Paul A. Rejto

An important prerequisite for computational structure-based drug design is prediction of the structures of ligand-protein complexes that have not yet been experimentally determined by X-ray crystallography or NMR. For this task, docking of rigid ligands is inadequate because it assumes knowledge of the conformation of the bound ligand. Docking of flexible ligands would be desirable, but requires one to search an enormous conformational space. We set out to develop a strategy for flexible docking by combining a simple model of ligand-protein interactions for molecular recognition with an evolutionary programming search technique.We have developed an intermolecular energy function that incorporates steric and hydrogen-bonding terms. The parameters in this function were obtained by docking in three different protein systems. The effectiveness of this method was demonstrated by conformationally flexible docking of the inhibitor AG-1343, a potential new drug against AIDS, into HIV-1 protease. For this molecule, which has nine rotatable bonds, the crystal structure was reproduced within 1.5 A root-mean-square deviation 34 times in 100 simulations, each requiring eight minutes on a Silicon Graphics R4400 workstation. The energy function correctly evaluates the crystal structure as the global energy minimum.We believe that a solution of the docking problem may be achieved by matching a simple model of molecular recognition with an efficient search procedure. The necessary ingredients of a molecular recognition model include only steric and hydrogen-bond interaction terms. Although these terms are not necessarily sufficient to predict binding affinity, they describe ligand-protein interactions faithfully enough to enable a docking program to predict the structure of the bound ligand. This docking strategy thus provides an important tool for the interdisciplinary field of rational drug design.

Hepatocellular carcinoma (HCC) is one of the most deadly cancers worldwide and has no effective treatment, yet the molecular basis of hepatocarcinogenesis remains largely unknown. Here we report findings from a whole-genome sequencing (WGS) study of 88 matched HCC tumor/normal pairs, 81 of which are Hepatitis B virus (HBV) positive, seeking to identify genetically altered genes and pathways implicated in HBV-associated HCC. We find beta-catenin to be the most frequently mutated oncogene (15.9%) and TP53 the most frequently mutated tumor suppressor (35.2%). The Wnt/beta-catenin and JAK/STAT pathways, altered in 62.5% and 45.5% of cases, respectively, are likely to act as two major oncogenic drivers in HCC. This study also identifies several prevalent and potentially actionable mutations, including activating mutations of Janus kinase 1 (JAK1), in 9.1% of patients and provides a path toward therapeutic intervention of the disease.

Cancer is a genetic disease with frequent somatic DNA alterations. Studying recurrent copy number aberrations (CNAs) in human cancers would enable the elucidation of disease mechanisms and the prioritization of candidate oncogenic drivers with causal roles in oncogenesis. We have comprehensively and systematically characterized CNAs and the accompanying gene expression changes in tumors and matched nontumor liver tissues from 286 hepatocellular carcinoma (HCC) patients. Our analysis identified 29 recurrently amplified and 22 recurrently deleted regions with a high level of copy number changes. These regions harbor established oncogenes and tumor suppressors, including CCND1 (cyclin D1), MET (hepatocyte growth factor receptor), CDKN2A (cyclin-dependent kinase inhibitor 2A) and CDKN2B (cyclin-dependent kinase inhibitor 2B), as well as many other genes not previously reported to be involved in liver carcinogenesis. Pathway analysis of cis-acting genes in the amplification and deletion peaks implicates alterations of core cancer pathways, including cell-cycle, p53 signaling, phosphoinositide 3-kinase signaling, mitogen-activated protein kinase signaling, Wnt signaling, and transforming growth factor beta signaling, in a large proportion of HCC patients. We further credentialed two candidate driver genes (BCL9 and MTDH) from the recurrent focal amplification peaks and showed that they play a significant role in HCC growth and survival. Conclusion: We have demonstrated that characterizing the CNA landscape in HCC will facilitate the understanding of disease mechanisms and the identification of oncogenic drivers that may serve as potential therapeutic targets for the treatment of this devastating disease. (Hepatology 2013;58:706–717)

To identify and characterize novel, activating mutations in Notch receptors in breast cancer and to determine response to the gamma secretase inhibitor (GSI) PF-03084014.We used several computational approaches, including novel algorithms, to analyze next-generation sequencing data and related omic datasets from The Cancer Genome Atlas (TCGA) breast cancer cohort. Patient-derived xenograft (PDX) models were sequenced, and Notch-mutant models were treated with PF-03084014. Gene-expression and functional analyses were performed to study the mechanism of activation through mutation and inhibition by PF-03084014.We identified mutations within and upstream of the PEST domains of NOTCH1, NOTCH2, and NOTCH3 in the TCGA dataset. Mutations occurred via several genetic mechanisms and compromised the function of the PEST domain, a negative regulatory domain commonly mutated in other cancers. Focal amplifications of NOTCH2 and NOTCH3 were also observed, as were heterodimerization or extracellular domain mutations at lower incidence. Mutations and amplifications often activated the Notch pathway as evidenced by increased expression of canonical Notch target genes, and functional mutations were significantly enriched in the triple-negative breast cancer subtype (TNBC). PDX models were also identified that harbored PEST domain mutations, and these models were highly sensitive to PF-03084014.This work suggests that Notch-altered breast cancer constitutes a bona fide oncogenic driver segment with the most common alteration being PEST domain mutations present in multiple Notch receptors. Importantly, functional studies suggest that this newly identified class can be targeted with Notch inhibitors, including GSIs.

The clinical success of immune checkpoint inhibitors demonstrates that reactivation of the human immune system delivers durable responses for some patients and represents an exciting approach for cancer treatment. An important class of preclinical in vivo models for immuno-oncology is immunocompetent mice bearing mouse syngeneic tumors. To facilitate translation of preclinical studies into human, we characterized the genomic, transcriptomic, and protein expression of a panel of ten commonly used mouse tumor cell lines grown in vitro culture as well as in vivo tumors.Our studies identified a number of genetic and cellular phenotypic differences that distinguish commonly used mouse syngeneic models in our study from human cancers. Only a fraction of the somatic single nucleotide variants (SNVs) in these common mouse cell lines directly match SNVs in human actionable cancer genes. Some models derived from epithelial tumors have a more mesenchymal phenotype with relatively low T-lymphocyte infiltration compared to the corresponding human cancers. CT26, a colon tumor model, had the highest immunogenicity and was the model most responsive to CTLA4 inhibitor treatment, by contrast to the relatively low immunogenicity and response rate to checkpoint inhibitor therapies in human colon cancers.The relative immunogenicity of these ten syngeneic tumors does not resemble typical human tumors derived from the same tissue of origin. By characterizing the mouse syngeneic models and comparing with their human tumor counterparts, this study contributes to a framework that may help investigators select the model most relevant to study a particular immune-oncology mechanism, and may rationalize some of the challenges associated with translating preclinical findings to clinical studies.

Abstract To elucidate the effects of neoadjuvant chemotherapy (NAC), we conduct whole transcriptome profiling coupled with histopathology analyses of a longitudinal breast cancer cohort of 146 patients including 110 pairs of serial tumor biopsies collected before treatment, after the first cycle of treatment and at the time of surgery. Here, we show that cytotoxic chemotherapies induce dynamic changes in the tumor immune microenvironment that vary by subtype and pathologic response. Just one cycle of treatment induces an immune stimulatory microenvironment harboring more tumor infiltrating lymphocytes (TILs) and up-regulation of inflammatory signatures predictive of response to anti-PD1 therapies while residual tumors are immune suppressed at end-of-treatment compared to the baseline. Increases in TILs and CD8+ T cell proportions in response to NAC are independently associated with pathologic complete response. Further, on-treatment immune response is more predictive of treatment outcome than immune features in paired baseline samples although these are strongly correlated.

The structure-based design, chemical synthesis, and biological evaluation of various human rhinovirus (HRV) 3C protease (3CP) inhibitors which incorporate P1 lactam moieties in lieu of an l-glutamine residue are described. These compounds are comprised of a tripeptidyl or peptidomimetic binding determinant and an ethyl propenoate Michael acceptor moiety which forms an irreversible covalent adduct with the active site cysteine residue of the 3C enzyme. The P1-lactam-containing inhibitors display significantly increased 3CP inhibition activity along with improved antirhinoviral properties relative to corresponding l-glutamine-derived molecules. In addition, several lactam-containing compounds exhibit excellent selectivity for HRV 3CP over several other serine and cysteine proteases and are not appreciably degraded by a variety of biological agents. One of the most potent inhibitors (AG7088, mean antirhinoviral EC90 ≈ 0.10 μM, n = 46 serotypes) is shown to warrant additional preclinical development to explore its potential for use as an antirhinoviral agent.

Abstract Context: The pathophysiological importance of glucocorticoids (GCs) is exemplified by patients with Cushing’s syndrome who develop hypertension, obesity, and insulin resistance. At a cellular level, availability of GCs to the glucocorticoid and mineralocorticoid receptors is controlled by the isoforms of 11β-hydroxysteroid dehydrogenase (11β-HSD). In liver and adipose tissue, 11β-HSD1 converts endogenous, inactive cortisone to active cortisol but also catalyzes the bioactivation of the synthetic prednisone to prednisolone. Objective: The objective of the study was to compare markers of 11β-HSD1 activity and demonstrate that inhibition of 11β-HSD1 activity limits glucocorticoid availability to adipose tissue. Design and Setting: This was a clinical study. Patients: Seven healthy male volunteers participated in the study. Intervention: Intervention included carbenoxolone (CBX) single dose (100 mg) and 72 hr of continuous treatment (300 mg/d). Main Outcome Measures: Inhibition of 11β-HSD1 was monitored using five different mechanistic biomarkers (serum cortisol and prednisolone generation, urinary corticosteroid metabolite analysis by gas chromatography/mass spectrometry, and adipose tissue microdialysis examining cortisol generation and glucocorticoid-mediated glycerol release). Results: Each biomarker demonstrated reduced 11β-HSD1 activity after CBX administration. After both a single dose and 72 hr of treatment with CBX, cortisol and prednisolone generation decreased as did the urinary tetrahydrocortisol+5α-tetrahydrocortisol to tetrahydrocortisone ratio. Using adipose tissue microdialysis, we observed decreased interstitial fluid cortisol availability with CBX treatment. Furthermore, a functional consequence of 11β-HSD1 inhibition was observed, namely decreased prednisone-induced glycerol release into adipose tissue interstitial fluid indicative of inhibition of GC-mediated lipolysis. Conclusion: CBX is able to inhibit rapidly the generation of active GC in human adipose tissue. Importantly, limiting GC availability in vivo has functional consequences including decreased glycerol release.

Abstract PF-03814735 is a novel, reversible inhibitor of Aurora kinases A and B that finished a phase I clinical trial for the treatment of advanced solid tumors. To find predictive biomarkers of drug sensitivity, we screened a diverse panel of 87 cancer cell lines for growth inhibition upon PF-03814735 treatment. Small cell lung cancer (SCLC) and, to a lesser extent, colon cancer lines were very sensitive to PF-03814735. The status of the Myc gene family and retinoblastoma pathway members significantly correlated with the efficacy of PF-03814735. Whereas RB1 inactivation, intact CDKN2A/p16, and normal CCND1/Cyclin D1 status are hallmarks of SCLC, activation or amplification of any of the three Myc genes (MYC, MYCL1, and MYCN) clearly differentiated cell line sensitivity within the SCLC panel. By contrast, we found that expression of Aurora A and B were weak predictors of response. We observed a decrease in histone H3 phosphorylation and polyploidization of sensitive lines, consistent with the phenotype of Aurora B inhibition. In vivo experiments with two SCLC xenograft models confirmed the sensitivity of Myc gene-driven models to PF-03814735 and a possible schedule dependence of MYC/c-Myc–driven tumors. Altogether our results suggest that SCLC and other malignancies driven by the Myc family genes may be suitable indications for treatment by Aurora B kinase inhibitors. Mol Cancer Ther; 11(3); 710–9. ©2012 AACR.

