A novel defined m7G regulator signature to investigate the association between molecular characterization and clinical significance in lung adenocarcinoma

BACKGROUND: About170 chemical modifications to RNAs have been identified, which significantly affect gene expression. Dysregulation of RNA modifications induced by abnormal expression or mutations in RNA modifiers might result in cancer. The most frequent RNA modifications are N6-methyladenosine (m6A), 5-methylcytosine (m5C), and N7-methylguanosine (m7G). Lung cancer is the leading cause of cancer-related deaths globally. The present study aimed to investigate whether the expression of the m7G-related genes is linked to lung cancer cases with lung adenocarcinoma (LUAD), which accounts for about 40% of lung cancer cases. METHODS: A total of 12 m7G-related differentially expressed genes (DEGs) were identified in LUAD patients by The Cancer Genome Atlas (TCGA). The least absolute shrinkage and selection operator (LASSO) Cox regression method was used to build a four-gene risk model. Then, LUAD patients in the TCGA cohort were divided into low- and high-risk groups based on their risk scores for subsequent molecular and clinical research. RESULTS: Compared to the low-risk group, the high-risk group had a decreased overall survival (OS) (P=0.047). The risk score and stage were independent factors for predicting the OS of LUAD (P=0.0004 and P<0.0001, respectively). Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses based on the two groups showed that the DEGs were metabolically and hormonally related. The high-risk group showed a higher mutation rate and lesser immune cell infiltration, especially in TP53, KRAS, and MET. The expression level of PD-L1 and CTLA4 was high in the high-risk group (P<0.05). The high-risk group is more sensitive to anti-cancer therapy with lower IC50 and higher immunophenoscore (IPS). CONCLUSIONS: In this study, we developed a novel LUAD stratification model based on m7G-related genes that successfully predicts the prognosis of LUAD patients and serves as a guide for clinically personalized treatment.