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The capstone of The Cancer Genome Atlas integrated DNA, RNA, protein and methylation data on about 10,000 tumours, showing that cell of origin dominates molecular classification but that some cancers regroup across organs.
The Pan-Cancer Atlas was a set of 27 papers in Cell Press journals in April 2018 summarising a decade of TCGA. The flagship classification paper (Hoadley et al.) integrated five data types on 9,759 tumours from 33 cancer types and identified 28 molecular clusters. Most clusters were dominated by tissue of origin, but squamous cancers from different organs grouped together, as did gastrointestinal adenocarcinomas and kidney cancers of different histologies.
Companion papers catalogued 299 driver genes and over 3,400 driver mutations (Bailey et al.), showed that 89% of tumours had at least one driver alteration in ten canonical signalling pathways and 57% had at least one potentially targetable alteration (Sanchez-Vega et al.), and characterised immune subtypes, oncogenic processes and cell-of-origin patterns.
TCGA data, freely available through the Genomic Data Commons, became the reference against which nearly every cancer genomics study is compared.
Cancers are defined as much by the tissue they come from as by the mutations they carry, which is why the same drug can work in one organ and fail in another with the same mutation. TCGA is the shared public dataset behind most modern biomarkers and target discovery.
Shares Mutational signature, Tumour mutational burden (TMB), Tumour heterogeneity and clonal evolution, Whole-exome & whole-genome sequencing.
Shares Broad Institute of MIT and Harvard, Trials do not represent the people who get cancer, Data silos, National Cancer Institute (NIH).
Shares Broad Institute of MIT and Harvard, Tumour heterogeneity and clonal evolution, Data silos, Whole-exome & whole-genome sequencing.
Shares Cell, Broad Institute of MIT and Harvard, Tumour mutational burden (TMB), Whole-exome & whole-genome sequencing.
Shares RNA sequencing & expression profiling, Data silos, Whole-exome & whole-genome sequencing, Comprehensive genomic profiling.
Shares Tumour heterogeneity and clonal evolution, Data silos, Whole-exome & whole-genome sequencing, Comprehensive genomic profiling.
Shares Charles M. Perou, PAM50 / intrinsic subtypes, RNA sequencing & expression profiling.
Shares Broad Institute of MIT and Harvard, Data silos, Comprehensive genomic profiling.