151 research outputs found

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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

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

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    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

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

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    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

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    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

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    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

    Association of the Genomic Profile of Medullary Thyroid Carcinoma with Tumor Characteristics and Clinical Outcomes in an International Multicenter Study

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    Purpose: The prognostic importance of RET and RAS mutations and their relationship to clinicopathologic parameters and outcomes in medullary thyroid carcinoma (MTC) need to be clarified. Experimental Design: A multicenter retrospective cohort study was performed utilizing data from 290 patients with MTC. The molecular profile was determined and associations were examined with clinicopathologic data and outcomes. Results: RET germ line mutations were detected in 40 patients (16.3%). Somatic RET and RAS mutations occurred in 135 (46.9%) and 57 (19.8%) patients, respectively. RETM918T was the most common somatic RET mutation (n = 75). RET somatic mutations were associated with male sex, larger tumor size, advanced American Joint Committee Cancer (AJCC) stage, vascular invasion, and high International Medullary Thyroid Carcinoma Grading System (IMTCGS) grade. When compared with other RET somatic mutations, RETM918T was associated with younger age, AJCC (eighth edition) IV, vascular invasion, extrathyroidal extension, and positive margins. RET somatic or germ line mutations were significantly associated with reduced distant metastasis-free survival on univariate analysis, but there were no significant independent associations on multivariable analysis, after adjusting for tumor grade and stage. There were no significant differences in outcomes between RET somatic and RET germ line mutations, or between RETM918T and other RET mutations. Other recurrent molecular alterations included TP53 (4.2%), ARID2 (2.9%), SETD2 (2.9%), KMT2A (2.9%), and KMT2C (2.9%). Among them, TP53 mutations were associated with decreased overall survival (OS) and disease-specific survival (DSS), independently of tumor grade and AJCC stage. Conclusions: RET somatic mutations were associated with high-grade, aggressive primary tumor characteristics, and decreased distant metastatic-free survival but this relationship was not significant after accounting for tumor grade and disease stage. RETM918T was associated with aggressive primary tumors but was not independently associated with clinical outcomes. TP53 mutation may represent an adverse molecular event associated with decreased OS and DSS in MTC, but its prognostic value needs to be confirmed in future studies

    Somatic mutations in solid tumors: a spectrum at the service of diagnostic armamentarium or an indecipherable puzzle? The morphological eyes looking for BRAF and somatic molecular detections on cyto-histological samples

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    This review article deals with the analysis and the detection of the morphological features associated with somatic mutations, mostly BRAF(V600E) mutation, on both cytological and histological samples of carcinomas. Few authors demonstrated that some architectural and specific cellular findings (i.e. polygonal eosinophilic cells defined as "plump cells" and sickle-shaped nuclei) are able to predict BRAF (V600E) mutation in both cytological and histological samples of papillary thyroid carcinoma (PTC) as well as in other carcinomas. In the current review article we evaluated the first comprehensive analysis of the morphological prediction of BRAFV600E and other somatic mutations in different malignant lesions with the description of the possible mechanisms beneath these morphologic features. The detection of predictive morphological features, mostly on FNAC, may add helpful information to the stratification of the malignant risk and personalized management of cancers. Additionally, the knowledge of the molecular mechanism of different oncogenic drivers can lead to the organ-specific triaging selection of cases and can provide significant insight for targeted therapies in different malignant lesions.info:eu-repo/semantics/publishedVersio
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