ArticleBMC bioinformatics2023
Integrative analysis of TP53 mutations in lung adenocarcinoma for immunotherapies and prognosis.
Article in BMC bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 24 citations in OpenAlex.
- Novel strategy of pemetrexed combined with localized therapy: breakthrough impact of long-term maintenance regimen on patient survival-a case report.Journal of medical case reports · 2026Article
- XAF1 nonsense mutation rs117407731 enhances lung adenocarcinoma susceptibility via apoptosis suppression.Molecular genetics and genomics : MGG · 2026Article
- Extracellular matrix-driven patient stratification and network modeling reveal distinct molecular grades with potential clinical implications.NPJ systems biology and applications · 2026Article
- Response to crizotinib treatment for ROS1 p.H1999N mutation and secondary EGFR p.V774M mutation after drug resistance: a Case Report.Frontiers in pharmacology · 2026Article
- Whole genome characterization of patient-derived lung cancer organoids.Translational lung cancer research · 2025Article
- Development of a prognostic model based on seven mitochondrial autophagy- and ferroptosis-related genes in lung adenocarcinoma.BMC medical genomics · 2025Article
- Integrative analysis of lung adenocarcinoma across diverse ethnicities and exposures.Cancer cell · 2025Article
- Effect of TP53 mutation, expression and polymorphism on the survival, immune infiltration and ferroptosis in patients with prostate cancer.Oncology letters · 2025Article
- Predicting response and survival of lung adenocarcinoma under anti-programmed death-1 therapy using biological deep learning.Briefings in bioinformatics · 2025Article
- The prognostic significance and Immunomodulatory role of SCGB3A1 expression in stage I lung adenocarcinoma.BMC medical genomics · 2025Article
- Zinc Finger Protein-Based Prognostic Signature Predicts Survival in Lung Adenocarcinoma.Cancers · 2025Article
- A Pilot Study: Contrasting Genomic Profiles of Lung Adenocarcinoma Between Patients of European and Latin American Ancestry.International journal of molecular sciences · 2025Article
- Utilizing TP53 hotspot mutations as effective predictors of gemcitabine treatment outcome in non-small-cell lung cancer.Cell death discovery · 2025Article
- Effects of Tp53 Gene Mutations on the Survival of Non-Small Cell Lung Cancer (NSCLC); A Short Review.Cancer management and research · 2025Review
- Comprehensive Survey of AACR GENIE Database of Tumor Mutation Burden (TMB) Among All Three Classes (I, II, III) ofLung Cancer (Auckland, N.Z.) · 2025Article
- Article
- The mitotic cell cycle-associated nomogram predicts overall survival in lung adenocarcinoma.Cancer medicine · 2023Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThe TP53 tumor suppressor gene is one of the most mutated genes in lung adenocarcinoma (LUAD) and plays a vital role in regulating the occurrence and progression of cancer. We aimed to elucidate the association between TP53 mutations, response to immunotherapies and the prognosis of LUAD.
methodsGenomic, transcriptomic, and clinical data of LUAD were downloaded from The Cancer Genome Atlas (TCGA) dataset. Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, gene set enrichment analysis (GSEA). Gene set variation analysis (GSVA) were performed to determine the differences in biological pathways. A merged protein-protein interaction (PPI) network was constructed and analyzed. MSIpred was used to analyze the correlation between the expression of the TP53 gene, tumor mutation burden (TMB) and tumor microsatellite instability (MSI). CIBERSORT was used to calculate the abundance of immune cells. Univariate and multivariate Cox regression analyses were used to determine the prognostic value of TP53 mutations in LUAD.
resultsTP53 was the most frequently mutated in LUAD, with a mutational frequency of 48%. GO and KEGG enrichment analysis, GSEA, and GSVA results showed a significant upregulation of several signaling pathways, including PI3K-AKT mTOR (P < 0.05), Notch (P < 0.05), E2F target (NES = 1.8, P < 0.05), and G2M checkpoint (NES = 1.7, P < 0.05). Moreover, we found a significant correlation between T cells, plasma cells, and TP53 mutations (R
conclusionsTP53 may be an independent predictor of response to immunotherapy in LUAD, and patients with TP53 mutations have higher immunogenicity and immune cell infiltration.
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