWISS uses Euclidean distance to determine which method does a better job of clustering the data elements based on a priori classifications. We apply SWISS to three different gene expression applications. The first application uses four different datasets to compare different experimental methods, normalizations, and gene sets. The second application, using data from the MicroArray Quality Control (MAQC) project, compares different microarray platforms. The third application compares different technologies: a single Agilent two-color microarray versus one lane of RNA-Seq. These applications give an indication of the variety of problems that SWISS can be helpful in solving. The SWISS analysis of one-color versus two-color microarrays provides investigators who use two-color arrays the opportunity to review their results in light of a single-channel analysis, with all of the associated benefits offered by this design. Analysis of the MACQ data shows differential intersite reproducibility by array platform. SWISS also shows that one lane of RNA-Seq clusters data by biological phenotypes as well as a single Agilent two-color microarray.

Abstract Background Next-generation sequencing technologies have become important tools for genome-wide studies. However, the quality scores that are assigned to each base have been shown to be inaccurate. If the quality scores are used in downstream analyses, these inaccuracies can have a significant impact on the results. Results Here we present ReQON, a tool that recalibrates the base quality scores from an input BAM file of aligned sequencing data using logistic regression. ReQON also generates diagnostic plots showing the effectiveness of the recalibration. We show that ReQON produces quality scores that are both more accurate, in the sense that they more closely correspond to the probability of a sequencing error, and do a better job of discriminating between sequencing errors and non-errors than the original quality scores. We also compare ReQON to other available recalibration tools and show that ReQON is less biased and performs favorably in terms of quality score accuracy. Conclusion ReQON is an open source software package, written in R and available through Bioconductor, for recalibrating base quality scores for next-generation sequencing data. ReQON produces a new BAM file with more accurate quality scores, which can improve the results of downstream analysis, and produces several diagnostic plots showing the effectiveness of the recalibration.

Identifying variants using high-throughput sequencing data is currently a challenge because true biological variants can be indistinguishable from technical artifacts. One source of technical artifact results from incorrectly aligning experimentally observed sequences to their true genomic origin (‘mismapping’) and inferring differences in mismapped sequences to be true variants. We developed BlackOPs, an open-source tool that simulates experimental RNA-seq and DNA whole exome sequences derived from the reference genome, aligns these sequences by custom parameters, detects variants and outputs a blacklist of positions and alleles caused by mismapping. Blacklists contain thousands of artifact variants that are indistinguishable from true variants and, for a given sample, are expected to be almost completely false positives. We show that these blacklist positions are specific to the alignment algorithm and read length used, and BlackOPs allows users to generate a blacklist specific to their experimental setup. We queried the dbSNP and COSMIC variant databases and found numerous variants indistinguishable from mapping errors. We demonstrate how filtering against blacklist positions reduces the number of potential false variants using an RNA-seq glioblastoma cell line data set. In summary, accounting for mapping-caused variants tuned to experimental setups reduces false positives and, therefore, improves genome characterization by high-throughput sequencing.

High-throughput sequencing technologies, including RNA-seq, have made it possible to move beyond gene expression analysis to study transcriptional events including alternative splicing and gene fusions. Furthermore, recent studies in cancer have suggested the importance of identifying transcriptionally altered loci as biomarkers for improved prognosis and therapy. While many statistical methods have been proposed for identifying novel transcriptional events with RNA-seq, nearly all rely on contrasting known classes of samples, such as tumor and normal. Few tools exist for the unsupervised discovery of such events without class labels. In this paper, we present SigFuge for identifying genomic loci exhibiting differential transcription patterns across many RNA-seq samples. SigFuge combines clustering with hypothesis testing to identify genes exhibiting alternative splicing, or differences in isoform expression. We apply SigFuge to RNA-seq cohorts of 177 lung and 279 head and neck squamous cell carcinoma samples from the Cancer Genome Atlas, and identify several cases of differential isoform usage including CDKN2A, a tumor suppressor gene known to be inactivated in a majority of lung squamous cell tumors. By not restricting attention to known sample stratifications, SigFuge offers a novel approach to unsupervised screening of genetic loci across RNA-seq cohorts. SigFuge is available as an R package through Bioconductor.

Posttraumatic stress disorder is developed by exposure to a threatening and/or a horrifying event and characterized by the presence of anxiety, hyperarousal, avoidance, and sleep abnormality for a prolonged period of time. To elucidate the potential molecular mechanisms, we constructed a mouse model by electric foot shock followed by situational reminders and performed transcriptome analysis in brain tissues. The stressed mice acquired anxiety-like behavior after 2 weeks and exaggerated startle response after 4 weeks. Avoidance latency and freezing behavior were sustained up to 5 weeks post stress and abnormal static behavior was observed during the sleep period. RNA sequencing was performed in two of the emotional regulatory regions, anterior cingulate cortex and amygdala, at 2 and 5 weeks post stress. More than 1000 differentially expressed genes were identified at 2 weeks in both regions. The number of the regulated genes remained constant in amygdala at 5 weeks post stress, whereas those in anterior cingulate cortex were plummeted. Although synaptic remodeling and endocrine system were the most enriched signaling pathways in both anterior cingulate cortex and amygdala, the individual gene expression profile was regulated in a region- and time-dependent manner. In addition, several genes associated with PTSD involved in Hypothalamic-Pituitary-Adrenal axis were differentially regulated. These findings suggested that global gene expression profile was dynamically regulated in accordance with the disease development stage, and therefore targeting the distinct signaling molecules in different region and development stage might be critical for effective treatment to PTSD.

Lymphocyte antigen 6K (LY6K) is a small GPI-linked protein that is normally expressed in testes. Increased expression of LY6K is significantly associated with poor survival outcomes in many solid cancers, including cancers of the breast, ovary, gastrointestinal tract, head and neck, brain, bladder, and lung. LY6K is required for ERK-AKT and TGF-β pathways in cancer cells and is required for in vivo tumor growth. In this report, we describe a novel role for LY6K in mitosis and cytokinesis through aurora B kinase and its substrate histone H3 signaling axis. Further, we describe the structural basis of the molecular interaction of small molecule NSC243928 with LY6K protein and the disruption of LY6K-aurora B signaling in cell cycle progression due to LY6K-NSC243928 interaction. Overall, disruption of LY6K function via NSC243928 led to failed cytokinesis, multinucleated cells, DNA damage, senescence, and apoptosis of cancer cells. LY6K is not required for vital organ function, thus inhibition of LY6K signaling is an ideal therapeutic approach for hard-to-treat cancers that lack targeted therapy such as triple-negative breast cancer.

NSC243928 induces cell death in triple-negative breast cancer cells in a LY6K-dependent manner. NSC243928 has been reported as an anti-cancer agent in the NCI small molecule library. The molecular mechanism of NSC243928 as an anti-cancer agent in the treatment of tumor growth in the syngeneic mouse model has not been established. With the success of immunotherapies, novel anti-cancer drugs that may elicit an anti-tumor immune response are of high interest in the development of novel drugs to treat solid cancer. Thus, we focused on studying whether NSC243928 may elicit an anti-tumor immune response in the in vivo mammary tumor models of 4T1 and E0771. We observed that NSC243928 induced immunogenic cell death in 4T1 and E0771 cells. Furthermore, NSC243928 mounted an anti-tumor immune response by increasing immune cells such as patrolling monocytes, NKT cells, B1 cells, and decreasing PMN MDSCs in vivo. Further studies are required to understand the exact mechanism of NSC243928 action in inducing an anti-tumor immune response in vivo, which can be used to determine a molecular signature associated with NSC243928 efficacy. NSC243928 may be a good target for future immuno-oncology drug development for breast cancer.

Numerous multi-omic investigations of cancer tissue have documented varying and poor pairwise transcript:protein quantitative correlations, and most deconvolution tools aiming to predict cell type proportions (cell admixture) have been developed and credentialed using transcript-level data alone. To estimate cell admixture using protein abundance data, we analyzed proteome and transcriptome data generated from contrived admixtures of tumor, stroma, and immune cell models or those selectively harvested from the tissue microenvironment by laser microdissection from high grade serous ovarian cancer (HGSOC) tumors. Co-quantified transcripts and proteins performed similarly to estimate stroma and immune cell admixture (r ≥ 0.63) in two commonly used deconvolution algorithms, ESTIMATE or ConsensusTME. We further developed and optimized protein-based signatures estimating cell admixture proportions and benchmarked these using bulk tumor proteomic data from over 150 patients with HGSOC. The optimized protein signatures supporting cell type proportion estimates from bulk tissue proteomic data are available at https://lmdomics.org/ProteoMixture/.

A combination of improved body armor, medical transportation, and treatment has led to the increased survival of warfighters from combat extremity injuries predominantly caused by blasts in modern conflicts. Despite advances, a high rate of complications such as wound infections, wound failure, amputations, and a decreased quality of life exist. To study the molecular underpinnings of wound failure, wound tissue biopsies from combat extremity injuries had RNA extracted and sequenced. Wounds were classified by colonization (colonized vs. non-colonized) and outcome (healed vs. failed) status. Differences in gene expression were investigated between timepoints at a gene level, and longitudinally by multi-gene networks, inferred proportions of immune cells, and expression of healing-related functions. Differences between wound outcomes in colonized wounds were more apparent than in non-colonized wounds. Colonized/healed wounds appeared able to mount an adaptive immune response to infection and progress beyond the inflammatory stage of healing, while colonized/failed wounds did not. Although, both colonized and non-colonized failed wounds showed increasing inferred immune and inflammatory programs, non-colonized/failed wounds progressed beyond the inflammatory stage, suggesting different mechanisms of failure dependent on colonization status. Overall, these data reveal gene expression profile differences in healing wounds that may be utilized to improve clinical treatment paradigms.

