Modulation of Bax and mTOR for Cancer Therapeutics.

A rationale exists for pharmacologic manipulation of the serine (S)184 phosphorylation site of the proapoptotic Bcl2 family member Bax as an anticancer strategy. Here, we report the refinement of the Bax agonist SMBA1 to generate CYD-2-11, which has characteristics of a suitable clinical lead compound. CYD-2-11 targeted the structural pocket proximal to S184 in the C-terminal region of Bax, directly activating its proapoptotic activity by inducing a conformational change enabling formation of Bax homooligomers in mitochondrial membranes. In murine models of small-cell and non-small cell lung cancers, including patient-derived xenograft and the genetically engineered mutant KRAS-driven lung cancer models, CYD-2-11 suppressed malignant growth without evident significant toxicity to normal tissues. In lung cancer patients treated with mTOR inhibitor RAD001, we observed enhanced S184 Bax phosphorylation in lung cancer cells and tissues that inactivates the propaoptotic function of Bax, contributing to rapalog resistance. Combined treatment of CYD-2-11 and RAD001 in murine lung cancer models displayed strong synergistic activity and overcame rapalog resistanc

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Prognostic biomarkers in patients with human immunodeficiency virusâ positive disease with head and neck squamous cell carcinoma

BackgroundWe examined the prognostic value of a panel of biomarkers in patients with squamous cell carcinoma of the head and neck (SCCHN) who were human immunodeficiency virus (HIV) positive (HIVâ positive head and neck cancer) and HIV negative (HIVâ negative head and neck cancer).MethodsTissue microarrays (TMAs) were constructed using tumors from 41 disease siteâ matched and ageâ matched HIVâ positive head and neck cancer cases and 44 HIVâ negative head and neck cancer controls. Expression of tumor biomarkers was assessed by immunohistochemistry (IHC) and correlations examined with clinical variables.ResultsExpression levels of the studied oncogenic and inflammatory tumor biomarkers were not differentially regulated by HIV status. Among patients with HIVâ positive head and neck cancer, laryngeal disease site (P = .003) and Clavienâ Dindo classification IV (CD4) counts <200 cells/μL (P = .01) were associated with poor prognosis. Multivariate analysis showed that p16 positivity was associated with improved overall survival (OS; P < .001) whereas increased expression of transforming growth factorâ beta (TGFâ β) was associated with poor clinical outcome (P = .001).ConclusionDisease site has significant effect on the expression of biomarkers. Expression of tumor TGFâ β could be a valuable addition to the conventional risk stratification equation for improving head and neck cancer disease management strategies.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139994/1/hed24911.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139994/2/hed24911_am.pd

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas

Summary Sarcomas are a broad family of mesenchymal malignancies exhibiting remarkable histologic diversity. We describe the multi-platform molecular landscape of 206 adult soft tissue sarcomas representing 6 major types. Along with novel insights into the biology of individual sarcoma types, we report three overarching findings: (1) unlike most epithelial malignancies, these sarcomas (excepting synovial sarcoma) are characterized predominantly by copy-number changes, with low mutational loads and only a few genes (TP53, ATRX, RB1) highly recurrently mutated across sarcoma types; (2) within sarcoma types, genomic and regulomic diversity of driver pathways defines molecular subtypes associated with patient outcome; and (3) the immune microenvironment, inferred from DNA methylation and mRNA profiles, associates with outcome and may inform clinical trials of immune checkpoint inhibitors. Overall, this large-scale analysis reveals previously unappreciated sarcoma-type-specific changes in copy number, methylation, RNA, and protein, providing insights into refining sarcoma therapy and relationships to other cancer types