Insight of a Metabolic Prognostic Model to Identify Tumor Environment and Drug Vulnerability for Lung Adenocarcinoma

Author:

Peng Shun-Li,Wang Rong,Zhou Yu-Ling,Wei Wei,Zhong Gui-Hua,Huang Xiao-Tao,Yang Shuai,Liu Qiao-Dan,Liu Zhi-Gang

Abstract

Metabolic reprogramming is a novel method for the treatment of malignant tumors. The exploration of metabolism procedures between radiosensitive and radioresistant tumors may provide novel perspectives for lung adenocarcinoma (LUAD) patients after radiation therapy. In our study, metabolic reprogramming and immune response changes were found between radioresistant cell line (A549RR) and its parent cells (A549) using gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Nucleotide/amino acid, lipid, and glucose metabolic process, including Alanine, aspartate and glutamate metabolism, Tryptophan/Tyrosine metabolism, Butanoate metabolism, Purine/Pyrimidine metabolism, were screened out. Then molecular signatures database and The Cancer Genome Atlas Program (TCGA) lung adenocarcinoma datasets were used to identify metabolism-related genes (MRGs) between radiosensitive and radioresistant lung adenocarcinoma (LUAD) cells. A metabolism-based prognostic model, receiver operating characteristic (ROC) curve and nomogram were constructed using Metabolism Score calculated by 14 metabolism-related genes (MRGs). Three independent public datasets, (GSE72094, GSE3141, GSE8894) and one immunotherapy cohort (IMvigor210) were used as external validation cohorts. Expression of 14 hub genes in cells, normal and LUAD specimens were explored by Human Protein Atlas, TIMER2.0 and RT-qPCR. Patients with low-Metabolism Scores were correlated with longer survival times, higher response rates to immune checkpoint inhibitors (ICIs), different immune cell infiltrations and drug vulnerability. Our study demonstrated a comprehensive landscape between radiosensitive and radioresistant LUAD, and provide novel targets for NSCLC, especially those patients received radiation therapy. Moreover, this metabolism-based prognostic model may help to investigate connections between radiosensitivity, immune response, metabolic reprogramming, and patients’ prognosis.

Funder

Basic and Applied Basic Research Foundation of Guangdong Province

China Postdoctoral Science Foundation

Fundamental Research Funds for the Central Universities

Publisher

Frontiers Media SA

Subject

Immunology,Immunology and Allergy

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