Ovarian Cancer Genomic Analysis Reveals Seven Disease-Stratifying Clusters

NEW YORK (GenomeWeb) – Genomic analysis appears to provide new information for classifying ovarian cancer, beyond what is available from traditional ovarian cancer histotypes, a new study suggests.

An international team led by investigators at the BC Cancer Agency and the University of British Columbia tracked point mutations and structural variants in more than 100 ovarian cancers, representing four established subtypes of the disease. From these alterations, the investigators identified seven tumor clusters — molecular subtypes that spanned histotype-based subtypes in some cases. The findings were published online in Nature Genetics today.

“Our results show that properties of the somatic genome on both the structural and point mutation scales are powerful, discriminant biomarkers between and within histotypes for subgroup discovery in ovarian cancer,” corresponding authors Sohrab Shah and David Huntsman and their co-authors wrote.

For their analysis, the researchers considered 133 ovarian cancer cases, through genome sequencing on matched tumor and normal samples from 59 individuals with high-grade serous ovarian cancer, 35 individuals with clear cell ovarian cancer, 29 endometrioid cases, and 10 cases of adult granulosa cell ovarian cancer.

In addition to verifying potential structural variants by amplicon sequencing, the team profiled BRCA1/2 germline mutations, methylation status at the

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