ArticleDiscover oncology2026
Identification and validation of prognostic genes associated with M2 macrophage and heme metabolism in lung adenocarcinoma through bulk and single-cell RNA sequencing analysis.
Article in Discover oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundResearch has demonstrated the pivotal role of M2 macrophages and heme metabolism in cancer development. This study aimed to identify and validate prognostic genes linked to M2 macrophages and heme metabolism-related genes (HMRGs) in lung adenocarcinoma (LUAD), offering valuable insights for the advancement of targeted therapeutic strategies.
methodsLUAD-related datasets were sourced from public databases. Initially, prognostic genes were ascertained through immune infiltration, correlation analysis, and regression analyses. A risk model was subsequently developed and evaluated. Finally, somatic mutation analysis, immunotherapy assessment, single-cell RNA sequencing (scRNA-seq), and immunohistochemical (IHC) analyses were conducted.
resultsIn this study, EPB41, ACP5, PPOX, RBM38, and TRIM58 were identified as prognostic genes for LUAD. A risk model was developed to stratify patients into high-risk groups (HRG) and low-risk groups (LRG), with HRG patients demonstrating poorer survival outcomes. Somatic mutation analysis revealed that TP53 (49%) and TTN (44%) were the most frequently mutated genes in both HRG and LRG samples. Furthermore, B cells, M2 macrophages, natural killer cells (NK), CD8 T cells, and regulatory T cells (Tregs) exhibited significant higher infiltration in HRG samples, whereas CD4 T cells exhibited notably lower infiltration in HRG samples. Additionally, ACP5 was found to have strong positive correlations with all immune checkpoints. Finally, scRNA-seq identified 14 annotated cell types, with ACP5 showing distinct expression in M2 macrophages.
conclusionThis study identified five prognostic genes for LUAD, offering valuable insights that could contribute to the development of prognostic markers and targeted therapies.
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