{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T10:59:53Z","timestamp":1789988393363,"version":"4.0.1"},"reference-count":54,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T00:00:00Z","timestamp":1789948800000},"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. Oncol."],"abstract":"<jats:p>Tumor-associated microbiomes are integral components of the tumor microenvironment, modulating tumorigenesis and progression through immune and metabolic pathways. Microbiome data are high-dimensional, sparse, and compositional, which limits conventional analytical approaches. Digital intelligence\u2014an umbrella term encompassing artificial intelligence (AI), machine learning (ML), big-data analytics, and multi-omics integration\u2014has emerged as a powerful paradigm for tumor microbiome research. In this review, we delineate the applications of digital intelligence across the full pipeline: intelligent preprocessing of sequencing data, multi-modal data integration, inference of microbe\u2013host interactions, construction of diagnostic and prognostic models, and discovery of immunotherapy biomarkers. We explicitly distinguish computational association from experimental mechanistic validation and clinical utility, and we critically appraise methodological limitations, including overfitting, data leakage, batch effects, and the scarcity of external prospective validation. Microbiome-related biomarkers are framed as prognostic, predictive, or dynamic, and we caution against equating retrospective performance with clinical value. Finally, we discuss current challenges\u2014data standardization, model interpretability, and ethical privacy\u2014and future directions, including spatial and single-cell microbiomics, FMT-based interventions, and prospectively validated clinical translation.<\/jats:p>","DOI":"10.3389\/fonc.2026.1972980","type":"journal-article","created":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T10:03:30Z","timestamp":1789985010000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Digital intelligence-enabled tumor microbiome research: from mechanistic dissection to clinical translation"],"prefix":"10.3389","volume":"16","author":[{"given":"Mingliang","family":"Shao","sequence":"first","affiliation":[{"name":"Department of Interventional Medicine, The Second People\u2019s Hospital of Nantong","place":["Nantong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luqi","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Basic Medical Sciences, Jiamusi University","place":["Jiamusi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qi","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Interventional Medicine, The Second People\u2019s Hospital of Nantong","place":["Nantong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaowen","family":"Shen","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory, The Second People\u2019s Hospital of Nantong","place":["Nantong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory, The Second People\u2019s Hospital of Nantong","place":["Nantong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,21]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"17587","DOI":"10.1038\/s41598-026-48719-5","article-title":"Breast tumor microbiome regulates anti-tumor immunity and T cell-associated metabolites","volume":"16","author":"Liu","year":"2026","journal-title":"Sci Rep"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1158\/2326-6066.CIR-24-0469","article-title":"Inflammation mediated by gut microbiome alterations promotes lung cancer development and an immunosuppressed tumor microenvironment","volume":"12","author":"Rahal","year":"2024","journal-title":"Cancer Immunol Res"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1126\/science.aay9189","article-title":"The human tumor microbiome is composed of tumor type-specific intracellular bacteria","volume":"368","author":"Nejman","year":"2020","journal-title":"Science"},{"key":"B4","doi-asserted-by":"publisher","first-page":"271ps1","DOI":"10.1126\/scitranslmed.3010473","article-title":"Cancer and the gut microbiota: an unexpected link","volume":"7","author":"Zitvogel","year":"2015","journal-title":"Sci Transl Med"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1038\/s41579-018-0029-9","article-title":"Best practices for analysing microbiomes","volume":"16","author":"Knight","year":"2018","journal-title":"Nat