Variations in salivary microbiome and metabolites are associated with immunotherapy efficacy in patients with advanced NSCLC.

IF 4.6 2区 生物学 Q1 MICROBIOLOGY
mSystems Pub Date : 2025-03-18 Epub Date: 2025-02-10 DOI:10.1128/msystems.01115-24
DanHui Huang, YueHua Chen, Cui Li, Shuang Yang, LiShan Lin, XiaoNan Zhang, XiaoFang Su, LaiYu Liu, Haijin Zhao, Tingyue Luo, Shaoxi Cai, QianNan Ren, Hangming Dong
{"title":"Variations in salivary microbiome and metabolites are associated with immunotherapy efficacy in patients with advanced NSCLC.","authors":"DanHui Huang, YueHua Chen, Cui Li, Shuang Yang, LiShan Lin, XiaoNan Zhang, XiaoFang Su, LaiYu Liu, Haijin Zhao, Tingyue Luo, Shaoxi Cai, QianNan Ren, Hangming Dong","doi":"10.1128/msystems.01115-24","DOIUrl":null,"url":null,"abstract":"<p><p>Lung cancer is a leading cause of cancer mortality, with non-small cell lung cancer (NSCLC) comprising the majority of cases. Despite the advent of immune checkpoint inhibitors (ICIs), a significant number of patients fail to achieve a durable response, highlighting the need to understand the factors influencing treatment efficacy. Saliva samples and tumor samples were collected from 20 NSCLC patients. The salivary microbiota was profiled using metagenomic next-generation sequencing, and metabolites were analyzed via liquid chromatography-mass spectrometry to identify correlations among bacteria, metabolites, and immunotherapy responses. Immunohistochemistry (IHC) analysis of tissue samples verified the result. Besides, <i>in vitro</i> experiments and tumor tissue microarray, including 70 NSCLC patients, were utilized to further explore the potential mechanism linking the oral microbiome and immunotherapy efficacy. The study revealed several differential species and distinct metabolite compositions between responders and non-responders to ICI therapy in NSCLC and explored correlations and mechanisms between microbiota metabolites and immunotherapy resistance. Notably, it was found that several <i>Neisseria</i> and <i>Actinomyces</i> species were significantly enriched in responders and identified lipids and lipid-like molecules associated with PD-L1 expression levels and treatment outcomes. Importantly, several differential lipid molecules were associated with differential species. Further, <i>in vitro</i> experiments and IHC experiments indicated that abnormal fat metabolism linked to dysbiosis is correlated with immunotherapy resistance through regulation of CD8<sup>+</sup> T cell activity/infiltration and PD-L1 expression. Specific saliva microbiome and its associated lipids metabolites are significantly associated with the efficacy of ICI-based therapy in lung cancer. Our findings suggest that oral microbiome modulation and targeting lipid metabolism could improve immunotherapy responses, offering new avenues for personalized treatment strategies.IMPORTANCEIn non-small cell lung cancer, our study links specific salivary microbiome profiles and related lipid metabolites to the efficacy of immune checkpoint inhibitor (ICI) therapies. Responders showed enrichment of certain <i>Neisseria</i> and <i>Actinomyces</i> species and distinct lipid compositions. These lipids correlate with PD-L1 expression and CD8<sup>+</sup> T cell activity, affecting treatment outcomes. Our results imply that modulating the oral microbiome and targeting lipid metabolism may enhance ICI effectiveness, suggesting novel personalized therapeutic approaches.