JOURNAL ARTICLE
RESEARCH SUPPORT, NON-U.S. GOV'T
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Genomic classification of serous ovarian cancer with adjacent borderline differentiates RAS pathway and TP53-mutant tumors and identifies NRAS as an oncogenic driver.

Clinical Cancer Research 2014 December 16
PURPOSE: Low-grade serous ovarian carcinomas (LGSC) are Ras pathway-mutated, TP53 wild-type, and frequently associated with borderline tumors. Patients with LGSCs respond poorly to platinum-based chemotherapy and may benefit from pathway-targeted agents. High-grade serous carcinomas (HGSC) are TP53-mutated and are thought to be rarely associated with borderline tumors. We sought to determine whether borderline histology associated with grade 2 or 3 carcinoma was an indicator of Ras mutation, and we explored the molecular relationship between coexisting invasive and borderline histologies.

EXPERIMENTAL DESIGN: We reviewed >1,200 patients and identified 102 serous carcinomas with adjacent borderline regions for analyses, including candidate mutation screening, copy number, and gene expression profiling.

RESULTS: We found a similar frequency of low, moderate, and high-grade carcinomas with coexisting borderline histology. BRAF/KRAS alterations were common in LGSC; however, we also found recurrent NRAS mutations. Whereas borderline tumors harbored BRAF/KRAS mutations, NRAS mutations were restricted to carcinomas, representing the first example of a Ras oncogene with an obligatory association with invasive serous cancer. Coexisting borderline and invasive components showed nearly identical genomic profiles. Grade 2 cases with coexisting borderline included tumors with molecular features of LGSC, whereas others were typical of HGSC. However, all grade 3 carcinomas with coexisting borderline histology were molecularly indistinguishable from typical HGSC.

CONCLUSION: Our findings suggest that NRAS is an oncogenic driver in serous ovarian tumors. We demonstrate that borderline histology is an unreliable predictor of Ras pathway aberration and underscore an important role for molecular classification in identifying patients that may benefit from targeted agents.

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