This study utilized The Cancer Genome Atlas (TCGA) database to identify cuproptosis-related long non-coding RNAs (CRlncRNAs) in patients with kidney renal clear cell carcinoma (KIRC) which was further applied to construct risk signatures. All KIRC patients were divided into the training and the validation sets at a ratio of 7:3. Lasso regression analysis identified two prognosis-associated CRlncRNAs (LINC01204 and LINC01711), and prognostic risk signatures were constructed in both the training and the validation sets. Kaplan-Meier survival curves showed that patients with high-risk scores had significantly shorter overall survival (OS) than those with low-risk scores both in both the training and the validation sets. The area under the curve (AUC) of the prognostic nomogram generated based on age, grade, stage and risk signature to predict the 1-, 3- and 5-year OS were 0.84, 0.81 and 0.77, respectively, and the calibration curves also showed the high accuracy of the nomogram. In addition, we constructed the LINC01204/LINC01711-miRNA-mRNA ceRNA network graph. Finally, we experimentally investigated the function of LINC01711 by knocking down LINC01711 and revealed that knockdown of LINC01711 inhibited the proliferation, migration and invasion of KIRC cells. Hence, in this study, we developed a signature of prognostic risk-associated CRlncRNAs that could accurately predict the prognosis of KIRC patients and constructed a related ceRNA network to shed light on the mechanistic study of KIRC. LINC01711 might serve as a potential biomarker for the early diagnosis and prognosis of KIRC patients.
Keywords: Cuproptosis; LINC01204; LINC01711; LncRNAs; kidney renal clear cell carcinoma.
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