Research Paper Volume 16, Issue 3 pp 2249—2272

Identification of gut microbes-related molecular subtypes and their biomarkers in colorectal cancer

Xuliang Liu1, *, , Guolin Zhang2, *, , Shiyao Li3, *, , Yuechuan Liu1, , Kexin Ma1, , Liming Wang1,4,5, ,

  • 1 Department of General Surgery, Division of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
  • 2 Department of Cardiovascular Medicine, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
  • 3 Department of Respiratory Medicine, The Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
  • 4 Engineering Research Center for New Materials and Precision Treatment Technology of Malignant Tumors Therapy, The Second Affiliated Hospital, Dalian Medical University, Dalian, Liaoning, China
  • 5 Engineering Technology Research Center for Translational Medicine, The Second Affiliated Hospital, Dalian Medical University, Dalian, Liaoning, China
* Equal contribution

Received: July 27, 2023       Accepted: December 6, 2023       Published: January 29, 2024      

https://doi.org/10.18632/aging.205480
How to Cite

Copyright: © 2024 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

The role of gut microbes (GM) and their metabolites in colorectal cancer (CRC) development has attracted increasing attention. Several studies have identified specific microorganisms that are closely associated with CRC occurrence and progression, as well as key genes associated with gut microorganisms. However, the extent to which gut microbes-related genes can serve as biomarkers for CRC progression or prognosis is still poorly understood. This study used a bioinformatics-based approach to synthetically analyze the large amount of available data stored in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Through this analysis, this study identified two distinct CRC molecular subtypes associated with GM, as well as CRC markers related to GM. In addition, these new subtypes exhibit significantly different survival outcomes and are characterized by distinct immune landscapes and biological functions. Gut microbes-related biomarkers (GMRBs), IL7 and BCL10, were identified and found to have independent prognostic value and predictability for immunotherapeutic response in CRC patients. In addition, a systematic collection and review of prior research literature on GM and CRC provided additional evidence to support these findings. In conclusion, this paper provides new insights into the underlying pathological mechanisms by which GM promotes the development of CRC and suggests potentially viable solutions for individualized prevention, screening, and treatment of CRC.

Abbreviations

GM: gut microbes; CRC: colorectal cancer; TCGA: The Cancer Genome Atlas; GEO: Gene Expression Omnibus; GMRBs: gut microbes-related biomarkers; IL10: interleukin 10; FOXP3: forkhead box P3; Tregs: regulatory T cells; IL23: interleukin 23; IL17: interleukin 17; NF-κB: nuclear factor kappa B; STAT3: signal transducer and activator of transcription 3; AHR: aryl hydrocarbon receptor; IL6: interleukin 6; IL12: interleukin 12; TNF: tumor necrosis factor; IL7: interleukin 7; DC: dendritic cell; PDL1: programmed death ligand 1; GMRGs: gut microbes-related genes; PCA: principal component analysis; K-M: Kaplan-Meier; OS: overall survival; CMS: consensus molecular subtypes; DEGs: differentially expressed genes; KEGG: Kyoto Encyclopedia of Genes and Genomes; GO: Gene Ontology; GSEA: gene set enrichment analysis; GSVA: gene set variation analysis; TME: tumor microenvironment; TICs: tumor-infiltrating immune cells; TGF-β: transforming growth factor-β; TIDE: Tumor Immune Dysfunction and Exclusion; PD1: programmed cell death 1; CTLA4: cytotoxic T-lymphocyte associated protein 4; ROC: receiver operating characteristic; AUCs: area under the curves; IBD: inflammatory bowel disease; TLR: Toll-like receptor; MAP3K14: mitogen-activated protein kinase kinase kinase 14; TGF-β: transforming growth factor-β; SOCS: suppressor of cytokine signaling; STAT5: signal transducer and activator of transcription 5; IL2: interleukin 2; IFN-γ: interferon-gamma ; MIF: migration inhibitory factor; MDSCs: myeloid-derived suppressor cells; IL13: interleukin 13; CARD: caspase activation and recruitment domain; MALT1: mucosa-associated lymphoid tissue lymphoma translocation protein 1; CBM: CARD11-BCL10-MALT1; BCR: B-cell receptor; TCR: T-cell receptor; MAPK: mitogen-activated protein kinase; ABC-DLBCL: activated B-cell-like diffuse large B-cell lymphoma; RNA-seq: RNA sequencing; MeSH: Medical Subject Headings.