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. 2025 Dec;14(1):2484880.
doi: 10.1080/2162402X.2025.2484880. Epub 2025 Apr 6.

Surrogate markers of intestinal dysfunction associated with survival in advanced cancers

Affiliations

Surrogate markers of intestinal dysfunction associated with survival in advanced cancers

Roxanne Birebent et al. Oncoimmunology. 2025 Dec.

Abstract

Deviations in the diversity and composition of the gut microbiota are called "gut dysbiosis". They have been linked to various chronic diseases including cancers and resistance to immunotherapy. Stool shotgun based-metagenomics informs on the ecological composition of the gut microbiota and the prevalence of homeostatic bacteria such as Akkermansia muciniphila (Akk), while determination of the serum addressin MAdCAM-1 instructs on endothelial gut barrier dysfunction. Here we examined patient survival during chemo-immuno-therapy in 955 cancer patients across four independent cohorts of non-small cell lung (NSCLC), genitourinary (GU) and colorectal (CRC) cancers, according to hallmarks of gut dysbiosis. We show that Akk prevalence represents a stable and favorable phenotype in NSCLC and CRC cancer patients. Over-dominance of Akk above the healthy threshold was observed in dismal prognosis in NSCLC and GU and mirrored an immunosuppressive gut ecosystem and excessive intestinal epithelial exfoliation in NSCLC. In CRC, the combination of a lack of Akk and low sMAdCAM-1 levels identified a subset comprising 28% of patients with reduced survival, independent of the immunoscore. We conclude that gut dysbiosis hallmarks deserve integration within the diagnosis toolbox in oncological practice.

Keywords: Akkermansia; Gut dysbiosis; MAdCAM-1; biomarker; chemotherapy; colorectal cancer; genitourinary cancers; immune checkpoint inhibitors; lung cancer.

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Conflict of interest statement

L.Z. is founder of everImmune and its SAB President. L.D. is an everImmune SAB member. Contracts from Kaleido, 9 meters/Innovate Pharma, Pileje: L.Z. Research grant/ Fees from Fondation Roche; Roche, MSD, BMS, aAstra Zeneca: G.Z is a consultant for Da Volterra & Inventiva. P.D. had consulting roles and ran clinical trials for AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Daiichi Sankyo, Eli Lilly, Merck, Novartis, Pfizer, prIME Oncology, Peer CME, Roche, MedImmune, Sanofi-Aventis, Taiho Pharma, Novocure, and Samsung. M.F. was supported by the Seerave Foundation. C.C. reported personal fees and research grants from Amgen, Bayer, Merck Serono, MSD, Nordic Pharma, Roche, Pierre Fabre, Servier, Seagen, Tempus and Takeda. F.B. received institutional interest from AbbVie, ACEA, Amgen, Astra Zeneca, Bayer, Bristol-Myers Squibb, Boehringer Ingelheim, EISAI, Eli Lilly Oncology, F. Hoffmann–La Roche Ltd, Genentech, Ipsen, Ignyta, Innate Pharma, Loxo, Novartis, MedImmune, Merck, Mirati, MSD, Pierre Fabre, Pfizer, Sanofi-Aventis, and Takeda. A.S. is an investigator in phases I, II & III clinical trials sponsored by Amphera, Astra-Zeneca, BMS, MSD, Regeneron, Roche, Trizell L.B. received speakers’ fees from AstraZeneca, Merck Sharp & Dohme, and Roche, and travel fees from Takeda. B.B. participates to Advisory Boards: Abbvie, Biontech SE, BristolMyerSqibb, Chugai pharmaceutical, CureVac AG, Daiichi Sankyo, F. Hoffmann-La Roche Ltd, Pharmamar, Regeneron, Sanofi aventis, Turning Point Therapeutics; Conseil: Eli Lilly, Ellipses pharma Ltd, Genmab, Immunocore, Janssen, MSD, Ose Immunotherapeutics, Owkin, Taiho oncology; Steering committee: Astrazeneca, Beigene, GENMAB A/S, GlaxoSmithKline, Pharmamar, Roche-Genentech, Sanofi, Takeda.