Rev Microbiol"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.3389\/fmicb.2017.02224","article-title":"Microbiome datasets are compositional: and this is not optional","volume":"8","author":"Gloor","year":"2017","journal-title":"Front Microbiol"},{"key":"B7","article-title":"Artificial intelligence and microbiome in cancer","volume":"128","author":"Wang","year":"2023","journal-title":"Br J Cancer"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1016\/j.ebiom.2022.104276","article-title":"Machine learning for classification of hypertension subtypes using multi-omics: a multi-centre, retrospective, data-driven study","volume":"84","author":"Reel","year":"2022","journal-title":"EBioMedicine"},{"key":"B9","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1186\/s13059-020-02015-1","article-title":"MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data","volume":"21","author":"Argelaguet","year":"2020","journal-title":"Genome Biol"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1128\/spectrum.05038-22","article-title":"Multi-omics analysis reveals intratumor microbes as immunomodulators in colorectal cancer","volume":"11","author":"Liu","year":"2023","journal-title":"Microbiol Spectr"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.1016\/j.canlet.2026.218359","article-title":"Emerging biomarkers in melanoma: bridging molecular discovery and precision oncology","volume":"645","author":"Xu","year":"2026","journal-title":"Cancer Lett"},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.3869","article-title":"DADA2: high-resolution sample inference from Illumina amplicon data","volume":"13","author":"Callahan","year":"2016","journal-title":"Nat Methods"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btr381","article-title":"UCHIME improves sensitivity and speed of chimera detection","volume":"27","author":"Edgar","year":"2011","journal-title":"Bioinformatics"},{"key":"B14","doi-asserted-by":"publisher","DOI":"10.1093\/nargab\/lqaa009","article-title":"DeepMicrobes: taxonomic classification for metagenomics with deep learning","volume":"2","author":"Liang","year":"2020","journal-title":"NAR Genom Bioinform"},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.1038\/s41564-026-02472-7","article-title":"MetaCAT enables reconstruction of high-quality microbial genomes and their association with host traits from metagenomic data","author":"Liu","year":"2026","journal-title":"Nat Microbiol"},{"key":"B16","article-title":"GraphSAINT: graph sampling based inductive learning method","author":"Zeng","year":"2020","journal-title":"ICLR"},{"key":"B17","doi-asserted-by":"publisher","DOI":"10.1101\/2024.03.15.585201","article-title":"MicrobiomeKG: a knowledge graph for microbiome research","author":"Goetz","year":"2024","journal-title":"bioRxiv"},{"key":"B18","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1004226","article-title":"Sparse and compositionally robust inference of microbial ecological networks","volume":"11","author":"Kurtz","year":"2015","journal-title":"PloS Comput Biol"},{"key":"B19","doi-asserted-by":"publisher","DOI":"10.1128\/mSystems.00013-15","article-title":"Metabolic model-based integration of microbiome taxonomic and metabolomic profiles elucidates mechanistic links between ecological and metabolic networks","volume":"1","author":"Noecker","year":"2016","journal-title":"mSystems"},{"key":"B20","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1016\/j.chom.2013.07.012","article-title":"Fusobacterium nucleatum promotes colorectal carcinogenesis by modulating E-cadherin\/\u03b2-catenin signaling via its FadA adhesin","volume":"14","author":"Rubinstein","year":"2013","journal-title":"Cell Host Microbe"},{"key":"B21","doi-asserted-by":"publisher","DOI":"10.1016\/j.ccr.2012.02.007","article-title":"Promotion of hepatocellular carcinoma by the intestinal microbiota and TLR4","volume":"21","author":"Dapito","year":"2012","journal-title":"Cancer Cell"},{"key":"B22","doi-asserted-by":"publisher","DOI":"10.1158\/1940-6207.capr-14-0129","article-title":"The human gut microbiome as a screening tool for colorectal cancer","volume":"7","author":"Zackular","year":"2014","journal-title":"Cancer Prev Res"},{"key":"B23","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1186\/s13073-016-0290-3","article-title":"Microbiota-based model improves