Exome and whole genome sequencing of esophageal adenocarcinoma identifies recurrent driver events and mutational complexity

The incidence of esophageal adenocarcinoma (EAC) has risen 600% over the last 30 years. With a five-year survival rate of 15%, identification of new therapeutic targets for EAC is greatly important. We analyze the mutation spectra from whole exome sequencing of 149 EAC tumors/normal pairs, 15 of which have also been subjected to whole genome sequencing. We identify a mutational signature defined by a high prevalence of A to C transversions at AA dinucleotides. Statistical analysis of exome data identified significantly mutated 26 genes. Of these genes, four (TP53, CDKN2A, SMAD4, and PIK3CA) have been previously implicated in EAC. The novel significantly mutated genes include chromatin modifying factors and candidate contributors: SPG20, TLR4, ELMO1, and DOCK2. Functional analyses of EAC-derived mutations in ELMO1 reveal increased cellular invasion. Therefore, we suggest a new hypothesis about the potential activation of the RAC1 pathway to be a contributor to EAC tumorigenesis

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 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

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

Integrated genomic characterization of endometrial carcinoma

SummaryWe performed an integrated genomic, transcriptomic, and proteomic characterization of 373 endometrial carcinomas using array- and sequencing-based technologies. Uterine serous tumors and ~25% of high-grade endometrioid tumors have extensive copy number alterations, few DNA methylation changes, low ER/PR levels, and frequent TP53 mutations. Most endometrioid tumors have few copy number alterations or TP53 mutations but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A, KRAS and novel mutations in the SWI/SNF gene ARID5B. A subset of endometrioid tumors we identified had a dramatically increased transversion mutation frequency, and newly identified hotspot mutations in POLE. Our results classified endometrial cancers into four categories: POLE ultramutated, microsatellite instability hypermutated, copy number low, and copy number high. Uterine serous carcinomas share genomic features with ovarian serous and basal-like breast carcinomas. We demonstrated that the genomic features of endometrial carcinomas permit a reclassification that may impact post-surgical adjuvant treatment for women with aggressive tumors

Cross-cutting principles for planetary health education

Since the 2015 launch of the Rockefeller Foundation Lancet Commission on planetary health,1 an enormous groundswell of interest in planetary health education has emerged across many disciplines, institutions, and geographical regions. Advancing these global efforts in planetary health education will equip the next generation of scholars to address crucial questions in this emerging field and support the development of a community of practice. To provide a foundation for the growing interest and efforts in this field, the Planetary Health Alliance has facilitated the first attempt to create a set of principles for planetary health education that intersect education at all levels, across all scales, and in all regions of the world—ie, a set of cross-cutting principles

Comprehensive molecular portraits of human breast tumours

This Article from the Cancer Genome Atlas consortium describes a multifaceted analysis of primary breast cancers in 825 people. Exome sequencing, copy number variation, DNA methylation, messenger RNA arrays, microRNA sequencing and proteomic analyses were performed and integrated to shed light on breast-cancer heterogeneity. Just three genes — TP53, PIK3CA and GATA3 — are mutated at greater than 10% frequency across all breast cancers. Many subtype-associated and novel mutations were identified, as well as two breast-cancer subgroups with specific signalling-pathway signatures. The analyses also suggest that much of the clinically observable plasticity and heterogeneity occurs within, and not across, the major subtypes of breast cancer

Comprehensive Molecular Characterization of Pheochromocytoma and Paraganglioma

SummaryWe report a comprehensive molecular characterization of pheochromocytomas and paragangliomas (PCCs/PGLs), a rare tumor type. Multi-platform integration revealed that PCCs/PGLs are driven by diverse alterations affecting multiple genes and pathways. Pathogenic germline mutations occurred in eight PCC/PGL susceptibility genes. We identified CSDE1 as a somatically mutated driver gene, complementing four known drivers (HRAS, RET, EPAS1, and NF1). We also discovered fusion genes in PCCs/PGLs, involving MAML3, BRAF, NGFR, and NF1. Integrated analysis classified PCCs/PGLs into four molecularly defined groups: a kinase signaling subtype, a pseudohypoxia subtype, a Wnt-altered subtype, driven by MAML3 and CSDE1, and a cortical admixture subtype. Correlates of metastatic PCCs/PGLs included the MAML3 fusion gene. This integrated molecular characterization provides a comprehensive foundation for developing PCC/PGL precision medicine