Hou, Xiaonan

Abstract Introduction: Despite treatment advances, ovarian cancer (OC) remains the deadliest gynecological cancer, with a ∼70% mortality rate. OCs initially respond to platinum chemotherapy but often develop resistance. While PARP inhibitors improve relapse-free survival in responsive cases, they do not extend overall survival. This underscores the need for effective combination therapies beyond BRCA status. The lysosomal protein cathepsin L (CTSL) can traffic to the nucleus, where it can regulate DNA repair and serve as a chromatin modifier. We found that nucleoside analog clofarabine (CLF) induces CTSL nuclear trafficking in OC cells. Here we tested the hypothesis that accumulation nuclear CTSL (nCTSL) is a biomarker of sensitivity to DNA damaging therapy in OCs for improved therapeutic options. Methods: To determine the role of CLF induced nuclear CTSL in DNA damage and its synergy with PARP and CRM1 inhibitors in PARP inhibitor–sensitive and –resistant ovarian cancer (OC) cell lines, ex vivo cultures of ascites-derived patient OC cells (OVA-3D spheroids), primary ovarian tumors, and patient-derived xenograft (PDX) models and validated by colony formation assays. Nuclear CTSL localization was determined in subcellular fractionated lysates by western blots and immunofluorescence cytometry (IFC). Tumor regression was determined in vivo using ex vivo cultures of PDX derived cells. Results: In ovarian cancer (OC) cell lines, CLF monotherapy induced nuclear CTSL (nCTSL) in a subset of models classified as CLF-responsive (CLF-r), sensitizing them to the PARP inhibitors olaparib and rucaparib. In CLF-non-responsive (CLF-nr) models, nCTSL induction and therapeutic synergy were observed only with the CLF+olaparib combination. Synergy was detected in 47% of CLF-r and 24% of CLF-nr patient-derived ascites samples (OVA). Mechanistically, CLF induced nuclear import of CTSL via KPNB1 in CLF-r cells, while this import was triggered by the CLF+olaparib combination in CLF-nr cells. CLF also downregulated the nuclear export protein CRM1 (XPO1) in both groups. Knockdown of CTSL in either CLF-r or CLF-nr cells abrogated sensitivity to the combination. Notably, in 29% of OVA samples classified as CLF-resistant (CLF-Res), CLF failed to suppress CRM1 expression. In these cases, CRM1 inhibition with KPT8602 restored CLF+PARP inhibitor synergy. In vivo, CLF-r and CLF-nr PDX models treated with the combination exhibited increased DNA damage, reduced tumor burden, and extended survival. Conclusion: These findings identify nuclear CTSL (nCTSL) induction as a potential biomarker of response to DNA-damaging therapies. The combination of CLF and olaparib represents a promising strategy to overcome drug resistance in ovarian cancer by promoting CTSL nuclear localization and enhancing DNA damage. Citation Format: Prabhu Thirusangu, Ling Jin, Upasana Ray, Anya Zhao, Julie Staub, Xinyan Wu, Xiaonan Hou, Jamison L. VanBlaricom, Syed Mohamed Musheer Aalam, Sun-Hee Lee, Ann Oberg, Nagarajan Kannan, John Weroha, Jeremy Chien, Scott H. Kaufmann, Jamie N. Bakkum-Gamez, Viji Shridhar. Role of drug induced nuclear CTSL (nCTSL) in DNA damage response in cancer- therapeutic implications [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Ovarian Cancer Research; 2025 Sep 19-21; Denver, CO. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl):Abstract nr A050.

Abstract Background: Epithelial ovarian cancer (EOC), commonly known as ovarian cancer (OvCa), is the deadliest gynecological malignancy. High tumor expression of either NR3C1 mRNA (encoding the glucocorticoid receptor or GR) or GR protein (IHC) are associated with poor overall survival (OS) in patients (pts) with advanced stage OvCa. We hypothesized that high GR expression and associated GR transcriptional activity favor OvCa cell survival and chemotherapy resistance, thereby reducing OS. Here we investigated whether a GR transcriptome-based gene signature (GR-sig) would be a better prognosticator than tumor NR3C1 mRNA expression alone. Methods: mRNAs up- or downregulated >1.5 fold after glucocorticoid treatment (Dex) in one or both cultured OvCa cell lines (OVSAHO and HEYA8) were defined as differentially expressed genes (DEGs). DEGs were then identified in n=1247 unique OvCa microarrays from 15 publicly available Gene Expression Omnibus (GEO) datasets with matched pt OS (training set). We then used the OS data to train a Cox proportional hazards model. The “best subset selection” (BeSS) algorithm and bootstrap sampling identified those GR-regulated DEGs whose tumor mRNA expression correlated most significantly with pt OS, creating a GR-sig “risk score.” Subsequently, all n=522 microarray and n=374 RNA-seq publicly available samples from the OvCa TCGA were used as two independent validation sets. Microarray and RNA-seq data were normalized using the MAS5 and FPKM-UQ algorithms respectively. The two validation sets were independently stratified relative to the median training set risk score into low- and high-risk score groups. To examine the prognostic ability of NR3C1 mRNA expression alone, the median training set NR3C1 expression value was used to stratify validation set pts into low- and high-expression groups. In all cases, OS was estimated by the Kaplan-Meier method. Results: We identified n=2288 protein-coding DEGs in one or both cell lines. Of these genes, n=1251 were expressed in each GEO microarray sample (training set). A 10-gene GR-signature (GR-Sig) was then identified using the BeSS algorithm and bootstrap sampling, yielding a median training set risk score of 1.02. In both the microarray and RNA-seq validation datasets, the 10-gene GR-sig risk score was associated with significant OS differences between low- and high-risk score groups (microarray p = 0.018; RNA-seq p = 0.00049). In contrast, the OS difference between low- and high- NR3C1 mRNA expression groups did not reach significance (microarray p = 0.12; RNA-seq p = 0.28). Conclusion: In this retrospective analysis, a 10-gene GR-sig derived from OvCa GR-regulated DEGs performed better as a prognosticator than NR3C1 mRNA expression alone. Prospective application of the GR-sig may be useful in stratifying patients for treatment response with novel agents in OvCa clinical trials. Citation Format: Ananth V. Panchamukhi, Lei Huang, Eleanore P. Gray, Yuanhang Liu, Manisha Taya, Jennifer T. Veneris, Xiaonan Hou, S John Weroha, Balázs Győrffy, Gini F. Fleming, Chen Wang, Suzanne D. Conzen. Development of a prognostic ovarian cancer gene signature based on glucocorticoid receptor transcriptional activity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4739.