Molecular Analysis of Short- versus Long-Term Survivors of High-Grade Serous Ovarian Carcinoma

Elaine Stur; Emine Bayraktar; Graziela Zibetti Dal Molin; Sherry Y Wu; Lingegowda S Mangala; Hui Yao; Ying Wang; Prahlad T Ram; Sara Corvigno; Hu Chen; Han Liang; Shelley S Tworoger; Douglas A Levine; Susan K Lutgendorf; Jinsong Liu; Kathleen N Moore; Keith A Baggerly; Beth Y Karlan; Anil K Sood

doi:10.3390/cancers14174198

Molecular Analysis of Short- versus Long-Term Survivors of High-Grade Serous Ovarian Carcinoma

Cancers (Basel). 2022 Aug 30;14(17):4198. doi: 10.3390/cancers14174198.

Authors

Elaine Stur¹, Emine Bayraktar¹, Graziela Zibetti Dal Molin², Sherry Y Wu³, Lingegowda S Mangala¹, Hui Yao⁴, Ying Wang⁴, Prahlad T Ram⁵, Sara Corvigno¹, Hu Chen⁴, Han Liang⁴, Shelley S Tworoger⁶, Douglas A Levine⁷, Susan K Lutgendorf⁸, Jinsong Liu⁹, Kathleen N Moore¹⁰, Keith A Baggerly⁴, Beth Y Karlan¹¹, Anil K Sood¹

Affiliations

¹ Department of Gynecologic Oncology & Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
² Medical Oncology Department, Beneficencia Portuguesa de Sao Paulo, Sao Paulo 13900-400, Brazil.
³ School of Biomedical Sciences, The University of Queensland, St. Lucia, QLD 4072, Australia.
⁴ Department of Bioinformatics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
⁵ Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
⁶ Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL 33612, USA.
⁷ Division of Gynecologic Oncology, New York University, New York, NY 11580, USA.
⁸ Department of Psychological & Brain Sciences, The University of Iowa, Iowa City, IA 52242, USA.
⁹ Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
¹⁰ Department of Gynecologic Oncology, The University of Oklahoma, Oklahoma City, OK 73117, USA.
¹¹ Department of Obstetrics and Gynecology, University of California, Los Angeles, CA 90095, USA.

Abstract

Despite having similar histologic features, patients with high-grade serous ovarian carcinoma (HGSC) often experience highly variable outcomes. The underlying determinants for long-term survival (LTS, ≥10 years) versus short-term survival (STS, <3 years) are largely unknown. The present study sought to identify molecular predictors of LTS for women with HGSC. A cohort of 24 frozen HGSC samples was collected (12 LTS and 12 STS) and analyzed at DNA, RNA, and protein levels. OVCAR5 and OVCAR8 cell lines were used for in vitro validation studies. For in vivo studies, we injected OVCAR8 cells into the peritoneal cavity of female athymic nude mice. From RNAseq analysis, 11 genes were found to be differentially expressed between the STS and LTS groups (fold change > 2; false discovery rate < 0.01). In the subsequent validation cohort, transmembrane protein 62 (TMEM62) was found to be related to LTS. CIBERSORT analysis showed that T cells (follicular helper) were found at higher levels in tumors from LTS than STS groups. In vitro data using OVCAR5 and OVCAR8 cells showed decreased proliferation with TMEM62 overexpression and positive correlation with a longevity-regulating pathway (KEGG HSA04213) at the RNA level. In vivo analysis using the OVCAR8-TMEM62-TetON model showed decreased tumor burden in mice with high- vs. low-expressing TMEM62 tumors. Our results demonstrate that restoring TMEM62 may be a novel approach for treatment of HGSC. These findings may have implications for biomarker and intervention strategies to help improve patient outcomes

Keywords: HGSC; TMEM62; long-term survival; ovarian cancer; short-term survival.

Grants and funding

Funding for this research was provided by the U.S. Department of Defense (DoD) and grants R35 CA209904 and U01 CA213759; by the American Cancer Society; and by the Frank McGraw Memorial Chair in Cancer Research). E.S. is supported by Ovarian Cancer Research Alliance (OCRA number FP00006137). S.Y.W. was supported by Ovarian Cancer Research Fund Alliance, Foundation for Women’s Cancer, Texas Center for Cancer Nanomedicine, and Cancer Prevention Research Institute of Texas training grants (RP101502 and RP101489). H.C. was supported by a Computational Cancer Biology Training Program fellowship on CPRIT RP170593. Part of this research was performed in the Flow Cytometry & Cellular Imaging Core Facility (supported in part by the National Institutes of Health through MD Anderson’s Cancer Center Support Grant CA016672, the NCI’s Research Specialist 1 R50 CA243707-01A1).