Han Lei,1 Zhengwei Zhou,1 Chang Liu,2 Weiting Chen,2 Yu Li,3 Guang Shu,1 Maonan Wang,1 Ke Guo,4 Qiong Pan,5 Gang Yin1,6,7 

1Department of Pathology, Xiangya Hospital, Xiangya School of Basic Medical Science, Central South University, Changsha, People’s Republic of China; 2Xiangya School of Basic Medical Science, Central South University, Changsha, People’s Republic of China; 3Intensive Care Unit for Children, Xiangtan Central Hospital, Xiangtan, People’s Republic of China; 4Department of Neurology, The Third Xiangya Hospital of Central South University, Changsha, People’s Republic of China; 5Department of Obstetrics and Gynecology, The Third Xiangya Hospital of Central South University, Changsha, People’s Republic of China; 6China-Africa Research Center of Infectious Diseases, Xiangya School of Basic Medical Science, Central South University, Changsha, People’s Republic of China; 7National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, People’s Republic of China

Correspondence: Qiong Pan, Email 1517682924@qq.com Gang Yin, Email gangyin@csu.edu.cn

Background: Cuproptosis, a novel form of cell death triggered by copper ion accumulation, has shown potential in cancer therapy, particularly through the involvement of cuproptosis-related lnRNAs (CRLs). In-depth analyses exploring the relationship between CRLs and ovarian cancer (OC) are currently limited.
Methods: LASSO-Cox regression analysis was conducted to assess the prognostic significance of CRLs and develop a cuproptosis-related prognostic model. Furthermore, tumor immune microenvironment and drug sensitivity were analyzed using ssGSEA, GSVA, ESTIMATE, and CIBERSORT algorithms. Finally, the tumorigenic effect of LINC02285 in OC and its correlation with cuproptosis were investigated by in vitro cell experiments.
Results: We identified 138 CRLs correlated with cuproptosis-related genes (CRGs), 4 key CRLs (AC080038.1, AC083880.1, LINC00861, and LINC02285) were used to develop a prognostic model that effectively distinguished between low-risk and high-risk patients with significant differences in overall survival and progression-free survival. ROC curve analysis further validated the predictive capacity of the signature. Additionally, the low-risk group had a favorable prognosis associated with a protective immune microenvironment and a better response to targeted drugs. Conversely, the high-risk group displayed aggressive tumor features and poor immunotherapy outcomes. Validation through qPCR confirmed the differential expression of these CRLs in OC cells compared to normal ovarian cells, underscoring their potential significance in tumor biology. Bioinformatics analyses corroborated the association of LINC02285 with poor prognosis in OC patients. Functional experiment results showed that abnormal expression of LINC02285 could significantly regulate the proliferation and migration of OC cells. In addition, overexpression of LINC02285 markedly attenuated the inhibitory effects of Elesclomol-CuCl2 on OC cell activity.
Conclusion: Our study established a prognostic model based on 4 CRLs to assess overall survival and the immune microenvironment in OC patients. As a high-risk factor, LINC02285 demonstrates potential as a prognostic biomarker for OC.

Keywords: ovarian cancer, cuproptosis, linc02285, prognostic signature, tumor microenvironment