{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T02:15:05Z","timestamp":1791944105250,"version":"4.3.4"},"reference-count":86,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T00:00:00Z","timestamp":1785801600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:p>\n                    Immune checkpoint inhibitors (ICIs) have changed the treatment of non-small cell lung cancer (NSCLC), but response, acquired resistance and immune-related adverse events (irAEs) remain variable. Gut microbiome features and microbial metabolites may contribute to this variation through systemic immunity, gut-lung communication and the tumor immune microenvironment. This structured narrative review synthesizes direct and near-direct NSCLC or lung-cancer immunotherapy evidence, including cohorts ranging from 37 to 556 patients, a phase III chemoimmunotherapy ancillary cohort with 270 baseline fecal samples and recent TOPOSCORE-based community-ecology studies. Clinical evidence reports recurrent but inconsistent associations among microbial diversity,\n                    <jats:italic>Akkermansia<\/jats:italic>\n                    -related states, community topology, functional microbial features, survival, treatment-duration questions and toxicity, with substantial variation by region, treatment setting and endpoint. Mechanistic studies support plausible pathways involving short-chain fatty acids (SCFAs), bile acids, tryptophan-related metabolites, inosine and exploratory bacterial extracellular vesicle-associated signals. Few studies, however, connect microbiome, metabolite, immune and clinical outcome data within the same patients. We use an evidence-boundary framework to state what each evidence layer can support. In the current evidence base, microbiome signals are better suited to prospective validation, trial design and communication of uncertainty than to routine microbiome testing or intervention outside regulated studies.\n                  <\/jats:p>","DOI":"10.3389\/fmed.2026.1890287","type":"journal-article","created":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T05:38:26Z","timestamp":1785821906000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Microbial metabolites and the gut-lung axis in non-small cell lung cancer immunotherapy: evidence boundaries and translational implications"],"prefix":"10.3389","volume":"13","author":[{"given":"Fangxiong","family":"Zheng","sequence":"first","affiliation":[{"name":"Department of Medical Laboratory, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology","place":["Wuhan, China"]},{"name":"School of Laboratory Medicine, Hubei University of Chinese Medicine","place":["Wuhan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuchen","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Laboratory Medicine, Hubei University of Chinese Medicine","place":["Wuhan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhongxin","family":"Lu","sequence":"additional","affiliation":[{"name":"Department of Medical Laboratory, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology","place":["Wuhan, China"]},{"name":"School of Laboratory Medicine, Hubei University of Chinese Medicine","place":["Wuhan, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,4]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.lungcan.2016.06.016","article-title":"Predictive biomarkers of response to PD-1\/PD-L1 immune 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