The metabolome of fecal extracellular vesicles in patients with malignant solid tumors

Dysregulated metabolism, a hallmark of cancer, creates unique metabolic features that can be employed to elucidate cancer prognosis, personalized treatment, and therapeutic response. Metabolomics has emerged as a powerful tool for profiling biomarkers in cancer studies. Most cancer metabolomic research on extracellular vesicles (EVs) has focused on human biofluids as samples. The metabolome of fecal EVs, a connecting link for host-microbiome interactions in cancer, has not been extensively studied. In this controlled study, we investigated the metabolomic signatures of fecal EVs in patients with solid tumors. Fecal samples were collected from adult patients with solid tumors (n = 28) and healthy controls (n = 7). After the isolation of EVs from fecal samples, EV metabolites were identified using targeted metabolomics profiling based on liquid chromatography-mass spectrometry (LC-MS). The metabolomic profiles of the fecal EVs from both patients and controls were compared using R and Metabolite Set Enrichment Analysis was done using Metaboanalyst 6.0. The metabolomic profiles of fecal EVs showed several differences between patients with solid tumors and control subjects. L-glutamic acid was identified as the most significantly enriched metabolite in patients with solid tumors. Conversely, guanine and N-acetylneuraminate were the most significantly depleted metabolites in the fecal EVs of these patients. Metabolite Set Enrichment Analysis linked the identified EV metabolites to key metabolic pathways, including arginine biosynthesis, glyoxylate and dicarboxylate metabolism, and the biosynthesis of branched-chain amino acids and unsaturated fatty acids. Receiver operating characteristic (ROC) revealed that glutamic acid is the most effective metabolite in distinguishing cancer patients from healthy controls. Some of these metabolites may also have plausible bacterial origins, as described in previous studies. Distinct metabolic phenotypes were identified in patients with solid tumors by analyzing fecal EVs in this study. The metabolomic profiling of fecal EVs offers valuable insights into the interactions between the gut microbiome and the host as well as unique metabolic snapshot of the disease status in the context of cancer. Thus, fecal EVs should be included in advanced multi-omics analyses of cancer research, alongside other human biofluids.

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Publication Details

Journal
Scientific Reports
Published
2025-08-11
DOI
https://doi.org/10.1038/s41598-025-14250-2
Citations
3
Primary Topic
Extracellular vesicles in disease
Type
article
Field-Weighted Citation Impact
2.42

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article

The metabolome of fecal extracellular vesicles in patients with malignant solid tumors

Mikael Niku, Ilja Kalashnikov, Juha Saarnio, Tero Rautio et al.
3 citations
Scientific Reports
Extracellular vesicles in disease
2.42
article

The metabolome of fecal extracellular vesicles in patients with malignant solid tumors

Mikael Niku, Ilja Kalashnikov, Juha Saarnio, Tero Rautio, Anni I. Nieminen, Päivi Auvinen, Arja Jukkola‐Vuorinen, Sanna Meriläinen, Jussi Pekka Koivunen, Peeter Karihtala, Okko‐Sakari Kääriäinen, Kaisa Sunela, Sirpa Leppä, Justus Reunanen, Surbhi Mishra, Raila Aro, Reetta Häivälä, Pia Vihinen, Jenni Hekkala, Arina L. Maltseva, Terhi Ruuska-Loewald, Sonja Karikka
article en
3 citations

Abstract

Dysregulated metabolism, a hallmark of cancer, creates unique metabolic features that can be employed to elucidate cancer prognosis, personalized treatment, and therapeutic response. Metabolomics has emerged as a powerful tool for profiling biomarkers in cancer studies. Most cancer metabolomic research on extracellular vesicles (EVs) has focused on human biofluids as samples. The metabolome of fecal EVs, a connecting link for host-microbiome interactions in cancer, has not been extensively studied. In this controlled study, we investigated the metabolomic signatures of fecal EVs in patients with solid tumors. Fecal samples were collected from adult patients with solid tumors (n = 28) and healthy controls (n = 7). After the isolation of EVs from fecal samples, EV metabolites were identified using targeted metabolomics profiling based on liquid chromatography-mass spectrometry (LC-MS). The metabolomic profiles of the fecal EVs from both patients and controls were compared using R and Metabolite Set Enrichment Analysis was done using Metaboanalyst 6.0. The metabolomic profiles of fecal EVs showed several differences between patients with solid tumors and control subjects. L-glutamic acid was identified as the most significantly enriched metabolite in patients with solid tumors. Conversely, guanine and N-acetylneuraminate were the most significantly depleted metabolites in the fecal EVs of these patients. Metabolite Set Enrichment Analysis linked the identified EV metabolites to key metabolic pathways, including arginine biosynthesis, glyoxylate and dicarboxylate metabolism, and the biosynthesis of branched-chain amino acids and unsaturated fatty acids. Receiver operating characteristic (ROC) revealed that glutamic acid is the most effective metabolite in distinguishing cancer patients from healthy controls. Some of these metabolites may also have plausible bacterial origins, as described in previous studies. Distinct metabolic phenotypes were identified in patients with solid tumors by analyzing fecal EVs in this study. The metabolomic profiling of fecal EVs offers valuable insights into the interactions between the gut microbiome and the host as well as unique metabolic snapshot of the disease status in the context of cancer. Thus, fecal EVs should be included in advanced multi-omics analyses of cancer research, alongside other human biofluids.

Scientific ReportsVol. 15(1)
University of Helsinki (FI), Oulu University Hospital (FI), Helsinki University Hospital (FI), Turku University Hospital (FI), Kuopio University Hospital (FI), Tampere University Hospital (FI), Tampere University (FI), Finnish Medicines Agency Fimea (FI), Oulu University of Applied Sciences (FI), University of Oulu (FI)
Academy of Finland, Biocenter Finland, Oulun Yliopistollinen Sairaala, Helsinki Institute of Life Science, Helsingin Yliopisto, European Regional Development Fund, Biocenter, University of Oulu
Good health and well-being
Openalex Percentile: Top 11%
Extracellular vesicles in disease
2.42
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