Tag: TCGA

TCGA PanCancer Atlas

A long list of articles to read!

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PancanQTL

[PMID: 29036324] [Nucleic Acids Research]

PancanQTL: systematic identification of cis-eQTLs and trans-eQTLs in 33 cancer types

“Using the genotype and expression data of 9196 tumor samples in 33 cancer types from The Cancer Genome Atlas (TCGA), we identified 5 606 570 eQTL-gene pairs in the cis-eQTL analysis and 231 210 eQTL-gene pairs in the trans-eQTL analysis.” “We developed PancanQTL, a user-friendly database, to store cis-eQTLs, trans-eQTLs, survival-associated eQTLs and GWAS-related eQTLs to enable searching, browsing and downloading.”

Bi-allelic Variants and HRD

[PMID: 29021619] [Nature Communications]

Pan-cancer analysis of bi-allelic alterations in homologous recombination DNA repair genes

“over 5% of all cancers harbor bi-allelic pathogenic mutations in HR-related genes” “bi-allelic alterations in HR DNA repair-related genes occur across cancer types, are mutually exclusive, and are associated with genomics features consistent with lack of competent HR DNA repair” mono-allelic alterations are not associated with HDR.

Genomic Metrics and Immune Infiltration in TNBC

[PMID: 28750120] [JAMA Oncology]

Association Between Genomic Metrics and Immune Infiltration in Triple-Negative Breast Cancer

“calculate previously described immune metagene expression values and histologic lymphocyte counts to quantify immune infiltration and assign prognostic categories to TNBCs” “compared clonal heterogeneity, somatic total mutational load, neoantigen load, and somatic copy number alteration levels between immune-rich TNBC cohorts with good prognosis and immune-poor TNBC cohorts with poor prognosis.”

HIT’nDRIVE

[PMID: 28720581] [Genome Research]

HIT’nDRIVE: Patient-specific multi-driver gene prioritization for precision oncology

“a computational method that integrates genomic and transcriptomic data to identify a set of patient-specific, sequence-altered genes, with sufficient collective influence over dysregulated transcripts. HIT’nDRIVE aims to solve the “random walk facility location” (RWFL) problem in a gene (or protein) interaction network, which differs from the standard facility location problem by its use of an alternative distance measure: “multi-hitting time”, the expected length of the shortest random walk from any one of the set of sequence-altered genes to an expression-altered target gene.”

TCGA Neoantigens

[PMID: 28694034] [Lancet Oncology]

Insertion-and-deletion-derived tumour-specific neoantigens and the immunogenic phenotype: a pan-cancer analysis

“analysed whole-exome sequencing data from 5777 solid tumours, spanning 19 cancer types from The Cancer Genome Atlas.” “Analysis of tumour-specific neoantigens showed that enrichment of indel mutations for high-affinity binders was three times that of non-synonymous SNV mutations. Furthermore, neoantigens derived from indel mutations were nine times enriched for mutant specific binding, as compared with non-synonymous SNV derived neoantigens.”