Brett Johnson

Although it is known that the methylation of DNA in 5' promoters suppresses gene expression, the role of DNA methylation in gene bodies is unclear. In mammals, tissue- and cell type-specific methylation is present in a small percentage of 5' CpG island (CGI) promoters, whereas a far greater proportion occurs across gene bodies, coinciding with highly conserved sequences. Tissue-specific intragenic methylation might reduce, or, paradoxically, enhance transcription elongation efficiency. Capped analysis of gene expression (CAGE) experiments also indicate that transcription commonly initiates within and between genes. To investigate the role of intragenic methylation, we generated a map of DNA methylation from the human brain encompassing 24.7 million of the 28 million CpG sites. From the dense, high-resolution coverage of CpG islands, the majority of methylated CpG islands were shown to be in intragenic and intergenic regions, whereas less than 3% of CpG islands in 5' promoters were methylated. The CpG islands in all three locations overlapped with RNA markers of transcription initiation, and unmethylated CpG islands also overlapped significantly with trimethylation of H3K4, a histone modification enriched at promoters. The general and CpG-island-specific patterns of methylation are conserved in mouse tissues. An in-depth investigation of the human SHANK3 locus and its mouse homologue demonstrated that this tissue-specific DNA methylation regulates intragenic promoter activity in vitro and in vivo. These methylation-regulated, alternative transcripts are expressed in a tissue- and cell type-specific manner, and are expressed differentially within a single cell type from distinct brain regions. These results support a major role for intragenic methylation in regulating cell context-specific alternative promoters in gene bodies.

Back with a Vengeance After surgery, gliomas (a type of brain tumor) recur in nearly all patients and often in a more aggressive form. Johnson et al. (p. 189 , published online 12 December 2013) used exome sequencing to explore whether recurrent tumors harbor different mutations than the primary tumors and whether the mutational profile in the recurrences is influenced by postsurgical treatment of patients with temozolomide (TMZ), a chemotherapeutic drug known to damage DNA. In more than 40% of cases, at least half of the mutations in the initial glioma were undetected at recurrence. The recurrent tumors in many of the TMZ-treated patients bore the signature of TMZ-induced mutagenesis and appeared to follow an evolutionary path to high-grade glioma distinct from that in untreated patients.

Analysis of DNA methylation patterns relies increasingly on sequencing-based profiling methods. The four most frequently used sequencing-based technologies are the bisulfite-based methods MethylC-seq and reduced representation bisulfite sequencing (RRBS), and the enrichment-based techniques methylated DNA immunoprecipitation sequencing (MeDIP-seq) and methylated DNA binding domain sequencing (MBD-seq). We applied all four methods to biological replicates of human embryonic stem cells to assess their genome-wide CpG coverage, resolution, cost, concordance and the influence of CpG density and genomic context. The methylation levels assessed by the two bisulfite methods were concordant (their difference did not exceed a given threshold) for 82% for CpGs and 99% of the non-CpG cytosines. Using binary methylation calls, the two enrichment methods were 99% concordant and regions assessed by all four methods were 97% concordant. We combined MeDIP-seq with methylation-sensitive restriction enzyme (MRE-seq) sequencing for comprehensive methylome coverage at lower cost. This, along with RNA-seq and ChIP-seq of the ES cells enabled us to detect regions with allele-specific epigenetic states, identifying most known imprinted regions and new loci with monoallelic epigenetic marks and monoallelic expression.

While the contentious politics (CP) model has come to dominate the field of social movements, scholars note the paradigm's shortcomings, especially its narrow focus on movement organizations, public protest, and political action. The conceptual wall between lifestyles and social movements has created a theoretical blind spot at the intersection of private action and movement participation, personal and social change, and personal and collective identity. We suggest that lifestyle movements (LMs) consciously and actively promote a lifestyle, or way of life, as a primary means to foster social change. Drawing upon our observations of a variety of LMs, we discuss three defining aspects of LMs: lifestyle choices as tactics of social change, the central role of personal identity work, and the diffuse structure of LMs. We also explore the links between LMs and social movements, CP, and conventional politics. Finally, we demonstrate that LM, as a new conceptual category, is applicable across a range of movement activities.

The evolutionary history of tumor cell populations can be reconstructed from patterns of genetic alterations. In contrast to stable genetic events, epigenetic states are reversible and sensitive to the microenvironment, prompting the question whether epigenetic information can similarly be used to discover tumor phylogeny. We examined the spatial and temporal dynamics of DNA methylation in a cohort of low-grade gliomas and their patient-matched recurrences. Genes transcriptionally upregulated through promoter hypomethylation during malignant progression to high-grade glioblastoma were enriched in cell cycle function, evolving in parallel with genetic alterations that deregulate the G1/S cell cycle checkpoint. Moreover, phyloepigenetic relationships robustly recapitulated phylogenetic patterns inferred from somatic mutations. These findings highlight widespread co-dependency of genetic and epigenetic events throughout brain tumor evolution.

Temozolomide (TMZ) increases the overall survival of patients with glioblastoma (GBM), but its role in the clinical management of diffuse low-grade gliomas (LGG) is still being defined. DNA hypermethylation of the O 6 -methylguanine-DNA methyltransferase (MGMT) promoter is associated with an improved response to TMZ treatment, while inactivation of the DNA mismatch repair (MMR) pathway is associated with therapeutic resistance and TMZ-induced mutagenesis. We previously demonstrated that TMZ treatment of LGG induces driver mutations in the RB and AKT–mTOR pathways, which may drive malignant progression to secondary GBM. To better understand the mechanisms underlying TMZ-induced mutagenesis and malignant progression, we explored the evolution of MGMT methylation and genetic alterations affecting MMR genes in a cohort of 34 treatment-naïve LGGs and their recurrences. Recurrences with TMZ-associated hypermutation had increased MGMT methylation compared to their untreated initial tumors and higher overall MGMT methylation compared to TMZ-treated non-hypermutated recurrences. A TMZ-associated mutation in one or more MMR genes was observed in five out of six TMZ-treated hypermutated recurrences. In two cases, pre-existing heterozygous deletions encompassing MGMT, or an MMR gene, were followed by TMZ-associated mutations in one of the genes of interest. These results suggest that tumor cells with methylated MGMT may undergo positive selection during TMZ treatment in the context of MMR deficiency.

Mechanisms of therapeutic resistance and vulnerability evolve in metastatic cancers as tumor cells and extrinsic microenvironmental influences change during treatment. To support the development of methods for identifying these mechanisms in individual people, here we present an omic and multidimensional spatial (OMS) atlas generated from four serial biopsies of an individual with metastatic breast cancer during 3.5 years of therapy. This resource links detailed, longitudinal clinical metadata that includes treatment times and doses, anatomic imaging, and blood-based response measurements to clinical and exploratory analyses, which includes comprehensive DNA, RNA, and protein profiles; images of multiplexed immunostaining; and 2- and 3-dimensional scanning electron micrographs. These data report aspects of heterogeneity and evolution of the cancer genome, signaling pathways, immune microenvironment, cellular composition and organization, and ultrastructure. We present illustrative examples of how integrative analyses of these data reveal potential mechanisms of response and resistance and suggest novel therapeutic vulnerabilities.

This prospective multicenter multireader study evaluated the performance of 40% scan-time reduced spinal magnetic resonance imaging (MRI) reconstructed with deep learning (DL).A total of 61 patients underwent standard of care (SOC) and accelerated (FAST) spine MRI. DL was used to enhance the accelerated set (FAST-DL). Three neuroradiologists were presented with paired side-by-side datasets (666 series). Datasets were blinded and randomized in sequence and left-right display order. Image features were preference rated. Structural similarity index (SSIM) and per pixel L1 was assessed for the image sets pre and post DL-enhancement as a quantitative assessment of image integrity impact.FAST-DL was qualitatively better than SOC for perceived signal-to-noise ratio (SNR) and artifacts and equivalent for other features. Quantitative SSIM was high, supporting the absence of image corruption by DL processing.DL enables 40% spine MRI scan time reduction while maintaining diagnostic integrity and image quality with perceived benefits in SNR and artifact reduction, suggesting potential for clinical practice utility.

Aberrant DNA hypomethylation may play an important role in the growth rate of glioblastoma (GBM), but the functional impact on transcription remains poorly understood. We assayed the GBM methylome with MeDIP-seq and MRE-seq, adjusting for copy number differences, in a small set of non-glioma CpG island methylator phenotype (non-G-CIMP) primary tumors. Recurrent hypomethylated loci were enriched within a region of chromosome 5p15 that is specified as a cancer amplicon and also encompasses TERT , encoding telomerase reverse transcriptase, which plays a critical role in tumorigenesis. Overall, 76 gene body promoters were recurrently hypomethylated, including TERT and the oncogenes GLI3 and TP73 . Recurring hypomethylation also affected previously unannotated alternative promoters, and luciferase reporter assays for three of four of these promoters confirmed strong promoter activity in GBM cells. Histone H3 lysine 4 trimethylation (H3K4me3) ChIP-seq on tissue from the GBMs uncovered peaks that coincide precisely with tumor-specific decrease of DNA methylation at 200 loci, 133 of which are in gene bodies. Detailed investigation of TP73 and TERT gene body hypomethylation demonstrated increased expression of corresponding alternate transcripts, which in TP73 encodes a truncated p73 protein with oncogenic function and in TERT encodes a putative reverse transcriptase-null protein. Our findings suggest that recurring gene body promoter hypomethylation events, along with histone H3K4 trimethylation, alter the transcriptional landscape of GBM through the activation of a limited number of normally silenced promoters within gene bodies, in at least one case leading to expression of an oncogenic protein.

In order to establish the workflows required to implement a real-time process involving multi-omic analysis of patient samples to support precision-guided therapeutic intervention, a tissue acquisition and analysis trial was implemented. This report describes our findings to date, including the frequency with which mutational testing led to precision-guided therapy and outcome for those patients.Eligible patients presenting to Oregon Health and Science University Knight Cancer Institute were enrolled on the study. Patients with biopsy proven metastatic or locally advanced unresectable prostate cancer, breast cancer, pancreatic adenocarcinoma, or refractory acute myelogenous leukemia receiving standard of care therapy were eligible. Metastatic site biopsies were collected and analyzed using the Knight Diagnostic Lab GeneTrails comprehensive solid tumor panel (124 genes). CLIA certified genomic information was made available to the treating physician.Between 1/26/2017 and 5/30/2018, 38 patients were enrolled, with 28 successfully undergoing biopsy. Of these, 25 samples yielded sufficient tumor for analysis. The median biopsy cellularity and number of cores collected were 70% (15-90%) and 5 (2-20), respectively. No procedure-related complications occurred. GeneTrails analysis revealed that 22 of 25 (88%) tumor samples harbored at least one potentially actionable mutation, and 18 (72%) samples harbored 2 or more potentially actionable mutations. The most common genetic alterations identified involved: DNA damage repair genes, cell cycle regulating genes, PIK3CA/Akt/mTOR pathway, and FGF gene family. To date, CLIA certified genomic results were used by treating physicians for precision-guided therapy in 5 (23%) patients.We report the feasibility of real-time tissue acquisition and analysis to support a successful translational oncology platform. The workflow will provide the foundation to improve access and accrual to biomarker driven precision oncology trials.

