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. 2025 Mar 13;28(4):112221.
doi: 10.1016/j.isci.2025.112221. eCollection 2025 Apr 18.

Gut microbiota and metabolome signatures in obese and normal-weight patients with colorectal tumors

Marta La Vecchia  1 , Michela Giulia Clavenna  1 , Marika Sculco  1 , Gloria Sala  1 , Denise Marradi  2   3 , Elettra Barberis  3   4 , Soni Joseph  1 , Marta Mellai  1   3 , Nico Pagano  5 , Renzo Boldorini  1   6 , Barbara Azzimonti  1   3 , Elisa Bona  3   7   8 , Edoardo Pasolli  9   10 , Flavia Prodam  1   11 , Carlotta Sacerdote  1 , Daniela Ferrante  2 , Emilia Ghelardi  12 , Marcello Manfredi  2   3 , Anna Aspesi  1 , Irma Dianzani  1
Affiliations

Gut microbiota and metabolome signatures in obese and normal-weight patients with colorectal tumors

Marta La Vecchia et al. iScience. .

Abstract

Here, we aim to improve our understanding of various colorectal cancer (CRC) risk factors (obesity, unhealthy diet, and gut microbiota/metabolome alteration), analyzing 120 patients with colon polyps, divided in normal-weight (NW) or overweight/obese (OB). Dietary habits data (validated EPIC questionnaires) revealed a higher consumption of processed meat among OB vs. NW patients. Both mucosa-associated microbiota (MAM) on polyps and lumen-associated microbiota (LAM) analyses uncovered distinct bacterial signatures in the two groups. Importantly, we found an enrichment of the pathogenic species Finegoldia magna in MAM of OB patients, regardless of their polyp stage. We observed distinct mucosal-associated metabolome signatures, with OB patients showing increased pyroglutamic acid and reduced niacin levels, and performed microbiota-metabolome integrated analysis. These findings support a model where different risk factors may contribute to tumorigenesis in OB vs. NW patients, highlighting the potential impact of processed meat consumption and F. magna on CRC development among OB patients.

Keywords: Cancer systems biology; Health sciences; Metabolomics; Microbiome.

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Conflict of interest statement

The authors declare no competing interests.

Figures

None
Graphical abstract
Figure 1
Figure 1
Mucosa-associated microbiota signatures Bacterial genera (A) and species (B) enriched in MAM from normal-weight (NW) and obese (OB) patients. Genera and species enriched in NW patients are highlighted in green (LDA score >2), whereas those prevalent in OB patients are shown in red (LDA score < −2). Data are represented as bars, ranking discriminative features found by LEfSe analysis (p < 0.05) according to their LDA score.
Figure 2
Figure 2
Mucosa-associated metabolome profile (A) Volcano plot reporting upregulated (red dots) and down regulated (blue dots) mucosa-associated molecules in obese (OB) patients. Each dot represents one metabolite. The x axis represents log2(FC) of abundances of each metabolite and the y axis represents the statistical significance (-log10(p-value)). (B) Hierarchical clustering heatmap showing different metabolite distributions between normal-weight (NW) (green) and OB (red) patients. All the metabolites listed show a statistically significant difference between NW and OB groups (p < 0.05). Higher concentrations are reported in red, while low levels are in blue (auto-scaled data). (C) Partial least square discriminant analysis (PLS-DA) showing different mucosa-associated metabolite distribution between NW (green) and OB (red) patients. Each dot represents one patient. (D) Boxplots of some of the most statistically significant mucosa-associated molecules discriminating NW (green) and OB (red) patients (∗∗∗∗: p < 0.0001; ∗∗∗: p < 0.001; ∗∗: p < 0.01; ∗: p < 0.05). Data are represented as metabolite abundances. NW: normal-weight, OB: obese patients.
Figure 3
Figure 3
Luminal metabolome profile (A) Volcano plot reporting upregulated (red dots) and down regulated (blue dots) luminal associated molecules in obese (OB) patients. Each dot represents one metabolite. The x axis represents log2(FC) of abundances of each metabolite and the y axis represents the statistical significance (-log10(p-value)). (B) Hierarchical clustering heatmap showing different metabolite distributions between normal-weight (NW) (green) and OB (red) patients. All the metabolites listed show a statistically significant difference between NW and OB groups (p < 0.05). Higher concentrations are reported in red, while lower levels are in blue (auto-scaled data). (C) Partial least square discriminant analysis (PLS-DA) showing different luminal-associated metabolite distribution between NW (green) and OB (red) patients. Each dot represents one patient. NW, normal-weight, OB, obese patients.
Figure 4
Figure 4
Interaction networks between specific microbes and metabolites at the species level Nodes in the network represent key metabolites or microbes identified using 3MCor software, with solid lines indicating positive (blue) or negative (red) correlations.
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References

    1. Ley R.E., Peterson D.A., Gordon J.I. Ecological and Evolutionary Forces Shaping Microbial Diversity in the Human Intestine. Cell. 2006;124:837–848. doi: 10.1016/j.cell.2006.02.017. - DOI - PubMed
    1. Belkaid Y., Hand T.W. Role of the Microbiota in Immunity and inflammation. Cell. 2014;157:121–141. doi: 10.1016/j.cell.2014.03.011. - DOI - PMC - PubMed
    1. Kosumi K., Mima K., Baba H., Ogino S. Dysbiosis of the gut microbiota and colorectal cancer: the key target of molecular pathological epidemiology. J. Lab. Precis. Med. 2018;3:76. doi: 10.21037/jlpm.2018.09.05. - DOI - PMC - PubMed
    1. Song M., Chan A.T., Sun J. Influence of the Gut Microbiome, Diet, and Environment on Risk of Colorectal Cancer. Gastroenterology. 2020;158:322–340. doi: 10.1053/j.gastro.2019.06.048. - DOI - PMC - PubMed
    1. Bai H., Xu Z., Li J., Zhang X., Gao K., Fei X., Yang J., Li Q., Qian S., Zhang W., et al. Independent and joint associations of general and abdominal obesity with the risk of conventional adenomas and serrated polyps: A large population-based study in East Asia. Int. J. Cancer. 2023;153:54–63. doi: 10.1002/ijc.34503. - DOI - PubMed

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