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Digital Immune-Related Gene Expression Signatures In High-Grade Serous Ovarian Carcinoma: Developing Prediction Models For Platinum Response

Authors Mairinger F, Bankfalvi A, Schmid KW, Mairinger E, Mach P, Walter RFH, Borchert S, Kasimir-Bauer S, Kimmig R, Buderath P

Received 18 June 2019

Accepted for publication 28 September 2019

Published 12 November 2019 Volume 2019:11 Pages 9571—9583


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Dr Eileen O'Reilly

Fabian Mairinger,1 Agnes Bankfalvi,1 Kurt Werner Schmid,1 Elena Mairinger,2 Pawel Mach,3 Robert FH Walter,2 Sabrina Borchert,1 Sabine Kasimir-Bauer,3 Rainer Kimmig,3 Paul Buderath3

1Institute for Pathology, University Hospital Essen, Essen, Germany; 2Ruhrlandklinik, West German Lung Centre, University Hospital Essen, University of Duisburg-Essen, Essen, Germany; 3Department of Gynecology and Obstetrics, University Hospital Essen, Essen, Germany

Correspondence: Paul Buderath
Department of Gynecology and Obstetrics, University Hospital Essen, Hufelandstraße 55, Essen 45122, Germany
Tel +49 201 723 2442

Purpose: Response to platinum-based therapy is a major prognostic factor in high-grade serous ovarian cancer (HGSOC). While the exact mechanisms of platinum-resistance remain unclear, evidence is accumulating for a connection between the organism’s immune-response and response to platinum. However, predictive tools are missing. This study was performed to examine the putative role of the genetic tumor immune-microenvironment in mediating differential chemotherapy response in HGSOC patients.
Patients and methods: Expression profiling of 770 immune-related genes was performed in tumor tissues from 23 HGSOC cases. Tumors were screened for prognostic and predictive biomarkers using the NanoString nCounter platform for digital gene expression analysis with the appurtenant PanCancer Immune Profiling panel. As validation cohort, gene expression data (RNA Seq) of 303 patients with epithelial ovarian carcinoma (EOC) were retrieved from the The Cancer Genome Atlas (TCGA) database. Different scoring-systems were computed for prediction of risk-of-resistance to cisplatin, disease-free survival (DFS) and overall survival (OS).
Results: Validated on the TCGA-dataset, the developed scores identified 11 significantly differentially expressed genes (p <0.01**) associated with platinum response. HSD11B1 was highly significantly associated with lower risk of recurrence and 7 targets were found highly significantly influencing OS time (p <0.01**).
Conclusion: Our results suggest that response to platinum-based therapy and DFS in ovarian HGSOC is associated with distinct gene-expression patterns related to the tumor immune-system. We generated predictive scoring systems which proved valid when applied to a set of 303 EOC patients.

Keywords: ovarian cancer, tumor microenvironment, predictive biomarkers, platinum-resistance, HGSOC, gene expression signatures

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