Abstract：Abstract: To explore the prognostic value of cuproptosis-related genes in cervical cancer, the clinical data of cervical cancer patients were downloaded from the TCGA database and randomly divided into training group and validation group. Cuproptosis-related genes were screened out by univariate Cox, LASSO-Cox and multivariate Cox analysis, and the risk model was constructed. Overall survival (OS) of the two subgroups and the entire cohort was analyzed by Kaplan-Meier curve, and the prognostic value of the model was verified by ROC curve and PCA. Univariate and multivariate analyses were performed to evaluate the independent prognostic value of clinical features and risk scores. The biological functions and pathways between the two subgroups were analyzed by gene ontology (GO) and Kyoto encyclopedia enrichment of genes and genomes (KGEE), and the sensitivities of the two subgroups to drugs were further analyzed. Finally, prognostic models of five cuproptosis-related genes (FDX1, ARF1, APP, HSF1, MT1A) were constructed. From the survival curve of risk score, OS in the low-risk group was much higher than that in the high-risk group, and the prognosis was good (P<0.05). By univariate and multivariate Cox analysis, risk score an independent prognostic factor (P<0.001). The predictive power of the prognostic model was demonstrated by receiver operating characteristic curve (ROC) and principal component analysis (PCA). ROC curve analysis was used to assess the sensitivity and specificity of risk scores and other clinical features, such as age, grade, and stage. And the results showed that the prognostic value of risk scores was superior to other clinical features. The results of enrichment analysis showed that gene function was mainly concentrated in extracellular matrix and extracellular structure. According to TIDE algorithm, immunotherapy efficacy of patients in the low-risk group was superior to that in the high-risk group. In addition, significant differences were found in the sensitivity of 24 drugs between the two subgroups. The study established a prognostic risk model composed of 5 cuproptosis-related genes, and proved that the model can accurately predict the prognosis of patients. And patients with low risk score are more likely to benefit from immunotherapy, which provides theoretical basis for clinical individualized therapy.
Key words: cervical cancer; cuprotosis related genes; risk model; immunotherapy; prognosis
（Acta Laser Biology Sinica, 2023, 32(3): 259-271）
引用本文:
薛莘子，赵 悦，张 丹，徐丹颖，王 侠. 构建宫颈癌铜死亡相关基因的预后模型和预测免疫治疗反应[J]. 激光生物学报, 2023, 32(3): 258-274.
XUE Xinzi, ZHAO Yue, ZHANG Dan, XU Danying, WANG Xia. Construction of the Prognostic Model for Cuproptosis-related Genes Prediction of the Immunotherapy Response in Cervical Cancer. journal1, 2023, 32(3): 258-274.