Abstract Background: Proteogenomic characterization efforts of high-grade serous ovarian cancer (HGSOC) have largely assessed tumors with high tumor cellularity (“purity”) to enhance detection of cancer-related biomarkers. Comprehensive analyses of cancers independent of purity are needed to reflect a “real-world” spectrum of patient phenotypes. To improve identification of clinically relevant molecular alterations associated with HGSOC independent of tumor purity, we applied cellular enrichment techniques coupled with comprehensive multi-omic analyses in HGSOC patient tumors spanning a broad spectrum of purity. Methods: Seventy HGSOC patient tumors were selected exhibiting low to high tumor purity (20-90%) balanced by clinical outcomes. Whole genome sequencing (WGS), mRNA-seq, quantitative global proteomics, methylation array and reverse phase protein array analyses of Bulk Tumor and laser microdissected (LMD) Enriched Tumor (ET) cells separately for each case. Prognostic and homologous recombination deficient (HRD) expression signatures were validated in two independent cohorts. Results: Analysis of WGS in ET compared to WT resulted in significant increases in sensitivity to identify somatic SNV, indel, structural variants, and neoepitopes (SNV p = 4.8E−3; indel p = 7.7E−5; SV, p = 1.1E−8, neoepitopes, p= 1.0E−10). Following LMD, 63% of cases characterized as mesenchymal subtype (C4) in WT samples were reclassified to other molecular subtypes (1.0E−3) suggesting that historical HGSOC expression subtypes strongly reflect tumor purity. Analysis of paired primary and metastatic tumors demonstrated that WT proteomic profiles largely cluster by anatomic location while ET proteomic profiles co-cluster in a patient centric manner. Hierarchical cluster analysis identified patients with longer progression free survival associated with increased immune signatures and validated proteins correlating with tumor infiltrating lymphocytes (TILs) in 65 tumors collected from an independent cohort of 12 HGSOC patients, as well as with overall survival in an additional cohort of 126 HGSOC patients. We identified that homologous recombination deficient (HRD) tumors express transcriptomic and proteomic pathways associated with metabolism and oxidative phosphorylation that we validated in independent patient cohorts, including 69 HRD-positive HGSOC tumors. We further identified that polycomb complex protein BMI-1 is elevated in HR proficient (HRP) tumors, that elevated BMI-1 correlates with poor overall survival in HRP but not HRD HGSOC patients, and that HRP HGSOC cells exhibit increased sensitivity to BMI-1 inhibition. Conclusion: Proteogenomic alterations in HGSOC tumors uncovered using enrichment techniques highlight the importance of specimen preparation in the identification of tumor alterations. Our efforts provide insights into low purity HGSOC correlating TILs with improved disease prognosis, expression alterations associated with HRD status, and increased sensitivity of HRP tumor cells to BMI-1 inhibitors. Citation Format: George Larry Maxwell, Nicholas Bateman, Tamara Abulez, Anthony Soltis, Andrew McPherson, Seongmin Choi, Dale Garsed, Chunqiao Tian, Brian Hood, Kelly Conrads, Pang-ning Teng, Julie Oliver, Glenn Gist, Dave Mitchell, Tracy Litzi, Christopher Tarney, Clifton Dalgard, Matthew Wilkerson, Mariaelena Pierobon, Emmanuel Petricoin, Chunhua Yan, Daoud Meerzaman, Clara Bodelon, Nicolas Wentzensen, Jerry S. H. Lee, David Huntsman, Sohrab Shah, Craig Shriver, Neil Phippen, Kathleen Darcy, David Bowtell, Thomas Conrads. Proteogenomic analysis of enriched tumor epithelium identifies prognostic signatures and an increased dependency of homologous recombination proficient cells on bmi1 in high grade serous ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_2):Abstract nr PR-012.

We performed a deep proteogenomic analysis of bulk tumor and laser microdissection enriched tumor cell populations from high-grade serous ovarian cancer (HGSOC) tissue specimens spanning a broad spectrum of purity. We identified patients with longer progression-free survival had increased immune-related signatures and validated proteins correlating with tumor-infiltrating lymphocytes in 65 tumors from an independent cohort of HGSOC patients, as well as with overall survival in an additional 126 HGSOC patient cohort. We identified that homologous recombination deficient (HRD) tumors are enriched in pathways associated with metabolism and oxidative phosphorylation that we validated in independent patient cohorts. We further identified that polycomb complex protein BMI-1 is elevated in HR proficient (HRP) tumors, that elevated BMI-1 correlates with poor overall survival in HRP but not HRD HGSOC patients, and that HRP HGSOC cells are uniquely sensitive to BMI-1 inhibition.

Databases used for clinical interpretation in oncology rely on genetic data derived primarily from patients of European ancestry, leading to biases in cancer genetics research and clinical practice. One practical issue that arises in this context is the potential misclassification of multi-ancestral population variants as tumor-associated because they are not represented in reference genomes against which tumor sequencing data is aligned.To systematically find misclassified variants, we compared somatic variants in census genes from the Catalogue of Somatic Mutations in Cancer (COSMIC) V99 with multi-ancestral population variants from the Genome Aggregation Databases' Linkage Disequilibrium (GnomAD). By comparing genomic coordinates, reference, and alternate alleles, we could identify misclassified variants in genes associated with cancer.We found 192 of 208 genes in COSMIC's cancer-associated census genes (92.31%) to be associated with variant misclassifications. Among the 1,906,732 variants in COSMIC, 6,957 variants (0.36%) aligned with normal population variants in GnomAD, concerning for misclassification. The African / African American ancestral population included the greatest number of misclassified variants and also had the greatest number of unique misclassified variants.The direct, systematic comparison of variants from COSMIC for co-occurrence in GnomAD supports a more accurate interpretation of tumor sequencing data and reduces bias related to genomic ancestry.

Abstract Solid tumors develop through a complex series of genome and downstream expression alterations that interact with the local tissue microenvironment, leading to a transformed cell and malignant phenotype. With massive multi-omic data, recent proteogenomics studies have jointly analyzed RNA and protein expression to uncover new gene regulatory relationships; however, many of these studies focused on single tumor types and lack a generalizable view of joint RNA and protein expression. Here, we present the first pan-cancer analysis of sample-wise RNA to protein correlation (SRPC). We re-analyzed over 1,000 tumors across 10 tumor types from published proteogenomic data from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) Research Network. We identified a wide range of SRPC across all tumors (ρ range: -0.08 to 0.70, median: 0.45). We then analyzed tumor pathologic and molecular characteristics versus the range of SRPC. High SRPC tumors had high tumor purity by pathology review, by somatic DNA whole exome sequencing, and by RNA and protein purity scores. In contrast, low SRPC tumors had high immune cell and stromal cell expression scores as inferred by either protein or RNA based signatures. We observed marked differences in cell type populations estimated by expression in different SRPC tumor tranches (low SRPC: macrophages, endothelial cells, cancer-associated fibroblasts; high SRPC: CD4+ Th2 cells). Tumors expressed signaling pathways depending on their SRPC (low SRPC: hypoxia, inflammatory response, and KRAS signaling; high SRPC: DNA repair and E2F targets). SRPC also stratifies tumors with distinct somatic DNA alterations (low SRPC: HRAS and NF2; high SRPC: TP53, MEN1, high Tumor Mutational Burden and high DNA chromosomal instability). Finally, we found that cancer driver genes displayed divergent gene-wise RNA to protein correlations (GRPC) among tumor types with a median absolute deviation interquartile range of 0.1 - 0.2, suggesting tumor-type-specific regulation. In summary, divergent RNA and protein expression is driven, in part, by tumor microenvironment composition across tumor types. Tumors with a diverse cellular microenvironment display a summation of RNA and protein expression resulting from this cell type diversity leading to a low SRPC, while tumors predominated by tumor cells display coordinated RNA and protein expression levels resulting from a pure clonal or cell type leading to a high SRPC. This first deep analysis into sample-wise RNA to protein correlation represents a large proteogenomic community resource for informing biomarker analysis by modality and by tranches of tumor microenvironment. The views expressed in this abstract are solely of the authors and do not reflect the official policy of the Departments of Army/Navy/Air Force, Department of Defense, USUHS, HJF, or U.S. Government. Citation Format: Joseph LaMorte, Nicholas Bateman, Thomas Conrads, Robert F. Browning, Craig D. Shriver, Robert L. Kortum, Matthew D. Wilkerson. Divergent proteogenomic gene expression is driven by microenvironment across tumor types [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4944.

Abstract The expression subtypes of lung adenocarcinoma (LUAD) capture tumors with distinct pathway activity, mutations and histopathology and also differentiate clinical outcomes. The microenvironments of these subtypes, proximal-inflammatory (PI), proximal-proliferative (PP), and terminal respiratory unit (TRU), have been described generally as immune hot, immune moderate and immune cold, respectively, but otherwise have not been analyzed at high resolution. Here, we aimed to characterize and compare tumor microenvironments between LUAD subtypes. Using spatially barcoded arrays and cDNA libraries (10x Genomics), we sequenced the spatial transcriptomes of a 6.5mm2 plane of 14 LUAD tumors from the Applied Proteogenomics and Organizational Learning Outcomes (APOLLO) program. Spatial transcriptomes had a median of 3,560 spots and a median of 4,026 genes detected per spot. First, collapsing the spatial array to a bulk measurement per sample, we applied our published expression subtype predictor classifying 4 PI, 5 PP, and 5 TRU cases. We then decomposed each tumor’s spatial expression profile by unsupervised clustering, followed by signature scoring and collapsing into tumor, immune, and stroma tumor microenvironment (TME) components. Twelve of the fourteen tumors harbored multiple components while two tumors had one component. The region areas of TME components showed trends among the subtypes, with PI having the greatest immune area and PP having the greatest tumor area. Within each tumor, we calculated differentially-expressed genes between each TME component. Comparing TME genes to the subtype predictor genes, we found significant overlap (chi-square p &amp;lt;&amp;lt; 0.001). This indicates that genes that are variable among bulk tumors also have variability within tumors. We then predicted expression subtype for decomposed compartments. Five tumors had the same expression subtype across their TME components, which we refer to as single subtype tumors. However, six tumors had more than one expression subtype prediction among the tumor’s TME components, which we call ‘multi-subtype tumors’. Multi-subtype tumors had lower bulk subtype prediction scores than single-subtype tumors (p &amp;lt; 0.01), indicating that the TME diversity among tumors affects the bulk expression subtype. Interestingly, the six multi-subtype tumors were in the PP and PI subtypes, suggesting greater TME component diversity than TRU. Calculating the spatial compactness of the tumors through continuity indices, we found that PI subtype trended with greater intermixing of TME components. In summary, the bulk LUAD expression subtypes capture differences between tumors and within tumors related to the tumor microenvironment. The views expressed in this abstract are solely of the authors and do not reflect the official policy of the Departments of Army/Navy/Air Force, Department of Defense, USUHS, HJF, or U.S. Government. Citation Format: Shaoqiu He, Camille Alba, Savannah Kounelis-Wuillaume, Teri J. Franks, Martin L. Doughty, Robert F. Browning, Craig D. Shriver, Clifton L. Dalgard, APOLLO Research Network, Matthew D. Wilkerson. Spatial decomposition of lung adenocarcinoma expression subtypes reveals tumor microenvironment characteristics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1142.

Sickle cell trait (SCT), although generally a benign carrier state of hemoglobin S (HbAS), is a risk factor for exertional rhabdomyolysis (ERM), a rare but potentially fatal consequence of highly intense physical exercise, particularly among active-duty military personnel and high-performance athletes. The association between SCT and ERM is poorly understood. The objective of this study was to elucidate the genetic basis of ERM in an SCT-positive African American cohort. SCT-positive African Americans with a personal history of ERM (cases, n = 30) and without history of ERM (controls, n = 53) were enrolled in this study. Whole-genome sequencing was performed on DNA samples isolated from peripheral white blood cells. Participants' demographic, behavioral, and medical history information was obtained. An additional 131 controls were extracted from SCT-positive subjects of African descent from the 1000 Genomes Project. SCT carriers with ERM were characterized by myotoxicity features, significant muscle involvement dominated by muscle weakness, and severe pain and substantial increase in serum creatine kinase, with a mean value of 50,480 U/L. A distinctive feature of the SCT individuals with ERM was exertional collapse, which was reported in 53.3% of the cases in the study cohort. An important factor for the development of ERM was the duration and frequency of strenuous physical activity in the cases compared to the controls. Whole-genome sequencing identified 79,696 protein-coding variants. Genome-wide association analysis revealed that the p.C477R, rs115958260 variant in the SLC44A3 gene was significantly associated with ERM event in SCT-positive African Americans. The study results suggest that a combination of vigorous exercise and a genetic predisposing factor is involved in ERM.

