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Pan-cancer analysis aims to examine the similarities and differences among the genomic and cellular alterations found across diverse tumor types. International efforts have performed pan-cancer analysis on exomes and the whole genomes of cancers, the latter including their non-coding regions. In 2018, The Cancer Genome Atlas (TCGA) Research Network used exome, transcriptome, and DNA methylome data to develop an integrated picture of commonalities, differences, and emergent themes across tumor types.

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  • Pan-cancer analysis (en)
  • 全基因组泛癌分析 (zh)
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  • 全基因组泛癌分析(英语:Pan-Cancer Analysis of Whole Genomes,PCAWG)是由国际癌症基因组联盟(ICGC)组织的一个国际性合作项目,对超过2600组癌细胞基因进行分析。 (zh)
  • Pan-cancer analysis aims to examine the similarities and differences among the genomic and cellular alterations found across diverse tumor types. International efforts have performed pan-cancer analysis on exomes and the whole genomes of cancers, the latter including their non-coding regions. In 2018, The Cancer Genome Atlas (TCGA) Research Network used exome, transcriptome, and DNA methylome data to develop an integrated picture of commonalities, differences, and emergent themes across tumor types. (en)
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  • Pan-cancer analysis aims to examine the similarities and differences among the genomic and cellular alterations found across diverse tumor types. International efforts have performed pan-cancer analysis on exomes and the whole genomes of cancers, the latter including their non-coding regions. In 2018, The Cancer Genome Atlas (TCGA) Research Network used exome, transcriptome, and DNA methylome data to develop an integrated picture of commonalities, differences, and emergent themes across tumor types. In 2020, the International Cancer Genome Consortium (ICGC)/TCGA Pan-Cancer Analysis of Whole Genomes project published a set of 24 papers analyzing whole cancer genomes and transcriptomic data from 38 tumor types. A comprehensive overview of the project is provided in its flagship paper. Another project, pan-cancer analysis of RNA-binding proteins (RBPs) across human cancers, explored the expression, somatic copy number alteration, and mutation profiles of 1,542 RBPs in ∼7,000 clinical specimens across 15 cancer types. This study characterized the oncogenic properties of six RBPs—, ZC3H13, BYSL, ELAC1, RBMS3, and ZGPAT—in colorectal and liver cancer cell lines. Several studies have found a causal, predictable connection between genomic alterations (single-nucleotide variants or large copy number variants) and gene expression across all tumor types. This pan-cancer relationship between genomic status and transcriptomic quantitative data can predict a specific genomic alteration from gene expression profiles alone; it can also be used as the basis for machine learning approaches. (en)
  • 全基因组泛癌分析(英语:Pan-Cancer Analysis of Whole Genomes,PCAWG)是由国际癌症基因组联盟(ICGC)组织的一个国际性合作项目,对超过2600组癌细胞基因进行分析。 (zh)
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