Evidence map›Paper›PMID 42014663›Full record

ArticleDiscover oncology2026

A transcriptomic-based model associated with PARP inhibitor sensitivity and immunogenic signatures in ovarian cancer.

Xinxin Sun, Cancan Li, Zhihong Wang, Jie Geng, Wuliang Wang, Kehong Deng, Zhen Xu, Hu Zhao, Dongmei Huang

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Article in Discover oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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9 authors.

Xinxin SunDepartment of Obstetrics and Gynecology, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, 450014, Henan, China.
Cancan LiDepartment of Obstetrics and Gynecology, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, 450014, Henan, China.
Zhihong WangDepartment of Obstetrics and Gynecology, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, 450014, Henan, China.
Jie GengDepartment of Obstetrics and Gynecology, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, 450014, Henan, China.
Wuliang WangDepartment of Obstetrics and Gynecology, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, 450014, Henan, China.
Kehong DengDepartment of Obstetrics and Gynecology, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, 450014, Henan, China.
Zhen XuDepartment of Obstetrics and Gynecology, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, 450014, Henan, China.
Hu ZhaoDepartment of Obstetrics and Gynecology, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, 450014, Henan, China. huzhao202511@163.com.
Dongmei HuangDepartment of Obstetrics and Gynecology, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, 450014, Henan, China. dongmeihuang2025@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPoly (ADP-ribose) polymerase inhibitors (PARPi) have emerged as a major therapeutic advance in ovarian cancer, particularly for patients with BRCA mutations or homologous recombination deficiency (HRD). However, a significant subset of BRCA wild-type patients also benefit from PARPi therapy, suggesting alternative mechanisms of action, including immune modulation, may be involved. Currently, no robust transcriptomic predictor exists to stratify such patients.

methodsWe developed a transcriptomic predictive model, termed the PARPi-sensor, using RNA-seq data from a patient-derived xenograft (PDX) model treated with niraparib. PARPi-responsive genes (PRGs) were identified and intersected with ovarian cancer–specific differentially expressed genes (DEGs) from TCGA and GTEx. Non-negative matrix factorization (NMF) was applied to define PARPi-responsive patterns (PRPs). A 23-gene PARPi-associated transcriptomic signature was constructed through Cox and LASSO regression analyses.es and validated in TCGA and ICGC cohorts.

resultsThe PARPi-sensor model effectively stratified patients into high- and low-risk subgroups, with the low-risk group exhibiting significantly better overall survival in both cohorts. Functional enrichment revealed that low-risk patients showed upregulation of immune-related pathways, including antigen presentation and B/T cell activation. Immune subtype analysis, immune checkpoint gene expression, and deconvolution using TCIA data indicated that the low-risk group displayed enhanced immune activation and greater inferred responsiveness to immune checkpoint inhibitors. These findings suggest that PARPi may exert immunostimulatory effects, particularly in low-risk patients, independent of BRCA status.

conclusionWe developed and validated a clinically applicable transcriptomic model for identifying transcriptomic features associated with PARPi sensitivity in ovarian cancer. The PARPi-sensor model offers a potential strategy for expanding the use of PARPi to BRCA-wild-type patients and reveals immunological features that may guide combination therapies with immune checkpoint inhibitors. Future research should focus on experimental validation of the proposed mechanisms and prospective clinical application of the model.

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PMID42014663
PMCPMC13230468

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