Introduction Cutaneous leishmaniasis is a neglected vector-borne parasitic disease prevalent in 92 countries with approximately one million new infections annually. Interactions between vector saliva and the human host alter the response to infection and outcome of disease. Methods To characterize the human immunological responses developed against saliva of Phlebotomus duboscqi , a Leishmania major (L. major) vector, we repeatedly exposed the arms of 14 healthy U.S volunteers to uninfected P. duboscqi bites. Blood was collected a week after each exposure and used to assess total IgG antibodies against the proteins of P. duboscqi salivary gland homogenate (SGH) and the levels of IFN-gamma and IL-10 from peripheral blood mononuclear cells (PBMCs) stimulated with SGH or recombinant sand fly proteins. We analyzed skin punch biopsies of the human volunteer arms from the insect bite site and control skin site after multiple P. duboscqi exposures (four volunteers) using immunohistochemical staining. Results A variety of immediate insect bite skin reactions were observed. Late skin reactions to insect bites were characterized by macular hyperpigmentation and/or erythematous papules. Hematoxylin and eosin staining showed moderate mononuclear skin infiltrate with eosinophils in those challenged recently (within 2 months), eosinophils were not seen in biopsies with recall challenge (6 month post bites). An increase in plasma antigen-specific IgG responses to SGH was observed over time. Western Blot results showed strong plasma reactivity to five P. duboscqi salivary proteins. Importantly, volunteers developed a cellular immunity characterized by the secretion of IFN-gamma upon PBMC stimulation with P. duboscqi SGH and recombinant antigens. Discussion Our results demonstrate that humans mounted a local and systemic immune response against P. duboscqi salivary proteins. Specifically, PduM02/SP15-like and PduM73/adenosine deaminase recombinant salivary proteins triggered a Th1 type immune response that might be considered in future development of a potential Leishmania vaccine.

Abstract Introduction: Breast cancer (BC) in women &amp;lt; 40 years old accounts for ~5% of BC diagnosed in the U.S. However, young women have more aggressive tumors and worse outcomes, including higher rates of recurrence and lower disease-free and overall survival, compared to older women. To better understand mechanisms for these disparities, an integrated proteogenomic study of tumors from young (&amp;lt; 40) and older (≥ 60) women was performed through the Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) program. Methods: 34 pairs of retrospectively collected, untreated primary breast tumors from young and older women, matched by immunohistochemistry (IHC) subtype and race, were selected from the Clinical Breast Care Project. Median patient follow-up was 7 years. Tumor cells were enriched by laser microdissection and analyzed using RNA sequencing, whole genome sequencing, global proteomics, phosphoproteomics, and reverse phase protein array (RPPA). Molecular and clinical data from tumors from young and old patients in the TCGA-BC and METABRIC studies, matched by IHC subtype and race, were used to corroborate findings from our cohort. Results are presented comparing young women and their tumors to their older counterparts. Results: Young women have worse clinical outcome measured by progression-free interval. Despite matching for IHC subtypes, tumors from young women are enriched for intrinsic basal-like subtype, BRCA1/2 germline mutations, and had fewer invasive lobular BCs. Differentially enriched molecules and pathways: A number of significantly differentially expressed genes (DEGs) and proteins were detected, which were able to separate luminal subtypes of BC by patient age. IRS1 and IRS2 were enriched at both transcript and protein levels; IRS1 has been reported to promote tamoxifen resistance. We observed limited overlap of DEGs between the APOLLO, TCGA, and METABRIC datasets. In contrast, 14 of the 28 significantly upregulated Cancer Hallmark pathways were also enriched in TCGA-BC and METABRIC datasets; suggesting targeting pathways, vs genes, may be more effective for therapeutic intervention. Integrated pathway/network analysis: Integrated pathway analysis of RNA and protein levels identified 5 Hallmark pathways upregulated in younger women, including ER response and proliferative pathways, and 6 downregulated immune-response pathways; 10 of the 11 were supported by the public datasets. Immune scores were also lower. Kinase substrate enrichment analysis identified 4 kinases with increased activity in tumors from young women. ESR1/ER: We identified for the first time a significant reduction of ER protein expression while confirming previously reported lower ESR1 gene expression and copy number variations. Surprisingly, integrated pathway analysis identified elevation of early and late estrogen responses in young women. ER activation, indicated by phosphorylated ER (pS118) normalized to total ER protein, was elevated in LumA tumors from young women. Conclusions: This first-ever integrated proteogenomic study shows that BC in young women is enriched for more aggressive molecular subtypes and for genes that promote tamoxifen resistance, exhibits lower immune pathways and immune scores, and shows enhanced ER responses despite lower gene and protein expression of ER. These findings may contribute to the understanding of the molecular mechanisms underlying worse outcomes of BC in young women, and offer new insight to therapeutic strategies. Disclaimer: The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views, opinions or policies of USUHS, HJF, the DoD or the Departments of the Army, Navy or Air Force. Mention of trade names, commercial products, or organizations does not imply endorsement by the U.S. Government. Citation Format: Praveen Kumar Raj Kumar, Jianfang Liu, Anthony Soltis, Nicholas Bateman, Qingrong Chen, Lori Sturtz, Brenda Deyarmin, Mariaelena Pierobon, Tamara Abulez, Anupama Praveen-Kumar, Xijun Zhang, Trinh Nguyen, Chunhua Yan, Ying Hu, Kate Guion, Jeffrey Hooke, Albert Kovatich, Leigh Fantacone-Campbell, Brad Mostoller, Leonid Kvecher, Stella Somiari, Patricia Steeg, Sheila Rajagopal, Kathleen Darcy, Jerry Lee, Clifton Dalgard, Thomas Conrads, Emanuel Petricoin, Daoud Meerzaman, Matthew Wilkerson, APOLLO Research Network, Xiaoying Lin, Craig Shriver, Stanley Lipkowitz, Hai Hu. Proteogenomic characterization of primary invasive breast tumors from young women compared to matched tumors from older women [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-13-10.

Black women are at an increased risk to develop uterine leiomyomas (ULMs) and to experience worse disease prognosis compared to White women. Epidemiological and molecular factors have been identified as underlying these disparities, but there remains a paucity of deep, multi-omic analysis investigating molecular differences in ULMs from Black and White patients.

Lung cancer histologic diagnosis is clinically relevant because there are histology-specific treatment indications and contraindications. Histologic diagnosis can be challenging owing to tumor characteristics, and it has been shown to have less-than-ideal agreement among pathologists reviewing the same specimens. Microarray profiling studies using frozen specimens have shown that histologies exhibit different gene expression trends; however, frozen specimens are not amenable to routine clinical application. Herein, we developed a gene expression-based predictor of lung cancer histology for FFPE specimens, which are routinely available in clinical settings. Genes predictive of lung cancer histologies were derived from published cohorts that had been profiled by microarrays. Expression of these genes was measured by quantitative RT-PCR (RT-qPCR) in a cohort of patients with FFPE lung cancer. A histology expression predictor (HEP) was developed using RT-qPCR expression data for adenocarcinoma, carcinoid, small cell carcinoma, and squamous cell carcinoma. In cross-validation, the HEP exhibited mean accuracy of 84% and κ = 0.77. In separate independent validation sets, the HEP was compared with pathologist diagnoses on the same tumor block specimens, and the HEP yielded similar accuracy and precision as the pathologists. The HEP also exhibited good performance in specimens with low tumor cellularity. Therefore, RT-qPCR gene expression from FFPE specimens can be effectively used to predict lung cancer histology.

Astrocytes respond to central nervous system (CNS) injury and disease by transforming to a reactive astrogliosis cell state that can contribute to either CNS dysfunction or repair. Neuroinflammation is a powerful driver of a harmful A1 astrogliosis phenotype associated with in vitro neurotoxicity and histopathology in human neurodegenerative diseases. Here we report a protocol for the rapid development of a human cell culture model of neuroinflammatory astrogliosis using induced pluripotent stem cells (iPSCs).Using RNA sequencing and in vitro cell assays, we measured transcriptional and cellular effects of chronic exposure of human iPSC-derived astrocytes to the cytokines TNFα (tumor necrosis factor alpha) or IL-1β (interleukin-1 beta).We show TNFα and IL-1β induce pro-inflammatory gene signatures but by widely different magnitudes. TNFα treatment results in 606 differential expressed genes, the suppression of glutamate-uptake, and increased phagocytic activity in astrocyte cultures. In contrast, IL-1β effects are attenuated to 33 differential expressed genes and no significant effects on glutamate-uptake or increased phagocytic activity.Our approach demonstrates a rapid tool for modeling neuroinflammatory human astrocytic responses in nervous system trauma and disease. In particular, we reveal a model for robust TNFα-induced human astrogliosis suitable for the study of neurotoxic A1 astrocytes.

Uncertainty and inconsistency of gene structure annotation remain limitations on research in the genome era, frustrating both biologists and bioinformaticians, who have to sort out annotation errors for their genes of interest or to generate trustworthy datasets for algorithmic development. It is unrealistic to hope for better software solutions in the near future that would solve all the problems. The issue is all the more urgent with more species being sequenced and analyzed by comparative genomics – erroneous annotations could easily propagate, whereas correct annotations in one species will greatly facilitate annotation of novel genomes. We propose a dynamic, economically feasible solution to the annotation predicament: broad-based, web-technology-enabled community annotation, a prototype of which is now in use for Arabidopsis. Uncertainty and inconsistency of gene structure annotation remain limitations on research in the genome era, frustrating both biologists and bioinformaticians, who have to sort out annotation errors for their genes of interest or to generate trustworthy datasets for algorithmic development. It is unrealistic to hope for better software solutions in the near future that would solve all the problems. The issue is all the more urgent with more species being sequenced and analyzed by comparative genomics – erroneous annotations could easily propagate, whereas correct annotations in one species will greatly facilitate annotation of novel genomes. We propose a dynamic, economically feasible solution to the annotation predicament: broad-based, web-technology-enabled community annotation, a prototype of which is now in use for Arabidopsis.

Your Gene structure Annotation Tool for Eukaryotes (yrGATE) provides an Annotation Tool and Community Utilities for worldwide web-based community genome and gene annotation. Annotators can evaluate gene structure evidence derived from multiple sources to create gene structure annotations. Administrators regulate the acceptance of annotations into published gene sets. yrGATE is designed to facilitate rapid and accurate annotation of emerging genomes as well as to confirm, refine, or correct currently published annotations. yrGATE is highly portable and supports different standard input and output formats. The yrGATE software and usage cases are available at http://www.plantgdb.org/prj/yrGATE.

Hospitalized older adults are susceptible to complications termed "hazards of hospitalization" (HOH), which collectively result in poor patient outcomes. Previous research has shown that residents are not aware of their patients' risk factors for HOH. This study investigated the effect of an educational intervention to increase internal medicine interns' knowledge and self-efficacy of HOH and to improve their care of hospitalized older adults as measured by their documentation of HOH. Targeted learners were internal medicine interns on their geriatrics rotation at a large academic hospital in 2011 to 2012. The intervention covered 10 specific HOH: delirium, pressure ulcers, urinary incontinence and retention, functional decline, falls, suboptimal prescribing, dehydration and malnutrition, infection, depression, and inappropriate interventions. Knowledge and self-efficacy were measured before and after training. HOH documentation rates of interns who did and did not complete the training were compared over a preset 8-week period. Forty-two of 43 eligible interns completed the curriculum. After training, knowledge was significantly greater (approximately 1 more correct question out of 3, P < .001). Self-reported confidence in managing each hazard also significantly increased (13 questions on two 5-point Likert scales, P < .001). Trained interns had significantly more-frequent documentation of patients' activities of daily living, gait, and plan for functional decline prevention than interns who were not trained (P < .05). Conversely, documentation of instrumental activities of daily living was more frequent among interns who were not trained (P < .01). Implementation of an educational intervention was successful in improving educational and behavior change outcomes regarding HOH.

