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TCGA Study Brings Ovarian Cancer Patients Closer to Personalized Medicine

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In the June 30 issue of Nature, researchers from The Cancer Genome Atlas (TCGA) Research Network provide a large-scale integrative report on genetic mutations and pathways that distinguish the most common and aggressive type of ovarian cancer from other types of ovarian cancer as well as from other solid tumors. The disease is not defined by one or few cancer-driving genes but rather numerous mutations that individually occur in only a small number of cases. Given the degree of genomic disarray, the study results suggest that genomic structural variation is the driver of ovarian cancer. The findings may be helpful in guiding physicians to choose experimental treatments that are most likely to target molecular alterations effectively in patients with high-grade serous ovarian adenocarcinoma.

To identify molecular abnormalities that influence pathophysiology, affect outcome and constitute therapeutic targets, The Cancer Genome Atlas (TCGA) project analyzed mRNA and microRNA expression, promoter methylation and DNA copy number from 489 high-grade serous ovarian adenocarcinomas (the most prevalent form of ovarian cancer that accounts for ~85% of all ovarian cancer deaths). They also performed exome sequencing, which examines the protein-coding regions of the genome, on a subset of 316 tumors as well as other genomic characterizations on these tumors and another 173 specimens.

TCGA researchers identified four transcriptional subtypes — labeled ‘immunoreactive’, ‘differentiated’, ‘proliferative’ and ‘mesenchymal’ based on cluster gene content — that all have poor prognosis but are distinct with respect to their biology, each being characterized by a different set of mutations.

The study found that mutations in TP53 (p53) are present in more than 96% of all serous ovarian adenocarcinomas. However, instead of finding a set of cancer-driving mutations that occurred across the population, TCGA researchers identified a number of less-frequent but statistically recurrent somatic mutations in nine other genes, including NF1, BRCA1, BRCA2, RB1 and CDK12.

Analysis of the frequency with which known cancer-associated pathways contained one or more mutations, copy number changes or changes in gene expression showed deregulation of the RB1 pathway and PI3K/RAS pathway in 67% and 45% of cases, respectively.

A search for altered subnetworks in a large protein–protein interaction network identified the NOTCH signaling pathway, which was altered in 22% samples, while probabilistic graphical modeling identified the FOXM1 transcription factor network, which was significantly altered in 87% of samples.

These pathways offer potential opportunities for therapy, as drugs are currently in development that target genes in the pathways.

In addition, TCGA researchers identified three microRNA subtypes, four promoter methylation subtypes and transcriptional signatures associated with length of survival. They defined a 193-gene expression signature predictive of overall survival using the integrated expression data set from 215 samples: 108 genes were correlated with poor survival and 85 were correlated with good survival. Patients with tumors whose transcription profile reflected poor survival lived an almost 25% shorter period of time than patients whose tumors reflected better survival.

Several of the findings have therapeutic implications. The TCGA team mined several databases — Ingenuity Systems’ pathway database, DrugBank and ClinicalTrials.gov — and found 22 targets for genes that were over-expressed in at least 10% of samples, including MECOM, MAPK1, KRAS and CCNE1.

Approximately 20% of samples contain BRCA1 and BCRA2 mutations, which have been found to be responsive to PARP inhibitors.

TCGA is jointly funded and managed by the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI), both part of the National Institutes of Health (NIH).

Study: Integrated genomic analyses of ovarian carcinoma

PubMed: View abstract