Tumor specimens contain a variety of healthy cells as well as cancerous cells, and this heterogeneity underlies resistance to various cancer therapies. But this problem has not been thoroughly investigated until recently. Meanwhile, technological breakthroughs in imaging have led to an explosion of molecular and cellular profiling data from large numbers of samples, and modern machine learning approaches including deep learning have been shown to produce encouraging results by finding hidden structures and make accurate predictions. In this paper, we propose a Deep learning based Nucleus Classification (DeepNC) approach using paired histopathology and immunofluorescence images (for label), and demonstrate its classification prediction power. This method can solve current issue on discrepancy between genomic- or transcriptomic-based and pathology-based tumor purity estimates by improving histological evaluation. We also explain challenges in training a deep learning model for huge dataset.

Abstract Spatially-resolved molecular profiling by immunostaining tissue sections is a key feature in cancer diagnosis, subtyping, and treatment, where it complements routine histopathological evaluation by clarifying tumor phenotypes. In this work, we present a deep learning-based method called speedy histological-to-immunofluorescent translation (SHIFT) which takes histologic images of hematoxylin and eosin (H&E)-stained tissue as input, then in near-real time returns inferred virtual immunofluorescence (IF) images that estimate the underlying distribution of the tumor cell marker pan-cytokeratin (panCK). To build a dataset suitable for learning this task, we developed a serial staining protocol which allows IF and H&E images from the same tissue to be spatially registered. We show that deep learning-extracted morphological feature representations of histological images can guide representative sample selection, which improved SHIFT generalizability in a small but heterogenous set of human pancreatic cancer samples. With validation in larger cohorts, SHIFT could serve as an efficient preliminary, auxiliary, or substitute for panCK IF by delivering virtual panCK IF images for a fraction of the cost and in a fraction of the time required by traditional IF.

In this paper, I use principles of civic education and social psychology to identify four main classroom contributors to students' pessimistic appraisals of their ability to improve social problems: authoritarian teaching methods, a culture of “doom and gloom,” little attention to solutions to social problems, and no linkage of social problems to individual behavior. I then propose a five-step process to effectively teach about social problems while empowering students to help solve these problems: (1) identify the process through which social problems are constructed, (2) identify existence of the social problem, (3) identify core causes of the social problem, (4) identify structural solutions to the social problem, and (5) identify individual actions that contribute to structural solutions.

Abstract Molecular heterogeneity in metastatic breast cancer presents multiple clinical challenges in accurately characterizing and treating the disease. Current diagnostic approaches offer limited ability to assess heterogeneity that exists among multiple metastatic lesions throughout the treatment course. We developed a precision oncology platform that combines serial biopsies, multi-omic analysis, longitudinal patient monitoring, and molecular tumor boards, with the goal of improving cancer management through enhanced understanding of the entire cancer ecosystem within each patient. We describe this integrative approach using comprehensive analytics generated from serial-biopsied lesions in a metastatic breast cancer patient. The serial biopsies identified remarkable heterogeneity among metastatic lesions that presented clinically as discordance in receptor status and genomic alterations with mixed treatment response. Based on our study, we highlight clinical scenarios, such as rapid progression or mixed response, that indicate consideration for repeat biopsies to evaluate intermetastatic heterogeneity (IMH), with the objective of refining targeted therapy. We present a framework for understanding the clinical significance of heterogeneity in breast cancer between metastatic lesions utilizing multi-omic analyses of serial biopsies and its implication for effective personalized treatment.

Back to table of contents Previous article Letters to the EditorNo AccessUnintentional Ketamine Overdose Via TelehealthBrett E. Johnson, M.D., Eric S. Borges, M.D., Romolo J. Gaspari, M.D. Ph.D., Gayle M. Galletta, M.D., Jeffrey T. Lai, M.D.Brett E. JohnsonSearch for more papers by this author, M.D., Eric S. BorgesSearch for more papers by this author, M.D., Romolo J. GaspariSearch for more papers by this author, M.D. Ph.D., Gayle M. GallettaSearch for more papers by this author, M.D., Jeffrey T. LaiSearch for more papers by this author, M.D.Published Online:1 Jan 2024https://doi.org/10.1176/appi.ajp.20230484AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InEmail View article"Unintentional Ketamine Overdose Via Telehealth." American Journal of Psychiatry, 181(1), pp. 81–82 Access content To read the fulltext, please use one of the options below to sign in or purchase access. Personal login Institutional Login Sign in via OpenAthens Register for access Purchase Save for later Item saved, go to cart PPV Articles - American Journal of Psychiatry $35.00 Add to cart PPV Articles - American Journal of Psychiatry Checkout Please login/register if you wish to pair your device and check access availability. Not a subscriber? Subscribe Now / Learn More PsychiatryOnline subscription options offer access to the DSM-5 library, books, journals, CME, and patient resources. This all-in-one virtual library provides psychiatrists and mental health professionals with key resources for diagnosis, treatment, research, and professional development. Need more help? PsychiatryOnline Customer Service may be reached by emailing [email protected] or by calling 800-368-5777 (in the U.S.) or 703-907-7322 (outside the U.S.). FiguresReferencesCited byDetailsCited byNone Volume 181Issue 1 January 01, 2024Pages 81-82 Metrics KeywordsketaminepsychiatryoverdosetoxicologyatropinetelemedicinePDF download History Accepted 10 August 2023 Published online 1 January 2024 Published in print 1 January 2024

In a pilot study, we evaluated the feasibility of real-time deep analysis of serial tumor samples from triple negative breast cancer patients to identify mechanisms of resistance and treatment opportunities as they emerge under therapeutic stress engendered by poly-ADP-ribose polymerase (PARP) inhibitors (PARPi). In a BRCA-mutant basal breast cancer exceptional long-term survivor, a striking tumor destruction was accompanied by a marked infiltration of immune cells containing CD8 effector cells, consistent with pre-clinical evidence for association between STING mediated immune activation and benefit from PARPi and immunotherapy. Tumor cells in the exceptional responder underwent extensive protein network rewiring in response to PARP inhibition. In contrast, there were minimal changes in the ecosystem of a luminal androgen receptor rapid progressor, likely due to indifference to the effects of PARP inhibition. Together, identification of PARPi-induced emergent changes could be used to select patient specific combination therapies, based on tumor and immune state changes.

Abstract Background: There are a growing number of targeted agents that have the potential to greatly improve the clinical outcomes of patients with PDAC beyond current standard of care chemotherapy. However, there is a lack in our understanding of which patients and intrinsic PDAC tumor types will best respond to a given targeted agent(s). In order to optimizing their clinical utility, it is crucial that we a deep understanding of the biological impact that these targeted agents (alone or combination) have within the human system. As such, we designed and implemented the WOO trial to provide a highly adaptable discovery platform for the preliminary assessment of biological activity of one or more targeted agents in patients with PDAC. Utilizing paired, pre- and on-treatment biopsies, along with a robust multiomics pipeline, the WOO trial enables independent assessment of the biological impact of targeted agent(s) on key signaling pathways that can be used to explore novel therapeutic strategies. Methods: WOO is a multi-arm early phase I trial platform designed to assess the pharmacodynamic (PD) effects of one or more study agent(s) alone or in combination in patients with PDAC. A Master Protocol is used to describe overarching design and logistics, and sub-protocols separately describe each study arm comprising the different investigational agent(s). Each participants undergoes a baseline tumor biopsy, then receives their assigned study agent(s) for a specified timeframe (not exceeding 30 days), before undergoing a repeated tumor biopsy, after which they continue to receive therapy per standard of care or clinical trials. Spatially-resolved, single cell multiplex assays are used to compare the effects of the study agent(s) on tumor cell state and heterogeneity between the paired samples. The primary study objective is to independently assess the PD feasibility of detecting a measurable change in tumor biology at post-treatment from baseline for participants within a study arm. The WOO trial uses a 2-stage Bayesian efficacy monitoring approach with a futility-stopping rule for each study arm. In stage 1 of each study arm, if 6 or more of the first 10 participants have a detectable change in tumor biology measurements (i.e., pre vs. post-treatment), then the study arm may continue to enroll an additional 10 participants. To date, 4 study arms are being evaluated: 1) poly (ADP-ribose) polymerase inhibitor (PARPi), olaparib (300 mg PO BID for 10 days), 2) MEK inhibitor (MEKi), cobimetinib (60 mg PO QD for 10 days), 3) ERK inhibitor, LY3214996 (400 mg PO QD for 10 days), and 4) PLK1 inhibitor, onvansertib (12 mg/m2 PO QD for 10 days). To date, a total of 34 participants have been enrolled and treated: n = 14 cobimetinib, n= 15 olaparib, n=2 onvansertib. Future arms to be added. Trial ID: NCT04005690. Citation Format: Charles D. Lopez, Adel Kardosh, Emerson Chen, Guillame Pegna, Alexander Guimaraes, Bryan Foster, Brian Brinkerhoff, Shaun M. Goodyear, Erin Taber, Brindha Rajagopalan, Johnson Vo, Kiara Siex, Brett Johnson, Danielle Galipeau, Dove Keith, Brett Sheppard, Brody Jonathan, Rosalie Sears, Gordon Mills. Advancing biomarker discovery using a novel window of opportunity (WOO) trial for pancreatic ductal adenocarcinoma: Trial updates [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr B003.

2015 Background: PEX is an oral small molecule inhibitor of KIT and CSF1 receptor expressed on microglia, blood vessels, and glioblastoma (GBM) tumor cells. PEX achieved good tissue exposure in a prior recurrent GBM study, and preclinical studies indicate PEX may sensitize GBM to standard of care (SOC) therapy through effects on both tumor and microenvironment. Methods: Phase Ib determined the recommended Phase II dose (RP2D) with SOC XRT/TMZ. Phase II primary endpoint was progression free survival (PFS); secondary endpoints included overall survival (OS) and safety. Patient entry criteria were designed to replicate the RTOG 0525 control arm, which was used as a historical control. Results: The identified RP2D was PEX 400mg BID 5 days/week during and 7 days/week after SOC XRT/TMZ. Of the total RP2D population, 42 were evaluable for comparison and demonstrated similar characteristics to the RTOG 0525 control arm. As of November 2017, mPFS from registration is 6.7 months in PEX patients (95% CI 4.2, 10.2) vs. 7.5 months in historical controls. Estimated mOS for PEX is 15.4 months (95% CI 12.3, 20.7) vs. 18.9 months in controls. PEX was well tolerated, with most common drug-related toxicities including neutropenia and increased ALT/AST. MGMT unmethylated patients comprised 60% of the patients, with estimated mOS of 13.8 months (95% CI 12.3, 20.7) vs. 68% and estimated mOS of 16.6 months in historical controls. MGMT methylated patients comprised 40%, and mOS not yet reached vs. 32% and estimated mOS of 23.5 months in historical controls. Tumors with high expression of monocyte/macrophage marker CD163 and macrophage stimulating factor CSF1 trended to worse overall survival. mOS was 13.8 months for tumors with high expression of CD163 vs. 19.2 in tumors with low expression (p = .323). mOS was 12.3 months in tumors with high CSF1 expression vs. 19.2 in tumors with low (p = .328). Conclusions: PEX can be safely combined with SOC XRT/TMZ in newly diagnosed GBM. Results suggest minimal PEX activity when added to XRT/TMZ in an unselected GBM population for improving PFS and OS compared to robust, well-matched historical controls. Further investigation in relevant biomarker subgroups is ongoing. Clinical trial information: NCT01790503.