To develop a comprehensive overview of copy number aberrations (CNAs) in stage-II/III colorectal cancer (CRC), we characterized 302 tumors from the PETACC-3 clinical trial. Microsatellite-stable (MSS) samples (n = 269) had 66 minimal common CNA regions, with frequent gains on 20 q (72.5%), 7 (41.8%), 8 q (33.1%) and 13 q (51.0%) and losses on 18 (58.6%), 4 q (26%) and 21 q (21.6%). MSS tumors have significantly more CNAs than microsatellite-instable (MSI) tumors: within the MSI tumors a novel deletion of the tumor suppressor WWOX at 16 q23.1 was identified (p<0.01). Focal aberrations identified by the GISTIC method confirmed amplifications of oncogenes including EGFR, ERBB2, CCND1, MET, and MYC, and deletions of tumor suppressors including TP53, APC, and SMAD4, and gene expression was highly concordant with copy number aberration for these genes. Novel amplicons included putative oncogenes such as WNK1 and HNF4A, which also showed high concordance between copy number and expression. Survival analysis associated a specific patient segment featured by chromosome 20 q gains to an improved overall survival, which might be due to higher expression of genes such as EEF1B2 and PTK6. The CNA clustering also grouped tumors characterized by a poor prognosis BRAF-mutant-like signature derived from mRNA data from this cohort. We further revealed non-random correlation between CNAs among unlinked loci, including positive correlation between 20 q gain and 8 q gain, and 20 q gain and chromosome 18 loss, consistent with co-selection of these CNAs. These results reinforce the non-random nature of somatic CNAs in stage-II/III CRC and highlight loci and genes that may play an important role in driving the development and outcome of this disease.

Colorectal cancer (CRC) patients have poor prognosis after formation of distant metastasis. Understanding the molecular mechanisms by which genetic changes facilitate metastasis is critical for the development of targeted therapeutic strategies aimed at controlling disease progression while minimizing toxic side effects. A comprehensive portrait of somatic alterations in CRC and the changes between primary and metastatic tumors has yet to be developed. We performed whole genome sequencing of two primary CRC tumors and their matched liver metastases. By comparing to matched germline DNA, we catalogued somatic alterations at multiple scales, including single nucleotide variations, small insertions and deletions, copy number aberrations and structural variations in both the primary and matched metastasis. We found that the majority of these somatic alterations are present in both sites. Despite the overall similarity, several de novo alterations in the metastases were predicted to be deleterious, in genes including FBXW7, DCLK1 and FAT2, which might contribute to the initiation and progression of distant metastasis. Through careful examination of the mutation prevalence among tumor cells at each site, we also proposed distinct clonal evolution patterns between primary and metastatic tumors in the two cases. These results suggest that somatic alterations may play an important role in driving the development of colorectal cancer metastasis and present challenges and opportunities when considering the choice of treatment.

Cyclin-dependent kinase 4/6 inhibitor (CDK4/6) therapy plus endocrine therapy (ET) is an effective treatment for patients with hormone receptor-positive/human epidermal receptor 2-negative metastatic breast cancer (HR+/HER2- MBC); however, resistance is common and poorly understood. A comprehensive genomic and transcriptomic analysis of pretreatment and post-treatment tumors from patients receiving palbociclib plus ET was performed to delineate molecular mechanisms of drug resistance.Tissue was collected from 89 patients with HR+/HER2- MBC, including those with recurrent and/or metastatic disease, receiving palbociclib plus an aromatase inhibitor or fulvestrant at Samsung Medical Center and Seoul National University Hospital from 2017 to 2020. Tumor biopsy and blood samples obtained at pretreatment, on-treatment (6 weeks and/or 12 weeks), and post-progression underwent RNA sequencing and whole-exome sequencing. Cox regression analysis was performed to identify the clinical and genomic variables associated with progression-free survival.Novel markers associated with poor prognosis, including genomic scar features caused by homologous repair deficiency (HRD), estrogen response signatures, and four prognostic clusters with distinct molecular features were identified. Tumors with TP53 mutations co-occurring with a unique HRD-high cluster responded poorly to palbociclib plus ET. Comparisons of paired pre- and post-treatment samples revealed that tumors became enriched in APOBEC mutation signatures, and many switched to aggressive molecular subtypes with estrogen-independent characteristics. We identified frequent genomic alterations upon disease progression in RB1, ESR1, PTEN, and KMT2C.We identified novel molecular features associated with poor prognosis and molecular mechanisms that could be targeted to overcome resistance to CKD4/6 plus ET.ClinicalTrials.gov, NCT03401359. The trial was posted on 18 January 2018 and registered prospectively.

The optimization of the pharmacokinetic performance of various 2-pyridone-containing human rhinovirus (HRV) 3C protease (3CP) inhibitors following oral administration to either beagle dogs or CM-monkeys is described. The molecules described in this work are composed of a 2-pyridone-containing peptidomimetic binding determinant and an alpha,beta-unsaturated ester Michael acceptor moiety which forms an irreversible covalent adduct with the active site cysteine residue of the 3C enzyme. Modification of the ester contained within these compounds is detailed along with alteration of the P(2) substituent present in the peptidomimetic portion of the inhibitors. The pharmacokinetics of several inhibitors in both dogs and monkeys are described (7 h plasma concentrations after oral administration) along with their human plasma stabilities, stabilities in incubations with human, dog, and monkey microsomes and hepatocytes, Caco-2 permeabilities, and aqueous solubilities. Compounds containing an alpha,beta-unsaturated ethyl ester fragment and either an ethyl or propargyl P(2) moiety displayed the most promising combination of 3C enzyme inhibition (k(obs)/[I] 170 000-223 000 M(-1) s(-1)), antiviral activity (EC(50) = 0.047-0.058 microM, mean vs seven HRV serotypes), and pharmacokinetics following oral administration (7 h dog plasma levels = 0.248-0.682 microM; 7 h CM-monkey plasma levels = 0.057-0.896 microM).

A microscopic study of functional disorder-order folding transitions coupled to binding is performed for the p27 protein, which derives a kinetic advantage from the intrinsically disordered unbound form on binding with the phosphorylated cyclin A-cyclin-dependent kinase 2 (Cdk2) complex. Hierarchy of structural loss during p27 coupled unfolding and unbinding is simulated by using high-temperature Monte Carlo simulations initiated from the crystal structure of the tertiary complex. Subsequent determination of the transition-state ensemble and the proposed atomic picture of the folding mechanism coupled to binding provide a microscopic rationale that reconciles the initiation recruitment of p27 at the cyclin A docking site with the kinetic benefit for a disordered alpha-helix in the unbound form of p27. The emerging structural polarization in the ensemble of unfolding/unbinding trajectories and in the computationally determined transition-state ensemble is not determined by the intrinsic folding preferences of p27 but rather is attributed to the topological requirements of the native intermolecular interface to order beta-hairpin and beta-strand of p27 that could be critical for nucleating rapid folding transition coupled to binding. In agreement with the experimental data, the disorder-order folding transition for p27 is largely determined by the functional requirement to form a specific intermolecular interface that ultimately dictates the folding mechanism and overwhelms any local folding preferences for creating a stable alpha-helix in the p27 structure before overcoming the major free energy barrier.

The energy landscape approach has contributed to recent progress in understanding the complexity and simplicity of ligand-macromolecule interactions. Significant advances in computational structure prediction of ligand-protein complexes have been made using approaches that include the effects of protein flexibility and incorporate a hierarchy of energy functions. The results suggest that the complexity of structure prediction in molecular recognition may be determined by low-resolution properties of the underlying binding energy landscapes and by the nature of the energy funnels near the native structures of the complexes.

The enzyme 17beta-hydroxysteroid dehydrogenase type 10 (HSD10), also known as amyloid beta-peptide-binding alcohol dehydrogenase (ABAD), has been implicated in the development of Alzheimer's disease. This protein, a member of the short-chain dehydrogenase/reductase family of enzymes, has been shown to bind beta-amyloid and to participate in beta-amyloid neurotoxicity. We have determined the crystal structure of human ABAD/HSD10 complexed with NAD(+) and an inhibitory small molecule. The inhibitor occupies the substrate-binding site and forms a covalent adduct with the NAD(+) cofactor. The crystal structure provides a basis for the design of potent, highly specific ABAD/HSD10 inhibitors with potential application in the treatment of Alzheimer's disease.

Human cancer is caused by the accumulation of tumor-specific mutations in oncogenes and tumor suppressors that confer a selective growth advantage to cells. As a consequence of genomic instability and high levels of proliferation, many passenger mutations that do not contribute to the cancer phenotype arise alongside mutations that drive oncogenesis. While several approaches have been developed to separate driver mutations from passengers, few approaches can specifically identify activating driver mutations in oncogenes, which are more amenable for pharmacological intervention.We propose a new statistical method for detecting activating mutations in cancer by identifying nonrandom clusters of amino acid mutations in protein sequences. A probability model is derived using order statistics assuming that the location of amino acid mutations on a protein follows a uniform distribution. Our statistical measure is the differences between pair-wise order statistics, which is equivalent to the size of an amino acid mutation cluster, and the probabilities are derived from exact and approximate distributions of the statistical measure. Using data in the Catalog of Somatic Mutations in Cancer (COSMIC) database, we have demonstrated that our method detects well-known clusters of activating mutations in KRAS, BRAF, PI3K, and beta-catenin. The method can also identify new cancer targets as well as gain-of-function mutations in tumor suppressors.Our proposed method is useful to discover activating driver mutations in cancer by identifying nonrandom clusters of somatic amino acid mutations in protein sequences.

P-cadherin is a calcium-dependent cell–cell adhesion glycoprotein. P-cadherin expression is restricted to the myoepithelial cells in normal breast tissue, and aberrant staining has also been described in invasive tumors. Several small studies have reported P-cadherin as a marker of poor outcome in breast cancer patients but its prognostic significance in relation to other variables has not been established in a large series of breast cancers. A tissue microarray was constructed from 3992 cases of invasive breast carcinoma, and P-cadherin expression was evaluated using immunohistochemistry. Median follow-up was 12.5 years. The immunohistochemistry-based definitions of cancer subtypes were luminal (ER+ or PR+/HER2−), luminal/HER2+ (ER+ or PR+/HER2+), HER2+ (ER−/PR−/HER2+), and basal (ER−/PR−/HER2−/CK5/6+ or EGFR+). Clinical covariate and biomarker associations were assessed using contingency tables, and Pearson's χ2 or Fisher's exact test. Survival associations were assessed using Kaplan–Meier plots, logrank and Breslow tests, and Cox proportional hazards regression analysis. P-cadherin was expressed in 34.8% (1290/3710, 50% cut point) of cases. P-cadherin staining was strongly associated with HER2+ and basal carcinoma subtypes (P<0.0005). P-cadherin-positive patients showed significantly poorer short-term (0–10 years) overall survival, disease-specific survival, distant relapse-free interval, and locoregional relapse-free interval in univariable models (P<0.05). In multivariable Cox models containing standard clinical covariates and cancer subtypes, P-cadherin did not show independent prognostic value. P-cadherin expression was positively associated with histological grade, chemotherapy, Ki-67, EGFR, CK5/6, p53, YB-1, and HER2 expression (P<0.002), and negatively associated with age at diagnosis, ER, PR, and Bcl-2 expression (P<0.0005). This study shows the value of P-cadherin as a marker of poor prognosis. The large sample size of this series clarifies contradictory findings of many smaller studies. P-cadherin positivity is associated with high-grade tumor subtypes and well-established markers of poor prognosis, and may represent a promising antibody therapeutic target.

