Identification of a cuproptosis‑related prognostic biomarker and therapeutic target in ovarian cancer.

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.