ArticleFrontiers in immunology2022
Insight of a Metabolic Prognostic Model to Identify Tumor Environment and Drug Vulnerability for Lung Adenocarcinoma.
Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- CS2164 combined with radiation suppressed tumor growth via γ-H2AX persistence and ROS accumulation.BMC cancer · 2026Article
- Predictive value of immunomodulatory-related genes for the prognosis of lung adenocarcinoma based on bioinformatics analysis.Discover oncology · 2025Article
- Application of a risk score model based on tyrosine-related genes in the prognosis and treatment of patients with lung adenocarcinoma.Frontiers in immunology · 2025Article
- Article
- Overexpression of ESYT3 improves radioimmune responses through activating cGAS-STING pathway in lung adenocarcinoma.Experimental hematology & oncology · 2024Article
- SP3-induced Timeless transcription contributes to cell growth of lung adenocarcinoma cells.PloS one · 2024Article
- Cholecystectomy Significantly Alters Gut Microbiota Homeostasis and Metabolic Profiles: A Cross-Sectional Study.Nutrients · 2023Article
- LINC00669 promotes lung adenocarcinoma growth by stimulating the Wnt/β-catenin signaling pathway.Cancer medicine · 2023Article
- A molecular classification system for estimating radiotherapy response and anticancer immunity for individual breast cancer patients.Frontiers in oncology · 2023Article
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Authors and funding
9 authors.
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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.
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