A Case of Intra and Extra-vascular Lipoma of the Subclavian Vein

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Social Factors Affecting Treatment of Cervical Cancer: Ethical Issues and Policy Implications

Health care in the United States has become a privilege rather than a right. Patients who have the greatest need are the ones most likely to be denied this privilege. Despite recent advances in disease detection and treatment, many patients do not receive even the bare minimum of care. The high complexity of the health care system in the setting of patients with low levels of health literacy significantly affects the ability to seek and receive treatment in a timely fashion. In addition, lack of insurance, transportation, and social support further complicate access to care. To truly provide a standard of care to all patients, regardless of resources, our health care system must evolve to address the needs of the population. In this paper, we report a tragic case where social factors affected the outcome of a single mother with advanced cervical cancer

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

HER2 gene amplification and EGFR expression in a large cohort of surgically staged patients with nonendometrioid (type II) endometrial cancer

Type II endometrial cancers (uterine serous papillary and clear cell histologies) represent rare but highly aggressive variants of endometrial cancer (EC). HER2 and EGFR may be differentially expressed in type II EC. Here, we evaluate the clinical role of HER2 and EGFR in a large cohort of surgically staged patients with type II (nonendometrioid) EC and compare the findings with those seen in a representative cohort of type I (endometrioid) EC. In this study HER2 gene amplification was studied by fluorescence in situ hybridisation (FISH) and EGFR expression by immunohistochemistry. Tissue microarrays were constructed from 279 patients with EC (145 patients with type I and 134 patients with type II EC). All patients were completely surgically staged and long-term clinical follow up was available for 258 patients. The rate of HER2 gene amplification was significantly higher in type II EC compared with type I EC (17 vs 1%, P<0.001). HER2 gene amplification was detected in 17 and 16% of the cases with uterine serous papillary and clear cell type histology, respectively. In contrast, EGFR expression was significantly lower in type II compared with type I EC (34 vs 46%, P=0.041). EGFR expression but not HER2 gene amplification was significantly associated with poor overall survival in patients with type II EC, (EGFR, median survival 20 vs 33 months, P=0.028; HER2, median survival 18 vs 29 months, P=0.113) and EGFR expression retained prognostic independence when adjusting for histology, stage, grade, and age (EGFR, P=0.0197; HER2, P=0.7855). We conclude that assessment of HER2 gene amplification and/or EGFR expression may help to select type II EC patients who could benefit from therapeutic strategies targeting both HER2 and EGFR

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

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

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