We aimed to assess the biologic activity of PF-03084014 in breast xenograft models. The biomarkers for mechanism and patient stratification were also explored.The in vitro and in vivo properties of PF-03084014 were investigated. The mRNA expressions of 40 key Notch pathway genes at baseline or after treatment were analyzed to link with the antitumor efficacy of PF-03084014 in a panel of breast cancer xenograft models.In vitro, PF-03084014 exhibited activity against tumor cell migration, endothelial cell tube formation, and mammosphere formation. In vivo, we observed apoptosis, antiproliferation, reduced tumor cell self-renewal ability, impaired tumor vasculature, and decreased metastasis activity after the treatment of PF-03084014. PF-03084014 treatment displayed significant antitumor activity in 10 of the 18 breast xenograft models. However, the antitumor efficacy in most models did not correlate with the in vitro antiproliferation results in the corresponding cell lines, suggesting the critical involvement of tumor microenvironment during Notch activation. In the tested breast xenograft models, the baseline expressions of the Notch receptors, ligands, and the cleaved Notch1 failed to predict the antitumor response to PF-03084014, whereas several Notch pathway target genes, including HEY2, HES4, and HES3, strongly corresponded with the response with a P value less than 0.01. Many of the best molecular predictors of response were also significantly modulated following PF-03084014 treatment.PF-03084014 showed antitumor and antimetastatic properties via pleiotropic mechanisms. The Notch pathway downstream genes may be used to predict the antitumor activity of PF-03084014 and enrich for responders among breast cancer patients.

Elucidating the molecular basis of hepatocellular carcinoma (HCC) is crucial to developing targeted diagnostics and therapies for this deadly disease. The landscape of somatic genomic rearrangements (GRs), which can lead to oncogenic gene fusions, remains poorly characterized in HCC. We have predicted 4314 GRs including large-scale insertions, deletions, inversions and translocations based on the whole-genome sequencing data for 88 primary HCC tumor/non-tumor tissues. We identified chromothripsis in 5 HCC genomes (5.7%) recurrently affecting chromosomal arms 1q and 8q. Albumin (ALB) was found to harbor GRs, deactivating mutations and deletions in 10% of cohort. Integrative analysis identified a pattern of paired intra-chromosomal translocations flanking focal amplifications and asymmetrical patterns of copy number variation flanking breakpoints of translocations. Furthermore, we predicted 260 gene fusions which frequently result in aberrant over-expression of the 3′ genes in tumors and validated 18 gene fusions, including recurrent fusion (2/88) of ABCB11 and LRP2.

PURPOSE Pancreatic cancer currently holds the position of third deadliest cancer in the United States and the 5-year survival rate is among the lowest for major cancers at just 12%. Thus, continued research efforts to better understand the clinical and molecular underpinnings of pancreatic cancer are critical to developing both early detection methodologies as well as improved therapeutic options. This study introduces Pancreatic Cancer Action Network's (PanCAN's) SPARK, a cloud-based data and analytics platform that integrates patient health data from the PanCAN's research initiatives and aims to accelerate pancreatic cancer research by making real-world patient health data and analysis tools easier to access and use. MATERIALS AND METHODS The SPARK platform integrates clinical, molecular, multiomic, imaging, and patient-reported data generated from PanCAN's research initiatives. The platform is built on a cloud-based infrastructure powered by Velsera. Cohort exploration and browser capabilities are built using Velsera ARIA, a specialized product for leveraging clinicogenomic data to build cohorts, query variant information, and drive downstream association analyses. Data science and analytic capabilities are also built into the platform allowing researchers to perform simple to complex analysis. RESULTS Version 1 of the SPARK platform was released to pilot users, who represented diverse end users, including molecular biologists, clinicians, and bioinformaticians. Included in the pilot release of SPARK are deidentified clinical (including treatment and outcomes data), molecular, multiomic, and whole-slide pathology images for over 600 patients enrolled in PanCAN's Know Your Tumor molecular profiling service. CONCLUSION The pilot release of the SPARK platform introduces qualified researchers to PanCAN real-world patient health data and analytical resources in a centralized location.

The search for novel leads is a critical step in the drug discovery process. Computational approaches to identify new lead molecules have focused on discovering complete ligands by evaluating the binding affinity of a large number of candidates, a task of considerable complexity. A new computational method is introduced in this work based on the premise that the primary molecular recognition event in the protein binding site may be accomplished by small core fragments that serve as molecular anchors, providing a structurally stable platform that can be subsequently tailored into complete ligands. To fulfill its role, we show that an effective molecular anchor must meet both the thermodynamic requirement of relative energetic stability of a single binding mode and its consistent kinetic accessibility, which may be measured by the structural consensus of multiple docking simulations. From a large number of candidates, this technique is able to identify known core fragments responsible for primary recognition by the FK506 binding protein (FKBP-12), along with a diverse repertoire of novel molecular cores. By contrast, absolute energetic criteria for selecting molecular anchors are found to be promiscuous. A relationship between a minimum frustration principle of binding energy landscapes and receptor-specific molecular anchors in their role as "recognition nuclei" is established, thereby unraveling a mechanism of lead discovery and providing a practical route to receptor-biased computational combinatorial chemistry.

Glucocorticoids, through activation of the glucocorticoid receptor (GR), regulate hepatic gluconeogenesis. Elevated hepatic expression and activity of 11β-hydroxysteroid dehydrogenase type 1 (11βHSD1) play a key role in ligand-induced activation of the GR through the production of cortisol. Evidence from genetically modified mice suggests that inhibition of 11βHSD1 might be a therapeutic approach to treat the metabolic syndrome. We have identified a potent 11βHSD1 inhibitor, 4′-cyano-biphenyl-4-sulfonic acid (6-amino-pyridin-2-yl)-amide (PF-915275), that is selective for the primate and human enzymes. The objective of this study was to demonstrate target inhibition with PF-915275 and to quantify the relationship between target inhibition and drug exposure in monkeys. We characterized the ability of PF-915275 to inhibit the conversion of prednisone, a synthetic cortisone analog that can be distinguished from the endogenous substrate cortisone, enabling a direct measure of substrate to product conversion without the complication of feedback. Adult cynomolgus monkeys were administered either vehicle or various doses of PF-915275 followed by a 10-mg/kg dose of prednisone. Prednisone conversion to prednisolone and the concentrations of PF-915275 were measured by liquid chromatography/tandem mass spectrometry. PF-915275 dose-dependently inhibited 11βHSD1-mediated conversion of prednisone to prednisolone, with a maximum of 87% inhibition at a 3-mg/kg dose. An exposure-response relationship was demonstrated, with an estimated EC₅₀ of 391 nM (total) and 17 nM (free). Insulin levels were also reduced in a dose-related manner. These results should enable the development of a biomarker for evaluating target modulation in humans that will aid in identifying 11βHSD1 inhibitors to treat diabetes and other related metabolic diseases.

Targeting cancers with amplified or abnormally activated c-Met (hepatocyte growth factor receptor) may have therapeutic benefit based on nonclinical and emerging clinical findings. However, the eventual emergence of drug resistant tumors motivates the pre-emptive identification of potential mechanisms of clinical resistance. We rendered a MET amplified gastric cancer cell line, GTL16, resistant to c-Met inhibition with prolonged exposure to a c-Met inhibitor, PF-04217903 (METi). Characterization of surviving cells identified an amplified chromosomal rearrangement between 7q32 and 7q34 which overexpresses a constitutively active SND1-BRAF fusion protein. In the resistant clones, hyperactivation of the downstream MAPK pathway via SND1-BRAF conferred resistance to c-Met receptor tyrosine kinase inhibition. Combination treatment with METi and a RAF inhibitor, PF-04880594 (RAFi) inhibited ERK activation and circumvented resistance to either single agent. Alternatively, treatment with a MEK inhibitor, PD-0325901 (MEKi) alone effectively blocked ERK phosphorylation and inhibited cell growth. Our results suggest that combination of a c-Met tyrosine kinase inhibitor with a BRAF or a MEK inhibitor may be effective in treating resistant tumors that use activated BRAF to escape suppression of c-Met signaling.

Structure prediction of ligand-protein complexes is greatly facilitated when the location of ligand functional groups relative to the protein is known. This situation arises in two applications of practical interest: when a covalent bond is formed between the ligand and the protein, and when a fragment of the ligand dominates the molecular recognition with the protein. In both of these cases, it is shown that the predicted structure corresponds to the experimentally observed structure with increased probability. Using this approach, a library of compounds is screened for potential inhibitors of dihydrofolate reductase and porcine pancreatic elastase; known inhibitors were ranked favorably in both cases.

The design and development of a series of highly selective pyrrolidine carboxamide 11beta-HSD1 inhibitors are described. These compounds including PF-877423 demonstrated potent in vitro activity against both human and mouse 11beta-HSD1 enzymes. In an in vivo assay, PF-877423 inhibited the conversion of cortisone to cortisol. Structure guided optimization effort yielded potent and stable 11beta-HSD1 selective inhibitor 42.

Pancreatic Ductal Adenocarcinoma (PDAC) is a highly lethal malignancy due to its propensity to invade and rapidly metastasize and remains very difficult to manage clinically. One major hindrance towards a better understanding of PDAC is the lack of molecular data sets and models representative of end stage disease. Moreover, it remains unclear how molecularly similar patient-derived xenograft (PDX) models are to the primary tumor from which they were derived. To identify potential molecular drivers in metastatic pancreatic cancer progression, we obtained matched primary tumor, metastases and normal (peripheral blood) samples under a rapid autopsy program and performed whole exome sequencing (WES) on tumor as well as normal samples. PDX models were also generated, sequenced and compared to tumors. Across the matched data sets generated for three patients, there were on average approximately 160 single-nucleotide mutations in each sample. The majority of mutations in each patient were shared among the primary and metastatic samples and, importantly, were largely retained in the xenograft models. Based on the mutation prevalence in the primary and metastatic sites, we proposed possible clonal evolution patterns marked by functional mutations affecting cancer genes such as KRAS, TP53 and SMAD4 that may play an important role in tumor initiation, progression and metastasis. These results add to our understanding of pancreatic tumor biology, and demonstrate that PDX models derived from advanced or end-stage likely closely approximate the genetics of the disease in the clinic and thus represent a biologically and clinically relevant pre-clinical platform that may enable the development of effective targeted therapies for PDAC.

