ArticleTranslational lung cancer research2025
Identification and validation of crotonylation-related diagnostic markers for lung adenocarcinoma via weighted correlation network analysis and machine learning.
Article in Translational lung cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Mitochondrial Carrier SLC25A13 Drives Ferroptosis Resistance and Immune Evasion via a STAT3-IFI6 Circuit in Breast Cancer.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Integrative single-cell and bulk transcriptomic analysis identifies lesion-associated gene signatures for prognostic stratification and therapeutic guidance in head and neck squamous cell carcinoma.Biochemistry and biophysics reports · 2026Article
- A putative prognostic model for lung adenocarcinoma based on crotonylation-related genes by bioinformatics and experimental verification.Frontiers in cell and developmental biology · 2026Article
- An Update of AI and Radiomics in Precision Oncology: Insights from Liver Tumors as Case Models.Technology in cancer research & treatmentReview
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12 authors.
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Abstract
Background: Lung adenocarcinoma (LUAD) is one of the most common tumors in terms of incidence and mortality worldwide. Posttranslational modifications, including crotonylation, play a crucial role in various biological processes and diseases. However, the role of crotonylation in LUAD remains unclear. Our research focuses on identifying key genes in LUAD that are linked to crotonylation and prognosis. We also aim to clarify their role in the LUAD microenvironment to advance clinical translation of related targets. Methods: We used RNA-sequencing data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) database to identify differentially expressed genes (DEGs) related to crotonylation in LUAD. Weighted correlation network analysis (WGCNA) was applied to construct gene networks, and hub genes were identified using protein-protein interaction (PPI) analysis. The prognostic value of hub genes was assessed using Kaplan-Meier plots, and the correlation with immune infiltration was analyzed via Tumor Immune Estimation Resource (TIMER) and other algorithms. We then verified these genes through clinical samples and confirmed the role of Results: We identified Conclusions: Our study suggests that crotonylation-related genes, particularly
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