Increased mTORC1 signaling from TSC1/TSC2 inactivation is found in cancer and causes tuberous sclerosis complex (TSC). The role of mesenchymal-derived cells in TSC tumorigenesis was investigated through disruption of Tsc2 in craniofacial and limb bud mesenchymal progenitors. Tsc2cKO Prrx1-cre mice had shortened lifespans and extensive hamartomas containing abnormal tortuous, dilated vessels prominent in the forelimbs. Abnormalities were blocked by the mTORC1 inhibitor sirolimus. A Tsc2/mTORC1 expression signature identified in Tsc2-deficient fibroblasts was also increased in bladder cancers with TSC1 / TSC2 mutations in the TCGA database. Signature component Lgals3 encoding galectin-3 was increased in Tsc2-deficient cells and serum of Tsc2cKO Prrx1 -cre mice. Galectin-3 was increased in TSC-related skin tumors, angiomyolipomas, and lymphangioleiomyomatosis with serum levels in patients with lymphangioleiomyomatosis correlating with impaired lung function and angiomyolipoma presence. Our results demonstrate Tsc2-deficient mesenchymal progenitors cause aberrant morphogenic signals, and identify an expression signature including Lgals3 relevant for human disease of TSC1/TSC2 inactivation and mTORC1 hyperactivity.

Abstract Pathogenic mutations in fumarate hydratase ( FH ) drive hereditary leiomyomatosis and renal cell cancer (HLRCC) and increase the risk of developing uterine leiomyomas (ULMs). An integrated proteogenomic analysis of ULMs from HLRCC (n = 16; FH -mutation confirmed) and non-syndromic (NS) patients (n = 12) identified a significantly higher protein:transcript correlation in HLRCC (R = 0.35) vs. NS ULMs (R = 0.242, MWU p = 0.0015). Co-altered proteins and transcripts (228) included antioxidant response element (ARE) target genes, such as thioredoxin reductase 1 ( TXNRD1 ), and correlated with activation of NRF2-mediated oxidative stress response signaling in HLRCC ULMs. We confirm 185 transcripts previously described as altered between HLRCC and NS ULMs, 51 co-altered at the protein level and several elevated in HLRCC ULMs are involved in regulating cellular metabolism and glycolysis signaling. Furthermore, 367 S-(2-succino)cysteine peptides were identified in HLRCC ULMs, of which sixty were significantly elevated in HLRCC vs. NS ULMs (LogFC = 1.86, MWU p &lt; 0.0001). These results confirm and define novel proteogenomic alterations in uterine leiomyoma tissues collected from HLRCC patients and underscore conserved molecular alterations correlating with inactivation of the FH tumor suppressor gene.

Characterization of ancestry-linked peptide variants in disease-relevant patient tissues represents a foundational step to connect patient ancestry with disease pathogenesis. Nonsynonymous single-nucleotide polymorphisms encoding missense substitutions within tryptic peptides exhibiting high allele frequencies in European, African, and East Asian populations, termed peptide ancestry informative markers (pAIMs), were prioritized from 1000 genomes. In silico analysis identified that as few as 20 pAIMs can determine ancestry proportions similarly to >260K SNPs (R2 = 0.99). Multiplexed proteomic analysis of >100 human endometrial cancer cell lines and uterine leiomyoma tissues combined resulted in the quantitation of 62 pAIMs that correlate with patient race and genotype-confirmed ancestry. Candidates include a D451E substitution in GC vitamin D-binding protein previously associated with altered vitamin D levels in African and European populations. pAIMs will support generalized proteoancestry assessment as well as efforts investigating the impact of ancestry on the human proteome and how this relates to the pathogenesis of uterine neoplasms.

8008 Background: Morphology remains the best biomarker for chemotherapy selection in NSCLC. Both bevacizumab and pemetrexed (in first line) are FDA indicated for non-SC histology only, making precise diagnosis key, although data are few on the reproducibility of their categorization. The standard of care, consensus-based World Health Organization diagnostic classification system, Ed. 4 (WHOC) includes 44 diagnostic categories (DC), does not include immunohistochemical (IHC) data, and is not independently validated. In this study, we estimate the reproducibility of SC versus non-SC classification to be only moderately precise. Methods: Pathologists (P) assigned WHOC diagnoses to virtual H&amp;E slides from an incident surgical cohort of 96 primary lung tumors. At a power of 80% we estimated 24 P reviewing 48 slides each would allow for a reproducibility measure in the clinically useful range kappa=0.7, standard error=0.09. In addition to the 44 DC, we also considered the reproducibility of a simplified 10 category system and a chemotherapy-directed 2 class system. Results: 12 self-identified “lung experts” (E) and 12 community (C) P scored slides based on the 44 possible WHOC DC totaling 222 pathologist-pairs and 7130 slides-pairs. P rated confidence in their choices as: high 53%, somewhat 38%, and not confident 8%. 92% of slides were rated as having sufficient quality. Distribution of DC included SC 30% and adenocarcinoma 36%. Conclusions: To our knowledge this is the largest study ever performed of the WHOC, the only one to consider all 44 DC and to distinguish E vs C P. Although this model tests the reproducibility of the WHOC, not clinical lung cancer diagnoses, it shows that reproducible diagnosis of SC based on H&amp;E morphology alone is inadequate. In the era of histology guided therapy, it highlights the need for strict diagnostic criteria and confirmatory IHC stains in the diagnosis of SC. [Table: see text] No significant financial relationships to disclose.

7006 Background: A third of patients with non-small cell lung cancer are diagnosed with squamous cell carcinoma (SCC) histology. This report describes findings from the comprehensive genomic analyses of 178 SCC samples. Methods: The Cancer Genome Atlas (TCGA) is conducting DNA, RNA, and miRNA sequencing along with DNA copy number profiling, quantification of mRNA expression and promoter methylation on surgically resected samples from previously untreated patients with stage I-III SCC of the lung. Results: The demographics of 178 patients enrolled in the study: median age 68 years (range: 40-85); female 47 (26%) and history of tobacco smoking 171 (96%). Over 30 sites of significant somatic copy number alteration (SCNA) were identified. Exome sequencing of 178 lung SCC and matched normal samples revealed 13 significantly mutated genes with a False Discovery Rate (FDR) of &lt;0.01 and high expression levels, including TP53, CDKN2A, PTEN, KEAP1, and NFE2L2. Apart from the near universal loss of TP53 and CDKN2A, alterations in the NFE2L2/KEAP1 and PI3K/AKT pathways were found in 35% and 43% of tumors analyzed. mRNA expression profiling revealed four distinct expression subtypes, each one enriched with distinct mutations and SCNAs - classical (37%): NFE2L2 and KEAP1 mutations, FGFR kinase alterations, increased global methylation and the highest rate of tobacco use; basal (24%): alterations in FGFR kinases; secretory (24%): PDGFRA alterations; primitive (15%): RB1 mutations. Rearrangements involving several known tumor suppressors were detected by whole genome shotgun sequencing of 20 tumor/normal pairs and confirmed by RNA sequencing including PTEN, RB1, NOTCH1, NF1 and CDKN2A. CDKN2A loss by one of several mechanisms (deletion, mutation, rearrangement with loss of function and methylation) was observed in 72% of specimens. Potential therapeutic targets for clinical trials with currently available drugs were identified in 127 patients (75%). Conclusions: SCC of the lung is a distinct molecular subtype of lung cancer potentially amenable to distinct molecularly targeted therapies.

Castration Resistant Prostate Cancer (CRPC) is thought to be driven by a collaborative mechanism between TNF/NFB and TGFsignaling, leading to inflammation, Epithelial-to-Mesenchymal-Transition (EMT), and metastasis. Initially, TGFis a tumor suppressor, but in advanced metastatic disease it switches to being a tumor promoter. TGFBR2 may play a critical role in this collaboration, as its expression is driven by NFB and it is the primary receptor for TGF. We have previously reported that the cardenolide drug digitoxin blocks TNF/NFB-driven proinflammatory signaling. We therefore hypothesized that digitoxin might break the collaborative process between NFB and TGF by also inhibiting expression of TGFBR2. We therefore tested whether TGF-driven EMT and resulting metastases would be suppressed. Here we show, in vitro, that digitoxin inhibits NFB-driven TGFBR2 expression, as well as Vimentin and SNAI1 expression, while E-cadherin expression is elevated. In vivo, in a syngeneic, immune competent rat model of metastatic CRPC, we show that digitoxin also suppresses Tgfbr2 expression, as well as expression of other genes classically driven by NFkB, and of multiple EMT genes associated with metastasis. Concurrently, digitoxin suppresses tumor growth and metastasis in these animals, and prolongs survival. Gross tumor recurrence following tumor resection also appears prevented in ca 30% of cases. While the existence of a collaboration between NFB and TGFto drive EMT and metastasis has previously been appreciated, we show here, for the first time, that chronic, low concentrations of digitoxin are able to block CRPC tumor progression, EMT and the ensuing metastatic disease.

Abstract Background Several small molecule corrector and potentiator drugs have recently been licensed for Cystic Fibrosis (CF) therapy. However, other aspects of the disease, especially inflammation, are less effectively treated by these drugs. We hypothesized that small molecule drugs could function either alone or as an adjuvant to licensed therapies to treat these aspects of the disease, perhaps emulating the effects of gene therapy in CF cells. The cardiac glycoside digitoxin, which has been shown to inhibit TNFα/NFκB signaling in CF lung epithelial cells, may serve as such a therapy. Methods IB3–1 CF lung epithelial cells were treated with different Vertex (VX) drugs, digitoxin, and various drug mixtures, and ELISA assays were used to assess suppression of baseline and TNFα-activated secretion of cytokines and chemokines. Transcriptional responses to these drugs were assessed by RNA-seq and compared with gene expression in AAV-[ wildtype ]CFTR-treated IB3–1 (S9) cells. We also compared in vitro gene expression signatures with in vivo data from biopsied nasal epithelial cells from digitoxin-treated CF patients. Results CF cells exposed to digitoxin exhibited significant suppression of both TNFα/NFκB signaling and downstream secretion of IL-8, IL-6 and GM-CSF, with or without co-treatment with VX drugs. No evidence of drug-drug interference was observed. RNA-seq analysis showed that gene therapy-treated CF lung cells induced changes in 3134 genes. Among these, 32.6% were altered by digitoxin treatment in the same direction. Shared functional gene ontology themes for genes suppressed by both digitoxin and gene therapy included inflammation (84 gene signature), and cell-cell interactions and fibrosis (49 gene signature), while genes elevated by both were enriched for epithelial differentiation (82 gene signature). A new analysis of mRNA data from digitoxin-treated CF patients showed consistent trends in expression for genes in these signatures. Conclusions Adjuvant gene therapy-emulating activities of digitoxin may contribute to enhancing the efficacy of currently licensed correctors and potentiators in CF patients.