While cyclin-dependent kinase 4/6 (CDK4/6) inhibitors, including palbociclib, combined with endocrine therapy (ET), are becoming the standard-of-care for hormone receptor-positive/human epidermal growth factor receptor 2‒negative metastatic breast cancer, further mechanistic insights are needed to maximize benefit from the treatment regimen. Herein, we conducted a systematic comparative analysis of gene expression/progression-free survival relationship from two phase 3 trials (PALOMA-2 [first-line] and PALOMA-3 [≥second-line]). In the ET-only arm, there was no inter-therapy line correlation. However, adding palbociclib resulted in concordant biomarkers independent of initial ET responsiveness, with shared sensitivity genes enriched in estrogen response and resistance genes over-represented by mTORC1 signaling and G2/M checkpoint. Biomarker patterns from the combination arm resembled patterns observed in ET in advanced treatment-naive patients, especially patients likely to be endocrine-responsive. Our findings suggest palbociclib may recondition endocrine-resistant tumors to ET, and may guide optimal therapeutic sequencing by partnering CDK4/6 inhibitors with different ETs. Pfizer (NCT01740427; NCT01942135).

Abstract Figitumumab (CP-751,871), a potent and fully human monoclonal anti–insulin-like growth factor 1 receptor (IGF1R) antibody, has been investigated in clinical trials of several solid tumors. To identify biomarkers of sensitivity and resistance to figitumumab, its in vitro antiproliferative activity was analyzed in a panel of 93 cancer cell lines by combining in vitro screens with extensive molecular profiling of genomic aberrations. Overall response was bimodal and the majority of cell lines were resistant to figitumumab. Nine of 15 sensitive cell lines were derived from colon cancers. Correlations between genomic characteristics of cancer cell lines with figitumumab antiproliferative activity revealed that components of the IGF pathway, including IRS2 (insulin receptor substrate 2) and IGFBP5 (IGF-binding protein 5), played a pivotal role in determining the sensitivity of tumors to single-agent figitumumab. Tissue-specific differences among the top predictive genes highlight the need for tumor-specific patient selection strategies. For the first time, we report that alteration or expression of the MYB oncogene is associated with sensitivity to IGF1R inhibitors. MYB is dysregulated in hematologic and epithelial tumors, and IGF1R inhibition may represent a novel therapeutic opportunity. Although growth inhibitory activity with single-agent figitumumab was relatively rare, nine combinations comprising figitumumab plus chemotherapeutic agents or other targeted agents exhibited properties of synergy. Inhibitors of the ERBB family were frequently synergistic and potential biomarkers of drug synergy were identified. Several biomarkers of antiproliferative activity of figitumumab both alone and in combination with other therapies may inform the design of clinical trials evaluating IGF1R inhibitors. Mol Cancer Ther; 12(12); 2929–39. ©2013 AACR.

Combination therapy with EGFR inhibitors may overcome acquired resistance to PI3K pathway inhibitors in some colorectal cancer patients.

Viral serine proteases have become increasingly attractive targets for rational drug design. Many known inhibitors of serine proteases form a covalent bond to the activated serine oxygen, an interaction not taken into account by available docking software used for database mining. We describe a new method for the fully automated and rapid flexible docking of inhibitors covalently bound to serine proteases. The method combines an energy function specifically tuned for molecular docking and an evolutionary programming search engine, and takes advantage of the constained geometry about the site of covalent attachment to dramatically limit the search space and increase search efficiency. Results for several test systems are presented, including a database search which yielded a known inhibitor as a highranking compound.

We present the results of molecular docking simulations with HIV-1 protease for the sb203386 and skf107457 inhibitors by Monte Carlo simulated annealing. A simplified piecewise linear energy function, the standard AMBER force field, and the AMBER force field with solvation and a soft-core smoothing component are employed in simulations with a single-protein conformation to determine the relationship between docking simulations with a simple energy function and more realistic force fields. The temperature-dependent binding free energy profiles of the inhibitors interacting with a single protein conformation provide a detailed picture of relative thermodynamic stability and a distribution of ligand binding modes in agreement with experimental crystallographic data. Using the simplified piecewise linear energy function, we also performed Monte Carlo docking simulations with an ensemble of protein conformations employing preferential biased sampling of low-energy protein conformations, and the results are analyzed in connection with the free energy profiles. ©1999 John Wiley & Sons, Inc. Int J Quant Chem 72: 73–84, 1999

We propose a general mean field model of ligand-protein interactions to determine the thermodynamic equilibrium of a system at finite temperature. The method is employed in structural assessments of two human immuno-deficiency virus type 1 protease complexes where the gross effects of protein flexibility are incorporated by utilizing a data base of crystal structures. Analysis of the energy spectra for these complexes has revealed that structural and thermo-dynamic aspects of molecular recognition can be rationalized on the basis of the extent of frustration in the binding energy landscape. In particular, the relationship between receptor-specific binding of these ligands to human immunodeficiency virus type 1 protease and a minimal frustration principle is analyzed.

The small-curvature semiclassical adiabatic (SCSA) approximation, which is based on a reaction-path Hamiltonian, is used to calculate the tunneling splitting due to the degenerate rearrangement of hydrogen fluoride dimer. The calculation employs a semiempirical potential energy surface which approximates the HF molecules as rigid rotators, and for which accurate tunneling splittings have been previously calculated. The semiclassical method is shown to be accurate within 33%. The internal motion of the dimer along the reaction path and the contributions of the generalized normal mode vibrations to reaction-path curvature in the tunneling region are also discussed.

The thermodynamic and kinetic aspects of molecular recognition for the methotrexate (MTX)-dihydrofolate reductase (DHFR) ligand-protein system are investigated by the binding energy landscape approach. The impact of 'hot' and 'cold' errors in ligand mutations on the thermodynamic stability of the native MTX-DHFR complex is analyzed, and relationships between the molecular recognition mechanism and the degree of ligand optimization are discussed. The nature and relative stability of intermediates and thermodynamic phases on the ligand-protein association pathway are studied, providing new insights into connections between protein folding and molecular recognition mechanisms, and cooperativity of ligand-protein binding. The results of kinetic docking simulations are rationalized based on the thermodynamic properties determined from equilibrium simulations and the shape of the underlying binding energy landscape. We show how evolutionary ligand selection for a receptor active site can produce well-optimized ligand-protein systems such as MTX-DHFR complex with the thermodynamically stable native structure and a direct transition mechanism of binding from unbound conformations to the unique native structure.

Abstract Monte Carlo simulations of molecular recognition at the consensus binding site of the constant fragment (Fc) of human immunoglobulin G (Ig) protein have been performed to analyze structural and thermodynamic aspects of binding for the 13‐residue cyclic peptide DCAWHLGELVWCT. The energy landscape analysis of a hot spot at the intermolecular interface using alanine scanning and equilibrium‐simulated tempering dynamics with the simplified, knowledge‐based energy function has enabled the role of the protein hot spot residues in providing the thermodynamic stability of the native structure to be determined. We have found that hydrophobic interactions between the peptide and the Met‐252, Ile‐253, His‐433, and His‐435 protein residues are critical to guarantee the thermodynamic stability of the crystallographic binding mode of the complex. Binding free energy calculations, using a molecular mechanics force field and a solvation energy model, combined with alanine scanning have been conducted to determine the energetic contribution of the protein hot spot residues in binding affinity. The conserved Asn‐434, Ser‐254, and Tyr‐436 protein residues contribute significantly to the binding affinity of the peptide–protein complex, serving as an energetic hot spot at the intermolecular interface. The results suggest that evolutionary conserved hot spot protein residues at the intermolecular interface may be partitioned in fulfilling thermodynamic stability of the native binding mode and contributing to the binding affinity of the complex. Proteins 2002;48:539–557. © 2002 Wiley‐Liss, Inc.

Abstract Background CDK4/6 inhibitors (CDK4/6i) plus endocrine therapies (ET) are the standard-of-care for hormone receptor–positive/human epidermal receptor 2–negative metastatic breast cancer (HR+/HER2− mBC). However, drug resistance remains a major unmet need. Investigations of drug resistance mechanisms has been hampered by a dearth of tumor molecular profiling data from the post-treatment setting. To address this challenge, we have conducted a real-world clinical genomics study to better understand the molecular mechanism of CDK4/6i resistance as well as to stratify patients based on integrated multi-omics profiles. Methods We retrospectively analyzed a multi-omics dataset of 400 HR+/HER2- mBC patients who had received CDK4/6i plus ET and developed progressive disease (PD) from the de-identified Tempus database. Pre-treatment and post-progression biopsies were taken  1 year prior to starting the CDK4/6i treatment or following PD respectively. Tempus xT next-generation sequencing (DNA-seq of 648 genes) and RNA sequencing assays were performed on 427 tumor FFPE samples, including 200 pre-treatment, 227 post-progression and 26 longitudinal pairs. Results The median age of the patients was 57 (54.9-57.4) and median progression free survival (PFS) is 379 (341-433) days. Two genes were found to harbor a significant increase in genomic alteration frequencies (GAF) after adjusting for FDR at post-progression vs. pre-treatment – ESR1 (41.9% vs. 15%, p=5.4e-10), RB1 (13.2% vs. 3%, p=8.5e-05). ESR1 and RB1 also harbored high frequencies of acquired genomic alterations among 26 paired samples at 34.6% and 11.5% respectively. TP53 mutation at baseline was significantly associated with shorter PFS at baseline (p=4.23e-05, HR=2.081) and TP53 GAF significantly increased after PD (37% vs. 28.5%, p=0.039). BRCA1/2 pathogenic mutations (p=1.63e-04, HR=3.066), APOBEC mutation signature S13 (p=0.0125, HR=1.55) and CCNE1 gene expression (p=0.024, HR=1.46) were significantly associated with shorter PFS. APOBEC signature (p=0.0035) and CCNE1 expression (p=1.33e-06) also significantly increased post-progression. Among the top molecular features associated with longer PFS were markers of estrogen signaling such as PGR gene expression (p=6.76e-04, HR=0.565) and the Hallmark estrogen response signature (p=0.021, HR=0.679). Applying a multi-omics pattern recognition algorithm, we identified a molecularly distinct cluster (IC1) characterized by down-regulation of estrogen signaling. IC1 is significantly associated with shorter PFS (p=3.72e-05, HR=0.22) and increased from 4% pre-treatment to 23% post-progression (p=7.3e-08). Further, IC1 is strongly enriched in markers previously implicated in CDK4/6i resistance including CCNE1 expression, RB1 mutation and MYC/E2F activation. We then developed machine learning models to predict gene-level dependency trained on cancer cell line expression and CRISPR-KO screen data. These models predicted decreased dependency on ESR1 and CDK4 and increased dependency on CDK2 in IC1, strengthening the association between ER independence and CDK4/6i resistance. Conclusions Our real-world clinical genomics study identified a comprehensive list of biomarkers associated with resistance to CDK4/6i plus ET and estimated patient prevalence for these markers in the post-treatment setting. Integrated and machine-learning analyses identified a subset of aggressive tumors with estrogen independence characteristics that are implicated in CDK4/6i resistance and suggested new therapeutic strategies. Citation Format: Zhengyan Kan, Ji Wen, Jennifer Webster, Vinicius Bonato, Whijae Roh, Xinmeng Jasmine Mu, Paul Rejto, Jadwiga Bienkowska. Real-world clinical genomics study of HR+/HER2- metastatic breast cancers treated by CDK4/6i plus endocrine therapies revealed a drug resistant tumor segment characterized by ER independence [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-14-08.

