4.6 Article

Comprehensive genomic profiling of epithelial ovarian cancer by next generation sequencing-based diagnostic assay reveals new routes to targeted therapies

期刊

GYNECOLOGIC ONCOLOGY
卷 130, 期 3, 页码 554-559

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ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ygyno.2013.06.019

关键词

Ovarian cancer; Next generation sequencing; Targeted therapy; Mutation; Deletion; Gene fusion

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Objective. Targeted next generation sequencing (NGS) was evaluated for its ability to identify unanticipated targetable genomic alterations (GA) for patients with relapsed ovarian epithelial carcinoma (OC). Methods. DNA sequencing was performed for 3320 exons of 182 cancer-related genes and 37 introns of 14 genes frequently rearranged in cancer on indexed, adaptor ligated, hybridization-captured libraries using DNA isolated from FFPE sections from 48 histologically verified relapsed OC specimens. The original primary tumor was sequenced in 26 (54%) of the cases and recurrent/metastatic tumor site biopsies were sequenced in 22 (46%) of the cases. Actionability was defined as: GA that predict sensitivity or resistance to approved or standard therapies or are inclusion or exclusion criteria for specific experimental therapies in NCI registered clinical trials. Results. There were 38 (80%) serous, 5 (10%) endometrioid, 3 (6%) clear cell, I mucinous (2%) and 1 (2%) undifferentiated carcinomas. 141 GA were identified with an average of 2.9 GA (range 0-8) per tumor, of which 67 were actionable for an average of 1.4 actionable GA per patient (range 0-5).33/48 (69%) of OC patient samples harbored at least one actionable GA. Most common GA were TP53 (79%); MYC (25%); BRCA1/2 (23%); KRAS (16.6%) and NF1 (14.5%). One tumor featured an ERBB2 point mutation. One of 3 (33%) of clear cell tumors featured cMET amplification validated by both FISH and IHC. Conclusions. NGS assessment of therapy resistant DC identifies an unexpectedly high frequency of GA that could influence targeted therapy selection for the disease. (C) 2013 The Authors. Published by Elsevier Inc. All rights reserved.

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