免疫相关肿瘤内微生物群和宿主基因表达对肿瘤预后的影响。

IF 4.6 2区 生物学 Q1 MICROBIOLOGY
mSystems Pub Date : 2025-09-15 DOI:10.1128/msystems.01146-25
Qingzhen Fu, Ning Zhao, Xia Li, Yanbing Li, Tian Tian, Lijing Gao, Yukun Cao, Liwan Wang, Jinyin Liu, Fan Wang, Yanlong Liu, Binbin Cui, Yashuang Zhao
{"title":"免疫相关肿瘤内微生物群和宿主基因表达对肿瘤预后的影响。","authors":"Qingzhen Fu, Ning Zhao, Xia Li, Yanbing Li, Tian Tian, Lijing Gao, Yukun Cao, Liwan Wang, Jinyin Liu, Fan Wang, Yanlong Liu, Binbin Cui, Yashuang Zhao","doi":"10.1128/msystems.01146-25","DOIUrl":null,"url":null,"abstract":"<p><p>The intratumoral microbiota has been identified as an indispensable part of the tumor microenvironment (TME). However, the relationship between the intratumoral microbiota and host gene expression, as well as its impact on prognosis and TME immunity, remains unclear. We utilized a machine learning-based framework to identify microbiota-host gene associations across 14 tumors from The Cancer Genome Atlas (TCGA) and validated them in 11 tumors from the Gene Expression Omnibus. By calculating immune scores and identifying immune-related microbiota, we developed both a pan-cancer Immune and Prognosis-Related Microbial Score (IPRMS) and cancer-specific IPRMSs and analyzed the relationship between the cancer-specific IPRMSs and immune infiltration at bulk level and single-cell level. Furthermore, we systematically analyzed the potential mechanisms in which the intratumoral microbiota might affect prognosis using survival mediation analyses (SMAs). We identified gene subsets associated with microbiota, which were predominantly enriched in immune-related and cell signaling regulation pathways. Subsequently, we constructed the overall survival-related IPRMS and found that high-IPRMS patients had poorer prognosis in pan-cancer and increased presence of macrophage and cancer-associated fibroblasts. In contrast, low-IPRMS patients showed enrichment in tumor-infiltrating lymphocytes. SMAs suggest that intratumoral microbiota may influence prognosis by affecting immune cells, pathways, and host genes. High-IPRMSs were consistently associated with poorer prognosis and lower abundance of tumor-infiltrating lymphocytes. At the single-cell level, cancer-associated fibroblasts were predominantly enriched in the high-IPRMS group, while tumor-infiltrating lymphocytes were also mainly enriched in the low-IPRMS group. Our research indicates that the intratumoral microbiota was associated with immune and prognosis, which may impact the cancer prognosis by modifying immune cells, pathways, and host gene expression.</p><p><strong>Importance: </strong>The intratumoral microbiota is a vital part of the tumor microenvironment, yet its interplay with host gene expression and immune regulation remains unclear. Based on a machine learning framework for the interaction analysis of intratumoral microbiota and host genes, as well as the construction of the Immune and Prognosis-Related Microbial Score, our findings suggest that intratumoral microbiota may influence gene expression by affecting host pathways, especially immune-related pathways. Moreover, immune-related intratumoral microbiota are significantly associated with patient survival and TME immunity and may influence prognosis by affecting immune cells, pathways, or gene expression, offering new perspectives and potential biomarkers for predicting personalized patient prognosis in the future.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0114625"},"PeriodicalIF":4.6000,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Effect of immune-related intratumoral microbiota and host gene expression on cancer prognosis.