Figures

Figure 1.
Figure 1.
Prevalence of Akkermansia spp. in cancer patients and matched healthy volunteers (HV). a. Stool prevalence of Akk9226 (left) and 9228 (right) in cancer patients and sex and age matched French HV. b. Sankey diagram showing Akk prevalence (either 9226 and/or Akk9228) prevalence over time in paired specimens from 141 NSCLC patients followed longitudinally.
Figure 2.
Figure 2.
Prevalence of Akk9226 is associated with clinical benefit to therapies in NSCLC and CRC. Kaplan-Meier curves and Cox regression analyses of OS. A. NSCLC n = 556 by Akk9226 prevalence (left), 1st L of treatment (middle), 2nd line (right). See Table S3A for multivariable analyses. B. CRC n = 172 by Akk9226 status (left); chemotherapy n = 56 (middle), chemo-immunotherapy n = 116 (right). C. GU n = 215, including UC (n = 133, middle), RCC (n = 82, right), by Akk9226 status. Between groups, survival comparisons were performed using the two-sided log-rank test. The hazard ratios correspond to the related univariable Cox regression analyses. The conclusions were similar in the multivariable (also refer to Table S3A) p = 0.071).
Figure 3.
Figure 3.
Low levels of Akk9226 are associated with favorable prognosis in NSCLC. A. Distribution of Akk9226 relative abundance in NSCLC patients: Akk9226Neg (undetectable), Akk9226Low (0–4.799%), Akk9226High (>4.799%). B-C. Kaplan-Meier curves and Cox model for OS (B) and PFS (C) in 556 NSCLC patients by Akk9226 status. D-E. Same for 1st L (D) and 2nd L (E) ICI in NSCLC. Between groups, survival comparisons were performed using the two-sided log-rank test. The hazard ratios correspond to the related univariable Cox analyses. The conclusions were similar in the multivariable (also refer to Table S3B, p = 0.014 vs Akk9226 neg and p = 0.007 vs Akk9226 high).
Figure 4.
Figure 4.
High Akk9226 relative abundance is a surrogate hallmark of gut dysbiosis and epithelial exfoliation. A. PCoA of fecal taxonomic composition (inset), Shannon and richness indices and VIP score for Akk9226Neg versus Akk9226Low (left) and Akk9226Low versus Akk9226High (right). ANOSIM and PERMANOVA assess group separation significance after 999 permutations. PLS-DA and VIP identify key microbial species by importance with bar color depicting the cohort with the highest mean relative abundance. Mann-Whitney test for significance (*p < 0.05, **p < 0.01, ***p < 0.001). B. Kernel density plot of the exfoliated human reads (Log10 scale) in three Akk9226 groups according to lines of therapy in NSCLC and significance between medians was computed with Kruskal-Wallis’s test and Dunn’s test.
Figure 5.
Figure 5.
High levels of Akk9226 are associated with dismal prognosis in urinary tract cancers (GU) but not CRC. a distribution of Akk9226 relative abundance in HV, GU and CRC patients: Akk9226Neg (undetectable), Akk9226Low (0–4.799%), Akk9226High (>4.799%). P-value are fisher exact test with FDR correction. b, c. Kaplan-Meier curves and Cox model for OS in 215 GU patients (b) and 172 CRC patients (c) by Akk9226 status (Akk9226Neg, Akk9226Low, and Akk9226High). Between groups, survival comparisons were performed using the two-sided log-rank test. The hazard ratios correspond to the related univariable Cox analyses.
Figure 6.
Figure 6.
Interaction between sMadCAM-1 and Akk9226 as a prognostic signature in CRC. a. Plasma sMadCAM-1 levels by treatment arm in CRC. Each dot is one patient/plasma. b-c. Kaplan-Meier curves and multivariable Cox model for OS in CRC n = 162, in chemotherapy n = 54 (C, left) and in chemo-immunotherapy n = 108 (C, right) by sMadCAM-1 levels according to the cohort median (Low≤s138.4803 ng.mL−1). d-e. Kaplan-Meier curves and Cox model for PFS (D) and OS (E) in 150 patients with paired stool and plasma samples according to sMadCAM-1 levels and Akk9226 prevalence (sMAdCAM-1Low or High, Akk9226Pos or Akk9226Neg). Between groups, survival comparisons were performed using the two-sided log-rank test. The hazard ratios correspond to the related univariable Cox analyses.

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