Abstract A hierarchical computational approach is used to identify the engineered binding‐site cavity at the remodeled intermolecular interface between the mutants of human growth hormone (hGH) and the extracellular domain of its receptor (hGHbp). Multiple docking simulations are conducted with the remodeled hGH–hGHbp complex for a panel of potent benzimidazole‐containing inhibitors that can restore the binding affinity of the wild‐type complex, and for a set of known nonactive small molecules that contain different heterocyclic motifs. Structural clustering of ligand‐bound conformations and binding free‐energy calculations, using the AMBER force field and a continuum solvation model, can rapidly locate and screen numerous ligand‐binding modes on the protein surface and detect the binding‐site hot spot at the intermolecular interface. Structural orientation of the benzimidazole motif in the binding‐site cavity closely mimics the position of the hot spot residue W104 in the crystal structure of the wild‐type complex, which is recognized as an important structural requirement for restoring binding affinity. Despite numerous pockets on the protein surface of the mutant hGH–hGHbp complex, the binding‐site cavity presents the energetically favorable hot spot for the benzimidazole‐containing inhibitors, whereas for a set of nonactive molecules, the lowest energy ligand conformations do not necessarily bind in the engineered cavity. The results reveal a dominant role of the intermolecular van der Waals interactions in providing favorable ligand–protein energetics in the redesigned interface, in agreement with the experimental and computational alanine scanning of the hGH–hGHbp complex. Proteins 2003. © 2003 Wiley‐Liss, Inc.

Ultra-deep next-generation sequencing of circulating tumor DNA (ctDNA) holds great promise as a tool for the early detection of cancer and for monitoring disease progression and therapeutic responses. However, the low abundance of ctDNA in the bloodstream coupled with technical errors introduced during library construction and sequencing complicates mutation detection.To achieve high accuracy of variant calling via better distinguishing low-frequency ctDNA mutations from background errors, we introduce TNER (Tri-Nucleotide Error Reducer), a novel background error suppression method that provides a robust estimation of background noise to reduce sequencing errors. The results on both simulated data and real data from healthy subjects demonstrate that the proposed algorithm consistently outperforms a current, state-of-the-art, position-specific error polishing model, particularly when the sample size of healthy subjects is small.TNER significantly enhances the specificity of downstream ctDNA mutation detection without sacrificing sensitivity. The tool is publicly available at https://github.com/ctDNA/TNER .

Energy landscapes of molecular recognition are explored by performing "semi-rigid" docking of FK-506 and rapamycin with the Fukisawa binding protein (FKBP-12), and flexible docking simulations of the Ro-31-8959 and AG-1284 inhibitors with HIV-1 protease by a genetic algorithm. The requirements of a molecular recognition model to meet thermodynamic and kinetic criteria of ligand-protein docking simultaneously are investigated using a family of simple molecular recognition energy functions. The critical factor that determines the success rate in predicting the structure of ligand-protein complexes is found to be the roughness of the binding energy landscape, in accordance with a minimal frustration principle. The results suggest that further progress in structure prediction of ligand-protein complexes can be achieved by designing molecular recognition energy functions that generate binding landscapes with reduced frustration.

Simulated tempering dynamics with the simplified energy model and the ensemble of protein conformations have been performed for the SB203386 inhibitor binding with HIV-1 protease. Equilibrium simulations with multiple protein conformations implicitly incorporate protein flexibility and rank HIV-1 protease conformations according to the average ligand–protein interaction energies. Subsequent energy refinement with a molecular mechanics force field accurately quantifies the energetics of the low-energy ligand binding modes. The results suggest that the mobility of the SB203386 inhibitor is effectively restricted to two symmetry-related binding modes and this may prevent the inhibitor from adapting to distorted binding sites in mutant conformations.

Genome-scale functional genomic screens across large cell line panels provide a rich resource for discovering tumor vulnerabilities that can lead to the next generation of targeted therapies. Their data analysis typically has focused on identifying genes whose knockdown enhances response in various pre-defined genetic contexts, which are limited by biological complexities as well as the incompleteness of our knowledge. We thus introduce a complementary data mining strategy to identify genes with exceptional sensitivity in subsets, or outlier groups, of cell lines, allowing an unbiased analysis without any a priori assumption about the underlying biology of dependency. Genes with outlier features are strongly and specifically enriched with those known to be associated with cancer and relevant biological processes, despite no a priori knowledge being used to drive the analysis. Identification of exceptional responders (outliers) may not lead only to new candidates for therapeutic intervention, but also tumor indications and response biomarkers for companion precision medicine strategies. Several tumor suppressors have an outlier sensitivity pattern, supporting and generalizing the notion that tumor suppressors can play context-dependent oncogenic roles. The novel application of outlier analysis described here demonstrates a systematic and data-driven analytical strategy to decipher large-scale functional genomic data for oncology target and precision medicine discoveries.

We present a microscopic model for the Xe/Pt(111) system that is consistent with the experimental desorption energy, the experimental vibrational frequency of the Xe atom in the direction normal to the Pt(111) surface, and salient features of the experimental phase diagram of Xe/Pt(111). The interatomic potentials in this model were obtained using a simple technique that we have developed for generalizing the typical pairwise-additive atom–atom central potentials used in modeling physisorption systems to make them noncentral and more flexible in their functional form. We applied this technique to the Lennard-Jones pair potential and fit the parameters to reproduce the experimental binding energy, the frequency for vibration of the adsorbate normal to the surface, and a reasonable choice of the binding distance. We adjusted the corrugation of the potential ΔV, defined as the energy barrier for motion of an adsorbate atom from one binding site to another, in order to fit as much of the phase diagram as possible. Our model for the Xe–Pt interaction was constructed on the basis of the assumption that the binding site is located in the threefold site of Pt(111). When the Xe–Xe interaction was represented by the form appropriate for atoms in the gas phase, we were unable to find a stable commensurate phase for any choice of the corrugation that predicted a low temperature incommensurate phase. When a substrate mediated contribution to the Xe–Xe interaction was included in the model, we found that the commensurate phase was stable in an intermediate temperature range with an incommensurate phase stable at low temperature for a range of values of the corrugation. For a choice of ΔV=171 K, the striped incommensurate phase is stable at low temperature, there is a phase transition to a √3 ×√3R30° phase at T=65±5 K, and the commensurate phase melts to become a liquid at T≊120 K. These results are in reasonably good agreement with the experiments.

The inhibition of 11betahydroxysteroid dehydrogenase 1 (11betaHSD1), an enzyme that catalyzes the conversion of inactive cortisone to active cortisol, is an attractive target to treat diabetes by suppressing hepatic gluconeogenesis. To test this hypothesis, we developed a novel glucocorticoid-induced diabetic KK mouse model and used 11betaHSD1 antisense oligonucleotide (ASO) as an inhibitory tool. KK mice were treated with 25 or 50mg/kg/day of 11betaHSD1 ASO for 28 days. On day 25, cortisone pellets were surgically implanted to induce diabetes. In the ASO-treated mice, plasma blood glucose levels were significantly reduced by up to 54%. In parallel, cortisol and other diabetes endpoints were also significantly reduced. Hepatic 11betaHSD1 mRNA was suppressed by up to 84% with a concomitant respective decrease of up to 49% in the expression of PEPCK. The results suggest that inhibition of 11betaHSD1 activity reduces the availability of cortisol to activate the glucocorticoid receptor, down regulates gluconeogenesis and thus reduces plasma glucose levels in cortisone-induced diabetic KK mice.

N-(Pyridin-2-yl) arylsulfonamides 1 and 2 (PF-915275) were identified as potent inhibitors of 11β-hydroxysteroid dehydrogenase type 1. A screen for bioactivation revealed that these compounds formed glutathione conjugates. This communication presents the results of a risk benefit analysis carried out to progress 2 (PF-915275) to a clinical study and the strategies used to eliminate reactive metabolites in this series of inhibitors. Based on the proposed mechanism of bioactivation and structure-activity relationships, design efforts led to N-(pyridin-2-yl) arylsulfonamides such as 18 and 20 that maintained potent 11β-hydroxysteroid dehydrogenase type 1 activity, showed exquisite pharmacokinetic profiles, and were negative in the reactive metabolite assay.

Mean field analysis of FKBP12 complexes with FK506 and rapamycin has been performed by using structures obtained from molecular docking simulations on a simple, yet robust molecular recognition energy landscape. When crystallographic water molecules are included in the simulations as an extension of the FKBP12 protein surface, there is an appreciable stability gap between the energy of the native FKBP12–FK506 complex and energies of conformations with the “native-like” binding mode. By contrast, the energy spectrum of the FKBP12–rapamycin complex is dense regardless of the presence of the water molecules. The stability gap in the FKBP12–FK506 system is determined by two critical water molecules from the effector region that participate in a network of specific hydrogen bond interactions. This interaction pattern protects the integrity and precision of the composite ligand-protein effector surface in the binary FKBP12–FK506 complex and is preserved in the crystal structure of the FKBP12–FK506–calcineurin ternary complex. These features of the binding energy landscapes provide useful insights into specific and nonspecific aspects of FK506 and rapamycin recognition. Proteins 28:313–324, 1997. © 1997 Wiley-Liss, Inc.

The thermodynamics of molecular recognition is investigated by a statistical energy landscape approach, where the temperature profile of the ligand–protein binding process is determined using the weighted histogram analysis method. The analysis reveals differences in the binding energy landscapes of two molecular fragments with the FKBP12 protein, which are reflected in their characteristic transition temperatures. The approach provides insight into the nature of transitions between unbound and bound phases of ligand–protein complexes. One molecular fragment proceeds from the unbound phase to the native complex via a short-lived intermediate at relatively high temperature. The second fragment has a significantly more rugged binding energy landscape and goes from unbound to a long-lived nonspecific bound species consisting of isoenergetic yet structurally different binding modes, and later via a second-order-like transition to the native complex. Emerging universalities in molecular recognition and protein folding mechanisms are highlighted in the context of the kinetic partitioning mechanism. ©1999 John Wiley & Sons, Inc. Int J Quant Chem 73: 113–121, 1999

A sensitive and specific imaging biomarker to monitor immune activation and quantify pharmacodynamic responses would be useful for development of immunomodulating anti-cancer agents. PF-07062119 is a T cell engaging bispecific antibody that binds to CD3 and guanylyl cyclase C, a protein that is over-expressed by colorectal cancers. Here, we used 89Zr-Df-IAB22M2C (89Zr-Df-Crefmirlimab), a human CD8-specific minibody to monitor CD8+ T cell infiltration into tumors by positron emission tomography. We investigated the ability of 89Zr-Df-IAB22M2C to track anti-tumor activity induced by PF-07062119 in a human CRC adoptive transfer mouse model (with injected activated/expanded human T cells), as well as the correlation of tumor radiotracer uptake with CD8+ immunohistochemical staining.NOD SCID gamma mice bearing human CRC LS1034 tumors were treated with four different doses of PF-07062119, or a non-targeted CD3 BsAb control, and imaged with 89Zr-Df-IAB22M2C PET at days 4 and 9. Following PET/CT imaging, mice were euthanized and dissected for ex vivo distribution analysis of 89Zr-Df-IAB22M2C in tissues on days 4 and 9, with additional data collected on day 6 (supplementary). Data were analyzed and reported as standard uptake value and %ID/g for in vivo imaging and ex vivo tissue distribution. In addition, tumor tissues were evaluated by immunohistochemistry for CD8+ T cells.The results demonstrated substantial mean uptake of 89Zr-Df-IAB22M2C (%ID/g) in PF-07062119-treated tumors, with significant increases in comparison to non-targeted BsAb-treated controls, as well as PF-07062119 dose-dependent responses over time of treatment. A moderate correlation was observed between tumor tissue radioactivity uptake and CD8+ cell density, demonstrating the value of the imaging agent for non-invasive assessment of intra-tumoral CD8+ T cells and the mechanism of action for PF-07062119.Immune-imaging technologies for quantitative cellular measures would be a valuable biomarker in immunotherapeutic clinical development. We demonstrated a qualification of 89Zr-IAB22M2C PET to evaluate PD responses (mice) to a novel immunotherapeutic.

