Definition and Independent Validation of a Proteomic-Classifier in Ovarian Cancer

• Main Authors: Sabine Kasimir-Bauer, Joanna Roder, Eva Obermayr, Sven Mahner, Ignace Vergote, Liselore Loverix, Elena Braicu, Jalid Sehouli, Nicole Concin, Rainer Kimmig, Lelia Net, Heinrich Roder, Robert Zeillinger, Stefanie Aust, on behalf of the OVCAD (Ovarian Cancer Diagnosis initiative)
• Format: Article
• Language: English
• Published: MDPI AG 2020-09-01
• Series: Cancers
• Subjects: ovarian cancer; proteomics; mass spectrometry; survival
• Online Access: https://www.mdpi.com/2072-6694/12/9/2519

Mass-spectrometry-based analyses have identified a variety of candidate protein biomarkers that might be crucial for epithelial ovarian cancer (EOC) development and therapy response. Comprehensive validation studies of the biological and clinical implications of proteomics are needed to advance them toward clinical use. Using the Deep MALDI method of mass spectrometry, we developed and independently validated (development cohort: <i>n</i> = 199, validation cohort: <i>n</i> = 135) a blood-based proteomic classifier, stratifying EOC patients into good and poor survival groups. We also determined an age dependency of the prognostic performance of this classifier, and our protein set enrichment analysis showed that the good and poor proteomic phenotypes were associated with, respectively, lower and higher levels of complement activation, inflammatory response, and acute phase reactants. This work highlights that, just like molecular markers of the tumor itself, the systemic condition of a patient (partly reflected in proteomic patterns) also influences survival and therapy response in a subset of ovarian cancer patients and could therefore be integrated into future processes of therapy planning.