The Cancer Genome Atlas

A Pan-Cancer Analysis Reveals High-Frequency Genetic Alterations in Mediators of Signaling by the TGF-β Superfamily

We present an integromic analysis of gene alterations that modulate transforming growth factor β (TGF-β)-Smad-mediated signaling in 9,125 tumor samples across 33 cancer types in The Cancer Genome Atlas (TCGA). Focusing on genes that encode mediators and regulators of TGF-β signaling, we found at least one genomic alteration (mutation, homozygous deletion, or amplification) in 39% of samples, with highest frequencies in gastrointestinal cancers. We identified mutation hotspots in genes that encode TGF-β ligands (BMP5), receptors (TGFBR2, AVCR2A, and BMPR2), and Smads (SMAD2 and SMAD4).

A Pan-Cancer Analysis of Enhancer Expression in Nearly 9000 Patient Samples

The role of enhancers, a key class of non-coding regulatory DNA elements, in cancer development has increasingly been appreciated. Here, we present the detection and characterization of a large number of expressed enhancers in a genome-wide analysis of 8928 tumor samples across 33 cancer types using TCGA RNA-seq data. Compared with matched normal tissues, global enhancer activation was observed in most cancers.

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.

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations.

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.

Molecular Characterization and Clinical Relevance of Metabolic Expression Subtypes in Human Cancers

Metabolic reprogramming provides critical information for clinical oncology. Using molecular
data of 9,125 patient samples from The Cancer Genome Atlas, we identified tumor subtypes in 33
cancer types based on mRNA expression patterns of seven major metabolic processes and assessed
their clinical relevance. Our metabolic expression subtypes correlated extensively with clinical
outcome: subtypes with upregulated carbohydrate, nucleotide, and vitamin/cofactor metabolism

© Università degli Studi di Roma "La Sapienza" - Piazzale Aldo Moro 5, 00185 Roma