Molecular stratification of clear cell ovarian carcinomas

Background and aims Advanced-stage CCOC has an exceptionally poor outcome and exhibits insensitivity to chemotherapy. With a lack of informative, quantitative prognostic and phenotypic markers defined, CCOC is poorly positioned to make use of emerging targeted therapies and the rise in personalized medicine. We aim to stratify biological subtypes of CCOC based on recurrent somatic alterations and prognostic biomarkers, ultimately developing a clinically relevant molecular classifier that will allow for patient-centered treatment decisions and outcome predictions, based on quantitative molecular patterns.

Materials A total of 215 formalin-fixed paraffin-embedded tissue blocks with cases from Tübingen (n = 46), Vancouver, Canada (n = 126), Munich (n = 18), Vienna, Austria (n = 18), and Friedrichshafen (n = 7) was assembled.

Methods Immunohistochemical (IHC) biomarker markers including NapsinA, WT1, HNF1B, p53, ARID1A, PMS2, MSH6, p16, IGFBP3, PTEN, CCNE1, PR, and CD8 were assessed in tissue microarray format. Hotspot cancer gene mutations, in genes previously reported to be altered in clear cell or related endometriosis-associated malignancies, were tested using a modified tailed-amplicon sequencing strategy. We tested for hotspot alterations in PIK3CA, PIK3R1, KRAS, POLE, CTNNB1, and TERT.

Results and Summary Our dataset will enable to validation of somatic mutation frequencies in recurrent driver genes previously reported to be altered in endometriosis associated malignancies. We will further asses both mutations and IHC biomarkers alone and in combination for potential prognostication and phenotypic characterization of subtypes within CCOC. For this relatively rare histotype of ovarian carcinoma our unique dataset provides a valuable resource on which to test the value of prognostic and biologically important biomarkers.

Publication History

Article published online:
07 October 2020