ArticleClinical oral investigations2024
Multi-omics analysis of immune-related microbiome and prognostic model in head and neck squamous cell carcinoma.
Article in Clinical oral investigations, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Microbiome Landscapes in Squamous Cell Carcinoma Tissue Microenvironments: A Comparative Analysis.Immunity, inflammation and disease · 2026Article
- The intratumoral microbiome: a review of the tumor microenvironment's fourth axis shaping anti-tumor immunity, cancer prognosis, and therapeutic response.Frontiers in immunology · 2026Review
- The application of AI-driven and engineered intratumoral microbes in cancer therapy.Journal of translational medicine · 2025Review
- Review
- Revolutionizing cervical cancer treatment: single-cell sequencing ofFrontiers in immunology · 2025Article
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Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
Abstract
objectivesThe aim of our study is to explore the transcriptional and microbial characteristics of head and neck cancer's immune phenotypes using a multi-omics approach. MATERIALS AND
methodsEmploying TCGA data, we analyzed head and neck squamous cell carcinoma (HNSCC) immune cells with CIBERSORT and identified differentially expressed genes using DESeq2. Microbial profiles, obtained from the TCMA database, were analyzed using LEfSe algorithm to identify differential microbes in immune cell infiltration (ICI) subgroups. Random Forest algorithm and deep neural network (DNN) were employed to select microbial features and developed a prognosis model.
resultsWe categorized HNSCC into three immune subtypes, finding ICI-2 with the worst prognosis and distinct microbial diversity. Our immune-related microbiome (IRM) model outperformed the TNM staging model in predicting survival, linking higher IRM model scores with poorer prognosis, and demonstrating clinical utility over TNM staging. Patients categorized as low-risk by the IRM model showed higher sensitivity to cisplatin and sorafenib treatments.
conclusionsThis study offers a comprehensive exploration of the ICI landscape in HNSCC. We provide a detailed scenario of immune regulation in HNSCC and report a correlation between differing ICI patterns, intratumor microbiome, and prognosis. This research aids in identifying prime candidates for optimizing treatment strategies in HNSCC. CLINICAL RELEVANCE: This study revealed the microbial signatures associated with immunophenotyping of HNSCC and further found the microbial signatures associated with prognosis. The prognostic model based on IRM microbes is helpful for early prediction of patient prognosis and assisting clinical decision-making.
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