the sensitivity of fecal immunochemical test for detecting colonic lesions","volume":"8","author":"Baxter","year":"2016","journal-title":"Genome Med"},{"key":"B24","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-025-94183-y","article-title":"Machine learning models for pancreatic cancer diagnosis using microbiome markers from extracellular vesicles","volume":"15","author":"Lee","year":"2025","journal-title":"Sci Rep"},{"key":"B25","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1038\/s41419-021-04092-x","article-title":"Prognostic correlations with the microbiome of breast cancer subtypes","volume":"7","author":"Banerjee","year":"2021","journal-title":"NPJ Breast Cancer"},{"key":"B26","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long short-term memory","volume":"9","author":"Hochreiter","year":"1997","journal-title":"Neural Comput"},{"key":"B27","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1186\/s12911-025-03050-3","article-title":"Multitask deep learning model based on multimodal data for predicting prognosis of rectal cancer: a multicenter retrospective study","volume":"25","author":"Ma","year":"2025","journal-title":"BMC Med Inform Decis Mak"},{"key":"B28","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-019-0405-7","article-title":"Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation","volume":"25","author":"Thomas","year":"2019","journal-title":"Nat Med"},{"key":"B29","doi-asserted-by":"publisher","DOI":"10.1126\/science.aan3706","article-title":"Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors","volume":"359","author":"Routy","year":"2018","journal-title":"Science"},{"key":"B30","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1126\/science.aan4236","article-title":"Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients","volume":"359","author":"Gopalakrishnan","year":"2018","journal-title":"Science"},{"key":"B31","doi-asserted-by":"publisher","DOI":"10.1016\/j.medj.2024.10.007","article-title":"Effects of gut microbiota on immune checkpoint inhibitors in multi-cancer and as microbial biomarkers for predicting therapeutic response","volume":"6","author":"Lin","year":"2025","journal-title":"Med"},{"key":"B32","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-021-01655-5","article-title":"Intestinal Akkermansia muciniphila predicts clinical response to PD-1 blockade in patients with advanced non-small-cell lung cancer","volume":"28","author":"Derosa","year":"2022","journal-title":"Nat Med"},{"key":"B33","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-022-01695-5","article-title":"Cross-cohort gut microbiome associations with immune checkpoint inhibitor response in advanced melanoma","volume":"28","author":"Lee","year":"2022","journal-title":"Nat Med"},{"key":"B34","doi-asserted-by":"publisher","DOI":"10.1126\/science.aaz7015","article-title":"Dietary fiber and probiotics influence the gut microbiome and melanoma immunotherapy response","volume":"374","author":"Spencer","year":"2021","journal-title":"Science"},{"key":"B35","doi-asserted-by":"publisher","DOI":"10.1177\/17562848251333527","article-title":"Gastrointestinal tumor personalized immunotherapy: an integrated analysis from molecular genetics to imaging biomarkers","volume":"17","author":"Guan","year":"2025","journal-title":"Ther Adv Med Oncol"},{"key":"B36","doi-asserted-by":"publisher","first-page":"595","DOI":"10.1126\/science.abf3363","article-title":"Fecal microbiota transplant overcomes resistance to anti-PD-1 therapy in melanoma patients","volume":"371","author":"Davar","year":"2021","journal-title":"Science"},{"key":"B37","doi-asserted-by":"publisher","DOI":"10.1126\/science.abb5920","article-title":"Fecal microbiota transplant promotes response in immunotherapy-refractory melanoma patients","volume":"371","author":"Baruch","year":"2021","journal-title":"Science"},{"key":"B38","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-025-04186-5","article-title":"Fecal microbiota transplantation plus immunotherapy in non-small cell lung cancer and melanoma: the phase 2 FMT-LUMINate trial","volume":"32","author":"Duttagupta","year":"2026","journal-title":"Nat Med"},{"key":"B39","doi-asserted-by":"publisher","DOI":"10.1126\/scitranslmed.aax0876","article-title":"Engineered probiotics for local tumor delivery of checkpoint blockade nanobodies","volume":"12","author":"Gurbatri","year":"2020","journal-title":"Sci