\",\"authors\":\"Qingzhen Fu, Ning Zhao, Xia Li, Yanbing Li, Tian Tian, Lijing Gao, Yukun Cao, Liwan Wang, Jinyin Liu, Fan Wang, Yanlong Liu, Binbin Cui, Yashuang Zhao\",\"doi\":\"10.1128/msystems.01146-25\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The intratumoral microbiota has been identified as an indispensable part of the tumor microenvironment (TME). However, the relationship between the intratumoral microbiota and host gene expression, as well as its impact on prognosis and TME immunity, remains unclear. We utilized a machine learning-based framework to identify microbiota-host gene associations across 14 tumors from The Cancer Genome Atlas (TCGA) and validated them in 11 tumors from the Gene Expression Omnibus. By calculating immune scores and identifying immune-related microbiota, we developed both a pan-cancer Immune and Prognosis-Related Microbial Score (IPRMS) and cancer-specific IPRMSs and analyzed the relationship between the cancer-specific IPRMSs and immune infiltration at bulk level and single-cell level. Furthermore, we systematically analyzed the potential mechanisms in which the intratumoral microbiota might affect prognosis using survival mediation analyses (SMAs). We identified gene subsets associated with microbiota, which were predominantly enriched in immune-related and cell signaling regulation pathways. Subsequently, we constructed the overall survival-related IPRMS and found that high-IPRMS patients had poorer prognosis in pan-cancer and increased presence of macrophage and cancer-associated fibroblasts. In contrast, low-IPRMS patients showed enrichment in tumor-infiltrating lymphocytes. SMAs suggest that intratumoral microbiota may influence prognosis by affecting immune cells, pathways, and host genes. High-IPRMSs were consistently associated with poorer prognosis and lower abundance of tumor-infiltrating lymphocytes. At the single-cell level, cancer-associated fibroblasts were predominantly enriched in the high-IPRMS group, while tumor-infiltrating lymphocytes were also mainly enriched in the low-IPRMS group. Our research indicates that the intratumoral microbiota was associated with immune and prognosis, which may impact the cancer prognosis by modifying immune cells, pathways, and host gene expression.</p><p><strong>Importance: </strong>The intratumoral microbiota is a vital part of the tumor microenvironment, yet its interplay with host gene expression and immune regulation remains unclear. Based on a machine learning framework for the interaction analysis of intratumoral microbiota and host genes, as well as the construction of the Immune and Prognosis-Related Microbial Score, our findings suggest that intratumoral microbiota may influence gene expression by affecting host pathways, especially immune-related pathways. Moreover, immune-related intratumoral microbiota are significantly associated with patient survival and TME immunity and may influence prognosis by affecting immune cells, pathways, or gene expression, offering new perspectives and potential biomarkers for predicting personalized patient prognosis in the future.</p>\",\"PeriodicalId\":18819,\"journal\":{\"name\":\"mSystems\",\"volume\":\" \",\"pages\":\"e0114625\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2025-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"mSystems\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1128/msystems.01146-25\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"mSystems","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1128/msystems.01146-25","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

肿瘤内微生物群已被确定为肿瘤微环境(TME)不可或缺的一部分。然而,肿瘤内微生物群与宿主基因表达之间的关系及其对预后和TME免疫的影响尚不清楚。我们利用基于机器学习的框架,从癌症基因组图谱(TCGA)中鉴定了14个肿瘤的微生物群-宿主基因关联,并在基因表达图谱(gene Expression Omnibus)中的11个肿瘤中验证了它们。通过计算免疫评分和识别免疫相关微生物群,我们建立了泛癌症免疫和预后相关微生物评分(IPRMS)和癌症特异性IPRMS,并分析了癌症特异性IPRMS与整体水平和单细胞水平免疫浸润的关系。此外,我们使用生存中介分析(sma)系统地分析了肿瘤内微生物群可能影响预后的潜在机制。我们确定了与微生物群相关的基因亚群,这些亚群主要富集于免疫相关和细胞信号调控途径。随后,我们构建了总体生存相关IPRMS,发现高IPRMS患者在泛癌中预后较差,巨噬细胞和癌症相关成纤维细胞的存在增加。相比之下,低iprms患者肿瘤浸润淋巴细胞富集。sma提示肿瘤内微生物群可能通过影响免疫细胞、途径和宿主基因来影响预后。高iprmss始终与较差的预后和较低的肿瘤浸润淋巴细胞丰度相关。在单细胞水平上,高iprms组主要富集癌相关成纤维细胞,而低iprms组也主要富集肿瘤浸润淋巴细胞。我们的研究表明,肿瘤内微生物群与免疫和预后相关,可能通过改变免疫细胞、途径和宿主基因表达来影响肿瘤预后。重要性:肿瘤内微生物群是肿瘤微环境的重要组成部分,但其与宿主基因表达和免疫调节的相互作用尚不清楚。基于肿瘤内微生物群与宿主基因相互作用分析的机器学习框架,以及免疫和预后相关微生物评分的构建,我们的研究结果表明,肿瘤内微生物群可能通过影响宿主途径,特别是免疫相关途径来影响基因表达。此外,免疫相关的肿瘤内微生物群与患者生存和TME免疫显著相关,并可能通过影响免疫细胞、途径或基因表达来影响预后,为未来预测个性化患者预后提供了新的视角和潜在的生物标志物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effect of immune-related intratumoral microbiota and host gene expression on cancer prognosis.