Assay conditions for the 11beta-hydroxysteroid dehydrogenase have been optimized by adding phospholipids in the media buffer to increase and stabilize the enzymatic activity. The presence of phospholipids greatly facilitates the study of the binding of cortisone and NADPH at the enzyme catalytic site. Kinetic analyses conducted with the human and rabbit enzyme isoforms suggest that both enzymes behave according to an ordered sequential bi-bi mechanism where the NADPH is the first to bind at the active site followed by cortisone. The equilibrium dissociation constant, K(i)a as well as the apparent Michaelis-Menten constants K(m)a, K(m)b, k(cat)a, and k(cat)b for NADPH and cortisone, have been determined to be 147.5 microM, 14.4 microM, 43.8 nM, 0.21 min(-1), and 0.27 min(-1), respectively, for the human enzyme and 41.1 microM, 3.1 microM, 161.7 nM, 0.49 min(-1), and 0.52min(-1), respectively, for the rabbit enzyme.

Pin1, a phosphorylation-dependent peptidyl-prolyl cis/trans isomerase (PPIase), regulates the activity of a number of cell cycle regulators, transcription factors, and microtubule-associated tau. Aberrant expression of Pin1 is implicated in carcinogenesis and neurodegenerative diseases. Yet, there are discrepancies regarding its biological significance in different organisms. Pin1 was essential in HeLa cells, while Pin1-deficient mice showed no lethal phenotypes. We here identified a novel murine Pin1 isoform (mPin1L) consisting of the WW domain and the PPIase domain. Murine Pin1L shares 92% sequence identity with the wild-type Pin1 and shows wide tissue distribution with highest levels in mouse testis. The recombinant mPin1L is enzymatically active, but is approximately three times less efficient than Pin1 in catalyzing the cis/trans isomerization. These data suggest that mPin1L may serve as a surrogate for Pin1. The finding provides insights into phenotypic consequences for Pin1-null mice and may facilitate future biological study and pharmacological development in mice.

The androgen receptor plays a critical role throughout the progression of prostate cancer and is an important drug target for this disease. While chromatin immunoprecipitation coupled with massively parallel sequencing (ChIP-Seq) is becoming an essential tool for studying transcription and chromatin modification factors, it has rarely been employed in the context of drug discovery.Here we report changes in the genome-wide AR binding landscape due to dose-dependent inhibition by drug-like small molecules using ChIP-Seq. Integration of sequence analysis, transcriptome profiling, cell viability assays and xenograft tumor growth inhibition studies enabled us to establish a direct cistrome-activity relationship for two novel potent AR antagonists. By selectively occupying the strongest binding sites, AR signaling remains active even when androgen levels are low, as is characteristic of first-line androgen ablation therapy. Coupled cistrome and transcriptome profiling upon small molecule antagonism led to the identification of a core set of AR direct effector genes that are most likely to mediate the activities of targeted agents: unbiased pathway mapping revealed that AR is a key modulator of steroid metabolism by forming a tightly controlled feedback loop with other nuclear receptor family members and this oncogenic effect can be relieved by antagonist treatment. Furthermore, we found that AR also has an extensive role in negative gene regulation, with estrogen (related) receptor likely mediating its function as a transcriptional repressor.Our study provides a global and dynamic view of AR's regulatory program upon antagonism, which may serve as a molecular basis for deciphering and developing AR therapeutics.

Computer simulations using the simplified energy function and simulated tempering dynamics have accurately determined the native structure of the pYVPML, SVLpYTAVQPNE, and SPGEpYVNIEF peptides in the complexes with SH2 domains. Structural and equilibrium aspects of the peptide binding with SH2 domains have been studied by generating temperature-dependent binding free energy landscapes. Once some native peptide-SH2 domain contacts are constrained, the underlying binding free energy profile has the funnel-like shape that leads to a rapid and consistent acquisition of the native structure. The dominant native topology of the peptide-SH2 domain complexes represents an extended peptide conformation with strong specific interactions in the phosphotyrosine pocket and hydrophobic interactions of the peptide residues C-terminal to the pTyr group. The topological features of the peptide-protein interface are primarily determined by the thermodynamically stable phosphotyrosyl group. A diversity of structurally different binding orientations has been observed for the amino-terminal residues to the phosphotyrosine. The dominant native topology for the peptide residues carboxy-terminal to the phosphotyrosine is tolerant to flexibility in this region of the peptide-SH2 domain interface observed in equilibrium simulations. The energy landscape analysis has revealed a broad, entropically favorable topology of the native binding mode for the bound peptides, which is robust to structural perturbations. This could provide an additional positive mechanism underlying tolerance of the SH2 domains to hydrophobic conservative substitutions in the peptide specificity region.

Structure and energetics of the Src Src Homology 2 (SH2) domain binding with the recognition phosphopeptide pYEEI and its mutants are studied by a hierarchical computational approach. The proposed structure prediction strategy includes equilibrium sampling of the peptide conformational space by simulated tempering dynamics with the simplified, knowledge-based energy function, followed by structural clustering of the resulting conformations and binding free energy evaluation of a single representative from each cluster, a cluster center. This protocol is robust in rapid screening of low-energy conformations and recovers the crystal structure of the pYEEI peptide. Thermodynamics of the peptide-SH2 domain binding is analyzed by computing the average energy contributions over conformations from the clusters, structurally similar to the predicted peptide bound structure. Using this approach, the binding thermodynamics for a panel of studied peptides is predicted in a better agreement with the experiment than previously suggested models. However, the overall correlation between computed and experimental binding affinity remains rather modest. The results of this study show that small differences in binding free energies between the Ala and Gly mutants of the pYEEI peptide are considerably more difficult to predict than the structure of the bound peptides, indicating that accurate computational prediction of binding affinities still remains a major methodological and technical challenge.

Abstract Effective treatment options for advanced colorectal cancer (CRC) are limited, survival rates are poor, and this disease continues to be a leading cause of cancer-related deaths worldwide. Despite being a highly heterogeneous disease, a significant subset of patients with sporadic CRC typically harbor relatively few established 'driver' lesions. Here, we describe a collection of genetically engineered mouse models (GEMM) of sporadic CRC that combine lesions frequently altered in human patients, including well-characterized tumor suppressors and activators of MAPK signaling. Primary tumors from these models were profiled, and individual GEMM tumors segregated into groups based on their genotypes. Unique allelic and genotypic expression signatures were generated from these GEMMs and applied to clinically annotated human CRC patient samples. We provide evidence that a Kras signature derived from these GEMMs is capable of distinguishing KRAS mutant patients, and tracks with poor prognosis in two independent human patient cohorts. Further, the analysis of a panel of human CRC cell lines suggests that high expression of the GEMM Kras signature correlates with sensitivity to targeted pathway inhibitors. Together, these findings implicate GEMMs as powerful preclinical tools with the capacity to recapitulate relevant human disease biology, and support the use of genetic signatures generated in these models to facilitate future drug discovery and validation efforts.

Thermodynamic and kinetic aspects of ligand–protein binding are studied for the methotrexate–dihydrofolate reductase system from the binding free energy profile constructed as a function of the order parameter. Thermodynamic stability of the native complex and a cooperative transition to the unique native structure suggest the nucleation kinetic mechanism at the equilibrium transition temperature. Structural properties of the transition state ensemble and the ensemble of nucleation conformations are determined by kinetic simulations of the transmission coefficient and ligand–protein association pathways. Structural analysis of the transition states and the nucleation conformations reconciles different views on the nucleation mechanism in protein folding.

The Cell Index Database, (CELLX) (http://cellx.sourceforge.net) provides a computational framework for integrating expression, copy number variation, mutation, compound activity, and meta data from cancer cells. CELLX provides the computational biologist a quick way to perform routine analyses as well as the means to rapidly integrate data for offline analysis. Data is accessible through a web interface which utilizes R to generate plots and perform clustering, correlations, and statistical tests for associations within and between data types for ~20,000 samples from TCGA, CCLE, Sanger, GSK, GEO, GTEx, and other public sources. We show how CELLX supports precision oncology through indications discovery, biomarker evaluation, and cell line screening analysis.

Abstract Background: The oral cdk4/6 inhibitor, Palbociclib (Palbo), has been shown to prolong progression-free survival when combined with anti-estrogen therapy and have single-agent activity in metastatic breast cancer (MBC). Progressive disease (PD) on therapy does occur, however, and little is known about resistance mechanisms. Preclinical data have suggested that cell cycle gene expression changes are a potential mechanism of resistance. We performed comprehensive genomic analyses on serial tumor samples from an exceptional responder to single-agent Palbo to determine whether such changes occur in vivo. Methods: Serial biopsies were obtained from a 67 year old patient with MBC treated on a phase II trial of single-agent Palbo at the University of Pennsylvania. Tissue was obtained from the primary lesion (1999, Stage 3, ER-/PR+/Her2+) and first recurrence (2005, contralateral breast, bone, lung; ER+/PR-/Her2+, treated with Herceptin/letrozole). At PD (2010), pt received single-agent P, 50 mg daily for 21 days each 28-day cycle, with PR for 33 months. A sample from metastatic skin lesion at PD on P (2013) was obtained. Next generation targeted sequencing was performed at Foundation Medicine using the Heme Panel. RNA was profiled using a 784-gene custom Nanostring array including cell cycle genes and ER pathway genes. Determination of pathway enrichment was performed using GSEA and the statistical significance of network neighborhood over-representation was calculated using cumulative hypergeometric distribution. Results: There was no genetic evidence suggesting loss of RB1, or alterations in p16, cyclin D1, cdk4, PIK3CA or ESR1, and the genomic profile did not change between the primary and recurrent tissue samples. As expected, amplification of ERRB2 was present in all samples. In contrast, expression of cell cycle-regulated genes (PLK1, TOP2A, CDK1, BUB1, CDC20, CCNA2, CCNE2, CCNB1 BIRC5) increased more than two-fold at PD on Palbo compared to pre-Palbo, along with evidence of activation of the FOXM1 network. Conclusion: Gene expression changes associated with cell cycle activation and FOXM1 activation may lead to acquired resistance to Palbociclib, despite wild-type RB1. These data demonstrate the importance of pre-/post-treatment biopsies and the feasibility of high-level genomic assessment in archival tissues to elucidate resistance mechanisms of novel therapies. Citation Format: DeMichele A, Shih NNC, Koehler M, Huang Bartlett C, Jiang Y, Harwick J, Huang D, Zheng X, Clark AS, Colameco C, Feldman MD, Gallagher M, Goodman N, O'Dwyer P, Rejto P. Upregulation of cell cycle pathway genes without loss of RB1 contributes to acquired resistance to single-agent treatment with palbociclib in breast cancer. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P4-13-04.

