Characterization of the fatty acid metabolism-related genes in lung adenocarcinoma to guide clinical therapy

BACKGROUND: Lung adenocarcinoma (LUAD) is a common cancer with a bad prognosis. Numerous investigations have indicated that the metabolism of fatty acids plays an important role in the occurrence, progression, and treatment of cancer. Consequently, the objective of the current investigation was to elucidate the role and prognostic significance of genes associated with fatty acid metabolism in patients diagnosed with LUAD. MATERIALS AND METHODS: The data files were acquired from The Cancer Genome Atlas database and GSE31210 dataset. Univariate Cox and least absolute shrinkage and selection operator regression analyses were conducted to establish a prognostic risk scoring model depending on fatty acid metabolism-associated genes to predict the prognosis of patients with LUAD. pRRophetic algorithm was utilized to evaluate the potential therapeutic agents. Gene set variation analysis combined with cell-type identification based on the estimation of relative subsets of RNA transcript and single-sample gene set enrichment analysis was used to determine the association between immune cell infiltration and risk score. Tumor immune dysfunction and exclusion algorithm was employed to predict immunotherapeutic sensitivity. RESULTS: To forecast the prognosis of patients with LUAD, a risk scoring model based on five genes associated with fatty acid metabolism was developed, including LDHA, ALDOA, CYP4B1, DPEP2, and HPGDS. Using the risk score algorithm, patients were divided into higher- and lower-risk categories. Patients classified as minimal risk showed superior prognosis than those with elevated risk. In addition, individuals in the higher-risk group had a proclivity toward chemoresistance and amenable to immunotherapy. CONCLUSION: The prognostic risk scoring model aids in estimating the prognosis of LUAD patients. It may also provide new insights into LUAD carcinogenesis and therapeutic strategies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-022-02286-3.