The intratumoral microbiota has been identified as an indispensable part of the tumor microenvironment (TME). However, the relationship between the intratumoral microbiota and host gene expression, as well as its impact on prognosis and TME immunity, remains unclear. We utilized a machine learning-based framework to identify microbiota-host gene associations across 14 tumors from The Cancer Genome Atlas (TCGA) and validated them in 11 tumors from the Gene Expression Omnibus. By calculating immune scores and identifying immune-related microbiota, we developed both a pan-cancer Immune and Prognosis-Related Microbial Score (IPRMS) and cancer-specific IPRMSs and analyzed the relationship between the cancer-specific IPRMSs and immune infiltration at bulk level and single-cell level. Furthermore, we systematically analyzed the potential mechanisms in which the intratumoral microbiota might affect prognosis using survival mediation analyses (SMAs). We identified gene subsets associated with microbiota, which were predominantly enriched in immune-related and cell signaling regulation pathways. Subsequently, we constructed the overall survival-related IPRMS and found that high-IPRMS patients had poorer prognosis in pan-cancer and increased presence of macrophage and cancer-associated fibroblasts. In contrast, low-IPRMS patients showed enrichment in tumor-infiltrating lymphocytes. SMAs suggest that intratumoral microbiota may influence prognosis by affecting immune cells, pathways, and host genes. High-IPRMSs were consistently associated with poorer prognosis and lower abundance of tumor-infiltrating lymphocytes. At the single-cell level, cancer-associated fibroblasts were predominantly enriched in the high-IPRMS group, while tumor-infiltrating lymphocytes were also mainly enriched in the low-IPRMS group. Our research indicates that the intratumoral microbiota was associated with immune and prognosis, which may impact the cancer prognosis by modifying immune cells, pathways, and host gene expression.

Importance: The intratumoral microbiota is a vital part of the tumor microenvironment, yet its interplay with host gene expression and immune regulation remains unclear. Based on a machine learning framework for the interaction analysis of intratumoral microbiota and host genes, as well as the construction of the Immune and Prognosis-Related Microbial Score, our findings suggest that intratumoral microbiota may influence gene expression by affecting host pathways, especially immune-related pathways. Moreover, immune-related intratumoral microbiota are significantly associated with patient survival and TME immunity and may influence prognosis by affecting immune cells, pathways, or gene expression, offering new perspectives and potential biomarkers for predicting personalized patient prognosis in the future.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
mSystems
mSystems Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
10.50
自引率
3.10%
发文量
308
审稿时长
13 weeks
期刊介绍: mSystems™ will publish preeminent work that stems from applying technologies for high-throughput analyses to achieve insights into the metabolic and regulatory systems at the scale of both the single cell and microbial communities. The scope of mSystems™ encompasses all important biological and biochemical findings drawn from analyses of large data sets, as well as new computational approaches for deriving these insights. mSystems™ will welcome submissions from researchers who focus on the microbiome, genomics, metagenomics, transcriptomics, metabolomics, proteomics, glycomics, bioinformatics, and computational microbiology. mSystems™ will provide streamlined decisions, while carrying on ASM''s tradition of rigorous peer review.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信