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- Publisher Website: 10.1007/s00784-024-05645-y
- Scopus: eid_2-s2.0-85190796199
- PMID: 38642188
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Article: Multi-omics analysis of immune-related microbiome and prognostic model in head and neck squamous cell carcinoma
Title | Multi-omics analysis of immune-related microbiome and prognostic model in head and neck squamous cell carcinoma |
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Authors | |
Keywords | Head and neck squamous cell carcinoma Immune subtype Microbiome Multi-omics Prognosis |
Issue Date | 1-May-2024 |
Publisher | Springer |
Citation | Clinical Oral Investigations, 2024, v. 28, n. 5 How to Cite? |
Abstract | Objectives: The 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 methods: Employing 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. Results: We 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. Conclusions: This 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. |
Persistent Identifier | http://hdl.handle.net/10722/347277 |
ISSN | 2023 Impact Factor: 3.1 2023 SCImago Journal Rankings: 0.942 |
DC Field | Value | Language |
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dc.contributor.author | Liu, Yingqiao | - |
dc.contributor.author | Lin, Haitao | - |
dc.contributor.author | Zhong, Weijun | - |
dc.contributor.author | Zeng, Yudi | - |
dc.contributor.author | Zhou, Guihai | - |
dc.contributor.author | Chen, Zhifeng | - |
dc.contributor.author | Huang, Shi | - |
dc.contributor.author | Zhang, Leitao | - |
dc.contributor.author | Liu, Xiqiang | - |
dc.date.accessioned | 2024-09-20T00:31:08Z | - |
dc.date.available | 2024-09-20T00:31:08Z | - |
dc.date.issued | 2024-05-01 | - |
dc.identifier.citation | Clinical Oral Investigations, 2024, v. 28, n. 5 | - |
dc.identifier.issn | 1432-6981 | - |
dc.identifier.uri | http://hdl.handle.net/10722/347277 | - |
dc.description.abstract | <p>Objectives: The 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 methods: Employing 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. Results: We 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. Conclusions: This 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.</p> | - |
dc.language | eng | - |
dc.publisher | Springer | - |
dc.relation.ispartof | Clinical Oral Investigations | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Head and neck squamous cell carcinoma | - |
dc.subject | Immune subtype | - |
dc.subject | Microbiome | - |
dc.subject | Multi-omics | - |
dc.subject | Prognosis | - |
dc.title | Multi-omics analysis of immune-related microbiome and prognostic model in head and neck squamous cell carcinoma | - |
dc.type | Article | - |
dc.identifier.doi | 10.1007/s00784-024-05645-y | - |
dc.identifier.pmid | 38642188 | - |
dc.identifier.scopus | eid_2-s2.0-85190796199 | - |
dc.identifier.volume | 28 | - |
dc.identifier.issue | 5 | - |
dc.identifier.eissn | 1436-3771 | - |
dc.identifier.issnl | 1432-6981 | - |