CANCER GENOME ATLAS

The first research from a massive collaboration — The Cancer Genome Atlas (TCGA) Pan-Cancer Initiative — has been reported in 2 analyses and 2 commentaries published in the October issue of Nature Genetics.

The primary findings are that tumors comprise 2 major genomic categories, regardless of tissue of origin; that tumors across several tissue types share the same oncogenic signature, suggesting that they might be responsive to the same therapies; and that recurrent gene copy-number alterations exist in 140 genomic regions, 102 of which had no known oncogene or tumor suppressor gene targets and 50 of which had significantly mutated genes.

The first analysis of the TGCA data was conducted by Giovanni Ciriello, PhD, and colleagues from the Memorial Sloan-Kettering Cancer Center in New York City. That team used genomic and epigenomic features to stratify 3299 tumors from 12 cancer types: bladder urothelial carcinoma, breast invasive carcinoma, colon and rectum adenocarcinoma, glioblastoma multiforme, head and neck squamous cell carcinoma, kidney renal clear-cell carcinoma, acute myeloid leukemia, lung adenocarcinoma, lung squamous cell carcinoma, ovarian serous cystadenocarcinoma, and uterine corpus endometrioid carcinoma.

Dr. Ciriello's team was surprised to find a "cancer genome hyperbola" independent of tumor tissue type. Tumors had "either a large number of somatic mutations or a large number of copy number alterations, never both," they explain.

They identified "oncogenic signature classes" that apply to groups of tumors across several tissue types. However, cancer-promoting gene signatures for 30 subclasses of tumor were independent of tissue of origin. Genomic subclasses were characterized "not only by single oncogenic events but also by specific combinations of events" that might be targets for combination therapy, they write.

"For example, subsets of lung and head and neck squamous cell carcinomas may benefit from concurrent blockade of the cell cycle and PI3K-AKT signaling, whereas inhibition of PARP and Aurora kinase A may be beneficial for subsets of BRCA1- or BRCA2-mutant ovarian and basal breast tumors," Dr. Ciriello and colleagues report.

The second analysis from the TGCA dataset was led by Rameen Beroukhim, MD, PhD, from Harvard Medical School, the Broad Institute of MIT, and the Dana-Farber Cancer Institute in Boston. That team characterized somatic copy-number alterations, such as deletions or amplifications (SCNAs), in 4934 cancers and genomic epigenetic features in 3299 tumors. They found whole-genome doubling in 37% of cancers, which was associated with higher rates of all other types of SCNAs.

"Significantly recurrent focal SCNAs were observed in 140 regions, including 102 without known oncogene or tumor suppressor gene targets and 50 with significantly mutated genes. Amplified regions without known oncogenes were enriched for genes involved in epigenetic regulation," Dr. Beroukhim and colleagues write.

In the first accompanying commentary, John Weinstein, MD, PhD, from the University of Texas M.D. Anderson Cancer Center in Houston, and colleagues write that "TCGA's principal aims are to generate, quality control, merge, analyze, and interpret molecular profiles at the DNA, RNA, protein, and epigenetic levels for hundreds of clinical tumors representing various tumor types and their subtypes." The TCGA research network plans to complete analysis of more than 10,000 specimens from more than 25 different tumor types by the end of 2015, and to make the data and results "freely available to the scientific community" by posting them on the TCGA Web site.

"One of the more exciting possibilities for this research is that we can take therapies effective in one tumor type, for example HER2 protein inhibitors for HER2-positive breast cancer, and check their effectiveness in other cancer types that we now know also have that mutation or overexpress that protein," Dr. Weinstein said in a press statement.

In the second accompanying commentary, Larsson Omberg, PhD, from Sage Bionetworks in Seattle, and colleagues describe the software platform and methodologies that made "transparent and collaborative computational analysis" of genomic data from multiple tumor types possible in ongoing research by hundreds of researchers. In the Pan-Cancer group model, all collaborators use the Synapse software platform to share data, results, and methodologies. The work is meant to provide a template for future large collaborative studies and "a public resource of highly curated data, results, and automated systems for the evaluation of community-developed models," Dr. Omberg and colleagues write.

TCGA is a joint project of the National Cancer Institute and the National Human Genome Research Institute.

The studies were supported by the National Cancer Institute, the National Institutes of Health, a Stand Up To Cancer Dream Team Translational Research Grant, a Program of the Entertainment Industry Foundation, and the Pediatric Low-Grade Astrocytoma Foundation. The authors have disclosed no relevant financial relationships.

Nat Genet. 2013;45:1113-1120, 1121-1126, 1127-1133, 1134-1140. Weinstein abstract, Omberg abstract, Ciriello abstract, Beroukhim abstract