Differential analysis of microbial profiles in colorectal cancer reveals modulations corresponding to immune subtypes

The proximity of the gut microbiome to the tumor microenvironment (TME) in colorectal cancer (CRC) presents a unique ecological niche. A systematic study of tumor-microbiome interactions will facilitate a deeper understanding of the heterogeneity in immune response and clinical outcomes in CRC. Previous studies have identified specific microbial species such as Fusobacterium nucleatum, pks<sup>+</sup> Escherichia coli, and enterotoxigenic Bacteroides fragilis as contributors to CRC initiation and progression. However, the extent to which interactions between the microbiome and immune landscape affect prognosis and tumor heterogeneity remains poorly understood. To address this, immune subtypes from The Cancer Genome Atlas (TCGA) were integrated with microbial profiles from The Cancer Microbiome Atlas (TCMA) to examine the relationship between immune subtypes and the tumor microbiome in CRC. A cohort of 631 TCGA CRC cases with clinical, microbial and immune subtype data was analyzed. Differential abundance analysis indicated significant associations between specific taxa and immune subtypes. We demonstrate that pathogenic genera such as Selenomonas, Butyricimonas and Centipeda are significantly enriched (p<sub>adjusted</sub> < 0.05) in the C2 IFN-ɣ dominant subtype. Our findings show that the abundance of pathogenic genera may play a critical role in driving the paradoxically poorer survival observed in CRC patients with the C2 subtype.

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Publication Details

Journal
Computers in Biology and Medicine
Published
2025-12-03
DOI
https://doi.org/10.1016/j.compbiomed.2025.111346
Citations
1
Primary Topic
Gut microbiota and health
Type
article
Field-Weighted Citation Impact
0.81
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article

Differential analysis of microbial profiles in colorectal cancer reveals modulations corresponding to immune subtypes

Sherlyn Jemimah, Amin F. Majdalawieh, Amjad Mahasneh, Mawieh Hamad
1 citations
Computers in Biology and Medicine
Gut microbiota and health
0.81
article

Differential analysis of microbial profiles in colorectal cancer reveals modulations corresponding to immune subtypes

Sherlyn Jemimah, Amin F. Majdalawieh, Amjad Mahasneh, Mawieh Hamad
article en
1 citations

Abstract

The proximity of the gut microbiome to the tumor microenvironment (TME) in colorectal cancer (CRC) presents a unique ecological niche. A systematic study of tumor-microbiome interactions will facilitate a deeper understanding of the heterogeneity in immune response and clinical outcomes in CRC. Previous studies have identified specific microbial species such as Fusobacterium nucleatum, pks<sup>+</sup> Escherichia coli, and enterotoxigenic Bacteroides fragilis as contributors to CRC initiation and progression. However, the extent to which interactions between the microbiome and immune landscape affect prognosis and tumor heterogeneity remains poorly understood. To address this, immune subtypes from The Cancer Genome Atlas (TCGA) were integrated with microbial profiles from The Cancer Microbiome Atlas (TCMA) to examine the relationship between immune subtypes and the tumor microbiome in CRC. A cohort of 631 TCGA CRC cases with clinical, microbial and immune subtype data was analyzed. Differential abundance analysis indicated significant associations between specific taxa and immune subtypes. We demonstrate that pathogenic genera such as Selenomonas, Butyricimonas and Centipeda are significantly enriched (p<sub>adjusted</sub> < 0.05) in the C2 IFN-ɣ dominant subtype. Our findings show that the abundance of pathogenic genera may play a critical role in driving the paradoxically poorer survival observed in CRC patients with the C2 subtype.

Computers in Biology and MedicineVol. 200
American University of Sharjah (AE), University of Sharjah (AE)
Openalex Percentile: Top 21%
Gut microbiota and health
0.81
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Differential analysis of microbial profiles in colorectal cancer reveals modulations corresponding to immune subtypes — Sherlyn Jemimah, Amin F. Majdalawieh, et al. · Computers in Biology and Medicine (2025) | TGRS Research Map | TGRS