Abstract Crizotinib (PF-02341066) is a small molecule tyrosine kinase inhibitor of ALK, ROS1 and c-MET that is approved in over 70 countries for the treatment of ALK fusion positive non-small cell lung cancer (ALK+ NSCLC). Crizotinib achieved robust objective response rates of approximately 60% in ALK+ NSCLC and significantly improved progression free survival compared to chemotherapy. The emergence of secondary mutations within the ALK kinase domain or the activation of compensatory signaling pathways in crizotinib and other ALKi refractory tumors prompted searches for next generation of ALKi active against resistance mutations as single agents or in combination with other treatments. Such effort led to our recent discovery of PF-06463922, an ALK/ROS1 inhibitor with greatly improved ALK potency, brain penetration, and broad spectrum activity against all known clinical ALKi-resistant mutations. PF-06463922 is being tested in a Phase I clinical trial in both ALK+ and ROS1 fusion positive NSCLC in treatment naive or ALKi relapsed patients. In our current preclinical study, we explored rational combination strategies to further improve the efficacy of PF-06463922 in ALKi resistant cells or tumors. Our results show that compared to PF-06463922 alone, the combination of this compound with PI3K pathway inhibitors, such as PF-05212384 (PI3K/mTOR), GDC0941 (pan-PI3K) or GDC0032 (beta-sparing) leads to more robust anti-proliferative activity in vitro and greater duration of efficacy in vivo in the ALKi resistant models. These PI3K pathway inhibitors also partially overcome EGF or HGF ligand-induced resistance to PF-06463922. Interestingly, in addition to AKT signaling, both compounds inhibit ERK signaling as well, which may be essential for their enhancement of PF-06463922 cell activity or tumor efficacy in combination settings. Studies are ongoing to identify optimal partners for PF-06463922 combination using isoform selective PI3Ki, AKTi and mTORi. We are also exploring the breadth of efficacy of this combination in overcoming resistance to crizotinib, PF-06463922 or other ALKi. The findings provide important evidence that will help define the clinical development path for PF-06463922. This research effort may ultimately lead to more effective approaches to treat ALKi refractory patients in the clinic. Citation Format: Ping Wei, Ming Qiu, Nathan Lee, Joan Cao, Hui Wang, Konstantinos Tsaparikos, Conglin Fan, Timothy Sargis, Justine Lam, Maruja E. Lira, Goldie Lui, James Hardwick, Valeria Fantin, Paul Rejto, Tod Smeal. Rational combination of PF-06463922 (next-generation ALK inhibitor) with PI3K pathway inhibitors overcomes ALKi resistance in EML4-ALK+ NSCLC models. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 764. doi:10.1158/1538-7445.AM2015-764

Computational structure prediction of streptavidin-peptide complexes for known recognition sequences and a number of random di-, tri-, and tetrapeptides has been conducted, and mechanisms of peptide recognition with streptavidin have been investigated by a new computational protocol. The structural consensus criterion, which is computed from multiple docking simulations and measures the accessibility of the dominant binding mode, identifies recognition motifs from a set of random peptide sequences, whereas energetic analysis is less discriminatory. The predicted conformations of recognition tripeptide and tetrapeptide sequences are also in structural harmony and composed of peptide fragments that are individually unfrustrated in their bound conformation, resulting in a minimally frustrated energy landscape for recognition peptides. Proteins 28:421–433, 1997. © 1997 Wiley-Liss, Inc.

Abstract Advances in cancer research and sequencing technologies have contributed to the proliferation of large-scale cancer omics data sets from both public consortia and privately funded collaborations. There are increasing demands for broadly accessible tools that enable scientists to perform ad hoc analyses of cancer omics data. Here we present OASIS (http://oasis.pfizer.com), an open-access web portal that enables complex analytical queries across somatic mutations, copy number changes (CNV) and gene expression data from public domain and Pfizer funded omics studies. OASIS was designed to perform multidimensional data integration, allowing users to analyze correlations among multiple data types, as well as visualize and compare alterations across different cancers. Users can browse alteration summary reports at the gene and sample level and perform analyses using interactive visualizations. These include the Pan-Cancer Report, a unique tool that provides a high-level overview of genetic variation across multiple cancer types. Through the use of the interactive visualizations researchers can explore differentially expressed genes, identify tumor samples for over expression, investigate the correlation between CNV and expression or survey alteration patterns for a list of genes. Users can explore molecular profiles from the Cancer Cell Line Encyclopedia (CCLE) and the Catalog of Somatic Mutations in Cancer (COSMIC), to identify cell line models of interest. Researchers can also construct complex queries through a user-friendly web interface supported by the Biomart query engine. Programmatic access is also available through web services. OASIS is a powerful tool that enables cancer researchers to perform integrative analyses of large-scale cancer omics data sets, thereby facilitating key steps in oncology drug discovery ranging from target identification to model selection. Citation Format: Julio Fernandez-Banet, Anthony Esposito, Scott Coffin, Sabine Schefzick, Ying Ding, Keith Ching, Istvan Horvath, Peter Roberts, Paul Rejto, Zhengyan Kan. OASIS: A centralized portal for cancer omics data analysis. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4874. doi:10.1158/1538-7445.AM2015-4874

Abstract Summary: The identification of genetic lesions that affect tumor sensitivity to targeted therapies is a major objective of precision medicine. Two reports in this issue combine tumor genome analyses with functional characterization to uncover activating mutations in MTOR that confer sensitivity to a clinically used mTOR inhibitor. Cancer Discov; 4(5); 513–5. ©2014 AACR. See related article by Wagle et al., p. 546 See related article by Grabiner et al., p. 554

Abstract Background: The Hedgehog (Hh) signaling pathway is key to development, differentiation, and stem cell maintenance. In cancer, dysregulation of Hh signaling is associated with solid tumors and hematological malignancies. Hh signaling in AML and MDS is thought to promote the renewal and maintenance of leukemic stem cells, which may lead to chemotherapy resistance and recurrence. Glasdegib is a potent and selective oral inhibitor of Smoothened, a transmembrane protein that stimulates Hh signaling. Here we report the results of an exploratory analysis to profile mutations in 118 bone marrow samples and 77 peripheral blood samples of patients with previously untreated AML or high-risk MDS treated with chemotherapy with or without glasdegib in phase I/II clinical trials. Materials and Methods: We used targeted resequencing to survey 109 genes, and a polymerase chain reaction assay to detect FLT3 internal tandem duplications. Resequencing and response data were obtained from two arms, 1) an intensive group (n=61) treated with a combination of cytarabine/daunorubicin plus glasdegib, and 2) a non-intensive group (n=73) treated with low-dose cytarabine (LDAC) plus glasdegib (n=44) or LDAC alone (n=19). We assessed significantly mutated genes by Fisher's Exact Test at p ≤ 0.05. Results: In the combined dataset we found that mutations in NF1 (P=0.006), KRAS (P=0.028), or a combination of KRAS, NRAS, and NF1 (P=0.013) were associated with a negative response. Mutations in NPM1 (P=0.006), MPL (P=0.041), RB1 (P=0.041), or SF3B1 (P=0.041) were associated with a positive response. When split by arm, in the intensive group mutations in TP53 (P=0.001), NF1 (P=0.035), or CREBBP (P=0.041) were associated with negative response, whereas mutation in NPM1 was associated with positive response (P=0.046). In the non-intensive group, mutations in RSPH10B2 (P=0.036) or a combination of KRAS, NRAS, and NF1 (P=0.031) were associated with negative response, whereas mutation in CREBBP (P=0.007) was associated with positive response. We discuss the implications of these mutations in the context of Smoothened inhibition and the leukemic stem cell hypothesis. Conclusions: Mutational profiling of patients with AML or high-risk MDS treated with glasdegib highlights alterations in genes associated with response and the potential role of Hh signaling in these malignancies. Citation Format: Keith A. Ching, Donghui Huang, Kai Wang, Mark Ozeck, Paul Lira, Jingjin Gao, Jadwiga Bienkowska, Paul Rejto, James Hardwick, Thomas O'Brien, Geoffrey Chan. Analysis of mutations associated with response to glasdegib in acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS) [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 LB-215.

&lt;p&gt;PDF file, 166K, Figure 1S. Differentially expressed genes between most sensitive and resistant models; Figure 2SA. Top genes differentially modulated gene between CC1599 and the remaining models; Figure 2SB. Unsupervised of cell cycle gene modulation after treatment; Figure 3S. Plots of correlation between gene modulation after treatment and baseline expression; Figure 4S. Correlation between modulation after treatment and TGI; Figure 5S. Correlation between TGI and Notch-10 score. Comparison between the Notch-10 score and tumor growth inhibition.&lt;/p&gt;

&lt;p&gt;XLS file, 53K, Target sequences NanoString assays.&lt;/p&gt;

&lt;p&gt;XLS file, 361K, Normalized NanoString expression values used in the analysis.&lt;/p&gt;

&lt;p&gt;PDF file, 208K, Methods for NanoString gene analysis.&lt;/p&gt;

&lt;p&gt;XLS file, 129K, Description of gene expression experiments from Table 2S for analysis in R.&lt;/p&gt;

&lt;p&gt;PDF file, 208K, Methods for NanoString gene analysis.&lt;/p&gt;

&lt;p&gt;XLS file, 53K, Target sequences NanoString assays.&lt;/p&gt;

&lt;p&gt;PDF file, 166K, Figure 1S. Differentially expressed genes between most sensitive and resistant models; Figure 2SA. Top genes differentially modulated gene between CC1599 and the remaining models; Figure 2SB. Unsupervised of cell cycle gene modulation after treatment; Figure 3S. Plots of correlation between gene modulation after treatment and baseline expression; Figure 4S. Correlation between modulation after treatment and TGI; Figure 5S. Correlation between TGI and Notch-10 score. Comparison between the Notch-10 score and tumor growth inhibition.&lt;/p&gt;

&lt;p&gt;XLS file, 129K, Description of gene expression experiments from Table 2S for analysis in R.&lt;/p&gt;

&lt;p&gt;XLS file, 361K, Normalized NanoString expression values used in the analysis.&lt;/p&gt;

&lt;p&gt;Supplementary Figures 1-13 Supplementary Figure 1: Simple mutations and copy number alterations in NOTCH1, NOTCH2 and NOTCH3. Supplementary Figure 2: Simple mutations and copy number alterations in NOTCH4. Supplementary Figure 3: Complex alterations identified by TopNotch Supplementary Figure 4: Intra-NOTCH1 deletion in TCGA-BH-A1FC. Supplementary Figure 5: BRD4-NOTCH3 fusion and PEST domain deletion in TCGA-AN-A0AR. Supplementary Figure 6: Three PEST domain alterations identified in the TCGA breast cancer dataset. Supplementary Figure 7: Notch altered tumors often exhibit increased pathway activity. Supplementary Figure 8: Notch aberrations in pre-clinical GSI sensitive models. Supplementary Figure 9: NOTCH1 aberrations in the HBCx-14 breast cancer PDX model. Supplementary Figure 10: Tumor growth inhibition plots of PF-03084014 in Notch wt models Supplementary Figure 11: Comparison of NICD1 between Notch wt and mutant models. Supplementary Figure 12: Quantitative RT-PCR of HES and HEY target genes in Notch wt and mutant xenograft models Supplementary Figure 13:Quantitative RT-PCR of Notch target genes in Notch wt and mutant xenograft models&lt;/p&gt;

