Lowered Abundance of Gut Bacteriophage Species Is Associated With Human Cancer Cachexia

Q: What question does the study address about cancer cachexia and the gut virome?

It tests whether the gut bacteriophage profile is associated with human cancer cachexia, complementing prior evidence focused mainly on bacterial microbiome changes.

Q: How was the microbiome and phage composition analyzed in cachectic vs noncachectic patients?

Shotgun metagenomic sequencing of stool DNA was processed using k-mer-based phage-inclusive matching, de novo phage assembly, functional inference, and replicated statistical plus machine-learning analyses across metagenome datasets.

Q: What were the key findings regarding phages, diversity, and functions?

Lowered abundance of bacteriophages was associated with cachexia, while beta-diversity differed but alpha-diversity did not. The study also reports reduced microbiome-encoded detoxification functions and changes in specific bacterial taxa, with phages ranking as top cachexia predictors in machine-learning models.

Sep 23, 2026

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Cancer cachexia represents a high unmet medical need characterized by severe unintended weight loss in advanced cancer patients. Evidence links alterations in the bacterial gut microbiome to cachexia, yet the role of the gut bacteriophage community remains unclear. This study profiles gut microbiome changes with phage-focused attention in gastrointestinal cancer patients, using shotgun metagenomics to assess diversity, phage abundance, and microbiome-encoded functions.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages17

Reading Time43 min

AccessFree to download

Abstract

Background

Methods

Results

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Introduction

Journal of Cachexia, Sarcopenia and Muscle ORIGINAL ARTICLE OPEN ACCESS Lowered Abundance of Gut Bacteriophage Species Is Associated With Human Cancer Cachexia Axel Stang1,2,3,4 | Thomas Illig5,6 | Karsten Hiller7 | Hauke Weilert1,2,3,4 | Rudi Schmidt3,8 | Raphael Gronauer9 | Martin Seifert3,10 1Department of Haematology, Oncology and Palliative Care Medicine, Asklepios Hospital Barmbek, Hamburg, Germany | 2Asklepios Tumorzentrum Hamburg, Hamburg, Germany | 3Asklepios Medical School, Hamburg, Germany | 4Asklepios Campus Hamburg, Semmelweis University, Budapest, Hungary | 5Department of Human Genetics, Hannover Medical School, Hannover, Germany | 6Hannover Unified Biobank (HUB), Hannover, Germany | 7Department of Bioinformatics and Biochemistry, Braunschweig Integrated Centre of Systems Biology (BRICS), Technische Universität Braunschweig, Braunschweig, Germany | 8Immunetrue, Cologne, Germany | 9Department of Bioinformatics, Universität Innsbruck, Innsbruck, Austria | 1010x Genomics, Leiden, the Netherlands Correspondence: Axel Stang ([a.stang@asklepios.com](a.stang@asklepios.com)) Received: 10 July 2024 | Revised: 29 April 2026 | Accepted: 27 May 2026 Keywords: cancer cachexia | gut bacteriophages | gut microbiome | metagenomics ABSTRACT Background: Cancer cachexia exemplifies a high medical need condition without effective treatment. Recent studies implicated bacterial gut microbiome alterations to cancer cachexia. Whether the gut bacteriophage profile, an important microbiome component for health and disease, is also related to cancer cachexia remains unknown. We aimed to profile gut microbiome alterations in human cancer cachexia with attention on bacteriophages. Methods: We performed shotgun metagenomic sequencing in stool samples from 78 cachectic and 42 noncachectic patients (53% male, mean age 67 ± 8years) with newly diagnosed, advanced-stage (UICC IV) gastrointestinal cancers. Cachexia was defined according to the main criterion agreed upon international consensus (weight loss [WL] adjusted to body mass index [BMI]) . Obtained DNA short-reads were used for k-mers-based, phage-inclusive matching with reference databases, de novo phage assembly and inferring microbiome-encoded functions. We replicated significance-based statistical and predictionoriented machine-learning analyses in 2022 and 2025 generated metagenome datasets to incorporate the recent change by the International Committee on Taxonomy of Viruses (ICTV) from morphology-based (valid until 2022) to revised genome-based phage taxonomy into microbiome findings of cachexia. Results: Cachectic and noncachectic patients differed significantly regarding BMI (mean 20.9 vs. 26.4 kg/m2), WL (mean −6.5 vs.−0.2kg), survival (median 5 vs. 13 months) and clinical cachexia domains (e.g., C-reactive proteine and appetite loss) (all p < 0.001) but not for other clinical covariables (e.g., cancer type) (all p >0.05). Read-based mapping (2022/2025) identified 1.312/1.513 species (74/39 phage species), and de novo assembly resulted in 4.184/4.209 contigs (corresponding to 65/39 phage species). Concordantly, both analyses (2022 and 2025) showed that prevalent cachexia associated significantly with beta-diversity (Bray-Curtis distance, PERMANOVA, p< 0.05), but not to alpha-diversity (Shannon-Index, ANOVA, p >0.05), reduced microbiome-encoded detoxification functions (e.g., enriched microbial β-glucuronidase and depleted bacterial efflux pumps) and lowered abundance of bacterial species with false-discovery-rate (FDR)-corrected p< 0.05 (2022: Faecalibacterium prausnitzii, Roseburia intestinalis, Streptococcus species and Lachnospiraceae species; 2025: Faecalibacterium species, Ruminococcus gauvreauii and Intestinibacter bartlettii). Further, lowered abundance of bacteriophages associated with cachexia, predominantly affecting double-stranded (2022: Caudovirales, Siphoviridae, FDR-corrected p< 0.05; 2025: Myoviridae, Siphoridae, p < 0.05) but also single-

FAQs

What question does the study address about cancer cachexia and the gut virome?

It tests whether the gut bacteriophage profile is associated with human cancer cachexia, complementing prior evidence focused mainly on bacterial microbiome changes.

How was the microbiome and phage composition analyzed in cachectic vs noncachectic patients?

Shotgun metagenomic sequencing of stool DNA was processed using k-mer-based phage-inclusive matching, de novo phage assembly, functional inference, and replicated statistical plus machine-learning analyses across metagenome datasets.

What were the key findings regarding phages, diversity, and functions?

Lowered abundance of bacteriophages was associated with cachexia, while beta-diversity differed but alpha-diversity did not. The study also reports reduced microbiome-encoded detoxification functions and changes in specific bacterial taxa, with phages ranking as top cachexia predictors in machine-learning models.

Sep 23, 2026

Uploaded by Grenda