ArticleHuman mutation2026
Acetylated Pyrimidine Metabolism Genes as Prognostic Markers and Their Influence on Immune Profiles in Lung Adenocarcinoma.
Article in Human mutation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung adenocarcinoma is a very aggressive cancer with poor clinical results. New molecular indicators are desperately needed to improve treatment decision-making. This study looks at the relationship between the immunological microenvironment and genes linked to pyrimidine metabolism, particularly those that undergo acetylation, and the prognostic significance of these genes. Using publicly accessible genomic and clinical data, we used Gene Set Variation Analysis (GSVA) to identify acetylated pyrimidine pathway components that are highly correlated with survival outcomes. Three potential genes-TK1, RRM2B, and NME4-were identified for their prognostic relevance by using sophisticated predictive modeling approaches including CoxBoost and a random forest survival analysis. Using CIBERSORT deconvolution and single-sample gene set enrichment, immunological landscape disparities were identified, and it was discovered that varied gene expression-acetylation patterns were linked to varying immune cell infiltration. Gene activity and acetylation status-based low-risk patients showed positive survival patterns and higher levels of antitumor immune populations, indicating possible receptivity to immune-based treatments. Functional validation experiments targeting TK1, including RNA interference followed by proliferation (CCK-8, EdU), migration (Transwell), and wound healing assays, substantiated its role in promoting tumor aggressiveness. Collectively, our findings suggest that integrating metabolic gene signatures with immunological context offers a promising framework for precision oncology in lung adenocarcinoma.
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