AI Article Synopsis

  • Lung adenocarcinoma is the most prevalent lung cancer subtype, known for its high mortality rates and poor prognosis, and its relation to a novel cell death process called cuproptosis remains unclear.
  • An analysis of 10 cuproptosis-related genes showed significant differences in expression between lung cancer tissues and adjacent tissues, leading to the identification of two patient molecular subtypes, with one subtype associated with worse outcomes.
  • Using a cuproptosis-related prognostic model validated across multiple cohorts, researchers found that a risk score based on gene expression can independently predict patient survival, revealing differences in immune microenvironment features between high- and low-risk groups.

Article Abstract

Lung adenocarcinoma is the most common subtype of lung cancer clinically, with high mortality and poor prognosis. Cuproptosis present a newly discovered mode of cell death characterized by aggregation of fatty acylated proteins, depletion of iron-sulfur clusterin, triggering of HSP70, and induction of intracellular toxic oxidative stress. However, the impact of cuproptosis on lung adenocarcinoma development, prognosis, and treatment has not been elucidated. By systematically analyzing the genetic alterations of 10 cuproptosis-related genes in lung adenocarcinoma, we found that CDKN2A, DLAT, LIAS, PDHA1, FDX1, GLS, and MTF1 were differentially expressed between lung cancer tissues and adjacent tissues. Based on the expression levels of 10 cuproptosis-related genes, we classified lung adenocarcinoma patients into two molecular subtypes using the Consensus clustering method, of which subtype 2 had a worse prognosis. Differential expression genes associated with prognosis between the two subtypes were obtained by differential analysis and survival analysis, and cox lasso regression was applied to construct a cuproptosis-related prognostic model. Its survival predicting ability was validated in three extrinsic validation cohorts. The results of multivariate cox analysis indicated that cuproptosis risk score was an independent prognostic predictor, and the mixed model formed by cupproptosis prognostic model combined with stage had more robust prognostic prediction accuracy. We found the differences in cell cycle, mitosis, and p53 signaling pathways between high- and low-risk groups according to GO and KEGG enrichment analysis. The results of immune microenvironment analysis showed that the enrichment score of activated dendritic cells, mast cells, and type 2 interferon response were down-regulated in the high-risk group, while the fraction of neutrophils and M0 macrophages were upregulated in the high-risk group. Compared with the high-risk group, subjects in the low-risk group had higher Immunophenoscore and may be more sensitive to immunotherapy. We identified seven chemotherapy agents may improve the curative effect in LUAD samples with higher risk score. Overall, we discovered that cuproptosis is closely related to the occurrence, prognosis, and treatment of lung adenocarcinoma. The cuproptosis prognostic model is a potential prognostic predictor and may provide new strategies for precision therapy in lung adenocarcinoma.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9877306PMC
http://dx.doi.org/10.3389/fgene.2022.1039983DOI Listing

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