e13001 Background: We designed and implemented a platform wherein patients with metastatic treatment-refractory cancer would receive individually tailored treatment informed by multi-omic data and iteratively adapted in real-time. Here we describe the workflow of this platform and quantify operational characteristics for a metastatic breast cancer cohort. Methods: Participants with metastatic breast cancer progressing after standard-of-care therapy were enrolled. Sites demonstrating disease progression were targeted for biopsy. Resultant tissue was analyzed by a next-generation sequencing (NGS) solid tumor panel, whole exome sequencing, whole transcriptomic sequencing, multiplex protein analysis of a panel of cancer-relevant proteins and phosphoproteins, and focused immunohistochemistry (IHC) and fluorescence in-situ hybridization (FISH) analysis. Results: Between 1/1/2017 to 12/31/2021, 74 participants were consented and 55 were enrolled. Median age at enrollment was 54 years, most were ECOG 0-1, and received a median of 2 lines of therapy in the metastatic setting. There were 95 biopsies collected from 55 individual participants and analytics were successfully generated in 94% of the cases. At the provider’s request, an integrated clinical, molecular, and cancer biology tumor board (TB) was convened for 25 participants. A total of 21 participants received matched therapy based on clinical parameters coupled to a consideration of biologically informed therapeutic vulnerabilities and 6 had a PFS2/PFS1 > 1.3. Twenty-one participants had a median of 2 repeat progression biopsies (range 2-5) and new alterations with potential therapeutic implications were identified. Repeat biopsies could have led to a new treatment in 11 of the participants, though only 3 received a therapy recommended by the tumor board owing to either rapid disease progression, clinical deterioration, or lack of access to drug. Conclusions: We demonstrated the practical feasibility and initial operating characteristics of a platform designed to comprehensively understand and integrate the clinical and molecular characteristics of a cohort with metastatic progressive breast cancer as they evolve on therapy and to use this information to deliver iteratively tailored therapy in real time. Further, clinical responses were observed in a subset of participants. These findings suggest an opportunity to incorporate this platform earlier in a disease course or to design adaptive clinical trials with access to therapies aimed at targeting new biological alteration.

Abstract Introduction There are no effective treatments for gliomas after progression on radiation, temozolomide, and bevacizumab. Microglia activation may be involved in radiation resistance and can be inhibited by the brain penetrating antibiotic minocycline. In this phase 1 trial, we examined the safety and effect on survival, symptom burden, and neurocognitive function of reirradiation, minocycline, and bevacizumab. Methods The trial used a 3 + 3 design for dose escalation followed by a ten person dose expansion. Patients received reirradiation with dosing based on radiation oncologist judgment, bevacizumab 10 mg/kg IV every two weeks, and oral minocycline twice a day. Symptom burden was measured using MDASI-BT. Neurocognitive function was measured using the COGSTATE battery. Results The maximum tolerated dose of minocycline was 400 mg twice a day with no unexpected toxicities. The PFS3 was 64.6%, and median overall survival was 6.4 months. Symptom burden and neurocognitive function did not decline in the interval between treatment completion and tumor progression. Conclusions Minocycline 400 mg orally twice a day with bevacizumab and reirradiation is well tolerated by physician and patient reported outcomes in people with gliomas that progress on bevacizumab.

The cellular heterogeneity and complex tissue architecture of most tumor samples is a major obstacle in image analysis on standard hematoxylin and eosin-stained (H&E) tissue sections. A mixture of cancer and normal cells complicates the interpretation of their cytological profiles. Furthermore, spatial arrangement and architectural organization of cells are generally not reflected in cellular characteristics analysis. To address these challenges, first we describe an automatic nuclei segmentation of H&E tissue sections. In the task of deconvoluting cellular heterogeneity, we adopt Landmark based Spectral Clustering (LSC) to group individual nuclei in such a way that nuclei in the same group are more similar. We next devise spatial statistics for analyzing spatial arrangement and organization, which are not detectable by individual cellular characteristics. Our quantitative, spatial statistics analysis could benefit H&E section analysis by refining and complementing cellular characteristics analysis.

TPS1111 Background: There is an urgent need to develop novel non chemotherapy treatments for metastatic triple negative breast cancer (mTNBC) patients who otherwise have a poor prognosis. Immune checkpoint blockade (ICB) and PARP inhibitors (PARPi) have independently shown promise for the treatment of mTNBC, and the combination has shown early benefit in the MEDIOLA and TOPACIO trials. This trial looks to 1) evaluate the efficacy of the combination of the PARPi olaparib and the PD-L1 inhibitor durvalumab, and 2) perform extensive multi-omics including protein based image analytics (multiplex IHC, cyclic immunofluorescence) on serial biopsies to identify predictive biomarkers and resistance mechanisms. Methods: Trial Design: This is a single-arm phase II study to assess the efficacy of the combination of olaparib and durvalumab in BRCA-wildtype mTNBC. mTNBC participants will undergo a pre-treatment biopsy, then will start a 4 week induction treatment with olaparib (300 mg PO BID). At the end of 4 weeks of single agent therapy, participants will undergo a repeat on-treatment biopsy, following which durvalumab (1500 mg IV every 4 weeks) will be added to olaparib. Participants will also be offered an optional biopsy on progression. Endpoints: The primary endpoint of this study is overall response rate (ORR) to olaparib and durvalumab therapy. Secondary efficacy endpoints include clinical benefit rate, duration of response, progression-free, and overall survival. The incidence and severity of on-treatment adverse events will be collected per CTCAE 5.0. Statistical Methods: 28 participants are planned for enrollment to this study. A 2-stage analysis will be performed using a Simon 2-stage Minimax design. The null (ICB alone) and alternative (ICB + PARPi) hypotheses are: H 0 : π = 0.15 and H a : π = 0.35. For the primary endpoint, a total sample size of 28 participants will achieve 80% power to detect the ORR difference of 0.20 with one-sided type I error =0.05. The trial will be terminated in stage I if 2 or less out of the first 15 participants respond. If the trial goes on to the stage II, a total of 28 participants will be studied. If the total number responding is less than or equal to 7, the combination is rejected. Current Enrollment: The study was activated on 1/7/2019. To date, 3 out of 15 patients have been accrued to stage I of the study Clinical trial information: NCT03801369.

We have mapped the Ah receptor nuclear translocator (ARNT) gene to a conserved linkage group located on mouse chromosome 3 and human chromosome 1. EcoRI-digested DNA from a panel of 17 human x mouse somatic cell hybrids was probed with a cDNA fragment of the human ARNT gene. Six of the 17 independent mouse x human hybrids were positive for human bands. Human chromosome 1 showed complete cosegregation with the gene, whereas discordant segregation was observed for all other human chromosomes. The human gene was localized to 1q21 by using DNA from mouse x human hybrid clones that retain translocations involving human chromosome 1, by segregation analysis in nine informative CEPH families, and by in situ hybridization. The mouse homologue was mapped to mouse chromosome 3 using a panel of 16 hamster x mouse somatic cell hybrids. Six of 16 mouse x hamster hybrids were positive for mouse bands, showing complete concordance with mouse chromosome 3. The mouse Arnt gene was regionally mapped on chromosome 3, using linkage analysis in an interspecific backcross. The results indicate that the mouse gene resides about 40 cM from the centromere and about 10 cM proximal to Cf-3, the gene for tissue factor.

e13092 Background: Longitudinal analysis of serial tumor biopsies is an under-utilized approach to studying adaptive mechanisms of resistance. We have established a comprehensive analytic platform to evaluate real-time trial sample analysis to inform precision oncology combinations in mTNBC. The primary endpoint of the study is feasibility of completing all CLIA assays within 28 days of biopsy. Methods: Following a pre-treatment biopsy and 4 weeks of olaparib monotherapy mTNBC patients underwent an on-treatment (tx) biopsy and durvalumab was added to their therapy. Pre- and on-tx biopsies underwent comparative analysis using CLIA assays (immunohistochemistry-IHC, whole exome seq, RNAseq and phospho-proteomics) as well as research assays (multiplex IHC-mIHC, cyclic immunofluorescence-IF, and reverse phase protein array-RPPA). Results: Serial biopsies were obtained from all 3 enrolled patients, and the primary endpoint was achieved for all patients (Table). Treatment was well tolerated, and 2 patients achieved clinical benefit > 6 months. In one patient with a prolonged CR ( > 18 months), the on-tx sample exhibited dramatic changes in protein network rewiring by protein data analysis (RPPA, cyclic-IF), and an increase in immune infiltrate by mIHC. Conclusions: This pilot confirmed the feasibility of rapid real-time analysis to inform treatment decisions. This led to the development and initiation of biomarker driven olaparib combination trials in mTNBC at our institution. Clinical trial information: NCT03544125 . [Table: see text]

Summary Mechanisms of therapeutic resistance manifest in metastatic cancers as tumor cell intrinsic alterations and extrinsic microenvironmental influences that can change during treatment. To support the development of methods for the identification of these mechanisms in individual patients, we present here an Omic and Multidimensional Spatial (OMS) Atlas generated from four serial biopsies of a metastatic breast cancer patient during 3.5 years of therapy. This resource links detailed, longitudinal clinical metadata including treatment times and doses, anatomic imaging, and blood-based response measurements to exploratory analytics including comprehensive DNA, RNA, and protein profiles, images of multiplexed immunostaining, and 2- and 3-dimensional scanning electron micrographs. These data reveal aspects of therapy-associated heterogeneity and evolution of the cancer’s genome, signaling pathways, immune microenvironment, cellular composition and organization, and ultrastructure. We present illustrative examples showing how integrative analyses of these data provide insights into potential mechanisms of response and resistance, and suggest novel therapeutic vulnerabilities.

Abstract SMMART is a precision medicine research program focused on understanding the evolution of actionable biology and mechanisms of resistance in human tumors during therapy. This is accomplished through in depth functional, ‘omic and multiscale image analysis of longitudinal samples acquired during treatment. Here we present a case report detailing the insights that can be gained from the comparative analysis of pre- and post-treatment biopsy specimens in a late-stage metastatic breast cancer patient. To understand the molecular evolution of cancer, we interrogated genomics with targeted and whole exome sequencing, transcriptomics with RNA and gene-fusion sequencing, and proteomics with reverse phase protein arrays. To understand cellular organization and architectural changes, we employed multi-scale imaging tools, including scanning electron microscopy (SEM), cyclic immunofluorescence, immune cell profiling with cyclic immunohistochemistry, and traditional pathological assessment. During the course of treatment, we monitored patient response to therapy with clinical imaging, circulating tumor DNA sequencing and cancer protein assessment. Individual assays revealed key aspects of how this individual's cancer evolved under therapeutic pressure. For example, mutational profiling revealed the patterns of clonal evolution and the acquisition of new genetic driver events. 2D and 3D SEM showed changes in ECM organization, macropinocytosis, mitochondrion size, number and density and number and organization of filopodia-like protrusions. We used a 30-color cyclic immunofluorescence analysis to identify differences in cancer cell proliferation and differentiation state, as well as the composition and organization of infiltrating immune cells. In addition, integrative analyses of multiple data types provided insight into the evolution of actionable biology within this patient's disease. This included changes in the suitability of the patient for immune checkpoint inhibitors as well as specific tyrosine kinase inhibitors. The comprehensive molecular and architectural characterization of an individual patient's cancer at multiple time points provides biologically novel and clinically relevant insight into the ways in which cancers become resistant to treatment. Citation Format: Brett Johnson, Jamie Keck, Max Morris, Kiara Siex, Annette Kolodzie, Swapnil Parmar, Jessica Riesterer, Koei Chin, Summer Gibbs, Laura Heiser, Paul Spellman, Kyle Ellrott, Ozgun Babur, Emek Demir, Adam Margolin, Jeremy Goecks, Lisa Coussens, Raymond Bergan, Joe Gray. SMMART: Serial measurements of molecular and architectural responses to therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3296.

