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CLINICAL RESEARCH
Prognostic index of immune-related lncRNAs for immunotherapy responsiveness and chemotherapy sensitivity in ovarian cancer patients
1
Department of Gynecology, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China
2
School of Medicine, Tongji University, Shanghai, China
3
Department of Gynecology, Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, School of Life Science and Technology, Tongji University, Shanghai, China
Submission date: 2025-08-22
Final revision date: 2025-11-18
Acceptance date: 2025-11-19
Online publication date: 2026-01-15
Corresponding author
Chen Zhang
School of Medicine Tongji University No. 1239, Siping Road Yangpu District Shanghai 200092, China
School of Medicine Tongji University No. 1239, Siping Road Yangpu District Shanghai 200092, China
Lingfei Han
Department of Gynecology Shanghai Tenth People’s Hospital Tongji University School of Medicine No. 301, Yanchang Middle Road Shanghai 200000, China Department of Gynecology Shanghai Key Laboratory of Maternal Fetal Medicine Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology Shanghai First Maternity and Infant Hospital School of Medicine School of Life Science and Technology Tongji University No. 2699, Gaoke West Road Pudong New Area Shanghai 200092, China
Department of Gynecology Shanghai Tenth People’s Hospital Tongji University School of Medicine No. 301, Yanchang Middle Road Shanghai 200000, China Department of Gynecology Shanghai Key Laboratory of Maternal Fetal Medicine Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology Shanghai First Maternity and Infant Hospital School of Medicine School of Life Science and Technology Tongji University No. 2699, Gaoke West Road Pudong New Area Shanghai 200092, China
KEYWORDS
TOPICS
ABSTRACT
Introduction:
Ovarian cancer (OV), ranking among the most lethal gynecologic malignancies, is characterized by elevated mortality rates primarily attributable to immature diagnostic tools and the insensitivity of chemotherapy. Despite the impressive success of immune checkpoint inhibitor (ICI) therapy in the treatment of several solid tumors, OV patients only partially benefit from immune checkpoint blockade. Therefore, a biomarker is necessary to predict the responsiveness of OV patients to immunotherapy. This study sought to identify an immune-associated lncRNA-based prognostic signature to predict immunotherapy efficacy and chemosensitivity in OV patients.
Material and methods:
We used ovarian cancer transcriptional profiles of patients from TCGA and GTEx databases with immune-related signature genes to screen immune-related lncRNAs. Furthermore, we integrated the GEO database to evaluate an immune-related lncRNA prognostic score (IRLRPI), and then verified the model in all aspects to distinguish biomarkers of IRLRPI subtypes.
Results:
Our findings demonstrated that patients with elevated IRLRPI scores had a poorer prognosis and tended to be more immunosuppressed; in terms of treatment, these patients may exhibit resistance to immunotherapy and be less sensitive to several chemotherapeutic agents. Finally, the biomarkers KIF26B and VSTM2L were found to distinguish IRLRPI type.
Conclusions:
The IRLRPI model we developed can predict immunotherapy responsiveness and chemotherapy sensitivity in ovarian cancer patients and demonstrates potential for clinical application.
Ovarian cancer (OV), ranking among the most lethal gynecologic malignancies, is characterized by elevated mortality rates primarily attributable to immature diagnostic tools and the insensitivity of chemotherapy. Despite the impressive success of immune checkpoint inhibitor (ICI) therapy in the treatment of several solid tumors, OV patients only partially benefit from immune checkpoint blockade. Therefore, a biomarker is necessary to predict the responsiveness of OV patients to immunotherapy. This study sought to identify an immune-associated lncRNA-based prognostic signature to predict immunotherapy efficacy and chemosensitivity in OV patients.
Material and methods:
We used ovarian cancer transcriptional profiles of patients from TCGA and GTEx databases with immune-related signature genes to screen immune-related lncRNAs. Furthermore, we integrated the GEO database to evaluate an immune-related lncRNA prognostic score (IRLRPI), and then verified the model in all aspects to distinguish biomarkers of IRLRPI subtypes.
Results:
Our findings demonstrated that patients with elevated IRLRPI scores had a poorer prognosis and tended to be more immunosuppressed; in terms of treatment, these patients may exhibit resistance to immunotherapy and be less sensitive to several chemotherapeutic agents. Finally, the biomarkers KIF26B and VSTM2L were found to distinguish IRLRPI type.
Conclusions:
The IRLRPI model we developed can predict immunotherapy responsiveness and chemotherapy sensitivity in ovarian cancer patients and demonstrates potential for clinical application.
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| eISSN: | 1896-9151 |
| ISSN: | 1734-1922 |
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