Abstract Purpose: The objective of this study is to characterize the role of miRNAs in the classification of head and neck squamous cell carcinoma (HNSCC). Experimental Design: Here, we analyzed 562 HNSCC samples, 88 from a novel cohort and 474 from The Cancer Genome Atlas, using miRNA microarray and miRNA sequencing, respectively. Using an integrative correlations method followed by miRNA expression–based hierarchical clustering, we validated miRNA clusters across cohorts. Evaluation of clusters by logistic regression and gene ontology approaches revealed subtype-based clinical and biological characteristics. Results: We identified two independently validated and statistically significant (P &amp;lt; 0.01) tumor subtypes and named them “epithelial” and “stromal” based on associations with functional target gene ontology relating to differing stages of epithelial cell differentiation. miRNA-based subtypes were correlated with individual gene expression targets based on miRNA seed sequences, as well as with miRNA families and clusters including the miR-17 and miR-200 families. These correlated genes defined pathways relevant to normal squamous cell function and pathophysiology. miRNA clusters statistically associated with differential mutation patterns including higher proportions of TP53 mutations in the stromal class and higher NSD1 and HRAS mutation frequencies in the epithelial class. miRNA classes correlated with previously reported gene expression subtypes, clinical characteristics, and clinical outcomes in a multivariate Cox proportional hazards model with stromal patients demonstrating worse prognoses (HR, 1.5646; P = 0.006). Conclusions: We report a reproducible classification of HNSCC based on miRNA that associates with known pathologically altered pathways and mutations of squamous tumors and is clinically relevant.

The eXtensible Genome Data Broker (xGDB) provides a software infrastructure consisting of integrated tools for the storage, display, and analysis of genome features in their genomic context. Common features include gene structure annotations, spliced alignments, mapping of repetitive sequence, and microarray probes, but the software supports inclusion of any property that can be associated with a genomic location. The xGDB distribution and user support utilities are available online at the xGDB project website, http://xgdb.sourceforge.net/.

Whole genome shotgun sequencing produces increasingly higher coverage of a genome with random sequence reads. Progressive whole genome assembly and eventual finishing sequencing is a process that typically takes several years for large eukaryotic genomes. In the interim, all sequence reads of public sequencing projects are made available in repositories such as the NCBI Trace Archive. For a particular locus, sequencing coverage may be high enough early on to produce a reliable local genome assembly. We have developed software, Tracembler, that facilitates in silico chromosome walking by recursively assembling reads of a selected species from the NCBI Trace Archive starting with reads that significantly match sequence seeds supplied by the user.Tracembler takes one or multiple DNA or protein sequence(s) as input to the NCBI Trace Archive BLAST engine to identify matching sequence reads from a species of interest. The BLAST searches are carried out recursively such that BLAST matching sequences identified in previous rounds of searches are used as new queries in subsequent rounds of BLAST searches. The recursive BLAST search stops when either no more new matching sequences are found, a given maximal number of queries is exhausted, or a specified maximum number of rounds of recursion is reached. All the BLAST matching sequences are then assembled into contigs based on significant sequence overlaps using the CAP3 program. We demonstrate the validity of the concept and software implementation with an example of successfully recovering a full-length Chrm2 gene as well as its upstream and downstream genomic regions from Rattus norvegicus reads. In a second example, a query with two adjacent Medicago truncatula genes as seeds resulted in a contig that likely identifies the microsyntenic homologous soybean locus.Tracembler streamlines the process of recursive database searches, sequence assembly, and gene identification in resulting contigs in attempts to identify homologous loci of genes of interest in species with emerging whole genome shotgun reads. A web server hosting Tracembler is provided at http://www.plantgdb.org/tool/tracembler/, and the software is also freely available from the authors for local installations.

Abstract Invasive lobular breast cancer (ILC) is the second most common histological subtype of breast cancer accounting for 10-15% of invasive breast tumors. ILC is typically ER+ and beyond the known mutation and/or loss of E-cadherin function, which contributes to a highly discohesive morphology, little is known about the additional mechanisms driving ILC tumorigenesis, or alterations that differentiate ILC from invasive ductal carcinomas (IDC). Methods A dataset of 817 breast tumors from the TCGA Project, including 490 IDC, 127 ILC and 88 samples with a mixed IDC-ILC histology, were profiled on six genomic platforms to develop a comprehensive atlas of mutational, epigenetic, transcriptional and proteomic data. Integrative genomic analyses, both supervised and unsupervised, of ILC tumors and across histological subtypes were performed to identify genomic drivers of ILC oncogenesis. Results Comprehensive multi-platform analyses identified distinct molecular events associated with ILC tumors. As expected, lack of E-cadherin protein, as determined by Reverse Phase Protein Array (RPPA), and CDH1 mRNA expression was uniformly observed in ILC cases associated with distinct alterations targeting CDH1. In addition to previously reported CDH1 and PIK3CA mutations, we identified a number of novel ILC-enriched recurrent mutations targeting PTEN, RUNX1, TBX3, and FOXA1. An increased incidence of PTEN inactivating events, both mutations and copy number changes, were identified in ILC (13%) compared to IDC ER+ (7%), which corresponded with altered PTEN protein expression. These alterations were largely mutually exclusive with PIK3CA mutations and correlate with increased Akt activation as evident by increased Akt phosphorylation (pS473 and pT308), thus identifying a potential therapeutic opportunity for ILC patients. GATA3 signaling, which regulates epithelial cell differentiation, is frequently altered in luminal/ER+ breast cancers. Our analyses determined GATA3 mutations are more frequent in IDC luminal tumors as compared to ILC (19 % vs 5%). ILC luminal tumors show significantly lower GATA3 protein expression, but a higher frequency of mutations in FOXA1 (9% vs 2% in Luminal IDC), a transcription factor required to promote ER transcriptional programs. Within ILC tumors, FOXA1 mutations were found to cluster into a specific region of the Forkhead (FK) DNA binding domain. A broader analysis of FOXA1 mutations in breast and prostate cancer confirm two specific hotspots in the FK domain and the C-terminal transactivation domain. Interestingly, these mutational classes are associated with distinct transcriptional changes suggesting different functional effects. Finally, mRNA-seq analyses identified three robust molecular subclasses that are characterized by distinct genetic, genomic and proteomic patterns, including an increased immune-related group (Class 2), as well as differences in prognosis. Conclusions In this study, we developed a comprehensive atlas of genomic alterations that reveals key molecular differences differentiating ILC (FOXA1) from IDC (GATA3) tumorigenesis, a potential therapeutic target for ILC (Akt), and novel ILC subclasses based on underlying biological events. These findings provide further insight into the molecular heterogeneity of ER+ breast cancer. Citation Format: Giovanni Ciriello, Michael L Gatza, Katherine A Hoadley, Hailei Zhang, Suhn K Rhie, Reanne Bowlby, Matthew D Wilkerson, Cyriac Kandoth, Michael McLellan, Andrew Cherniack, Peter W Laird, Chris Sander, Tari A King, Charles M Perou. Comprehensive molecular characterization of invasive lobular breast tumors [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr S2-04.

Objective: The aim of this study was to identify serum microRNA (miRNA) biomarkers that indicate deployment-associated exposures in service members at military installations with open burn pits. Another objective was to determine detection rates of miRNAs in Department of Defense Serum Repository (DoDSR) samples with a high-throughput methodology. Methods: Low-volume serum samples (n = 800) were profiled by miRNA-capture isolation, pre-amplification, and measurement by a quantitative PCR-based OpenArray platform. Normalized quantitative cycle values were used for differential expression analysis between groups. Results: Assay specificity, dynamic range, reproducibility, and detection rates by OpenArray passed target desired specifications. Serum abundant miRNAs were consistently measured in study specimens. Four miRNAs were differentially expressed in the case deployment group subjects. Conclusions: miRNAs are suitable RNA species for biomarker discovery in the DoDSR serum specimens. Serum miRNAs are candidate biomarkers for deployment and environmental exposure in military service members.

