Chen Bingxin, Yuan Shuo, Wang Hui
Department of Gynecologic Oncology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310006, P.R. China.
Zhejiang Provincial Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310006, P.R. China.
Oncol Lett. 2025 Apr 16;29(6):302. doi: 10.3892/ol.2025.15048. eCollection 2025 Jun.
Ovarian cancer (OV) constitutes a significant hazard to the health of women and has low survival and high recurrence rates. Cuproptosis is a newly reported form of copper-dependent regulatory cell death. The present study identified cuproptosis-related long non-coding (lnc)RNAs in OV, highlighting their potential application as prognostic biomarkers and therapeutic targets. The RNA-sequencing data and clinical records of patients with OV were sourced from The Cancer Genome Atlas. Cuproptosis-related lncRNAs were filtered for their prognostic value using univariate and multivariate Cox regression, and least absolute shrinkage selection operator regression. Then, a risk model was formulated using these cuproptosis-related lncRNAs based on correlation coefficients. The risk model was calculated using the following formula: Risk = (0.687927022 × RP11-552D4.1) - (0.659783022 × AP001372.2) - (0.652465319 × RP11-505K9.1) - (1.627006889 × LINC00996). The predictive potential and clinical values of this risk model were identified through survival status, Kaplan-Meier survival curves, immune function, receiver operating characteristic curves, calibration curves, C-index and principal component analysis. Subsequently, the effects of LINC00996 (the lncRNA with the highest correlation coefficient in the risk model) on proliferation, metastasis and sensitivity to cuproptosis were assessed in OV cells. Finally, intracellular location of LINC00996 and the relative regulatory mechanism were predicted. In conclusion, the present study constructed a prognostic risk model based on lncRNAs associated with cuproptosis in OV, which can stratify risk and predict prognosis, and explored the regulatory mechanism of LINC00996 in cuproptosis.
卵巢癌（OV）对女性健康构成重大危害，生存率低且复发率高。铜死亡是一种新报道的铜依赖性调节性细胞死亡形式。本研究在OV中鉴定了与铜死亡相关的长链非编码（lnc）RNA，突出了它们作为预后生物标志物和治疗靶点的潜在应用。OV患者的RNA测序数据和临床记录来自癌症基因组图谱。使用单变量和多变量Cox回归以及最小绝对收缩选择算子回归，筛选与铜死亡相关的lncRNA的预后价值。然后，基于相关系数，使用这些与铜死亡相关的lncRNA建立风险模型。风险模型使用以下公式计算：风险 =（0.687927022×RP11 - 552D4.1） - （0.659783022×AP001372.2） - （0.652465319×RP11 - 505K9.1） - （1.627006889×LINC00996）。通过生存状态、Kaplan - Meier生存曲线、免疫功能、受试者工作特征曲线、校准曲线、C指数和主成分分析，确定了该风险模型的预测潜力和临床价值。随后，在OV细胞中评估了LINC00996（风险模型中相关系数最高的lncRNA）对增殖、转移和对铜死亡敏感性的影响。最后，预测了LINC00996的细胞内定位和相关调控机制。总之，本研究构建了基于OV中与铜死亡相关lncRNA的预后风险模型，该模型可对风险进行分层并预测预后，并探索了LINC00996在铜死亡中的调控机制。
