Identification of novel lactate metabolism-related lncRNAs with prognostic value for bladder cancer - Wang, Xiushen; Pan, Jing; Guan, Qiutong; Ren, Ninghui; Wang, Ping; Wei, Minjie; Li, Zhenhua (Frontiers in Pharmacology, 2023)
Background: Bladder cancer (BCA) has high recurrence and metastasis rates, and current treatment options show limited efficacy and significant adverse effects. It is crucial to find diagnostic markers and therapeutic targets with clinical value. This study aimed to identify lactate metabolism-related lncRNAs (LM_lncRNAs) to establish a model for evaluating BCA prognosis.Method: A risk model consisting of LM_lncRNAs was developed to forecast BCA patient prognosis using The Cancer Genome Atlas (TCGA) database. Kaplan-Meier survival analysis, receiver operating characteristic curve (ROC) analysis and decision curve analysis (DCA) were used to evaluate the reliability of risk grouping for predictive analysis of BCA patients. The results were also validated in the validation set. Chemotherapeutic agents sensitive to lactate metabolism were assessed using the Genomics of Drug Sensitivity in Cancer (GDSC) database.Results: As an independent prognostic factor for patients, LM_lncRNAs can be used as a nomogram chart that predicts survival time. There were significant differences in survival rates between the high-risk and low-risk groups based on the Kaplan-Meier survival curve. DCA and ROC analysis confirmed its good predictive capacity. As a result, 22 chemotherapeutic agents were predicted to positively affect the high-risk group.An LM_lncRNA prediction model was proposed to predict the prognosis for patients with BCA and chemotherapeutic drug sensitivity in high-risk groups, which provided a new idea for the prognostic evaluation of the clinical treatment of BCA.