Back

KLF4 promotes apoptosis evasion and PARP inhibitor resistance in BRCA2-mutated epithelial ovarian cancer

Fera, E.; Zhang, T.; Grechukhina, V. M.; Zhu, Y.-L.; Ratner, E. S.; Lin, Z. P. P.

2026-08-24 cancer biology
10.64898/2026.08.23.746472 bioRxiv
Show abstract

BRCA2-mutated epithelial ovarian cancer (EOC) is deficient in homologous recombination (HR) repair and hypersensitive to PARP inhibitors. However, BRCA2-mutated EOC frequently develops PARP inhibitor resistance and the underlying mechanisms involving apoptosis evasion remain poorly understood. In this study, our bioinformatic analysis of clinical transcriptomic datasets revealed that increased expression of KLF4, a zinc finger transcription factor, was strongly associated with high-grade serous EOC subtype and reduced overall survival of patients. Using isogenic EOC cells, we demonstrated that BRCA2 mutation led to pronounced KLF4 up-regulation by PARP inhibition in an ATM-dependent manner. Silencing of KLF4 and its target gene NR4A1 enhanced olaparib-induced apoptosis. Inhibition of anti-apoptotic effectors using the BH3-mimetic navitoclax, but not the SMAC-mimetic birinapant, selectively sensitized BRCA2-mutated EOC cells to olaparib. Furthermore, KLF4 silencing abrogated olaparib-induced BCL-w and BCL-xL, while olaparib-induced cIAP2 was attenuated only by NR4A1 silencing in BRCA2-mutated EOC cells. In vivo, combined treatment of navitoclax and olaparib synergized to impede the progression of BRCA2-mutated EOC xenografts and prolong mouse survival time. Collectively, our investigations discovered KLF4 as a regulatory hub of DNA damage response and apoptosis evasion in BRCA2-mutated EOC. These findings support targeting KLF4-driven anti-apoptotic pathways as a rational strategy to overcome PARP inhibitor resistance.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.