ArticleFrontiers in microbiology2024
The characteristics of intratumoral microbial community reflect the development of lung adenocarcinoma.
Article in Frontiers in microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Review
- Analysis of intratumoural bacteria: Opportunities and challenges for cancer therapy.Acta pharmaceutica Sinica. B · 2026Review
- Lung microbiota analysis in early-stage lung adenocarcinoma.Microbiology spectrum · 2026Article
- 3D models for cancer-microbe interaction studiesFrontiers in immunology · 2026Article
- Paired comparison of tumor core and airway lumen (BALF) microbiomes in lung adenocarcinoma: deciphering specificFrontiers in cellular and infection microbiology · 2026Article
- The Current Roadmap of Lung Cancer Biology, Genomics and Racial Disparity.International journal of molecular sciences · 2025Review
- Influence of stage-specific and location-related intratumoral microbiota on prognosis and metabolic reprogramming in non-small cell lung cancer.Frontiers in immunology · 2025Article
- Characterizing microbial communities and their correlation with genetic mutations in early-stage lung adenocarcinoma: implications for disease progression and therapeutic targets.Frontiers in oncology · 2024Article
- Clinical Relevance and Drug Modulation of PPAR Signaling Pathway in Triple-Negative Breast Cancer: A Comprehensive Analysis.PPAR research · 2024Article
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4 authors.
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Abstract
Introduction: An increasing number of studies have demonstrated the pivotal role of microbiota changes in the onset, progression, diagnosis, treatment, and prognosis of lung adenocarcinoma (LUAD). However, a comprehensive analysis of intratumoral microbiome variation across distinct LUAD stages has not been performed. The aim of this study was to identify the microbial markers that significantly vary during tumor stage of LUAD. Methods: Here, we used the cancer genome atlas (TCGA) database to comprehensively compare and analyze the differences in microbial composition between 267 patients with early and 224 patients with advanced LUAD. In order to determine the best biomarkers, we used the random forest (RF) model and found that the microbial markers have a certain ability in predicting the stage of LUAD. Results: We found that there were certain differences in the microbiome of patients with LUAD at different stages, especially in the tumor tissues of patients with advanced LUAD, whose co-abundance network was significantly more complex. We also found that five bacterial biomarkers ( Discussion: Our study revealed the microbial profile of patients with LUAD and the intrinsic pathogenic mechanism between the microbiome and the disease, and established a multi-omics model to determine LUAD tumor stage.
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