BackgroundChronic tobacco smoke exposure results in a broad range of lung pathologies including emphysema, airway disease and parenchymal fibrosis as well as a multitude of extra-pulmonary comorbidities. Prior work using CT imaging has identified several clinically relevant subgroups of smoking related lung disease, but these investigations have generally lacked organ specific molecular correlates.Research QuestionCan CT imaging be used to identify clinical phenotypes of smoking related lung disease that have specific bronchial epithelial gene expression patterns to better understand disease pathogenesis?Study Design and MethodsUsing K-means clustering, we clustered participants from the COPDGene study (n = 5,273) based on CT imaging characteristics and then evaluated their clinical phenotypes. These clusters were replicated in the Detection of Early Lung Cancer Among Military Personnel (DECAMP) cohort (n = 360), and were further characterized using bronchial epithelial gene expression.ResultsThree clusters (preserved, interstitial predominant and emphysema predominant) were identified. Compared to the preserved cluster, the interstitial and emphysema clusters had worse lung function, exercise capacity and quality of life. In longitudinal follow-up, individuals from the emphysema group had greater declines in exercise capacity and lung function, more emphysema, more exacerbations, and higher mortality. Similarly, genes involved in inflammatory pathways (tumor necrosis factor-α, interferon-β) are more highly expressed in bronchial epithelial cells from individuals in the emphysema cluster, while genes associated with T-cell related biology are decreased in these samples. Samples from individuals in the interstitial cluster generally had intermediate levels of expression of these genes.InterpretationUsing quantitative CT imaging, we identified three groups of individuals in older ever-smokers that replicate in two cohorts. Airway gene expression differences between the three groups suggests increased levels of inflammation in the most severe clinical phenotype, possibly mediated by the tumor necrosis factor-α and interferon-β pathways.Clinical Trial RegistrationCOPDGene (NCT00608764), DECAMP-1 (NCT01785342), DECAMP-2 (NCT02504697) Chronic tobacco smoke exposure results in a broad range of lung pathologies including emphysema, airway disease and parenchymal fibrosis as well as a multitude of extra-pulmonary comorbidities. Prior work using CT imaging has identified several clinically relevant subgroups of smoking related lung disease, but these investigations have generally lacked organ specific molecular correlates. Can CT imaging be used to identify clinical phenotypes of smoking related lung disease that have specific bronchial epithelial gene expression patterns to better understand disease pathogenesis? Using K-means clustering, we clustered participants from the COPDGene study (n = 5,273) based on CT imaging characteristics and then evaluated their clinical phenotypes. These clusters were replicated in the Detection of Early Lung Cancer Among Military Personnel (DECAMP) cohort (n = 360), and were further characterized using bronchial epithelial gene expression. Three clusters (preserved, interstitial predominant and emphysema predominant) were identified. Compared to the preserved cluster, the interstitial and emphysema clusters had worse lung function, exercise capacity and quality of life. In longitudinal follow-up, individuals from the emphysema group had greater declines in exercise capacity and lung function, more emphysema, more exacerbations, and higher mortality. Similarly, genes involved in inflammatory pathways (tumor necrosis factor-α, interferon-β) are more highly expressed in bronchial epithelial cells from individuals in the emphysema cluster, while genes associated with T-cell related biology are decreased in these samples. Samples from individuals in the interstitial cluster generally had intermediate levels of expression of these genes. Using quantitative CT imaging, we identified three groups of individuals in older ever-smokers that replicate in two cohorts. Airway gene expression differences between the three groups suggests increased levels of inflammation in the most severe clinical phenotype, possibly mediated by the tumor necrosis factor-α and interferon-β pathways. COPDGene (NCT00608764), DECAMP-1 (NCT01785342), DECAMP-2 (NCT02504697) Chronic tobacco smoke exposure results in a broad range of lung diseases that includes emphysema, airway disease, parenchymal fibrosis, and a multitude of extrapulmonary comorbidities.1Leopold J.G. Gough J. The centrilobular form of hypertrophic emphysema and its relation to chronic bronchitis.Thorax. 1957; 12: 219-235Crossref PubMed Scopus (149) Google Scholar, 2Hernandez J.A. Anderson A.E. Holmes W.L. Foraker A.G. Pulmonary parenchymal defects in dogs following prolonged cigarette smoke exposure.Am Rev Respir Dis. 1966; 93: 78-83PubMed Google Scholar, 3Divo M.J. Casanova C. Marin J.M. et al.COPD comorbidities network.Eur Respir J. 2015; 46: 640-650Crossref PubMed Scopus (94) Google Scholar Identification of more homogenous subsets of disease with the use of tools such as CT imaging may better enable clinical, epidemiologic, and genetic investigation. Prior work in this area has identified several clinically relevant subgroups,4Castaldi P.J. Dy J. Ross J. et al.Cluster analysis in the COPDGene study identifies subtypes of smokers with distinct patterns of airway disease and emphysema.Thorax. 2014; 69: 415-422Crossref PubMed Scopus (104) Google Scholar, 5Garcia-Aymerich J. Gómez F.P. Benet M. et al.Identification and prospective validation of clinically relevant chronic obstructive pulmonary disease (COPD) subtypes.Thorax. 2011; 66: 430-437Crossref PubMed Scopus (226) Google Scholar, 6Rennard S.I. Chronic obstructive pulmonary disease: linking outcomes and pathobiology of disease modification.Proc Am Thorac Soc. 2006; 3: 276-280Crossref PubMed Scopus (37) Google Scholar, 7Rennard S.I. Locantore N. Delafont B. et al.Identification of five chronic obstructive pulmonary disease subgroups with different prognoses in the ECLIPSE cohort using cluster analysis.Ann Am Thorac Soc. 2015; 12: 303-312Crossref PubMed Scopus (98) Google Scholar, 8Sieren J.P. Newell J.D. Barr R.G. et al.SPIROMICS protocol for multicenter quantitative computed tomography to phenotype the lungs.Am J Respir Crit Care Med. 2016; 194: 794-806Crossref PubMed Scopus (126) Google Scholar but these investigations generally have lacked organ-specific molecular correlates. We sought to leverage clinical and imaging data from a large research cohort, the COPDGene Study, combined with clinical and bronchial epithelial gene expression data from the Detection of Early Lung Cancer Among Military Personnel (DECAMP) Study to identify smoking-related lung disease subgroups and to begin to determine their biologic differences. The COPDGene Study (NCT00608764) cohort has been described in detail previously.9Regan E.A. Hokanson J.E. Murphy J.R. et al.Genetic epidemiology of COPD (COPDGene) study design.COPD. 2010; 7: 32-43Crossref PubMed Scopus (726) Google Scholar Briefly, it is a multicenter longitudinal observational investigation of smokers that is focused on the epidemiologic and genetic factors associated with COPD.10American Thoracic SocietyStandardization of spirometry, 1994 Update.Am J Respir Crit Care Med. 1995; 152: 1107-1136Crossref PubMed Scopus (6241) Google Scholar, 11ATS Committee on Proficiency Standards for Clinical Pulmonary Function LaboratoriesATS statement: guidelines for the six-minute walk test.Am J Respir Crit Care Med. 2002; 166: 111-117Crossref PubMed Scopus (7335) Google Scholar, 12Kim D.K. Jacobson F.L. Washko G.R. et al.Clinical and radiographic correlates of hypoxemia and oxygen therapy in the COPDGene Study.Respir Med. 2011; 105: 1211-1221Abstract Full Text Full Text PDF PubMed Scopus (29) Google Scholar, 13Mahler D.A. Wells C.K. Evaluation of clinical methods for rating dyspnea.Chest. 1988; 93: 580-586Abstract Full Text Full Text PDF PubMed Scopus (996) Google Scholar, 14Jones P.W. Quirk F.H. Baveystock C.M. The St. George’s Respiratory Questionnaire.Respir Med. 1991; 85: 25-31Abstract Full Text PDF PubMed Scopus (1347) Google Scholar The baseline enrollment of 10,306 COPDGene participants occurred between October 2006 and January 2011. All participants were invited to return for 5- and 10-year follow-up visits. They are also followed longitudinally through the longitudinal follow-up program. For this study, analyses were limited to those individuals who had completed both baseline and 5-year follow-up visits. The DECAMP Study is a multicenter consortium comprised of 15 military treatment facilities, Veterans Affairs hospitals, and academic centers across the United States. Participants were recruited into one of two study protocols, designated as DECAMP-1 (NCT01785342) and DECAMP-2 (NCT02504697).15Billatos E. Duan F. Moses E. et al.Detection of early lung cancer among military personnel (DECAMP) consortium: study protocols.BMC Pulm Med. 2019; 19: 59Crossref PubMed Scopus (8) Google Scholar Study participants of DECAMP-1 were adults aged ≥45 years with indeterminate pulmonary nodules and a heavy smoking history. Study participants of DECAMP-2 were aged 50 to 79 years with a heavy smoking history and a family history of lung cancer or a personal history of COPD. Additional details regarding the study design, institutional review board approval (e-Tables 1, 2), biospecimen collection, and CT image acquisition protocols are available in the Online Supplement. The objective imaging measurements used for cluster definition in both cohorts were obtained by previously defined methods. The breadth of possible quantitative imaging measures that could be used to define clusters of individuals with cigarette smoking-related lung diseases is beyond the scope of this study. Based on prior experience and expertise in this area, we selected a parsimonious list of imaging features to attempt to represent the breadth of both pulmonary and extrapulmonary quantitative CT metrics of lung disease.16Sanders K.J.C. Ash S.Y. Washko G.R. Mottaghy F.M. Schols A.M.W.J. Imaging approaches to understand disease complexity: chronic obstructive pulmonary disease as a clinical model.J Appl Physiol. 2017; 124: 512-520Crossref PubMed Scopus (3) Google Scholar, 17Albert R.K. Connett J. Bailey W.C. et al.Azithromycin for prevention of exacerbations of COPD.N Engl J Med. 2011; 365: 689-698Crossref PubMed Scopus (880) Google Scholar, 18Anzueto A, Heijdra Y, Hurst JR. Controversies in COPD. European Respiratory Society; 2015.Google Scholar, 19Washko G.R. Diagnostic imaging in COPD.Semin Respir Crit Care Med. 2010; 31: 276-285Crossref PubMed Scopus (47) Google Scholar These included (1) the objective characterization of interstitial features and emphysema-like tissue with the use of a local histogram-based technique, (2) the measurement of pectoralis muscle area (expressed in square centimeters) that is performed on a single axial image above the level of the aortic arch, and (3) airway wall thickness as defined by the mean thickness of 6 segmental airways from each subject.20Diaz A.A. Zhou L. Young T.P. et al.Chest CT measures of muscle and adipose tissue in COPD: gender-based differences in content and in relationships with blood biomarkers.Acad Radiol. 2014; 21: 1255-1261Abstract Full Text Full Text PDF PubMed Scopus (27) Google Scholar, 21McDonald M.-L.N. Diaz A.A. 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Harmouche R. Ross J.C. et al.Interstitial features at chest CT enhance the deleterious effects of emphysema in the COPDGene Cohort.Radiology. 2018; 288: 600-609Crossref PubMed Scopus (18) Google Scholar, 26Kim V. Desai P. Newell J.D. et al.Airway wall thickness is increased in COPD patients with bronchodilator responsiveness.Respir Res. 2014; 15: 84Crossref PubMed Scopus (26) Google Scholar, 27Putman R.K. Hatabu H. Araki T. et al.Association between interstitial lung abnormalities and all-cause mortality.JAMA. 2016; 315: 672-681Crossref PubMed Scopus (207) Google Scholar, 28Hunninghake G.M. Hatabu H. Okajima Y. et al.MUC5B promoter polymorphism and interstitial lung abnormalities.N Engl J Med. 2013; 368: 2192-2200Crossref PubMed Scopus (258) Google Scholar, 29Washko G.R. Lynch D.A. Matsuoka S. et al.Identification of early interstitial lung disease in smokers from the COPDGene Study.Acad Radiol. 2010; 17: 48-53Abstract Full Text Full Text PDF PubMed Scopus (133) Google Scholar Further details and supplemental analyses with an expanded list of quantitative measures are available in the Online Supplement. Changes in the airways and lung parenchyma and extrapulmonary tissues, such as the thoracic musculature, have been shown to be related both directly to cigarette smoke exposure and, when measured using quantitative CT imaging, to clinical outcomes and disease pathophysiologic condition.16Sanders K.J.C. Ash S.Y. Washko G.R. Mottaghy F.M. Schols A.M.W.J. Imaging approaches to understand disease complexity: chronic obstructive pulmonary disease as a clinical model.J Appl Physiol. 