&lt;p&gt;Supplementary Tables 1-4 Supplemental Table 1: Receptor status, mutation, gene expression and copy number data obtained from TCGA Supplemental Table 2: Sequences surrounding the upstream breakpoint used when estimating the support of the mutant and wildtype allele. Supplemental Table 3: Differential expression of Notch pathway genes between Notch altered vs. wildtype tumors Supplemental Table 4: Amino acid sequences downstream of PEST domain alterations in Notch altered samples&lt;/p&gt;

&lt;p&gt;Supplemental Materials and Methods&lt;/p&gt;

&lt;div&gt;Abstract&lt;p&gt;&lt;b&gt;Purpose:&lt;/b&gt; We aimed to assess the biologic activity of PF-03084014 in breast xenograft models. The biomarkers for mechanism and patient stratification were also explored.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Experimental Design:&lt;/b&gt; The &lt;i&gt;in vitro&lt;/i&gt; and &lt;i&gt;in vivo&lt;/i&gt; properties of PF-03084014 were investigated. The mRNA expressions of 40 key Notch pathway genes at baseline or after treatment were analyzed to link with the antitumor efficacy of PF-03084014 in a panel of breast cancer xenograft models.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Results:&lt;/b&gt;&lt;i&gt;In vitro&lt;/i&gt;, PF-03084014 exhibited activity against tumor cell migration, endothelial cell tube formation, and mammosphere formation. &lt;i&gt;In vivo&lt;/i&gt;, we observed apoptosis, antiproliferation, reduced tumor cell self-renewal ability, impaired tumor vasculature, and decreased metastasis activity after the treatment of PF-03084014. PF-03084014 treatment displayed significant antitumor activity in 10 of the 18 breast xenograft models. However, the antitumor efficacy in most models did not correlate with the &lt;i&gt;in vitro&lt;/i&gt; antiproliferation results in the corresponding cell lines, suggesting the critical involvement of tumor microenvironment during Notch activation. In the tested breast xenograft models, the baseline expressions of the Notch receptors, ligands, and the cleaved Notch1 failed to predict the antitumor response to PF-03084014, whereas several Notch pathway target genes, including &lt;i&gt;HEY2&lt;/i&gt;, &lt;i&gt;HES4&lt;/i&gt;, and &lt;i&gt;HES3&lt;/i&gt;, strongly corresponded with the response with a &lt;i&gt;P&lt;/i&gt; value less than 0.01. Many of the best molecular predictors of response were also significantly modulated following PF-03084014 treatment.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Conclusions:&lt;/b&gt; PF-03084014 showed antitumor and antimetastatic properties via pleiotropic mechanisms. The Notch pathway downstream genes may be used to predict the antitumor activity of PF-03084014 and enrich for responders among breast cancer patients. &lt;i&gt;Clin Cancer Res; 18(18); 5008–19. ©2012 AACR&lt;/i&gt;.&lt;/p&gt;&lt;/div&gt;

&lt;div&gt;Abstract&lt;p&gt;&lt;b&gt;Purpose:&lt;/b&gt; To identify and characterize novel, activating mutations in Notch receptors in breast cancer and to determine response to the gamma secretase inhibitor (GSI) PF-03084014.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Experimental Design:&lt;/b&gt; We used several computational approaches, including novel algorithms, to analyze next-generation sequencing data and related omic datasets from The Cancer Genome Atlas (TCGA) breast cancer cohort. Patient-derived xenograft (PDX) models were sequenced, and Notch-mutant models were treated with PF-03084014. Gene-expression and functional analyses were performed to study the mechanism of activation through mutation and inhibition by PF-03084014.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Results:&lt;/b&gt; We identified mutations within and upstream of the PEST domains of NOTCH1, NOTCH2, and NOTCH3 in the TCGA dataset. Mutations occurred via several genetic mechanisms and compromised the function of the PEST domain, a negative regulatory domain commonly mutated in other cancers. Focal amplifications of &lt;i&gt;NOTCH2&lt;/i&gt; and &lt;i&gt;NOTCH3&lt;/i&gt; were also observed, as were heterodimerization or extracellular domain mutations at lower incidence. Mutations and amplifications often activated the Notch pathway as evidenced by increased expression of canonical Notch target genes, and functional mutations were significantly enriched in the triple-negative breast cancer subtype (TNBC). PDX models were also identified that harbored PEST domain mutations, and these models were highly sensitive to PF-03084014.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Conclusions:&lt;/b&gt; This work suggests that Notch-altered breast cancer constitutes a &lt;i&gt;bona fide&lt;/i&gt; oncogenic driver segment with the most common alteration being PEST domain mutations present in multiple Notch receptors. Importantly, functional studies suggest that this newly identified class can be targeted with Notch inhibitors, including GSIs. &lt;i&gt;Clin Cancer Res; 21(6); 1487–96. ©2015 AACR&lt;/i&gt;.&lt;/p&gt;&lt;/div&gt;

&lt;div&gt;Abstract&lt;p&gt;&lt;b&gt;Purpose:&lt;/b&gt; We aimed to assess the biologic activity of PF-03084014 in breast xenograft models. The biomarkers for mechanism and patient stratification were also explored.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Experimental Design:&lt;/b&gt; The &lt;i&gt;in vitro&lt;/i&gt; and &lt;i&gt;in vivo&lt;/i&gt; properties of PF-03084014 were investigated. The mRNA expressions of 40 key Notch pathway genes at baseline or after treatment were analyzed to link with the antitumor efficacy of PF-03084014 in a panel of breast cancer xenograft models.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Results:&lt;/b&gt;&lt;i&gt;In vitro&lt;/i&gt;, PF-03084014 exhibited activity against tumor cell migration, endothelial cell tube formation, and mammosphere formation. &lt;i&gt;In vivo&lt;/i&gt;, we observed apoptosis, antiproliferation, reduced tumor cell self-renewal ability, impaired tumor vasculature, and decreased metastasis activity after the treatment of PF-03084014. PF-03084014 treatment displayed significant antitumor activity in 10 of the 18 breast xenograft models. However, the antitumor efficacy in most models did not correlate with the &lt;i&gt;in vitro&lt;/i&gt; antiproliferation results in the corresponding cell lines, suggesting the critical involvement of tumor microenvironment during Notch activation. In the tested breast xenograft models, the baseline expressions of the Notch receptors, ligands, and the cleaved Notch1 failed to predict the antitumor response to PF-03084014, whereas several Notch pathway target genes, including &lt;i&gt;HEY2&lt;/i&gt;, &lt;i&gt;HES4&lt;/i&gt;, and &lt;i&gt;HES3&lt;/i&gt;, strongly corresponded with the response with a &lt;i&gt;P&lt;/i&gt; value less than 0.01. Many of the best molecular predictors of response were also significantly modulated following PF-03084014 treatment.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Conclusions:&lt;/b&gt; PF-03084014 showed antitumor and antimetastatic properties via pleiotropic mechanisms. The Notch pathway downstream genes may be used to predict the antitumor activity of PF-03084014 and enrich for responders among breast cancer patients. &lt;i&gt;Clin Cancer Res; 18(18); 5008–19. ©2012 AACR&lt;/i&gt;.&lt;/p&gt;&lt;/div&gt;

&lt;div&gt;Abstract&lt;p&gt;&lt;b&gt;Purpose:&lt;/b&gt; To identify and characterize novel, activating mutations in Notch receptors in breast cancer and to determine response to the gamma secretase inhibitor (GSI) PF-03084014.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Experimental Design:&lt;/b&gt; We used several computational approaches, including novel algorithms, to analyze next-generation sequencing data and related omic datasets from The Cancer Genome Atlas (TCGA) breast cancer cohort. Patient-derived xenograft (PDX) models were sequenced, and Notch-mutant models were treated with PF-03084014. Gene-expression and functional analyses were performed to study the mechanism of activation through mutation and inhibition by PF-03084014.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Results:&lt;/b&gt; We identified mutations within and upstream of the PEST domains of NOTCH1, NOTCH2, and NOTCH3 in the TCGA dataset. Mutations occurred via several genetic mechanisms and compromised the function of the PEST domain, a negative regulatory domain commonly mutated in other cancers. Focal amplifications of &lt;i&gt;NOTCH2&lt;/i&gt; and &lt;i&gt;NOTCH3&lt;/i&gt; were also observed, as were heterodimerization or extracellular domain mutations at lower incidence. Mutations and amplifications often activated the Notch pathway as evidenced by increased expression of canonical Notch target genes, and functional mutations were significantly enriched in the triple-negative breast cancer subtype (TNBC). PDX models were also identified that harbored PEST domain mutations, and these models were highly sensitive to PF-03084014.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Conclusions:&lt;/b&gt; This work suggests that Notch-altered breast cancer constitutes a &lt;i&gt;bona fide&lt;/i&gt; oncogenic driver segment with the most common alteration being PEST domain mutations present in multiple Notch receptors. Importantly, functional studies suggest that this newly identified class can be targeted with Notch inhibitors, including GSIs. &lt;i&gt;Clin Cancer Res; 21(6); 1487–96. ©2015 AACR&lt;/i&gt;.&lt;/p&gt;&lt;/div&gt;

&lt;p&gt;Supplemental Materials and Methods&lt;/p&gt;

&lt;p&gt;Supplementary Tables 1-4 Supplemental Table 1: Receptor status, mutation, gene expression and copy number data obtained from TCGA Supplemental Table 2: Sequences surrounding the upstream breakpoint used when estimating the support of the mutant and wildtype allele. Supplemental Table 3: Differential expression of Notch pathway genes between Notch altered vs. wildtype tumors Supplemental Table 4: Amino acid sequences downstream of PEST domain alterations in Notch altered samples&lt;/p&gt;

&lt;p&gt;Supplementary Figures 1-13 Supplementary Figure 1: Simple mutations and copy number alterations in NOTCH1, NOTCH2 and NOTCH3. Supplementary Figure 2: Simple mutations and copy number alterations in NOTCH4. Supplementary Figure 3: Complex alterations identified by TopNotch Supplementary Figure 4: Intra-NOTCH1 deletion in TCGA-BH-A1FC. Supplementary Figure 5: BRD4-NOTCH3 fusion and PEST domain deletion in TCGA-AN-A0AR. Supplementary Figure 6: Three PEST domain alterations identified in the TCGA breast cancer dataset. Supplementary Figure 7: Notch altered tumors often exhibit increased pathway activity. Supplementary Figure 8: Notch aberrations in pre-clinical GSI sensitive models. Supplementary Figure 9: NOTCH1 aberrations in the HBCx-14 breast cancer PDX model. Supplementary Figure 10: Tumor growth inhibition plots of PF-03084014 in Notch wt models Supplementary Figure 11: Comparison of NICD1 between Notch wt and mutant models. Supplementary Figure 12: Quantitative RT-PCR of HES and HEY target genes in Notch wt and mutant xenograft models Supplementary Figure 13:Quantitative RT-PCR of Notch target genes in Notch wt and mutant xenograft models&lt;/p&gt;

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