ABSTRACT Spatially-resolved molecular profiling by immunostaining tissue sections is a key feature in cancer diagnosis, subtyping, and treatment, where it complements routine histopathological evaluation by clarifying tumor phenotypes. In this work, we present a deep learning-based method called speedy histological-to-immunofluorescent translation (SHIFT) which takes histologic images of hematoxylin and eosin-stained tissue as input, then in near-real time returns inferred virtual immunofluorescence (IF) images that accurately depict the underlying distribution of phenotypes without requiring immunostaining of the tissue being tested. We show that deep learning-extracted feature representations of histological images can guide representative sample selection, which improves SHIFT generalizability. SHIFT could serve as an efficient preliminary, auxiliary, or substitute for IF by delivering multiplexed virtual IF images for a fraction of the cost and in a fraction of the time required by nascent multiplexed imaging technologies. KEY POINTS Spatially-resolved molecular profiling is an essential complement to histopathological evaluation of cancer tissues. Information obtained by immunofluorescence imaging is encoded by features in histological images. SHIFT leverages previously unappreciated features in histological images to facilitate virtual immunofluorescence staining. Feature representations of images guide sample selection, improving model generalizability.

While patients with primary glioblastoma (GBM) have benefited from increased overall survival due to treatment with the alkylating chemotherapy temozolomide (TMZ), the benefit of TMZ for patients with diffuse low-grade gliomas (LGG) remains unknown. We previously demonstrated that among ten TMZ-treated patients with initial LGG (IDH1 mutant, 1p19q intact), treatment induced hypermutation in the recurrent tumors of six patients, all six of whom underwent malignant progression to secondary GBM (sGBM) (Johnson & Mazor, Science, 2014). To further explore the relationships among TMZ treatment, hypermutation and malignant progression, we studied tumor evolution in an expanded cohort of 35 TMZ-treated patients by exome-sequencing of paired IDH1/2-mutant LGGs and their post-TMZ recurrences. This expanded cohort allowed us to contrast patterns of hypermutation between 1p19q intact versus co-deleted subgroups. Hypermutated recurrences were common in both subgroups and consistently underwent malignant progression to the highest grade while acquiring somatic mutations in mismatch repair (MMR) genes. In contrast to the 1p19q intact subgroup in which TP53 mutations were present at diagnosis, the hypermutated recurrences of the 1p19q co-deleted subgroup frequently acquired TMZ-associated mutations in TP53. This suggests that TP53 mutations may cooperate with MMR mutations to convert TMZ-induced cytotoxicity to mutagenicity. Once hypermutated clones arose, we found that they dominated subsequent recurrences. In one case, a hypermutated sGBM was resected, but soon recurred with leptomeningeal spread, at which point hypermutated clones were found in the spinal cord. We examined the clonality of hypermutated tumors through exome-sequencing of multiple spatially distinct samples, from which we estimate that hypermutated recurrent tumors can originate from a single initiating cell. Together, these findings further our understanding of the molecular features and clinical behavior of hypermutated clones, raising concerns about the potent mutagenic activity of TMZ and other alkylating agents in LGG patients.

TPS781 Background: Even as the number of targeted agents increases, therapeutic options for PDAC patients remain limited by a lack of biomarkers that can predict the potential clinical benefit of single agents or combination therapeutic strategies. To address this challenge, we implemented the WOO-M trial to serve as a highly adaptable, biomarker discovery platform that enables a preliminary assessment of biological activity of one or more targeted agents in patients with metastatic (m) PDAC. By using paired pre- and on-treatment biopsies, we can assess the independent biological impact of targeted agent(s) that perturb key signaling pathways predicted to drive PDAC tumorigenesis and resistance to therapy in order to identify new combination therapy strategies. Methods: WOO-M is a multi-arm early phase I trial platform to obtain longitudinal tumor samples to assess the pharmacodynamic (PD) effects of one or more study agent(s) alone or in combination in patients with mPDAC. The trial uses a Master Protocol to describe overarching design and logistics, and sub-protocols separately describe each study arm with different agent(s) – alone or in combination. Participants are alternatingly assigned to an available study arm (max. 20 participants per arm). There are no limits to the number of prior therapies. Participants undergo a baseline tumor biopsy, then receive their assigned study agent(s) for a specified timeframe (not exceeding 30 days), and then undergo a repeat tumor biopsy before proceeding to receive therapy per standard of care or clinical trials. The paired biopsy material from each patient is analyzed using multiplex assays that provides spatially-resolved, single-cell strategies to assess the effects of targeted therapies on tumor cell state and heterogeneity. The primary study objective is to independently assess the PD feasibility of detecting a measurable change in tumor biology at post-treatment from baseline for participants within a study arm. WOO-M uses a 2-stage Bayesian efficacy monitoring approach with a futility-stopping rule for each study arm. In stage 1, if 6 or more of the first 10 participants of a study arm have a detectable change in tumor biology measurements post-treatment from baseline, then the study arm may enroll up to an additional 10 participants. A study arm stops enrolling if 5 or fewer of the first 10 participants do not have a measurable change in tumor biology. To date, 4 study arms are being evaluated: 1) poly (ADP-ribose) polymerase inhibitor (PARPi), olaparib (300 mg PO BID for 10 days), 2) MEK inhibitor (MEKi), cobimetinib (60 mg PO QD for 10 days), 3) ERK inhibitor, LY3214996 (400 mg PO QD for 10 days), and 4) PLK1 inhibitor, onvansertib (12 mg/m 2 PO QD for 10 days). Of 21 participants enrolled and treated to date, 8 received cobimetinib, and 13 received olaparib. Additional arms are in the process of opening at time of submission. Clinical trial information: NCT04005690

Abstract BACKGROUND PARP inhibitors (PARPi) afford a rational therapeutic strategy in metastatic TNBC (mTNBC) due to the high incidence of dysregulated DNA damage repair mechanisms and high-level genomic instability that resemble tumors originating in germline BRCA-mutated carriers. However, PARPi monotherapy has limited efficacy in BRCA wild-type mTNBC; in BRCA mutant disease following initial response, compensatory mechanisms inevitably restore replication fork protection. AMTEC leverages pre- and on-therapy biopsies from a 4-week PARPi monotherapy run-in period for personalized biomarker-driven patient selection to interdict adaptive resistance to the PARPi. Data from our pilot study (NCT03544125) and from Arm 1 of AMTEC (olaparib + durvalumab) identified PI3K-AKT, RAS-MEK, and ATR/CHK1/WEE1 as targetable pathways contributing to PARPi adaptive resistance in individual participants. Clinically validated assays (DNA, RNA, and protein) enable the identification of cellular mechanisms of PARPi sensitivity and resistance in individual patients and further reveal combined drug treatments that could prevent emergence of PARPi resistance. METHODS AMTEC is a non-comparative, multi-arm, open-label, phase II study to assess the efficacy of combining olaparib (ola) with durvalumab (dur), or MEKi, selumetinib (sel), or AKTi, capivasertib (cap), or monotherapy with ATRi, ceralasertib, (cer mono) in mTNBC patients. Participants with biopsy proven mTNBC (ER< 10%, PR< 10%, and HER-2 non-amplified), AR< 80% are eligible. - Participants undergo a pre-treatment biopsy, then start a 28-day induction with ola (300 mg PO BID, D1-28). On C1D14, patients undergo a repeat, on-treatment biopsy. Clinically validated assays (DNA, RNA, protein) from both biopsies inform patient assignment to a specific ola combination arm starting on C2D1: - Arm 1 tumor immune activated: ola + dur (1500 mg IV Q4W) - Arm 2 RAS-MEK-ERK pathway activation: ola + sel (BSA-based BID D1-28) - Arm 3 PI3K-AKT pathway activation: ola + cap (400 mg PO BID, 4 days on/3 days off) - Arm 4: If not eligible for Arms 1-3 (per biomarker selection criteria): Cer mono (240 mg PO BID D1-14) Endpoints: The primary endpoint is objective response rate (ORR per RECIST 1.1). Secondary endpoints include safety and toxicity, clinical benefit rate, duration of response, and survival. Statistical Methods: - Arm 1 will enroll 28 patients to detect an ORR difference of 20% (H0: π = 0.15 and Ha: π =0.35). Arm 1 will continue on to stage 2 if ORR ≥3 of the first 15 patients. The null hypothesis for Arm 1 is rejected if ≥ 7/28 patient achieve a response. - Arms 2, 3, and 4, will each enroll 22 patients to detect an ORR difference of 25% (H0: π = 0.15 and Ha: π =0.40). Arms 2, 3, and 4 will each continue on to stage 2 if ORR ≥2 of first 11 patients in each arm, respectively. The null hypothesis for Arm 2, 3, and 4 is rejected if ≥ 7/22 patients achieve a response in each arm, respectively. For arms 2 and 3, if there are ≥5/11 responses, the trial will open a biomarker negative expansion cohort for each arm (N = 19 patients/arm). ENROLLMENT The study was activated on 1/7/2019. Arm 1 met pre-specified interim analysis criteria in 12/2020, and accrual to stage 2 began in 1/2021. Arms 2, 3, and 4 start enrolling in Q4 of 2022. Up to 132 patients will be enrolled. Clinical trial information: NCT03801369 Contact information: For more information or to refer a patient, email hobbev@ohsu.edu Citation Format: Evthokia Hobbs, Gordon Mills, Jeong Lim, Marlana Klinger, Kiara Siex, Sidney Huszti, Annie Yang, Danielle Galipeau, Christina Zheng, Lauren Murray, Becky Goodford, Nicholas Marter-Sanders, Anastasiya Olson, Jayne Stommel, Brett Johnson, Jamie Keck, Ben Kong, Allison Solanki, Shaun Goodyear, Christopher Corless, Joe Gray, Mitri Zahi. Adaptive Multi-Drug Treatment of Evolving Cancers (AMTEC): A Phase II, Open-Label, Study of Olaparib in Combination with either Durvalumab, Selumetinib or Capivasertib, or Ceralasertib Monotherapy in Patients with Metastatic TNBC [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr OT3-05-01.

