M7G-Related lncRNAs predict prognosis and regulate the immune microenvironment in lung squamous cell carcinoma

M7G相关lncRNA可预测肺鳞状细胞癌的预后并调控其免疫微环境

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Abstract

BACKGROUND: N7-Methylguanosine (m7G) and long non-coding RNAs (lncRNAs) have been widely studied in cancer and have been found to be useful for assessing tumor progression. However, the role of m7G-related lncRNAs in lung squamous cell carcinoma (LUSC) remains unclear. Thus, it is crucial to identify m7G-associated lncRNAs with definitive prognostic value. This study aimed to investigate the prognostic value, correlation with tumor mutation burden, and impact on the tumor immune microenvironment of m7G-related lncRNAs in LUSC.  METHODS: LUSC transcriptome data and clinical data were downloaded from The Cancer Genome Atlas, and an m7G-related lncRNA-mRNA co-expression network was constructed using Pearson's correlation analysis. Cox regression analyses were used to determine a risk model for m7G-associated lncRNAs with prognostic value. The risk signature was verified using the Kaplan-Meier method, receiver operating characteristic curve analysis, and principal component analysis. A nomogram based on risk scores and clinical characteristics was then developed. Gene set enrichment analysis was used for functional annotation to analyze the risk signature. The association among the risk signature, tumor mutational burden, and tumor-infiltrating immune cells was then analyzed. RT-qPCR was used to investigate the expression of 6 m7G-related lncRNAs in LUSC cells. The cytological function of SRP14-AS1 was verified by wound-healing assay and transwell assay. RESULTS: A total of 293 m7G-related lncRNAs were identifed, 27 candidate m7G-related lncRNAs were signifcantly associated with overall survival (OS). Six of these lncRNAs (CYP4F26P, LINC02178, MIR22HG, SRP14-AS1, TMEM99, PTCSC2) were selected for establishment of the risk model. The OS of patients in the low-risk group was higher than that of patients in the high-risk group (p < 0.001). Multivariate cox regression analysis indicated that the model could be an independent prognostic factor for LUSC (HR = 1.859; 95% CI 1.452-2.380, p < 0.001). The ROC curve analysis revealed that the AUCs for OS in the 3-, and 5-year were 0.682, 0.657, respectively. GSEA analysis revealed that the risk model was closely related to immune-related pathways. Compared with normal lung epithelial cells, four m7G-related lncRNAs were higher expressed in cancer cells and two were lower expressed, among which knockdown of SRP14-AS1 promoted the proliferation and migration of LUSC cells. CONCLUSION: A risk model based on six m7G-related lncRNAs with prognostic value may be a promising prognostic tool in LUSC and guide individualized patient treatment.

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