ArticleScientific reports2025
Integrative analysis of multi-omics data and gut microbiota composition reveals prognostic subtypes and predicts immunotherapy response in colorectal cancer using machine learning.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed.
- Review
- Mechanism-Driven Diagnostic Development: A Specimen-Aware Framework Illustrated by Colorectal Cancer and Solid Tumours.Cancers · 2026Review
- Gut Microbiome-Driven Strategies to Overcome Immunotherapy Resistance in Microsatellite-Stable Colorectal Cancer.Cancers · 2026Review
- Microbiome-Shaped Metastatic Niches in Colorectal Cancer: Organ-Specific Patterns, Immune-Metabolic Mechanisms, and Therapeutic Translation.Microorganisms · 2026Review
- Microbiome-guided cancer immunotherapy: immune mechanisms, resistance pathways, and translational opportunities for precision oncology.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- Development of a Metagenomics-Guided Personalized Synbiotic Protocol for Children with Autism Spectrum Disorder: An Exploratory Case Series.Nutrients · 2026Article
- Gut Microbiota Biomarkers in Patients with Hepatocellular Carcinoma in the Era of Immune Checkpoint Inhibitors.Life (Basel, Switzerland) · 2026Review
- Development and validation of machine learning models for predicting cancer-specific survival in colorectal signet ring cell carcinoma.BMC gastroenterology · 2026Article
- Exploring the role of metabolic disorders and gut microbiome in immune checkpoint regulation in cancer: PI3K/AKT/mTOR focus.Journal of physiology and biochemistry · 2026Review
- Multimodal foundation models in colorectal cancer: from prediction to trustworthy clinical insight.Briefings in bioinformatics · 2026Review
- Unlocking therapeutic impacts of the gut microbiota with computational tools.Current opinion in biotechnology · 2026Review
- Cerebrospinal Fluid Biomarkers in Creutzfeldt-Jakob Disease: Diagnostic Value, Limitations, and Future Multi-Omics Strategies.International journal of molecular sciences · 2026Review
- Integrated multi-omics characterization of SPTBN2 overexpression reveals its pro-tumorigenic role and immune microenvironment remodeling in colorectal cancer.Frontiers in cell and developmental biology · 2026Article
- Microbial dysbiosis drives colorectal carcinogenesis via integrated inflammatory, metabolic, and biofilm pathways.Frontiers in microbiology · 2026Review
- Review
- Cancer and Environmental Xenobiotics: Mechanisms, Controversies, and Innovations.Journal of xenobiotics · 2025Review
- Diagnostic Pathways and Molecular Biomarkers in Colorectal Cancer: Current Evidence and Perspectives in Poland.Current issues in molecular biology · 2025Review
- Genetic insights into colorectal cancer pathogenesis: a multi-omics and immunity perspective.Translational cancer research · 2025Article
- A new paradigm in postoperative colorectal cancer surveillance: integrating advanced imaging and multi-omics.Frontiers in physiology · 2025Review
- The bidirectional regulatory mechanism of gut microbiota metabolites on myocardial injury in heart failure from the perspective of the gut-heart axis: a review.Frontiers in microbiology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Colorectal cancer (CRC) exhibits substantial heterogeneity in molecular subtypes and clinical outcomes. We performed an integrative analysis of multi-omics data from 274 CRC patients to investigate the impact of gut microbiota composition on prognosis, identify novel subtypes, and develop a machine learning-based prognostic model. Our microbiome analysis revealed significant differences between CRC and normal tissues. Multi-omics clustering identified two major CRC subtypes, CS1 and CS2, with distinct molecular characteristics and survival outcomes. We developed the Multi-Omics Integrative Clustering and Machine Learning Score (MCMLS) model, which demonstrated strong prognostic value in predicting patient survival and outperformed existing models. The MCMLS low-score group exhibited higher immune cell infiltration, increased metabolic pathway activity, and potentially better immunotherapy response. In contrast, the MCMLS high-score group showed higher mutation burden, fibroblast infiltration, and enrichment of cell adhesion and migration pathways. Bacterial analysis revealed differentially abundant bacteria associated with prognosis. Importantly, MCMLS consistently predicted immunotherapy response across six independent datasets. Our findings highlight the complex interplay between the gut microbiome, tumor microenvironment, and immune landscape in CRC, providing valuable insights for improving patient stratification and personalized treatment strategies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.