{"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.
mSystemsBiochemistry, 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.