2017; 124: 512-520Crossref PubMed Scopus (3) Google Scholar Cluster analysis was performed with the use of a parsimonious set of variables that were selected to represent the breadth of the airway, lung parenchyma, and extrapulmonary processes that are evident in smokers. The imaging features were log-transformed and standardized as needed to address distribution skewness and range of each variable and differences between cohorts related to technical differences in image acquisition and reconstruction. K-means clustering was then applied to these variables to group the subjects into clusters. The optimum number of clusters was determined with a combination of the Silhouette and Elbow methods (e-Fig 1). Further details regarding methods of both the clustering, including variable selection, and the statistical analyses that compare the clusters are available in the Online Supplement. Details regarding RNA isolation, sequencing, data pre-processing, and gene expression analysis are available in the online supplement. From the COPDGene cohort, a total of 5,273 subjects completed both the baseline and 5-year follow-up visits and had CT imaging data available. These were used for the derivation of imaging clusters. Of these, 5,067 subjects had complete clinical data, and 4,954 subjects had complete mortality data. From the DECAMP study, a total of 360 subjects (169 from DECAMP-1 and 191 from DECAMP-2) had imaging data available and were used to replicate the imaging clusters. Of these, 146 subjects had bronchial epithelial samples available for bulk-RNA sequencing. Detailed demographic data on the subjects from both cohorts are presented in Table 1.Table 1Cohort Characteristics for the COPDGene and Detection of Early Lung Cancer Among Military Personnel StudiesStudyPreservedInterstitial PredominantEmphysema PredominantPaBased on analysis of variance for continuous variables and chi-square test for categoric variables.COPDGene No.2,6231,910740… Clinical characteristicsAge, mean (SD), y60.22 (8.64)59.97 (9.10)65.57 (7.70)<.001Male, No. (%)987 (37.6)1,364 (71.4)431 (58.2)<.001Black, No. (%)592 (22.6)675 (35.3)120 (16.2)<.001Current smoker, No. (%)1,144 (43.6)1,087 (56.9)153 (20.7)<.001Smoking exposure, mean (SD), pack-y39.11 (21.09)48.35 (28.14)55.57 (26.81)<.001BMI, mean (SD), kg/m227.92 (5.56)30.97 (6.22)25.47 (5.00)<.001FEV1, mean (SD), % predicted86.58 (20.07)73.14 (22.08)40.62 (19.91)<.001 Longitudinal follow upTime between phase 1 and phase 2 visits, mean (SD), y5.35 (0.52)5.34 (0.56)5.31 (0.48).409Total duration of follow up, mean (SD), y6.85 (1.83)6.18 (2.18)5.67 (2.43)<.001Died, No. (%)232 (9.3)323 (18.4)299 (42.5)<.001 Radiologic measuresInterstitial features, mean (SD), % lung4.55 (2.66)7.89 (5.37)5.34 (3.27)<.001Emphysema, mean (SD), % lung3.66 (5.42)4.97 (6.63)48.65 (15.22)<.001Pectoralis muscle area, mean (SD), cm236.26 (12.38)48.64 (16.66)30.94 (10.63)<.001Airway wall thickness, mean (SD), mm0.91 (0.13)1.25 (0.19)1.08 (0.22)<.001Detection of Early Lung Cancer Among Military Personnel No.14115366 Clinical characteristicsAge, mean (SD), y63.91 (8.11)66.14 (7.63)68.11 (6.35).001Male, No. (%)97 (68.8)131 (85.6)58 (87.9)<.001Black, No. (%)13 (10.7)32 (22.4)12 (19.7).041Current smoker, No. (%)68 (51.5)64 (45.1)24 (38.7).227Smoking exposure, mean (SD), pack-y47.01 (25.89)49.08 (25.51)52.49 (26.56).381BMI, mean (SD), kg/m227.49 (6.01)28.52 (6.13)24.40 (5.40)<.001FEV1, mean (SD), % predicted80.13 (17.27)73.49 (18.12)54.61 (19.61)<.001 Radiologic measuresInterstitial features, mean (SD), % lung7.06 (4.50)12.62 (9.31)6.81 (8.18)<.001Emphysema, mean (SD), % lung2.81 (2.77)13.08 (8.32)52.18 (16.60)<.001Pectoralis muscle area, mean (SD), cm243.04 (13.62)47.60 (12.87)39.37 (10.08)<.001Airway wall thickness, mean (SD), mm2.10 (0.35)2.22 (0.35)2.01 (0.36)<.001Comparisons of the absolute values of imaging variables between cohorts are limited due to technical differences in image acquisition and reconstruction.a Based on analysis of variance for continuous variables and chi-square test for categoric variables. Open table in a new tab Comparisons of the absolute values of imaging variables between cohorts are limited due to technical differences in image acquisition and reconstruction. Using quantitative imaging features, we identified three distinct clusters of COPDGene participants that were labeled based on their parenchymal phenotype: preserved, interstitial predominant, and emphysema predominant (Figs 1, 2, 3A). From a CT imaging standpoint, the individuals in the preserved cluster generally had the lowest amount of parenchymal abnormalities (emphysema and interstitial features) and had normal airway wall-thickness. Those individuals in the emphysema cluster demonstrated the highest emphysema scores and mildly thickened airway walls, and those individuals in the interstitial predominant cluster had the highest amount of interstitial changes and highest airway wall-thickness.Figure 2Cluster Assignment Using Principal Component Analysis. Overlap of the Detection of Early Lung Cancer Among Military Personnel imaging clusters projected onto the first two principal components of the COPDGene imaging features. DECAMP = Detection of Early Lung Cancer Among Military Personnel; PC1 = principal component 1; PC2 = principal component 2.View Large Image Figure ViewerDownload Hi-res image Download (PPT)Figure 3A-B, Comparison of Imaging Characteristics of the Clusters in the COPDGene and Detection of Early Lung Cancer Among Military Personnel Cohorts. A, The imaging features used in the identification of the patient clusters in COPDGene were compared between patients assigned to each of the three clusters. B, The same imaging clusters were compared between DECAMP patients assigned to each of the three clusters. Global differences for each imaging feature among the three clusters were assessed using analysis of variance and found to be statistically significantly different (P < .001). Pairwise differences were assessed with the use of t-tests. Two asterisks indicate P ≤ .01; four asterisks indicate P ≤ .0001. ns = not significant at P > .05.View Large Image Figure ViewerDownload Hi-res image Download (PPT)Figure 3A-B, Comparison of Imaging Characteristics of the Clusters in the COPDGene and Detection of Early Lung Cancer Among Military Personnel Cohorts. A, The imaging features used in the identification of the patient clusters in COPDGene were compared between patients assigned to each of the three clusters. B, The same imaging clusters were compared between DECAMP patients assigned to each of the three clusters. Global differences for each imaging feature among the three clusters were assessed using analysis of variance and found to be statistically significantly different (P < .001). Pairwise differences were assessed with the use of t-tests. Two asterisks indicate P ≤ .01; four asterisks indicate P ≤ .0001. ns = not significant at P > .05.View Large Image Figure ViewerDownload Hi-res image Download (PPT) With regards to clinical characteristics (Fig 4A), individuals in the preserved cluster group tended to have normal spirometry, normal 6-minute walk distance, and preserved respiratory health quality of life. Individuals in the emphysema cluster group tended to have expiratory airflow obstruction, reduced 6-minute walk distance, and the lowest respiratory health quality of life, with the exception that the peripheral measures of inflammation the baseline clinical disease severity of those individuals in the interstitial cluster were generally intermediate between the preserved and emphysema clusters (Figs 4A, 5). In addition, the emphysema cluster had the highest mortality rate followed by the interstitial cluster and then the preserved cluster (Fig 4B, C). Similar findings were present when an expanded set of imaging features was used to define the clusters (e-Figs 2, 3) and the majority of individuals (75.5%) were assigned to the same feature-based cluster using when clustered using the expanded imaging variables as they were with the primary imaging variables (e-Table 2).Figure 4A-C, Comparison of Clinical Characteristics and Mortality Rates of the Clusters in the COPDGene Cohort. A, The clinical characteristics identified in COPDGene were compared among the three clusters. Global differences for each clinical characteristic among the three clusters were assessed with the use of analysis of variance and found to be statistically significantly different (P < .001). Pairwise differences were assessed with the use of t-tests without adjustment for multiple comparisons. Four asterisks indicate P ≤ .0001. B, The survival rate of the three clusters identified in COPDGene is demonstrated in this Kaplan-Meier curve. Individuals in the emphysema-predominant cluster had the lowest 5-year survival rate; individuals in the preserved cluster had the highest 5-year survival rate. C, The inset table shows the results of multivariable Cox regression analyses that compared the interstitial predominant cluster and emphysema cluster with the preserved cluster. Note that these analyses were adjusted for age, sex, race, smoking status, and FEV1 at baseline. SGRQ = St. George's Respiratory Questionnaire.View Large Image Figure ViewerDownload Hi-res image Download (PPT)Figure 5A-B, Peripheral Eosinophilia and Inflammation in the COPDGene Cohort. A, The percent of peripheral WBCs that are eosinophils by imaging cluster. B, C-reactive protein by imaging cluster. Global differences for each biomarker among the three clusters were assessed with the use of analysis of variance and found to be statistically significantly different for C-reactive protein (P = .003) and not significant for eosinophilia (P = .05). Pairwise differences were assessed with the use of t-tests without adjustment for multiple comparisons. One asterisk indicates P ≤ .05; two asterisks indicate P ≤ .01. ns = not significant at P > .05.View Large Image Figure ViewerDownload Hi-res image Download (PPT) The COPDGene patients in the emphysema cluster had the greatest evidence of disease activity and disease progression during follow up, followed by those in the interstitial group. For example, relative to the preserved group, those in the emphysema group had greater declines in both FEV1 and 6-minute walk distance, gained more emphysema, and had a higher rate of exacerbations (Tables 2, 3). Those patients in the interstitial group did not have a significantly higher rate of lung function decline than those in the preserved group, but they did have a higher rate of decline in exercise capacity, gained more emphysema, and had a higher rate of exacerbations than those in the preserved group (Tables 2, 3). Finally, over 5 years of follow-up, the majority of individuals (79.4%) remained in their original cluster (e-Table 3).Table 2Rate of Acute Respiratory Disease Events by ClusterVariableIncidence Rate RatioaExpressed compared with the preserved cluster (eg, those individuals in the emphysema predominant cluster had 32% more acute respiratory disease events over the course of follow up than those in the preserved cluster).95% CIPLower LimitUpper LimitPreservedReferenceInterstitial predominant1.141.001.30.043Emphysema predominant1.321.121.56<.001a Expressed compared with the preserved cluster (eg, those individuals in the emphysema predominant cluster had 32% more acute respiratory disease events over the course of follow up than those in the preserved cluster). Open table in a new tab Table 3Longitudinal Changes in Clinical Measures by ClusterVariableDifference in Annual ChangeaExpressed as the annualized absolute difference in the change of that cluster compared to the preserved cluster (eg, those individuals in the emphysema predominant cluster lost an average of 15.9 feet more per year over the course of follow up than those in the preserved cluster.95% CIPLower LimitUpper LimitFEV1, % predicted PreservedReference Interstitial predominant0.02−0.100.15.703 Emphysema predominant−0.66−0.87−0.44<.0016-Minute walk distance, ft/y PreservedReference Interstitial predominant−6.2−10.6−1.7.007 Emphysema predominant−15.9−23.4−8.5<.001Emphysema, % lung volume/y PreservedReference Interstitial predominant0.130.030.23.011 Emphysema predominant0.300.130.47<.001a Expressed as the annualized absolute difference in the change of that cluster compared to the preserved cluster (eg, those individuals in the emphysema predominant cluster lost an average of 15.9 feet more per year over the course of follow up than those in the preserved cluster. Open table in a new tab After clustering, the first two principal components of the analytic variables from COPDGene were plotted against each other for a geometric interpretation of the grouped data points. The participants from the DECAMP study were clustered independently based on the same imaging variables from COPDGene and projected onto the same principal component plot (Fig 2) and by the similarity in the distribution of the imaging characteristics within the DECAMP clusters (Fig 3B). Similar to COPDGene, in the DECAMP cohort, those in the preserved cluster and those in the emphysema cluster had the least severe and most severe clinical phenotypes, respectively, and the interstitial cluster had an intermediate clinical phenotype (Table 1). We analyzed the bronchial epithelial gene expression associated with imaging cluster membership using a subset of individuals from the DECAMP study. Although no genes were differentially expressed when we compared the interstitial group with either the emphysema or preserved predominant groups, we identified 41 genes that were expressed differentially between the preserved and emphysema clusters (false discovery rate, < 0.25) (Fig 6A). Eight of these were expressed at lower levels in individuals from the emphysema cluster, including those involved in T-cell biology (T-cell receptor alpha constant, T-cell receptor antigen, thymocyte-expressed molecule involved in selection, which have a regulatory role in both positive and negative T-cell selection during late thymocyte development, and signaling threshold regulating transmembrane adaptor 1, which negatively regulates T-cell antigen receptor-mediated signaling in T cells). Among the 33 genes that were expressed at higher levels in individuals from the emphysema cluster are genes that are related to acute and chronic inflammation (chemokine ligand 20, IL1B, IL8, and IL1R2), tumor necrosis factor-alpha (TNF-α) signaling pathway (TNFA1P6, CXCL3), and mucus production (MUC6) (e-Table 4). To more fully characterize the biology of the gene expression differences associated with the imaging clusters, gene set enrichment analysis was performed on preranked gene lists created b