Abstract The power of spatial biology lies in the integration of multiple scales of information from subcellular to tissue scale. Until recently, spatial analysis of protein biomarkers in tissues was limited to a few markers at a time using traditional IHC colorimetric or fluorescent readout. Here, we demonstrate the ability of NanoString’s CosMx™ Spatial Molecular Imager (SMI) platform to quantify more than 70 proteins encompassing key targets in immuno-oncology and tumor biology, localize the proteins and analyze protein expression at a single cell level. Key to the technology is the use of fully automated fluidics and imaging systems, short turnaround time, and high sensitivity. The CosMx protein assay has been optimized for FFPE samples, which represent the largest collection of biospecimens available for clinical investigation. To that end, we explored the utility of CosMx spatial proteomics on a series of clinical samples from cancer patients, including the Serial Measurements of Molecular and Architectural Response to Therapy (SMMART) trial, across multiple cancer types. CosMx SMI’s high-level protein multiplexing capabilities enabled spatial analysis of metastatic tumors in response to personalized treatment for a single patient over time. Combining spatial data obtained from both CosMx RNA and protein assays on the same sample reveals distinct regions of Tumor Associated Macrophages and their interactions with tumor cells in some samples. Detection of phosphoproteins also allows for analysis of the impact of kinase inhibitor treatment on the spatial environment in longitudinal biopsies. The highly-multiplexed spatial analysis of proteins in longitudinal metastatic breast cancer biopsies under therapeutic pressure provides a unique opportunity to understand evolution of tumors and develop and implement therapeutic approaches that can directly target mutations arising in the tumor cells while effectively engaging the immune system. FOR RESEARCH USE ONLY. Not for use in diagnostic procedures. Citation Format: Zachary R. Lewis, Brian Birditt, Emily Brown, Kan Chantranuvatana, Brian Filanoski, Chris Corless, Tiên Phan-Everson, Gary Geiss, Tyler Hether, Evie Hobbs, Brett Johnson, Taylor Kelley, Charles Lopez, Rhonda Meredith, Anastasiya Olson, Giang Ong, Mithra Korukonda, Erin Piazza, Jason Reeves, Alyssa Rosenbloom, Kiara Siex, Hye Son Yi, Edward Zhao, Joseph M. Beechem, Gordon Mills. Single cell spatial molecular imaging of 76-plex proteins in clinical cancer samples in response to personalized treatment. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5641.

e22006 Background: DSRCT is an extremely rare and highly aggressive soft-tissue sarcoma affecting adolescents and young adults with male predominance. The 5-year overall survival is < 25% despite intensive multi-modality treatment including aggressive surgical resection, radiotherapy, chemotherapy, and targeted therapy. Therefore, more effective and innovative therapeutic options are urgently needed. Recent advances in genomic, epigenomic, proteomic, and immune profiling have uncovered a large number of therapeutic targets that are transforming the field of cancer medicine. This study aimed to identify novel targetable pathways in DSRCT using a deep multi-omics-based platform. Methods: Three patients with biopsy proven metastatic DSRCT were enrolled under an IRB-approved observational study within the “Serial Measurements of Molecular and Architectural Responses to Therapy” (SMMART) program at OHSU. Biopsies taken at enrollment were analyzed with targeted DNA sequencing, whole transcriptome sequencing, immunohistochemistry (IHC), NanoString GeoMx digital spatial profiling (DSP) multiplexed proteomics, single cell cyclic immunofluorescence (Cyc-IF), and reverse phase protein array (RPPA). Results: Multiple clinically relevant targets were identified, including HER2, androgen receptor (AR), elevated DNA damage response, and MAPK and mTOR signaling pathways. All three DSRCTs expressed HER2: clinical IHC identified HER2 low (1+) to HER2 equivocal (2+) expression; DSP analysis showed high HER2 and phospho-HER2 expression; and HER2 RNA expression was elevated compared to the TCGA sarcoma cohort. Two of the three patients displayed high AR protein expression, assessed by clinical IHC (90-100% positive cells) and DSP (top quartile compared to a 20 mixed-subtype breast cancer cohort). Strong evidence of DNA damage response was demonstrated at both RNA and protein levels, and RPPA revealed high PARP1, PAR, p-ATM, p-RPA32, and RAD51. Within cell signaling pathways, one DSRCT exhibited high total and phospho-ERK1/2 protein across all clinical and exploratory assays, while another patient displayed evidence of elevated mTOR pathway signaling by RPPA. Conclusions: Overall, this multi-omic analysis provided new insights into possible therapeutic targets for this rare and difficult to treat sarcoma subtype. Results from this study will be further validated in vivo using patient-derived xenograft (PDX) models, providing support for development of multiple early phase trials.

Tumors may contain billions of cells including distinct malignant clones and nonmalignant cell types. Clarifying the evolutionary histories, prevalence, and defining molecular features of these cells is essential for improving clinical outcomes, since intratumoral heterogeneity provides fuel for acquired resistance to targeted therapies. Here we present a statistically motivated strategy for deconstructing intratumoral heterogeneity through multiomic and multiscale analysis of serial tumor sections (MOMA). By combining deep sampling of IDH-mutant astrocytomas with integrative analysis of single-nucleotide variants, copy-number variants, and gene expression, we reconstruct and validate the phylogenies, spatial distributions, and transcriptional profiles of distinct malignant clones. By genotyping nuclei analyzed by single-nucleus RNA-seq for truncal mutations, we further show that commonly used algorithms for identifying cancer cells from single-cell transcriptomes may be inaccurate. We also demonstrate that correlating gene expression with tumor purity in bulk samples can reveal optimal markers of malignant cells and use this approach to identify a core set of genes that is consistently expressed by astrocytoma truncal clones, including AKR1C3, whose expression is associated with poor outcomes in several types of cancer. In summary, MOMA provides a robust and flexible strategy for precisely deconstructing intratumoral heterogeneity and clarifying the core molecular properties of distinct cellular populations in solid tumors.

Abstract CDK4/6 inhibitors (CDK4/6i) have transformed the treatment of hormone receptor-positive (HR+), HER2-negative (HR+) breast cancers as they are effective across all clinicopathological, age, and ethnicity subgroups for metastatic HR+ breast cancer. In metastatic ER+ breast cancer, CDK4/6i lead to strong and consistent improvement in survival across different lines of therapy. To understand how metastatic HR+ breast cancers become refractory to CDK4/6i, we have created a multimodal and longitudinal tumor atlas to investigate therapeutic adaptations in malignant cells and in the tumor immune microenvironment. This atlas is part of the NCI Cancer Moonshot Human Tumor Atlas Network and includes seven pairs of pre- and on-progression biopsies from five metastatic HR+ breast cancer patients treated with CDK4/6i. Biopsies were profiled with bulk genomics, transcriptomics, and proteomics as well as single-cell ATAC-seq and multiplex tissue imaging for spatial, single-cell resolution. These molecular datasets were then linked with detailed clinical metadata to create an atlas for understanding tumor adaptations during therapy. Analysis of our atlas datasets revealed a diverse but tractable set of tumor adaptations to CDK4/6i therapy. Malignant cells adapted to therapy via mTORC1 activation, cell cycle bypass, and increased replication stress. The tumor immune microenvironment displayed evidence of both immune activation and immune suppression, including increased PD-1 expression, features of T cell dysfunction, and CD163 + macrophage infiltration. Together, our metastatic ER+ breast cancer atlas represents a rich multimodal resource to understand tumor therapeutic adaptations to CDK4/6i therapy.

Abstract Understanding the molecular consequences of oncogenic mutations is an important goal that may reveal essential features of malignant cells and new therapeutic targets for diverse cancers. However, this task is complicated by substantial inter- and intra-tumoral heterogeneity, which obscure the molecular consequences of oncogenic mutations in malignant cells. Although single-cell methods hold promise for this task, it remains non-trivial to isolate DNA and RNA from the same cell at scale. Here we describe a statistically motivated strategy that controls for inter-tumoral heterogeneity and exploits intra-tumoral heterogeneity to reveal the most consistent molecular phenotypes of malignant cells. By combining deep, multiscale sampling of IDH-mutant astrocytomas with integrative, multiomic analysis, we reconstruct and validate the phylogenies, spatial distributions, and molecular profiles of distinct malignant clones. Importantly, by genotyping nuclei for driver mutations, we show that existing strategies for inferring malignancy from gene expression profiles of single cells may be inaccurate. We identify genes that are consistently upregulated in the truncal clone of IDH-mutant astrocytomas, which are significantly enriched with genes involved in RNA splicing, mRNA transport and the nuclear pore, and WNT / MYC signaling. Furthermore, we find that expression phenotypes of malignancy persist despite loss of the mutant IDH1 protein following chr2q deletion in a subset of malignant cells. More broadly, our work provides a generalizable strategy for precisely deconstructing intra-tumoral heterogeneity and determining the most robust molecular consequences of oncogenic mutations in any kind of solid tumor.

Over 95% of patients with metastatic colorectal cancer (mCRC) are ineligible for immune checkpoint inhibitors as standard of care due to a lack of observed response in microsatellite stable/mismatch repair proficient (MSS/pMMR) tumors. Current standard of care includes chemotherapy and targeted therapy regimens. Botensilimab (BOT) – a multifunctional Fc-enhanced anti-CTLA-4 antibody designed to enhance T cell priming, activation, and memory formation; deplete intratumoral Treg cells; and minimize complement fixation – has demonstrated preclinical and promising early phase clinical data. In an ongoing Phase 1 study (NCT03860272), BOT ± balstilimab (BAL; anti-PD-1) has shown responses across a wide variety of cold/I-O refractory solid tumors, particularly in CRC patients without active liver metastases, with a managable safety profile. The aim of this randomized Phase 2 study is to evaluate the clinical efficacy and safety of BOT alone and in combination with BAL in patients with refractory non-microsatellite instability-high (non-MSI-H)/non-deficient MMR mCRC. This study (NCT05608044) includes adults ≥18 years old with confirmed non-MSI-H/non-deficient MMR mCRC who have received ≥1 prior chemotherapy regimen for metastatic disease with fluoropyrimidine, oxaliplatin, and irinotecan plus a monoclonal antibody as appropriate. Patients are excluded if they have active liver metastases or have previously received an immune checkpoint inhibitor, regorafenib, or trifluridine/tipiracil. Patients are randomized 1:1:1:1:1 to the following treatments: Arm A: BOT dose 1 every 6 weeks (Q6W) and BAL dose Q2W; Arm B: BOT dose 2 Q6W and BAL dose Q2W; Arm C: BOT dose 1 Q6W; Arm D: BOT dose 2 Q6W; Arm E: Investigator choice of regorafenib or trifluridine/tipiracil until disease progression/unacceptable toxicity. The primary endpoint is objective response rate (ORR) by RECISTv1.1. Secondary endpoints include duration of response, progression-free survival, overall survival, and safety. Global enrollment is ongoing with 111 patients currently enrolled across 8 countries. NCT05608044. Editorial assistance was provided by Dan Rigotti and Frankie Sorrell, Excel Medical Affairs, Glasgow, UK. Agenus Inc. Agenus Inc.

