Identification of a m6A-related ferroptosis signature as a potential predictive biomarker for lung adenocarcinoma

• Published in: BMC pulmonary medicine 2023-04, Vol.23 (1), p.1-128, Article 128
• Main Authors: Li, Dongdong, Chen, Ting, Li, Qiu-Gen
• Format: Article
• Language: English
• Subjects: Adenocarcinoma; Algorithms; Bioinformatics; Biomarkers; Cancer therapies; CD4 antigen; Correlation analysis; Datasets; DNA biosynthesis; Ferroptosis; Gene expression; Immunological memory; Infiltration; Lung adenocarcinoma; Lung cancer; Lungs; Lymphocytes T; m6A; Macrophages; Medical prognosis; Memory cells; Metastases; Mutation; Mutation rates; N6-methyladenosine; p53 Protein; Prognosis; Pulmonology; Regression analysis; Risk groups; Therapeutic targets
• ISSN: 1471-2466; 1471-2466
• DOI: 10.1186/s12890-023-02410-x

BackgroundBoth N6-methyladenosine (m6A) and ferroptosis-related genes are associated with the prognosis of lung adenocarcinoma. However, the predictive value of m6A-related ferroptosis genes remains unclear. Here, we aimed to identify the prognostic value of m6A-related ferroptosis genes in lung adenocarcinoma.MethodsLung adenocarcinoma sample data were downloaded from the University of California Santa Cruz Xena and Gene Expression Omnibus databases. Spearman’s correlation analysis was used to screen for m6A-related ferroptosis genes. Univariate Cox regression, Kaplan–Meier, and Lasso analyses were conducted to identify prognostic m6A-related ferroptosis genes, and stepwise regression was used to construct a prognostic gene signature. The predictive value of the gene signature was assessed using a multivariate Cox analysis. In the validation cohort, survival analysis was performed to verify gene signature stability. The training cohort was divided into high- and low-risk groups according to the median risk score to assess differences between the two groups in terms of gene set variation analysis, somatic mutations, and tumor immune infiltration cells.ResultsSix m6A-related ferroptosis genes were used to construct a gene signature in the training cohort and a multivariate Cox analysis was conducted to determine the independent prognostic value of these genes in lung adenocarcinoma. In the validation cohort, Kaplan–Meier and receiver operating characteristic analyses confirmed the strong predictive power of this signature for the prognosis of lung adenocarcinoma. Gene set variation analysis showed that the low-risk group was mainly related to immunity, and the high-risk group was mainly related to DNA replication. Somatic mutation analysis revealed that the TP53 gene had the highest mutation rate in the high-risk group. Tumor immune infiltration cell analysis showed that the low-risk group had higher levels of resting CD4 memory T cells and lower levels of M0 macrophages.ConclusionOur study identified a novel m6A-related ferroptosis-associated six-gene signature (comprising SLC2A1, HERPUD1, EIF2S1, ACSL3, NCOA4, and CISD1) for predicting lung adenocarcinoma prognosis, yielding a useful prognostic biomarker and potential therapeutic target.