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

- Using targeted NGS, 141 genomic alterations were identified in 48 ovarian epithelial carcinomas 67of which were actionable.
- Most common alterations were in TP53 (79%); MYC (25%); BRCA1/2 (23%); KRAS (16.6%) and NF1 (14.5%).
- NGS identifies an unexpectedly high frequency of genomic alterations that could influence targeted therapy selection for ovarian carcinoma.

ObjectiveTargeted next generation sequencing (NGS) was evaluated for its ability to identify unanticipated targetable genomic alterations (GA) for patients with relapsed ovarian epithelial carcinoma (OC).MethodsDNA 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.ResultsThere were 38 (80%) serous, 5 (10%) endometrioid, 3 (6%) clear cell, 1 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.ConclusionsNGS assessment of therapy resistant OC identifies an unexpectedly high frequency of GA that could influence targeted therapy selection for the disease.