Thymidine kinase 1 as a target is regulated by the hsa-let-7b-5p/LINC00665 axis and affects NSCLC prognosis

Abstract

BackgroundIn the past, multiple studies have offered incremental evidence that indicates that competitive endogenous RNA (ceRNA) regulatory networks are involved in tumor growth and present novel therapeutic targets. Herein, we investigated the impact of thymidine kinase 1 (TK1)-related ceRNA networks on the prognosis of non-small cell lung cancer (NSCLC). MethodsTK1 expression data in NSCLC and normal tissue samples were retrieved from the Cancer Genome Atlas (TCGA) database and were then compared. Thereafter, the findings of the immunohistochemical staining experiments and clinical follow-up data derived from patients with NSCLC were used for conducting prognostic analysis. The starBase database was searched to determine TK1-targeted microRNAs and long non-coding RNAs, and clinical data from TCGA were used for survival analysis to construct a ceRNA network associated with TK1 expression and prognosis. Finally, the roles played by methylation and immunity in the prognosis and treatment of NSCLC were analyzed. ResultsOur findings revealed that the cancer tissues expressed significantly higher TK1 levels than normal tissues, and the follow-up clinical data revealed that the prognosis was generally worse in the high-expression patients than in the low-expression patients. In addition, clinical data collected from the starBase and TCGA databases showed that the LINC00665/has-let-7b-5p/TK1 network could influence the growth and prognosis of NSCLC. It was also noted that the TK1 methylation site was correlated with the prognosis of NSCLC, and immunoprognostic analysis further indicated that patients with higher TK1 expression levels displayed a worse prognosis. ConclusionWhen the regulatory network of LINC00665/has-let-7b-5p/TK1 was assessed, it was observed that elevated TK1 levels may affect the prognosis of NSCLC. Therefore, it could be considered a prognostic biomarker and a probable therapeutic target for predicting NSCLC prognosis.