Transl Med"},{"key":"B40","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2025.1595977","article-title":"The gut-immune axis in primary immune thrombocytopenia (ITP): a paradigm shift in treatment approaches","volume":"16","author":"Guo","year":"2025","journal-title":"Front Immunol"},{"key":"B41","doi-asserted-by":"publisher","first-page":"789","DOI":"10.1016\/j.chom.2019.05.005","article-title":"Daily sampling reveals personalized diet-microbiome associations in humans","volume":"25","author":"Johnson","year":"2019","journal-title":"Cell Host Microbe"},{"key":"B42","doi-asserted-by":"publisher","DOI":"10.1016\/j.tim.2018.11.003","article-title":"Contamination in low microbial biomass microbiome studies: issues and recommendations","volume":"27","author":"Eisenhofer","year":"2019","journal-title":"Trends Microbiol"},{"key":"B43","doi-asserted-by":"publisher","DOI":"10.1093\/nargab\/lqaa078","article-title":"ComBat-seq: batch effect adjustment for RNA-seq count data","volume":"2","author":"Zhang","year":"2020","journal-title":"NAR Genom Bioinform"},{"key":"B44","doi-asserted-by":"publisher","DOI":"10.1038\/nbt.3960","article-title":"Towards standards for human fecal sample processing in metagenomic studies","volume":"35","author":"Costea","year":"2017","journal-title":"Nat Biotechnol"},{"key":"B45","doi-asserted-by":"publisher","DOI":"10.1002\/widm.1312","article-title":"Causability and explainability of artificial intelligence in medicine","volume":"9","author":"Holzinger","year":"2019","journal-title":"Wiley Interdiscip Rev Data Min Knowl Discov"},{"key":"B46","article-title":"A unified approach to interpreting model predictions","volume":"30","author":"Lundberg","year":"2017","journal-title":"Adv Neural Inf Process Syst"},{"key":"B47","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-022-01772-9","article-title":"Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI","volume":"28","author":"Vasey","year":"2022","journal-title":"Nat Med"},{"key":"B48","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1423854112","article-title":"Identifying personal microbiomes using metagenomic codes","volume":"112","author":"Franzosa","year":"2015","journal-title":"Proc Natl Acad Sci USA"},{"key":"B49","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1561\/9781601988195","article-title":"The algorithmic foundations of differential privacy","volume":"9","author":"Dwork","year":"2014","journal-title":"Found Trends Theor Comput Sci"},{"key":"B50","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1038\/s41591-018-0272-7","article-title":"Privacy in the age of medical big data","volume":"25","author":"Price","year":"2019","journal-title":"Nat Med"},{"key":"B51","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMp1714229","article-title":"Implementing AI in health care \u2014 the importance of ethics","volume":"378","author":"Char","year":"2018","journal-title":"N Engl J Med"},{"key":"B52","doi-asserted-by":"publisher","DOI":"10.52843\/cassyni.77602k","article-title":"Effect of the intratumoral microbiota on spatial and cellular heterogeneity in cancer","volume":"611","author":"Galeano Ni\u00f1o","year":"2022","journal-title":"Nature"},{"key":"B53","doi-asserted-by":"publisher","first-page":"10:1","DOI":"10.1147\/jrd.2018.2888987","article-title":"Potential of quantum computing for drug discovery","volume":"66","author":"Cao","year":"2022","journal-title":"IBM J Res Dev"},{"key":"B54","doi-asserted-by":"publisher","first-page":"37","DOI":"10.18203\/2349-3259.ijct20161408","article-title":"In silico clinical trials: how computer simulation will transform the biomedical industry","volume":"3","author":"Viceconti","year":"2016","journal-title":"Int J Clin Trials"}],"container-title":["Frontiers in Oncology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fonc.2026.1972980\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T10:03:32Z","timestamp":1789985012000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fonc.2026.1972980\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,21]]},"references-count":54,"alternative-id":["10.3389\/fonc.2026.1972980"],"URL":"https:\/\/doi.org\/10.3389\/fonc.2026.1972980","relation":{},"ISSN":["2234-943X"],"issn-type":[{"value":"2234-943X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,21]]},"article-number":"1972980"}}