Unravelling the prognostic and operative role of intratumoural microbiota in non‐small cell lung cancer: Insights from 16S rRNA and RNA sequencing
Abstract Background Complex interrelationships between the microbiota and cancer have been identified by several studies. However, despite delineating microbial composition in non‐small cell lung cancer (NSCLC), key pathogenic microbiota and their underlying mechanisms remain unclear. Methods We per...
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Wiley
2025-01-01
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| Series: | Clinical and Translational Medicine |
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| Online Access: | https://doi.org/10.1002/ctm2.70156 |
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| author | Fuling Mao Zixuan Hu Ruifeng Shi Hongbing Zhang Zihe Zhang Yongwen Li Xuanguang Li Penghu Gao Jinhui Li Minghui Liu Hongyu Liu Jun Chen |
| author_facet | Fuling Mao Zixuan Hu Ruifeng Shi Hongbing Zhang Zihe Zhang Yongwen Li Xuanguang Li Penghu Gao Jinhui Li Minghui Liu Hongyu Liu Jun Chen |
| author_sort | Fuling Mao |
| collection | DOAJ |
| description | Abstract Background Complex interrelationships between the microbiota and cancer have been identified by several studies. However, despite delineating microbial composition in non‐small cell lung cancer (NSCLC), key pathogenic microbiota and their underlying mechanisms remain unclear. Methods We performed 16S rRNA V3–V4 amplicon and transcriptome sequencing on cancerous and adjacent normal tissue samples from 30 patients with NSCLC, from which clinical characteristics and prognosis outcomes were collected. We used 16S rRNA sequencing to dissect microbial composition and perform prognosis correlations, and in conjunction with transcriptome sequencing, we determined potential mechanisms underpinning significant microbiota actions. Results In comparing different sample types, we identified more pronounced beta diversity disparity between NSCLC, lung squamous cell carcinoma (LUSC) and corresponding paired normal tissues. Concurrently, LUSC and lung adenocarcinoma exhibited distinct microbial composition traits at genus levels. Subsequently, four phyla, five classes, nine orders, 17 families and 36 genera were filtered out and were related to prognosis outcomes. Intriguingly, a protective microbial cluster was identified encompassing nine genera associated with delayed disease recurrence, with functional analyses suggested that these microbiota predominantly exerted metabolism‐related functions. Additionally, a harmful microbial cluster (HMC) was identified, including three genera. In this HMC and subsequent prognosis model analyses, harmful intratumoural microbiota were potentially implicated in infection, inflammation and immune regulation. Crucially, we identified a microbial genus, Peptococcus, which was as an independent, detrimental NSCLC prognostic factor and potentially impacted prognosis outcomes via tumour necrosis factor (TNF) signalling. Conclusions We identified a substantial connection between intratumoural microbiota and NSCLC prognosis outcomes. Protective microbiota primarily exerted metabolic functions, whereas harmful microbiota were mainly implicated in infection, inflammation and immune modulation. Furthermore, Peptococcus may be significant in adverse NSCLC prognoses and serve as a potential biomarker for patient management and cancer screening. Key points Four phyla, five classes, nine orders, 17 families and 36 genera have been found associated with NSCLC prognosis. We identified a protective microbial cluster associated with delayed recurrence and a harmful microbial cluster related to shorter survival and earlier recurrence. We identified Peptococcus as an independent, detrimental prognostic factor for NSCLC, potentially impacting prognosis via TNF signalling. |
| format | Article |
| id | doaj-art-0c54d60ea0db425aa57e733b4d9bed16 |
| institution | Kabale University |
| issn | 2001-1326 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
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| series | Clinical and Translational Medicine |
| spelling | doaj-art-0c54d60ea0db425aa57e733b4d9bed162025-01-25T04:00:38ZengWileyClinical and Translational Medicine2001-13262025-01-01151n/an/a10.1002/ctm2.70156Unravelling the prognostic and operative role of intratumoural microbiota in non‐small cell lung cancer: Insights from 16S rRNA and RNA sequencingFuling Mao0Zixuan Hu1Ruifeng Shi2Hongbing Zhang3Zihe Zhang4Yongwen Li5Xuanguang Li6Penghu Gao7Jinhui Li8Minghui Liu9Hongyu Liu10Jun Chen11Department of Lung Cancer Surgery Tianjin Medical University General Hospital Tianjin ChinaDepartment of Lung Cancer Surgery Tianjin Medical University General Hospital Tianjin ChinaDepartment of Thoracic Surgery and Oncology the First Affiliated Hospital of Guangzhou Medical University State Key Laboratory of Respiratory Disease National Clinical Research Center for Respiratory Disease Guangzhou Institute of Respiratory Health Guangzhou ChinaDepartment of Lung Cancer Surgery Tianjin Medical University General Hospital Tianjin ChinaDepartment of Lung Cancer Surgery Tianjin Medical University General Hospital Tianjin ChinaTianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment Tianjin Lung Cancer Institute Tianjin Medical University General Hospital Tianjin ChinaDepartment of Lung Cancer Surgery Tianjin Medical University General Hospital Tianjin ChinaDepartment of Lung Cancer Surgery Tianjin Medical University General Hospital Tianjin ChinaDepartment of Lung Cancer Surgery Tianjin Medical University General Hospital Tianjin ChinaDepartment of Lung Cancer Surgery Tianjin Medical University General Hospital Tianjin ChinaTianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment Tianjin Lung Cancer Institute Tianjin Medical University General Hospital Tianjin ChinaDepartment of Lung Cancer Surgery Tianjin Medical University General Hospital Tianjin ChinaAbstract Background Complex interrelationships between the microbiota and cancer have been identified by several studies. However, despite delineating microbial composition in non‐small cell lung cancer (NSCLC), key pathogenic microbiota and their underlying mechanisms remain unclear. Methods We performed 16S rRNA V3–V4 amplicon and transcriptome sequencing on cancerous and adjacent normal tissue samples from 30 patients with NSCLC, from which clinical characteristics and prognosis outcomes were collected. We used 16S rRNA sequencing to dissect microbial composition and perform prognosis correlations, and in conjunction with transcriptome sequencing, we determined potential mechanisms underpinning significant microbiota actions. Results In comparing different sample types, we identified more pronounced beta diversity disparity between NSCLC, lung squamous cell carcinoma (LUSC) and corresponding paired normal tissues. Concurrently, LUSC and lung adenocarcinoma exhibited distinct microbial composition traits at genus levels. Subsequently, four phyla, five classes, nine orders, 17 families and 36 genera were filtered out and were related to prognosis outcomes. Intriguingly, a protective microbial cluster was identified encompassing nine genera associated with delayed disease recurrence, with functional analyses suggested that these microbiota predominantly exerted metabolism‐related functions. Additionally, a harmful microbial cluster (HMC) was identified, including three genera. In this HMC and subsequent prognosis model analyses, harmful intratumoural microbiota were potentially implicated in infection, inflammation and immune regulation. Crucially, we identified a microbial genus, Peptococcus, which was as an independent, detrimental NSCLC prognostic factor and potentially impacted prognosis outcomes via tumour necrosis factor (TNF) signalling. Conclusions We identified a substantial connection between intratumoural microbiota and NSCLC prognosis outcomes. Protective microbiota primarily exerted metabolic functions, whereas harmful microbiota were mainly implicated in infection, inflammation and immune modulation. Furthermore, Peptococcus may be significant in adverse NSCLC prognoses and serve as a potential biomarker for patient management and cancer screening. Key points Four phyla, five classes, nine orders, 17 families and 36 genera have been found associated with NSCLC prognosis. We identified a protective microbial cluster associated with delayed recurrence and a harmful microbial cluster related to shorter survival and earlier recurrence. We identified Peptococcus as an independent, detrimental prognostic factor for NSCLC, potentially impacting prognosis via TNF signalling.https://doi.org/10.1002/ctm2.70156microbiotanon‐small cell lung cancer (NSCLC)Peptococcusprognosisprotective and harmful microbial clusters |
| spellingShingle | Fuling Mao Zixuan Hu Ruifeng Shi Hongbing Zhang Zihe Zhang Yongwen Li Xuanguang Li Penghu Gao Jinhui Li Minghui Liu Hongyu Liu Jun Chen Unravelling the prognostic and operative role of intratumoural microbiota in non‐small cell lung cancer: Insights from 16S rRNA and RNA sequencing Clinical and Translational Medicine microbiota non‐small cell lung cancer (NSCLC) Peptococcus prognosis protective and harmful microbial clusters |
| title | Unravelling the prognostic and operative role of intratumoural microbiota in non‐small cell lung cancer: Insights from 16S rRNA and RNA sequencing |
| title_full | Unravelling the prognostic and operative role of intratumoural microbiota in non‐small cell lung cancer: Insights from 16S rRNA and RNA sequencing |
| title_fullStr | Unravelling the prognostic and operative role of intratumoural microbiota in non‐small cell lung cancer: Insights from 16S rRNA and RNA sequencing |
| title_full_unstemmed | Unravelling the prognostic and operative role of intratumoural microbiota in non‐small cell lung cancer: Insights from 16S rRNA and RNA sequencing |
| title_short | Unravelling the prognostic and operative role of intratumoural microbiota in non‐small cell lung cancer: Insights from 16S rRNA and RNA sequencing |
| title_sort | unravelling the prognostic and operative role of intratumoural microbiota in non small cell lung cancer insights from 16s rrna and rna sequencing |
| topic | microbiota non‐small cell lung cancer (NSCLC) Peptococcus prognosis protective and harmful microbial clusters |
| url | https://doi.org/10.1002/ctm2.70156 |
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