</p>","PeriodicalId":18819,"journal":{"name":"mSystems","volume":" ","pages":"e0111524"},"PeriodicalIF":4.6000,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11915794/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"mSystems","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1128/msystems.01115-24","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/10 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Lung cancer is a leading cause of cancer mortality, with non-small cell lung cancer (NSCLC) comprising the majority of cases. Despite the advent of immune checkpoint inhibitors (ICIs), a significant number of patients fail to achieve a durable response, highlighting the need to understand the factors influencing treatment efficacy. Saliva samples and tumor samples were collected from 20 NSCLC patients. The salivary microbiota was profiled using metagenomic next-generation sequencing, and metabolites were analyzed via liquid chromatography-mass spectrometry to identify correlations among bacteria, metabolites, and immunotherapy responses. Immunohistochemistry (IHC) analysis of tissue samples verified the result. Besides, in vitro experiments and tumor tissue microarray, including 70 NSCLC patients, were utilized to further explore the potential mechanism linking the oral microbiome and immunotherapy efficacy. The study revealed several differential species and distinct metabolite compositions between responders and non-responders to ICI therapy in NSCLC and explored correlations and mechanisms between microbiota metabolites and immunotherapy resistance. Notably, it was found that several Neisseria and Actinomyces species were significantly enriched in responders and identified lipids and lipid-like molecules associated with PD-L1 expression levels and treatment outcomes. Importantly, several differential lipid molecules were associated with differential species. Further, in vitro experiments and IHC experiments indicated that abnormal fat metabolism linked to dysbiosis is correlated with immunotherapy resistance through regulation of CD8+ T cell activity/infiltration and PD-L1 expression. Specific saliva microbiome and its associated lipids metabolites are significantly associated with the efficacy of ICI-based therapy in lung cancer. Our findings suggest that oral microbiome modulation and targeting lipid metabolism could improve immunotherapy responses, offering new avenues for personalized treatment strategies.IMPORTANCEIn non-small cell lung cancer, our study links specific salivary microbiome profiles and related lipid metabolites to the efficacy of immune checkpoint inhibitor (ICI) therapies. Responders showed enrichment of certain Neisseria and Actinomyces species and distinct lipid compositions. These lipids correlate with PD-L1 expression and CD8+ T cell activity, affecting treatment outcomes. Our results imply that modulating the oral microbiome and targeting lipid metabolism may enhance ICI effectiveness, suggesting novel personalized therapeutic approaches.

唾液微生物组和代谢物的变化与晚期非小细胞肺癌患者的免疫治疗效果有关。
肺癌是癌症死亡的主要原因,非小细胞肺癌(NSCLC)占大多数病例。尽管出现了免疫检查点抑制剂(ICIs),但仍有相当数量的患者未能获得持久的反应,这突出表明需要了解影响治疗效果的因素。采集20例非小细胞肺癌患者的唾液和肿瘤样本。使用新一代宏基因组测序对唾液微生物群进行了分析,并通过液相色谱-质谱分析了代谢物,以确定细菌,代谢物和免疫治疗反应之间的相关性。组织样本的免疫组织化学(IHC)分析证实了这一结果。此外,采用体外实验和肿瘤组织芯片技术,包括70例NSCLC患者,进一步探讨口腔微生物组与免疫治疗疗效的潜在联系机制。该研究揭示了非小细胞肺癌对ICI治疗的应答者和无应答者之间的几种差异物种和不同的代谢物组成,并探讨了微生物群代谢物与免疫治疗耐药性之间的相关性和机制。值得注意的是,研究发现应答者中几种奈瑟菌属和放线菌属显著富集,并鉴定出与PD-L1表达水平和治疗结果相关的脂质和类脂质分子。重要的是,几种不同的脂质分子与不同的物种有关。此外,体外实验和免疫组化实验表明,与生态失调相关的脂肪代谢异常通过调节CD8+ T细胞活性/浸润和PD-L1表达与免疫治疗耐药相关。特异性唾液微生物组及其相关脂质代谢物与基于ci的肺癌治疗的疗效显著相关。我们的研究结果表明,口服微生物组调节和靶向脂质代谢可以改善免疫治疗反应,为个性化治疗策略提供新的途径。在非小细胞肺癌中,我们的研究将特异性唾液微生物组谱和相关脂质代谢物与免疫检查点抑制剂(ICI)治疗的疗效联系起来。应答者表现出某些奈瑟菌和放线菌种类的富集和不同的脂质组成。这些脂质与PD-L1表达和CD8+ T细胞活性相关,影响治疗结果。我们的研究结果表明,调节口腔微生物组和靶向脂质代谢可能提高ICI的有效性,提出了新的个性化治疗方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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