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Abstract Due to complexity of advanced epithelial cancers, it is necessary to implement patient specific combination therapies if we are to markedly improve patient outcomes. However, our ability to select and implement patient specific combination therapies based on dynamic molecular changes in the tumor and tumor ecosystem in response to therapy remains extremely limited. In a pilot study, we evaluated the feasibility of real-time deep analysis of serial tumor samples from triple negative breast cancer patients to identify mechanisms of resistance and treatment opportunities as they emerge under therapeutic stress engendered by poly-ADP-ribose polymerase (PARP) inhibitors (PARPi). Although PARP inhibition was consistently observed in all patients, deep molecular analysis of the tumor and its ecosystem revealed insights into potentially effective therapeutic PARPi combinations. In a BRCA-mutant basal breast cancer exceptional long-term survivor, we noted striking PARPi-induced tumor destruction accompanied by a marked infiltration of immune cells containing CD8 effector cells, consistent with pre-clinical evidence for association between STING mediated immune activation and benefit from PARPi and immunotherapy. Tumor cells in the exceptional responder underwent extensive protein network rewiring in response to PARP inhibition. In contrast, there were minimal changes in the ecosystem of a luminal androgen receptor (LAR) rapid progressor in response to PARPi likely due to indifference to the effects of PARP inhibition. In this rapid progressor, there was minimal evidence of immune activation or protein network rewiring in response to PARPi, despite PARP being inhibited, and no clinical benefit was noted for this participant. Together, deep real-time analysis of longitudinal biopsies identified a suite of PARPi-induced emergent changes including immune activation, DNA damage checkpoint activation, apoptosis and signaling pathways including RTK, PI3K-AKT and RAS-MAPK, that could be used to select patient specific combination therapies, based on tumor and immune state changes that are likely to benefit specific patients. Highlights Longitudinal analysis of serial tumor samples in real-time identifies adaptive mechanisms of resistance to PARPi therapies. Deep molecular analysis of the tumor reveals insights into potentially effective therapeutic PARPi combinations. Extensive protein network rewiring, microenvironment and immune state changes are assessable factors for patient specific combination therapies.

Pexidartinib (PEX) is a small molecule inhibitor of KIT and the CSF1 receptor expressed on microglia, blood vessels, and glioblastoma (GBM) tumor cells. A prior recurrent GBM study showed that PEX readily crossed the blood-brain barrier. Preclinical studies indicate that PEX effects on tumor and microenvironment may sensitize newly diagnosed GBM to standard therapy. Phase Ib dose escalation determined the recommended Phase II dose (RP2D) with XRT and TMZ. Phase II primary endpoint was progression free survival (PFS); secondary endpoints included overall survival (OS) and safety. Patient inclusion/exclusion were designed to replicate the RTOG 0525 control arm, which was used as historical control. PEX 400mg BID daily 5 days/week during and 7 days/week after XRT was identified as the RP2D. In Phase II, 42 of 44 patients were evaluable. Prognostic factors showed good concordance between PEX population and the RTOG 0525 control arm. 28 of 42 patients experienced a PFS event. Median PFS from registration is 9.7 months in PEX patients (95% CI 7.3, 13.2) vs. 7.5 months in historical controls (p= 0.035)(HR 0.71, (95% CI 0.49, 1.03)). Initial OS analyses show 8 of 42 PEX patients with events at 9-months vs. 13.1 expected deaths in controls (p=0.046) and 12-month OS events of 9 (PEX) vs. 16.8 (expected control) (p=0.029). Estimated mOS for PEX is 25.1 months (95% CI 15.7, 41.0) vs. 18.9 months controls (p=0.108)(HR 0.72, 95% CI 0.43, 1.21), and updated data will be presented as additional events occur. PEX was well tolerated, with most common drug-related toxicities including neutropenia and increased ALT/AST. PEX 400mg BID can be safely combined with XRT/TMZ in newly diagnosed GBM. Initial Phase II results suggest promising effects of PEX in improving PFS and OS compared to robust, well-matched historical controls. Further investigation of PEX in randomized trials is warranted.

Low-grade gliomas frequently recur after surgical resection and may undergo malignant progression to a higher grade with a significantly worse prognosis. Understanding the origin and evolution of recurrences is critical for effectively treating residual disease to delay or prevent recurrence. Here, we extend previous work by sequencing the exomes of over 30 initial low-grade gliomas and their patient-matched recurrences to reconstruct the patterns of clonal evolution. We also sequence multiple spatially distinct samples from both initial low-grade and recurrent high-grade tumors to extensively dissect intratumoral heterogeneity. We identify a broad spectrum of genetic relatedness within tumor pairs, with the unexpected loss of canonical driver mutations upon recurrence. Therefore, resected portions of initial tumors can differ dramatically from tumorigenic portions of adjacent residual disease. The identification of common ancestral clones additionally reveals the order in which key driver mutations are acquired, allowing for a model of low-grade astrocytoma gliomagenesis. We have also previously shown that the treatment of low-grade gliomas with temozolomide induces hypermutation and alters the function of key cancer genes and their cognate pathways, potentially driving malignant progression. We extend that finding with an analysis of the evolution and intratumoral heterogeneity of additional hypermutated glioblastoma recurrences. These evolutionary trajectories have immediate ramifications for the use of mutagenic chemotherapies such as temozolomide, and for personalizing therapy to eliminate residual disease.

Extensive neuropil invasion is a hallmark of glioma growth and a subset of tumors demonstrate recurrence in the contralateral hemisphere without a path of tumor spread detected by MR imaging. We used an integrated genomic and radiographic approach to study a patient with a right nonenhancing insular mass histologically diagnosed as IDH1/2 wild-type anaplastic astrocytoma (AA) and a punctate nonenhancing T2 hyperintense focus within the left middle frontal gyrus subcortical white matter. Follow-up MR imaging, six months after initiation of Temozolomide based chemoradiotherapy, demonstrated focal enhancement within the left middle frontal gyrus lesion. Six months later a rim enhancing centrally necrotic mass involving left frontal lobe white matter was observed and diagnosed as glioblastoma. Whole exome sequencing of both tumors and targeted Sanger sequencing of 7-9 samplings from each tumor identified a novel five amino acid in-frame insertion in the PTEN C2 domain in both tumors that potentially disrupts cell membrane interaction and activates phosphotidylinositol 3-kinase (PI3K) signaling. As wild-type PTEN inhibits cellular migration, this early PTEN mutation might also promote invasion and the seeding of metastatic foci remote from the initial tumor mass. The right insular AA harbored amplifications of EGFR, MDM4 and PDGFRA (amplified and mutated) that were not detected within the contralateral glioblastoma. Conversely, the glioblastoma acquired CDKN2A homozygous deletion, probable NF1 biallelic inactivation (mutation and heterozygous loss), and a second hit to PTEN (heterozygous loss). Thirty-six shared mutations (including PTEN) and two shared copy number alterations unequivocally indicate a common origin for these spatially and temporally separated tumors. Taken together, these integrated radiographic and genomic data strongly suggest that the cells seeding the left frontal lobe tumor migrated from the evolving right insular tumor at an early time point and then followed an independent evolutionary trajectory.

Author(s): Johnson, Brett Earl | Advisor(s): Costello, Joseph | Abstract: Low-grade gliomas are slow-growing tumors that often undergo malignant progression to an aggressive high-grade glioblastoma (GBM) with a significantly worse prognosis. Treatment options after surgical resection include temozolomide (TMZ), an alkylating chemotherapeutic which is cytotoxic but can induce CgT/GgA transition mutations when DNA mismatch repair is deficient. However, the extent and clinical impact of TMZ-associated mutagenesis is poorly understood. To investigate the genomic evolution of recurrent tumors and the contribution of TMZ-induced mutagenesis to their mutational landscape, we sequenced the exomes of 23 initial low-grade gliomas and their patient-matched recurrences resected up to 11 years later. We identified a diverse set of evolutionary trajectories that included unexpected losses of canonical driver mutations and radical differences in the genetic relatedness of initial-recurrent tumor pairs. Notably, we found that the recurrent tumors of six patients treated after surgery with TMZ became hypermutated and subsequently recurred as GBM. In each, TMZ-associated mutations altered the function of key cancer genes in pathways involved in malignant progression, including activating mutations in MTOR and PIK3CA, and inactivating mutations in CDKN2A, PTEN, and RB1. These findings suggest that this widely used chemotherapeutic agent has the potential to accelerate tumor evolution with unintended clinical and biological consequences. The ongoing evolution of the genetic landscape in all recurrences emphasizes the need for a longitudinal approach to personalized cancer genomics.

Identifying the transcriptional consequences of mutations that cause tumors may reveal new targets for the development of cancer therapies. However, this task is complicated by the variability that characterizes tumors from different individuals, which arise from unique genetic backgrounds, consist of various cell types in different proportions, and often exhibit clonal heterogeneity. Here we present a novel strategy to connect mutant genotypes to aberrant transcriptional signatures within individual human tumors. This strategy deconstructs a tumor by extracting RNA from serial sections and comparing genome-wide gene coexpression relationships to control samples analyzed in a similar fashion. In parallel, quantitative genomic analysis of the same serial sections enables identification and mapping of clonal populations within the tumor. We apply this strategy to a single grade II human astrocytoma and identify tumor-specific transcriptional signatures. Genomic analysis reveals clonal heterogeneity, including a dominant clone marked by mutations in IDH1 and TP53. Expression patterns of the two largest tumor-specific transcriptional signatures are almost perfectly associated with the spatial distribution of the dominant clone and consist of genes that are activated or repressed within malignant cells and their microenvironment. Our experimental strategy offers an unbiased and personalized method for identifying aberrant transcriptional signatures that are associated with specific mutant genotypes in any solid tumor while preserving the complex cellular milieu of the tumor microenvironment. More generally, this strategy can reveal shared and distinct patterns of transcriptional organization between any pair of tissue samples, thereby facilitating novel comparisons of diverse biological systems in health and disease.

Brain tumors can be classified by highly recurrent somatic alterations that have predictable molecular consequences and promote malignancy. By correlating mutant allele frequencies with molecular features such as DNA methylation and gene expression over many tumor specimens, it should be possible to identify and prioritize molecular features of malignant cells that are sensitive, specific, and druggable. However, this task is complicated by the variability that characterizes tumors from different individuals, which arise from unique genetic backgrounds, exist in variable environments, exhibit clonal heterogeneity, and may originate in different cell types. These factors, along with technical variation introduced during the collection and processing of tumor specimens from different individuals, obscure the molecular consequences of oncogenic mutations. We describe a novel strategy that controls for these factors by generating an arbitrary number of standardized biological replicates from a single tumor through serial sectioning for personalized multiomic analysis. We apply this strategy to low-grade glioma by analyzing mutant allele frequencies, copy number variation, DNA methylation, and gene expression in serial sections of individual tumor specimens. We identify genetic, epigenetic, and transcriptional signatures of clonal malignant populations and chart their distributions. More specifically, we observe DNA methylation and gene expression signatures that are almost perfectly associated with the distribution of IDH1MUT / TP53MUT cells within astrocytoma, including MGMT, whose methylation status correlates inversely with expression. Comparison of molecular signatures associated with IDH1 mutant allele frequencies using MASS or TCGA data reveals significant overlap, but with far stronger associations in serial sections vs. single biopsy specimens. In summary, MASS offers an unbiased, personalized, and generalizable approach for determining the molecular consequences of driver mutations in solid tumors while abrogating the need for large cohorts of samples sharing common genomic aberrations.

This study has brought together image processing, clustering and spatial pattern analysis to quantitatively analyze hematoxylin and eosin-stained (HE) tissue sections. A mixture of tumor and normal cells (intratumoral heterogeneity) as well as complex tissue architectures of most samples complicate the interpretation of their cytological profiles. To address these challenges, we develop a simple but effective methodology for quantitative analysis for HE section. We adopt comparative analyses of spatial point patterns to characterize spatial distribution of different nuclei types and complement cellular characteristics analysis. We demonstrate that tumor and normal cell regions exhibit significant differences of lymphocytes spatial distribution or lymphocyte infiltration pattern.