Random sensor deployments following Poisson or Gaussian distribution are the most widely adopted deployment strategies for hostile and unpredictable application scenarios such as environment surveillance and malicious mobile target detection. In the literature, researchers assume either Poisson distributed or Gaussian distributed sensors in modeling wireless sensor networks for performance evaluation. This paper instead examines the performance of a wireless sensor network that employs a hybrid random sensor deployment where a set of the sensors are deployed following Poisson distribution and others follow Gaussian distribution around hot spot(s), which are more important than elsewhere and require higher surveillance and target detection capability. The performance of the hybrid wireless sensor network is evaluated in terms of surveillance and target detection probability theoretically and by simulations. The simulation outcomes match with the theoretical results.

Poor sleep hygiene is a growing problem, with detrimental effects on many biological systems. The pituitary gland plays a crucial role in the regulation of sleep and the stress response, and its dysfunction leads to sleep-related disorders. However, the interaction between these critical functions remains unclear. Thus, we performed a comparative, whole-transcriptome, analysis to identify stress-induced genes and relevant pathways that may be affected by sleep deprivation. One day following 12 h of Paradoxical Sleep Deprivation (PSD), mice were restrained for 20 min. Gene expression changes in the pituitary were assessed via RNA-Seq and Gene Ontology in PSD and/or restrained groups compared to controls. We show that restraint triggers transcriptional responses involved in hormone secretion, the glucocorticoid response, and apoptosis in both sexes, with 285 differentially expressed genes in females and 93 in males. When PSD preceded restraint stress, the numbers of differentially expressed genes increased to 613 in females and 580 in males. The pituitary transcriptome of restraint+PSD animals was enriched for microglia and macrophage proliferation, cellular response to corticosteroids, and apoptosis, among others. Finally, we identify sex-specific differences in restraint-induced genes following PSD. These findings provide genetic targets to consider when studying sleep and the response to stress.

In the current study, we determined the effects of IGF-1 receptor haploinsufficiency on osteoblast differentiation and bone formation throughout the lifespan. Bone mineral density was significantly decreased in femurs of male and female Igf1r+/− mice compared with wild-type mice. mRNA expression of osteoblast differentiation markers was significantly decreased in femurs and calvariae from Igf1r+/− mice compared with cells from wild-type mice. Bone morphogenetic protein-7-induced ectopic bone in Igf1r+/− mice was significantly smaller with fewer osteoblasts but more lipid droplets and had reduced expression of osteoblast differentiation markers compared with wild-type mice. In bone marrow cells from middle-aged and old wild-type and Igf1r+/− male mice, palmitate inhibited osteoblast markers expression. In cells from young wild-type male mice, palmitate did not inhibit marker expression, but in cells from young male Igf1r+/− mice, palmitate inhibited bone sialoprotein and osterix but not osteocalcin or type I collagen (TIC). In female wild-type mice, palmitate inhibited osteoblast markers expression in cells from young, middle-aged, and old mice except TIC in cells from middle-aged mice. Palmitate inhibited bone sialoprotein expression in cells from middle-aged and old female Igf1r+/− mice and osteocalcin, osterix, and TIC expression in young and middle-aged female Igf1r+/− mice but stimulated expression in cells from old female Igf1r+/− mice. We conclude that IGF-1 receptor haploinsufficiency results in a prolipid accrual phenotype in bone in association with inhibition of growth factor-induced osteoblast differentiation, a situation which may phenocopy age-related decreases in bone formation.

The formation of pathological anti-FVIII antibodies, referred to as “inhibitors” affects up to 1/3 of severe Hemophilia A (HA) patients. “Immune Tolerance Induction” (ITI), enables ~2/3 of treated patients to achieve peripheral tolerance to FVIII. Inhibitor formation is a classical T-cell dependent adaptive immune response. As such, it requires help from the innate immune system. However, the roles of innate immune cells and mechanisms of inhibitor development versus peripheral tolerance, achieved with or without ITI therapy, are not well understood. To address these questions, temporal transcriptomics profiling was carried out for FVIII-stimulated peripheral blood mononuclear cells (PBMCs) from the following groups of blood donors (40 total): (A) HA with a past inhibitor; (B) HA with a current inhibitor; (C) HA with no inhibitor history; (D) non-HA. PBMCs were stimulated with 5 nM FVIII, and total RNA was isolated 4, 16, 24 and 48 hours following stimulation. Time-series differential expression analysis was performed with DESeq2 followed by clustering and gene ontology (GO) analysis. Subjects in Groups A, B, C and D showed differential expression of 15, 56, 195 and 63 genes, respectively. A clustering analysis of Group B identified 3 distinct clusters. Interestingly, GO enrichment analysis revealed enrichments for innate immune modulators including NLRP3, TLR8, IL32, CLEC10A and COLEC12. NLRP3 and TLR8 are associated with enhanced secretion of the pro-inflammatory cytokines IL-1beta and TNF-alpha, while IL32, which has several isoforms, has been associated with both inflammatory and regulatory immune processes. Expression levels were validated by RT-PCR, ELISAs and flow cytometry. Group C temporal profiles fell into 4 distinct clusters. GO enrichment analysis revealed biological processes related to epithelial cell proliferation, responses to toxic substances, and positive/negative regulation of cytokine secretion (TNF, NQO1, PMEPA1). Group D temporal profiles fell into 4 distinct clusters. GO analysis identified expression patterns associated with leukocyte-mediated immunity, T-cell activation, and a hypoxia response. The inflammatory status of HA patients suffering from an ongoing inhibitor clearly includes up-regulation of innate immune modulators, some of which may act as ongoing danger signals that influence the responses to, and eventual outcome of, ITI therapy.

Abstract Background Analysis of somatic mutations from tumor whole exomes has fueled discovery of novel cancer driver genes. However, ~ 98% of the genome is non-coding and includes regulatory elements whose normal cellular functions can be disrupted by mutation. Whole genome sequencing (WGS), on the other hand, allows for identification of non-coding somatic variation and expanded estimation of background mutation rates, yet fewer computational tools exist for specific interrogation of this space. Results We present MutEnricher, a flexible toolset for investigating somatic mutation enrichment in both coding and non-coding genomic regions from WGS data. MutEnricher contains two distinct modules for these purposes that provide customizable options for calculating sample- and feature-specific background mutation rates. Additionally, both MutEnricher modules calculate feature-level and local, or “hotspot,” somatic mutation enrichment statistics. Conclusions MutEnricher is a flexible software package for investigating somatic mutation enrichment that is implemented in Python, is freely available, can be efficiently parallelized, and is highly configurable to researcher's specific needs. MutEnricher is available online at https://github.com/asoltis/MutEnricher .

Low-grade serous ovarian cancer (LGSOC) is a rare disease that occurs more frequently in younger women than those with high-grade disease. The current treatment is suboptimal and a better understanding of the molecular pathogenesis of this disease is required. In this study, we compared the proteogenomic analyses of LGSOCs from short- and long-term survivors (defined as < 40 and > 60 months, respectively). Our goal was to identify novel mutations, proteins, and mRNA transcripts that are dysregulated in LGSOC, particularly in short-term survivors.Initially, targeted sequencing of 409 cancer-related genes was performed on 22 LGSOC and 6 serous borderline ovarian tumor samples. Subsequently, whole-genome sequencing analysis was performed on 14 LGSOC samples (7 long-term survivors and 7 short-term survivors) with matched normal tissue samples. RNA sequencing (RNA-seq), quantitative proteomics, and phosphoproteomic analyses were also performed.We identified single-nucleotide variants (SNVs) (range: 5688-14,833 per sample), insertion and deletion variants (indels) (range: 880-1065), and regions with copy number variants (CNVs) (range: 62-335) among the 14 LGSOC samples. Among all SNVs and indels, 2637 mutation sites were found in the exonic regions. The allele frequencies of the detected variants were low (median12%). The identified recurrent nonsynonymous missense mutations included KRAS, NRAS, EIF1AX, UBR5, and DNM3 mutations. Mutations in DNM3 and UBR5 have not previously been reported in LGSOC. For the two samples, somatic DNM3 nonsynonymous missense mutations in the exonic region were validated using Sanger sequencing. The third sample contained two missense mutations in the intronic region of DNM3, leading to a frameshift mutation detected in RNA transcripts in the RNA-seq data. Among the 14 LGSOC samples, 7754 proteins and 9733 phosphosites were detected by global proteomic analysis. Some of these proteins and signaling pathways, such as BST1, TBXAS1, MPEG1, HBA1, and phosphorylated ASAP1, are potential therapeutic targets.This is the first study to use whole-genome sequencing to detect somatic mutations in LGSOCs with matched normal tissues. We detected and validated novel mutations in DNM3, which were present in 3 of the 14 samples analyzed. Additionally, we identified novel indels, regions with CNVs, dysregulated mRNA, dysregulated proteins, and phosphosites that are more prevalent in short-term survivors. This integrated proteogenomic analysis can guide research into the pathogenesis and treatment of LGSOC.

[This corrects the article DOI: 10.1371/journal.pone.0056823.].

Context A histologic classification of lung cancer subtypes is essential in guiding therapeutic management. Objective To complement morphology-based classification of lung tumors, a previously developed lung subtyping panel (LSP) of 57 genes was tested using multiple public fresh-frozen gene-expression data sets and a prospectively collected set of formalin-fixed, paraffin-embedded lung tumor samples. Design The LSP gene-expression signature was evaluated in multiple lung cancer gene-expression data sets totaling 2177 patients collected from 4 platforms: Illumina RNAseq (San Diego, California), Agilent (Santa Clara, California) and Affymetrix (Santa Clara) microarrays, and quantitative reverse transcription–polymerase chain reaction. Gene centroids were calculated for each of 3 genomic-defined subtypes: adenocarcinoma, squamous cell carcinoma, and neuroendocrine, the latter of which encompassed both small cell carcinoma and carcinoid. Classification by LSP into 3 subtypes was evaluated in both fresh-frozen and formalin-fixed, paraffin-embedded tumor samples, and agreement with the original morphology-based diagnosis was determined. Results The LSP-based classifications demonstrated overall agreement with the original clinical diagnosis ranging from 78% (251 of 322) to 91% (492 of 538 and 869 of 951) in the fresh-frozen public data sets and 84% (65 of 77) in the formalin-fixed, paraffin-embedded data set. The LSP performance was independent of tissue-preservation method and gene-expression platform. Secondary, blinded pathology review of formalin-fixed, paraffin-embedded samples demonstrated concordance of 82% (63 of 77) with the original morphology diagnosis. Conclusions The LSP gene-expression signature is a reproducible and objective method for classifying lung tumors and demonstrates good concordance with morphology-based classification across multiple data sets. The LSP panel can supplement morphologic assessment of lung cancers, particularly when classification by standard methods is challenging.

Sodium taurocholate cotransporting polypeptide (NTCP), which is highly expressed in the sinusoidal membrane of hepatocytes, maintains bile acid homeostasis and participates in the hepatic disposition of a variety of endogenous substances as well as xenobiotics. Manifested by the involvement of organic anion-transporting polypeptides 1B1 and 1B3 (OATP1B1 and OATP1B3) in the hepatic uptake of statin drugs, sinusoidal membrane transporters play an important role in the pharmacokinetics and pharmacodynamics of these agents. It has been speculated that NTCP may function as an alternative pathway for statin hepatic uptake, complementary to OATP1B1 and OATP1B3. In the current study, we produced stable NTCP-expressing human embryonic kidney 293 (HEK293) cells and developed a fluorescence-based assay using flow cytometry for measuring NTCP transport with chenodeoxycholyl-(Nε-7-nitrobenz-2-oxa-1,3-diazole)-lysine (CDCA-NBD) as the substrate. NTCP-mediated CDCA-NBD transport was time-dependent and exhibited typical Michaelis–Menten kinetics, with a K m of 6.12 µM. Compounds known to interact with NTCP, including chenodeoxycholic acid and taurocholic acid, displayed concentration-dependent inhibition of NTCP-mediated CDCA-NBD transport. We report here a systematic evaluation of the interaction between statins and the NTCP transporter. Utilizing this system, several statins were either found to inhibit NTCP-dependent transport or act as substrates. We find a good correlation between the reported lipophilicity of statins and their ability to inhibit NTCP. The objective was to develop a higher-throughput system to evaluate potential inhibitors such as the statins. The in vitro assays using CDCA-NBD as fluorescent substrate are convenient, rapid, and have utility in screening drug candidates for potential drug–NTCP interactions.