A novel immune-related radioresistant lncRNAs signature based model for risk stratification and prognosis prediction in esophageal squamous cell carcinoma - Zheng, Jianqing; Chen, Xiaohui; Huang, Bifen; Li, Jiancheng (Frontiers in Genetics, 2022)
Background and purpose: Radioresistance is a major reason underlying radiotherapeutic failure in esophageal squamous cell carcinoma (ESCC). An insight on the mechanism of radioresistance would help boost its prognosis. The purpose of this study was to screen the immune-related long non-coding RNA (ir-lncRNAs) of radiation-resistant ESCC (rr-ESCC) based on the Gene Expression Omnibus (GEO) database, and to construct a prognostic risk model for it. Methods: The microarray data (GSE45670) related to radioresistance of ESCC was downloaded from GEO. According to the pathological response of the tumor after radiotherapy and chemotherapy, the patients were divided into a non-responding group (17 samples) and a responding group (11 samples), and the difference in expression profiles of ir-lncRNAs were compared within groups. Ir-lncRNA pairs were constructed for the differentially expressed lncRNAs as prognostic variables, and the microarray dataset (GSE53625) was downloaded from GEO to verify the effect of ir-lncRNA pairs on the long-term survival of ESCC. After modelling, patients are divided into high-risk and low-risk groups according to prognostic risk scores, and the survival outcomes were compared between the two groups based on the COX proportional hazards model. Results: 26 ir-lncRNA genes were screened in the GSE45670 dataset with differential expression, and 180 ir-lncRNA pairs were constructed. After matching with ir-lncRNA pairs constructed by GSE53625, 6 ir-lncRNA pairs had a significant impact on the prognosis of ESCC from univariate analysis model, of which 3 ir-lncRNA pairs were significantly associated with prognosis in multivariate COX analysis. The 3 lncRNA pairs were used as prognostic indicators to construct a prognostic risk model, and the predicted risk scores were calculated. With a median value of 2.371, the patients were divided into 2 groups. The overall survival (OS) in the high-risk group was significantly worse than that in the low-risk group (P<0.001). The 1-, 2-, and 3-year prediction performance of this risk-model was 0.666, 0.702, and 0.686, respectively. Conclusions: Ir-lncRNAs may be involved in the biological regulation of radioresistance in patients with ESCC; and the prognostic risk-model, established by 3 ir-lncRNAs pairs has important clinical value in predicting the prognosis of patients with rr-ESCC.