This lecture begins with a description of historical materialism (without naming it) and is full of examples of exploitation (recent and historical). I have abandoned a Marxist definition of exploitation (extraction of surplus value) and used a more common definition of exploitation. It ends with explaining class interests and class conflict. I also sometimes use a covert simulation to start off the class. I announce that some course assignment has changed in a manner that seems completely unfair to my students (e.g. paper due date moved up, paper lengthened, extra paper added) and I announce that it is out of my control (i.e. administration has someone imposed it upon me). I then proceed with my lecture about exploitation. At the end of the lecture, I announce that the above mentioned syllabus change was just a simulation.

The following understanding of alienation is based on three main sources: (1) Marx, Karl. [1844] 1964. Economic and Philosophical Manuscripts. NY: International Publishers, (2) a reworking of Marx to fit modern factory workers by Robert Blauner. 1964. Alienation and Freedom: the factory worker and his industry. University of Chicago Press, and (3) my reworking of Blauner’s work to better incorporate modern white-collar workers. While introducing components of alienation, you can have students apply them to jobs that they have had and indicate whether their job had a low, medium, or high level of alienation for each component. You can also have students apply alienation to the following readings and videos.

In my experience, students’ understanding of sociological concepts can be immensely improved through short video clips and articles from alternative media. These materials provide excellent opportunities for students to apply theoretical concepts they have learned in lecture. This method allows theoretical insights to emanate from and be illuminated by descriptive accounts. I have found this to be especially true when teaching Marxist concepts and perspectives. The following resource list highlights some common economic and social concepts and a few examples of video clips and readings that I have used over the past 10 years to bring alive these topics for undergraduate students. The readings have been chosen for their accessibility, brevity, and ability to describe lived experiences for illustration of Marxist concepts. I recommend using these resources to augment traditional methods of teaching theoretical concepts.

e14521 Background: To implement real-time multi-omic analysis of proximal tumor biopsies to support precision-guided therapeutic intervention, a tissue acquisition and analysis trial was implemented. Here we report on anticipated findings and the unanticipated impact on patient management of this trial in the context of the broader initiative. Methods: Eligible patients presenting to Oregon Health and Science University Knight Cancer Institute were enrolled. Patients with biopsy proven metastatic or locally advanced unresectable prostate cancer, breast cancer, pancreatic cancer, or refractory acute myelogenous leukemia receiving standard of care therapy were eligible. Image guided percutaneous metastatic biopsies were collected and analyzed by the Knight Diagnostic Laboratories using CLIA/CAP-compliant next-generation DNA sequencing (GeneTrails Comprehensive Solid Tumor Panel - 124 genes) and RNA sequencing (GeneTrails Solid Tumor Fusion Gene Panel - 20 genes). Results were made available to the treating physician. Results: Between 1/26/2017 and 11/2/2017, 35 patients were enrolled, of which 25 successfully underwent biopsy. Of 23 samples yielding sufficient tumor for analysis, median biopsy cellularity and number of cores collected were 70% (15-90%) and 6 (2-20), respectively. No procedure-related complications were reported. 20 of 23 (87%) tumor samples harbored at least one potentially actionable mutation, with 18 (78%) harboring > 1 potential actionable mutation. The most common genetic alterations identified involved DNA damage repair genes, cell cycle regulating genes, the PIK3CA/Akt/mTOR pathway, and the FGFR gene family. To date, genomic results were used by treating physicians to guide next line of therapy for 4 (20%) patients. Conclusions: Real-time prospective tissue acquisition and analysis to support a successful translational oncology platform is feasible, frequently identifies potentially actionable mutations, and alters treatment selection in patients. This program is being expanded to additional clinical and research biomarker tests, and will provide the foundation to improve access and accrual to biomarker driven precision oncology trials.

Rapid advances in molecular diagnostics have led to a growing need for sophisticated and adaptive biospecimen collection methodologies that employ careful acquisition, preservation, and allocation of limited biopsy tissue and blood specimens. To facilitate the comprehensive characterization of serial biospecimens from patients participating in real-time adaptive treatment precision medicine clinical trials, we designed a multi-omic and multi-imaging analytical platform and sought to maximize the quality and suitability of tissue for each downstream analytic. We optimized this biospecimen management system over 38 research-protocol driven biopsies on 33 patients with late stage metastatic breast, prostate, and pancreatic cancer. Importantly, no biopsy-related adverse events occurred. All tissue samples and derivatives therefrom were barcoded and tracked using a custom database built on the LabVantage platform. Here, we report successful strategies for coordination between medical and surgical oncology, interventional radiology, pathology, and clinical and research laboratories. We developed a biopsy prioritization schema that considers patient safety, site selection, procedure type, and amount of tissue required. We evaluated specimens from a variety of biopsy procedures, including radiologically-guided needle cores, as well as laparoscopic, video-assisted thoracoscopic, and excisional biopsies. Radiologically-guided biopsies using 18 gauge needles yielded a median of 5 (1 cm) cores with 70% tumor cellularity, and was the best substrate to rapidly allocate known quantities of tissue into a variety of preservation formats. We also examined enhanced biospecimen preservation methods that improved performance of downstream analytics. For example, optimization of the formalin fixation process included transferring tissue from bedside to formalin within 2 minutes, maintaining low temperature throughout fixation, and standardizing the time spent in formalin. These efforts resulted in recovery of higher quality RNA from FFPE blocks, less tissue required for RNA sequencing, and opened the door to immunofluorescent staining of phosphoproteomic markers. Our protocol uses several preservation methods, including: FFPE for immunohistochemical and cyclic immunofluorescent staining as well as targeted panel, whole exome, and transcriptomic sequencing; OCT freezing for multiple single cell sequencing methods; flash freezing for proteomic profiling; disaggregation of live cells for 2D and 3D culturing; and a specialized fixative for electron microscopy. In conclusion, we demonstrate the feasibility of collecting high quality biospecimens for a variety of downstream analytical platforms with diverse sample requirements. These methods can be used to comprehensively characterize limited amounts of valuable tissue in molecularly driven clinical trials.Citation Format: Brett E. Johnson, Swapnil Parmar, Kiara Siex, Anastasiya Olson, Jennifer Laverdure, Jamie Keck, Annette Kolodzie, Alexander R. Guimaraes, Christopher Corless, Joe Gray, Gordon Mills, Raymond Bergan. Biospecimen management for the serial measurement of molecular and architectural responses to therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 480.

Comprehensive characterization of an individual’s cancer using multi-omic analyses and an expanding list of targeted therapies is providing an opportunity to uncover therapeutic vulnerabilities and rationally target multiple driving alterations in the tumor. To leverage this opportunity, a multi-disciplinary team is required to unravel the complexity of tumor behavior and genomic variant information, integrate data from multi-omic assays, and exploit potential synergies from combination therapy while avoiding toxicity, all of which occurs within the context of the patient’s clinical history and comorbidities. We report the preliminary experience of OHSU Knight Cancer Institute’s SMMART (Serial Measurements of Molecular and Architectural Responses to Therapy) Treatments Program Multi-omics Tumor Board (MTB). The role of the SMMART MTB, to date, has been to develop and optimize procedures in a feasibility protocol for future application in the clinical setting where we will provide personalized combinatorial treatment suggestions. Here we report our preliminary experience over the last 15 months with multi-disciplinary tumor boards for metastatic breast cancer. A deep analysis of data, in many cases from serial biopsies, enabled identification of personalized, multi-targeted therapy. Clinical and laboratory data are explored individually and collectively by oncologists, oncology pharmacists, molecular pathologists, cancer biologists, and computational biologists. Data from CLIA-certified analytics include, but are not limited to, a 124 gene targeted panel, whole exome sequencing, MSI, gene-fusion, RNAseq, and clinical IHC assays that provide status information about receptors (ER/PR/AR/HER2), proliferation rate, and tumor immunogenicity along with reflexive assays for expression of relevant proteins such as p16, RB, and PTEN. A customized LabKey® system allows for visual display of a patient’s clinical timeline with information about diagnoses, treatments, biopsies events, radiographic changes, and blood biomarkers; thereby providing MTB participants with a holistic view of the patient’s case summary. Our experience with several example breast cancer case scenarios identified therapeutic vulnerabilities that would not have been considered by a standard clinical tumor board with genomic data alone. Recent cases have included observations such as HER2 status switching, a rare pathogenic germline mutation, high PD-L1 expression, and gained expression of the androgen receptor. These cases further emphasize the value and importance of MTB discussions to oncologists for interpreting and analyzing complex multi-omic data and uncovering therapeutic options for patients. This experience will be utilized in the future for employing SMMART MTBs in a clinical setting as a platform to triage patients into different multi-targeted combinatorial treatment options.Citation Format: Jamie M. Keck, Swapnil Parmar, Ben Kong, Zahi Mitri, Christopher Corless, Annette Kolodzie, Allison Creason, Jeremy Goecks, Patrick Leyshock, Kiara Siex, Brett E. Johnson, Janice Patterson, Laura Heiser, Anastasiya Olson, Matt Viehdorfer, Georgia Mayfield, Jennifer Laverdure, Joe W. Gray, Gordon B. Mills, Raymond C. Bergan. Leveraging multi-omics tumor boards for precision medicine in the OHSU SMMART Treatments Program [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4929.

Spatially-resolved molecular profiling by immunostaining tissue sections is a key feature in cancer diagnosis, subtyping, and treatment, where it complements routine histopathological evaluation by clarifying tumor phenotypes. In this work, we present a deep learning-based method called speedy histological-to-immunofluorescent translation (SHIFT) which takes histologic images of hematoxylin and eosin-stained tissue as input, then in near-real time returns inferred virtual immunofluorescence (IF) images that accurately depict the underlying distribution of phenotypes without requiring immunostaining of the tissue being tested. We show that deep learning-extracted feature representations of histological images can guide representative sample selection, which improves SHIFT generalizability. SHIFT could serve as an efficient preliminary, auxiliary, or substitute for IF by delivering multiplexed virtual IF images for a fraction of the cost and in a fraction of the time required by nascent multiplexed imaging technologies.

