Research Papers:

Impact of molecular profiling on overall survival of patients with advanced ovarian cancer

Thomas J. Herzog _, David Spetzler, Nick Xiao, Ken Burnett, Todd Maney, Andreas Voss, Sandeep Reddy, Robert Burger, Thomas Krivak, Matthew Powell, Michael Friedlander and William McGuire

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Oncotarget. 2016; 7:19840-19849. https://doi.org/10.18632/oncotarget.7835

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Thomas J. Herzog1,*, David Spetzler2, Nick Xiao2, Ken Burnett2, Todd Maney2, Andreas Voss2, Sandeep Reddy2, Robert Burger3, Thomas Krivak4, Matthew Powell5, Michael Friedlander6, William McGuire7

1 University of Cincinnati Cancer Institute, Cincinnati, OH, USA

2 Caris Life Sciences, Phoenix, AZ, USA

3 University of Pennsylvania, Philadelphia, PA, USA

4 Western Pennsylvania Gynecological Oncology, Mars, PA, USA

5 Washington University School of Medicine, St. Louis, MO, USA

6 Prince of Wales Hospital, Sydney, Australia

7 VCU Massey Cancer Center, Richmond, VA, USA

Correspondence to:

Thomas J. Herzog, email:

Keywords: ovarian, cancer, molecular, profiling, survival

Received: January 08, 2016 Accepted: February 18, 2016 Published: March 01, 2016


Objective: Patients with recurrent epithelial ovarian cancer (EOC) have limited treatment options. Studies have reported that biomarker profiling may help predict patient response to available treatments. This study sought to determine the value of biomarker profiling in recurrent EOC.

Results: Patients in the Matched cohort had a median OS of 36 months compared to 27 months for patients in the Unmatched cohort (HR 0.62, 95% CI 0.41-0.96; p < 0.03). Individual biomarkers were analyzed, with TUBB3, and PGP prognostic for survival. Biomarker analysis also identified a molecular subtype (positive for at least two of the following markers: ERCC1, RRM1, TUBB3, PGP) with particularly poor overall survival.

Methods: 224 patients from a commercial registry (NCT02678754) with stage IIIC/IV EOC at diagnosis, or restaged to IIIC/IV EOC at the time of molecular profiling, were retrospectively divided into two cohorts based on whether or not the drugs they received matched their profile recommendations. The Matched cohort received no drugs predicted to be lack-of-benefit while the Unmatched cohort received at least one drug predicted to be lack-of-benefit. Profile biomarker/drug associations were based on multiple test platforms including immunohistochemistry, fluorescent in situ hybridization and DNA sequencing.

Conclusions: This report demonstrates the ability of multi-platform molecular profiling to identify EOC patients at risk of inferior survival. It also suggests a potential beneficial role of avoidance of lack-of-benefit therapies which, when administered, resulted in decreased survival relative to patients who received only therapies predicted to be of benefit.

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