Applying Precision Medicine to Ovarian Cancer: Proof-of-Principle for a "Molecular Second Look".

Schwartz M, Camacho-Vanegas O, Wood AM, Dashkoff M, Whitelock C, Harkins TT, Cohen CJ, Beddoe AM, Dottino P, Martignetti JA.

Abstract

OBJECTIVES:

The objectives of this study were to assess if targeted investigation for tumor-specific mutations by ultradeep DNA sequencing of peritoneal washes of ovarian cancer patients after primary surgical debulking and chemotherapy, and clinically diagnosed as disease free, provides a more sensitive and specific method to assess actual treatment response and tailor future therapy and to compare this "molecular second look" with conventional cytology and histopathology-based findings.

METHODS/MATERIALS:

We identified 10 patients with advanced-stage, high-grade serous ovarian cancer who had undergone second-look laparoscopy and for whom DNA could be isolated from biobanked paired blood, primary and recurrent tumor, and second-look peritoneal washes. A targeted 56 gene cancer-relevant panel was used for next-generation sequencing (average coverage, >6500×). Mutations were validated using either digital droplet polymerase chain reaction (ddPCR) or Sanger sequencing.

RESULTS:

A total of 25 tumor-specific mutations were identified (median, 2/patient; range, 1-8). TP53 mutations were identified in at least 1 sample from all patients. All 5 pathology-based second-look positive patients were confirmed positive by molecular second look. Genetic analysis revealed that 3 of the 5 pathology-based negative second looks were actually positive. In the 2 patients, the second-look mutations were present in either the original primary or recurrent tumors. In the third, 2 high-frequency, novel frameshift mutations in MSH6 and HNF1A were identified.

CONCLUSIONS:

The molecular second look detects tumor-specific evidence of residual disease and provides genetic insight into tumor evolution and future recurrences beyond standard pathology. In the precision medicine era, detecting and genetically characterizing residual disease after standard treatment will be invaluable for improving patient outcomes.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.