Abstract Comprehensive characterization of an individual’s cancer using multi-omic analyses and an expanding list of targeted therapies is providing an opportunity to uncover therapeutic vulnerabilities and rationally target multiple driving alterations in the tumor. To leverage this opportunity, a multi-disciplinary team is required to unravel the complexity of tumor behavior and genomic variant information, integrate data from multi-omic assays, and exploit potential synergies from combination therapy while avoiding toxicity, all of which occurs within the context of the patient’s clinical history and comorbidities. We report the preliminary experience of OHSU Knight Cancer Institute’s SMMART (Serial Measurements of Molecular and Architectural Responses to Therapy) Treatments Program Multi-omics Tumor Board (MTB). The role of the SMMART MTB, to date, has been to develop and optimize procedures in a feasibility protocol for future application in the clinical setting where we will provide personalized combinatorial treatment suggestions. Here we report our preliminary experience over the last 15 months with multi-disciplinary tumor boards for metastatic breast cancer. A deep analysis of data, in many cases from serial biopsies, enabled identification of personalized, multi-targeted therapy. Clinical and laboratory data are explored individually and collectively by oncologists, oncology pharmacists, molecular pathologists, cancer biologists, and computational biologists. Data from CLIA-certified analytics include, but are not limited to, a 124 gene targeted panel, whole exome sequencing, MSI, gene-fusion, RNAseq, and clinical IHC assays that provide status information about receptors (ER/PR/AR/HER2), proliferation rate, and tumor immunogenicity along with reflexive assays for expression of relevant proteins such as p16, RB, and PTEN. A customized LabKey® system allows for visual display of a patient’s clinical timeline with information about diagnoses, treatments, biopsies events, radiographic changes, and blood biomarkers; thereby providing MTB participants with a holistic view of the patient’s case summary. Our experience with several example breast cancer case scenarios identified therapeutic vulnerabilities that would not have been considered by a standard clinical tumor board with genomic data alone. Recent cases have included observations such as HER2 status switching, a rare pathogenic germline mutation, high PD-L1 expression, and gained expression of the androgen receptor. These cases further emphasize the value and importance of MTB discussions to oncologists for interpreting and analyzing complex multi-omic data and uncovering therapeutic options for patients. This experience will be utilized in the future for employing SMMART MTBs in a clinical setting as a platform to triage patients into different multi-targeted combinatorial treatment options. Citation Format: Jamie M. Keck, Swapnil Parmar, Ben Kong, Zahi Mitri, Christopher Corless, Annette Kolodzie, Allison Creason, Jeremy Goecks, Patrick Leyshock, Kiara Siex, Brett E. Johnson, Janice Patterson, Laura Heiser, Anastasiya Olson, Matt Viehdorfer, Georgia Mayfield, Jennifer Laverdure, Joe W. Gray, Gordon B. Mills, Raymond C. Bergan. Leveraging multi-omics tumor boards for precision medicine in the OHSU SMMART Treatments Program [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4929.

Abstract Rapid advances in molecular diagnostics have led to a growing need for sophisticated and adaptive biospecimen collection methodologies that employ careful acquisition, preservation, and allocation of limited biopsy tissue and blood specimens. To facilitate the comprehensive characterization of serial biospecimens from patients participating in real-time adaptive treatment precision medicine clinical trials, we designed a multi-omic and multi-imaging analytical platform and sought to maximize the quality and suitability of tissue for each downstream analytic. We optimized this biospecimen management system over 38 research-protocol driven biopsies on 33 patients with late stage metastatic breast, prostate, and pancreatic cancer. Importantly, no biopsy-related adverse events occurred. All tissue samples and derivatives therefrom were barcoded and tracked using a custom database built on the LabVantage platform. Here, we report successful strategies for coordination between medical and surgical oncology, interventional radiology, pathology, and clinical and research laboratories. We developed a biopsy prioritization schema that considers patient safety, site selection, procedure type, and amount of tissue required. We evaluated specimens from a variety of biopsy procedures, including radiologically-guided needle cores, as well as laparoscopic, video-assisted thoracoscopic, and excisional biopsies. Radiologically-guided biopsies using 18 gauge needles yielded a median of 5 (1 cm) cores with 70% tumor cellularity, and was the best substrate to rapidly allocate known quantities of tissue into a variety of preservation formats. We also examined enhanced biospecimen preservation methods that improved performance of downstream analytics. For example, optimization of the formalin fixation process included transferring tissue from bedside to formalin within 2 minutes, maintaining low temperature throughout fixation, and standardizing the time spent in formalin. These efforts resulted in recovery of higher quality RNA from FFPE blocks, less tissue required for RNA sequencing, and opened the door to immunofluorescent staining of phosphoproteomic markers. Our protocol uses several preservation methods, including: FFPE for immunohistochemical and cyclic immunofluorescent staining as well as targeted panel, whole exome, and transcriptomic sequencing; OCT freezing for multiple single cell sequencing methods; flash freezing for proteomic profiling; disaggregation of live cells for 2D and 3D culturing; and a specialized fixative for electron microscopy. In conclusion, we demonstrate the feasibility of collecting high quality biospecimens for a variety of downstream analytical platforms with diverse sample requirements. These methods can be used to comprehensively characterize limited amounts of valuable tissue in molecularly driven clinical trials. Citation Format: Brett E. Johnson, Swapnil Parmar, Kiara Siex, Anastasiya Olson, Jennifer Laverdure, Jamie Keck, Annette Kolodzie, Alexander R. Guimaraes, Christopher Corless, Joe Gray, Gordon Mills, Raymond Bergan. Biospecimen management for the serial measurement of molecular and architectural responses to therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 480.

Abstract Background: Achieving a pathologic complete response (pCR) to neoadjuvant therapy correlates with excellent outcome in early stage breast cancer, including HR+ breast cancer (HRBC). Unfortunately, less than 10% of HRBC patients achieve pCR to neoadjuvant therapy; indicating a need for novel HRBC therapies, especially in the neoadjuvant setting. This study evaluates the novel combination of the cyclin dependent kinase inhibitor (CDKi), abemaciclib, in combination with the poly-ADP ribose polymerase inhibitor (PARPi), niraparib, as a neoadjuvant therapy for HRBC. Niraparib is an orally bioavailable PARPi indicated for the maintenance treatment of platinum-responsive, ovarian cancer, both 1st line and 2nd line. Abemaciclib is approved as a monotherapy or in combination with endocrine therapy in metastatic HRBC. In addition to targeting CDK4/6, abemaciclib also inhibits CDK1, CDK2, and Aurora A/B kinases, which are involved in DNA damage repair. Targeting kinases with abemaciclib sensitizes tumors to DNA-damaging agents, including PARPi. Preclinical data justifies the combination of abemaciclib and niraparib as a novel combination for the treatment of HRBC. Trial Design: This is a phase I dose-finding study evaluating the combination of abemaciclib and niraparib as a neoadjuvant therapy in patients with early stage HRBC. All eligible participants with biopsy-proven HRBC will undergo a pre-treatment biopsy and start on-study treatment with the combination of abemaciclib and niraparib using a traditional 3+3 dose-escalation algorithm to determine maximum-tolerated dose (MTD). Dose levels are outlined in Table 1. Each cycle is 28 days. After 2 cycles, participants will undergo repeat imaging and biopsy: those with stable or responding disease will continue to receive an additional 2 cycles of abemaciclib and niraparib, followed by surgical resection. Participants with progressive disease will be switched to standard of care chemotherapy. Once the MTD is determined, additional participants up to a sample size maximum of 25 will be enrolled into an expansion cohort (including those from the dosing finding phase) and treated at the established MTD. Eligibility Criteria: Key Inclusion Criteria: Age ≥ 18 years, biopsy-proven HR+ Her2 non-amplified breast cancer planned for neoadjuvant chemotherapy, ECOG PS ≤1, disease amenable to curative surgical resection. Key Exclusion Criteria: Evidence of metastatic disease, prior PARPi or CDK 4/6i exposure Specific Aims: Primary Endpoints: Incidence of dose-limiting toxicities (DLTs), incidence of adverse events (AEs) and serious AEs (per CTCAE 5.0). Secondary Endpoints: overall objective response rate, clinical benefit rate, pCR rate, and rate of residual cancer burden 0-1 Statistical Methods: This phase I dose-escalation study for the proposed combination will follow traditional 3+3 escalation rules. The sample size maximum of 25 (including both those from the dosing finding and expansion portions) allows for a greater than 80% chance that the incidence of any AE as rare as 6.4% or greater will be observed in the cohort. For assessments of preliminary efficacy, the sample size provides a two-sided 95% confidence interval with a half width equal to 0.140 when the targeted pCR is 0.15. Planned Activation Date: Target Accrual: n=25 participants Contact: Zahi Mitri, MD, MS 3181 SW Sam Jackson Park Road, OC14HO, Portland, OR 97239 503-494-9160, mitri@ohsu.edu Table 1. Study Regimen Dose LevelsDose Levels (DLAbemaciclib (PO)Niraparib (PO)DL -1100 mg BID100 mg QDDL 1 starting150 mg BID100 mg QDDL 2150 mg BID200 mg QD Citation Format: Allen Li, Arpana Naik, Nathalie Johnson, Shaun Goodyear, Brett Johnson, Byung Park, Christopher Corless, Joe Gray, Gordon Mills, Zahi Mitri. A phase 1 study of abemaciclib and niraparib as neoadjuvant therapy in hormone receptor positive (HR+) HER2 negative (HER2-) breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr OT-16-01.

Abstract Many of the current approaches to personalized medicine rely on sequencing DNA to identify actionable mutations. However, growing evidence suggests that a multi-omic approach to more broadly assess biology is needed to improve patient outcomes. We have implemented a workflow for tissue acquisition, multi-omic clinical testing, and correlated computational biology analysis, within the Serial Measurements of Molecular and Architectural Responses to Therapy (SMMART) Program (Mitri et al, J Transl Med 2018). We report biopsy metrics, CLIA analytics utilized, the operation of a multi-omics tumor board, and clinical outcomes in metastatic breast cancer patients. A detailed clinical history of each patient was obtained, including demographics, tumor type, treatment and response to prior therapies, imaging, and blood tumor biomarkers. A comprehensive set of clinical assays was performed on newly obtained tumor biopsies, including immunohistochemistry (ER, PR, HER2, AR, BCL-2, and PD-L1), a targeted next-generation sequencing panel covering 225 genes (GeneTrails® Comprehensive Solid Tumor Panel), whole exome sequencing (Tempus xE), whole transcriptomic sequencing (Illumina TruSeq RNA exome), and a multiplex protein analysis of 22 key cancer proteins and phosphoproteins on the Nanostring platform (NanoString Vantage 3D™ Solid Tumor Panel). The integrated clinical and analytical information was made available to the multidisciplinary SMMART Clinical Tumor Board that provided treatment recommendations; the final treatment plan was at the discretion of the treating physician. Between 1/1/2017-1/1/2020, 53 breast cancer patients were consented. Seven screen-failed due to a lack of sites amenable to biopsy and 8 were actively co-consented to other clinical trials. The remaining 38 patients are included in this preliminary report. A total of 63 biopsies were collected from lymph node, liver, bone, soft tissue, lung, skin, breast, and brain. Serial biopsies (≥2) were obtained for 15 patients. Analytics were generated in 93.7% of biopsies. Tumor boards were held for 15 patients (17 total sessions). The experience and information gathered thus far have yielded the following unique cases: (1) single patient analysis of omics, imaging, and response over 42 months, (2) identification of an ERBB3 mutation with downstream pathway activation that responded to HER2-targeted therapy, and (3) clinically significant variation in hormonal and HER2 receptor status over time. We will provide an analysis across the 38 patients of treatment outcomes, analytics information content, biological changes observed through serial biopsies, and tumor board interventions. We demonstrate the feasibility of implementing a deep, real-time analytics platform for metastatic breast cancer patients that can provide new insight into therapeutic opportunities. The observed clinical responses support further use and investigation of this approach. Citation Format: Ben L. Kong, Brett E. Johnson, Jamie M. Keck, Souraya Mitri, Patrick Leyshock, Jayne M. Stommel, Kiara Siex, Marlana Klinger, Christina L. Zheng, Rochelle Williams-Belizaire, Shannon McWeeney, Jeremy Goecks, Annette Kolodzie, Alexander R. Guimaraes, George V. Thomas, Christopher L. Corless, Zahi I. Mitri, Joe W. Gray, Gordon B. Mills, Raymond C. Bergan. SMMART Program: A multi-omics tumor board with a focus on breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB010.