{"doi":"10.3389/frmbi.2025.1589686","title":"Microbial hallmarks of the respiratory tract in lung cancer: a meta-analysis","abstract":"Introduction Lung cancer is a leading cause of cancer-related deaths and has been associated with the microbiota of the human respiratory tract. However, the optimal sample type for studying the role of microbiota in lung cancer and the microbial hallmarks of lung cancer patients remain unclear. Methods In this study, we downloaded 16S rRNA sequencing data of 1,105 high-quality samples from 13 BioProjects, including lung tissues, bronchoalveolar lavage (BAL) fluids, and saliva, and performed a meta-analysis. Results Our results revealed that the BAL microbiota, dominated by taxa such as Sphingomonas and Pseudomonas , which are not typically abundant in the oral microbiota, served as hallmarks of individuals without lung cancer. In contrast, BAL samples from lung cancer patients showed higher relative abundances of oral-associated taxa, e.g., Streptococcus and Prevotella , with increased rates of dominance by these taxa in the BAL microbiota of lung cancer patients. Additionally, beta diversity analysis revealed significant compositional differences between the BAL microbiota of healthy individuals and those with lung cancer. Furthermore, while compositional differences were observed in the oral microbiota between healthy participants and lung cancer patients, as well as between microbiota from lung tumors and normal adjacent tissues, these differences were less pronounced than those observed in the BAL samples between healthy individuals and lung cancer patients. Cross-site correlations indicated limited associations between the relative abundances of taxa in the oral, BAL, and lung tissue microbiota, implying that differences in lower respiratory microbiota may not be directly driven by upper respiratory tract microbiota. Discussion These findings highlight distinct microbial patterns linked to lung cancer in the respiratory tract. More pronounced differences were observed in the BAL microbiota between healthy individuals and lung cancer patients, with the predominance of taxa, typically not abundant in the oral microbiota, serving as hallmarks of health.","journal":"Frontiers in Microbiomes","year":2025,"id":545076,"datarank":0.10397207708399181,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.0,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.0,"corpus_percentile":22.178386323199504,"corpus_rank":9377,"citation_count":1,"citer_count":1,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.8938,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":4.1667,"fair_percentile":4.891470498318557,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":618681,"name":"Stephanie A. Simko","orcid":"0000-0002-2193-4588","position":1,"is_corresponding":false},{"id":790177,"name":"Michelle Van Scoyk","orcid":"0000-0001-6631-8300","position":2,"is_corresponding":false},{"id":1293903,"name":"Gregory Riddick","orcid":null,"position":3,"is_corresponding":false},{"id":533099,"name":"Pei‐Ying Wu","orcid":"0000-0002-8168-6125","position":4,"is_corresponding":false},{"id":946101,"name":"Chu‐Fang Chou","orcid":"0000-0002-1372-4054","position":5,"is_corresponding":false},{"id":774035,"name":"Katherine Y. Tossas","orcid":"0000-0001-6872-2294","position":6,"is_corresponding":false},{"id":946100,"name":"Ching‐Yi Chen","orcid":"0000-0002-1978-6424","position":7,"is_corresponding":false},{"id":521079,"name":"Robert A. Winn","orcid":"0000-0001-5948-9291","position":8,"is_corresponding":false},{"id":379067,"name":"Bin Zhu","orcid":"0000-0003-2829-2925","position":0,"is_corresponding":true}],"reference_count":39,"raw_metadata":null,"created_at":"2026-07-19T02:53:17.418915Z","pmid":"41852386","pmcid":"PMC12993565","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":0.0,"fair_a":0.0,"fair_i":20.0,"fair_r":25.0,"fair_zscore":-1.1986,"fair_rationale":{"fair_score":4.17,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":0.0,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No persistent identifier (DOI, Handle, ARK, or repository accession) is given for the study's own dataset.","anchors":["RDA-F1-01D — FAIR Data Maturity Model: 'Data is identified by a persistent identifier' (priorit","RDA-F1-02D — FAIR Data Maturity Model: 'Data is identified by a globally unique identifier'","FsF-F1-02D — F-UJI/FAIRsFAIR: 'Data is assigned a persistent identifier'"],"scored":true,"signal":null},{"key":"f_repository_named","label":"Named repository","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"The study's own data are not deposited in a named repository; the source data repositories are not the study's own data.","anchors":["RDA-F4-01M — FAIR Data Maturity Model: metadata is offered so it can be harvested and indexed (","NIH DMS Policy Element 4 (NOT-OD-21-014) — name the repository where data will be archived","NSTC Desirable Characteristics of Data Repositories (2022) — 'Long-Term Sustainability', 'Reten"],"scored":true,"signal":null},{"key":"f_data_availability_statement","label":"Data-availability statement","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"The data availability statement describes source datasets, not the study's own data; no statement for the study's own data exists.","anchors":["Colavizza, Hrynaszkiewicz, Staden, Whitaker & McGillivray (2020), 'The citation advantage of li","Springer Nature research data policy — Data Availability Statements: standard statement templat","RDA-F3-01M — metadata clearly and explicitly includes the identifier of the data it describes"],"scored":false,"signal":null},{"key":"f_discovery_metadata","label":"Description of the dataset as an object","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":"The 1,105 high-quality samples spanned 8 countries (Supplementary Figure S2b). 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A bare URL is not persistent: it is the single most common cause of a dead data link five years after publication. For clinical / human-subjects data, deposit in dbGaP or the European Genome-phenome Archive (EGA).","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No persistent identifier (DOI, Handle, ARK, or repository accession) is given for the study's own dataset.","gain":16.67,"priority":"essential","scored":true},{"key":"f_repository_named","dimension":"F","label":"Named repository","action":"Deposit the data in a repository registered in re3data/FAIRsharing (a domain repository such as GEO, SRA, dbGaP, PRIDE, or a generalist such as Zenodo, Dryad, Dataverse) and name it explicitly in the paper. A lab website is not an archive: it has no retention commitment and no accession. 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