Theranostics 2022; 12(5):2015-2027. doi:10.7150/thno.66464 This issue

Research Paper

Faecal microbiome and metabolic signatures in rectal neuroendocrine tumors

Wei Hu1,2†, Ze Min Chen1,2†, Xia Xi Li1,2†, Lan Lu3†, Gen Hua Yang1,2, Zheng Xia Lei1,2, Li Juan You1,2, Xiao Bing Cui1,2, Si Cun Lu1,2, Zhi Yong Zhai1,2, Zhi Yu Zeng1,2, Ye Chen1,2✉, Si Lin Huang4✉, Wei Gong1,2✉

1. Department of Gastroenterology, Shenzhen Hospital, Southern Medical University, Shenzhen, Guangdong, China
2. The Third School of Clinical Medicine, Southern Medical University, Shenzhen, Guangdong, China
3. Antibiotics Research and Re-evaluation Key Laboratory of Sichuan Province, Sichuan Industrial Institute of Antibiotics, School of Pharmacy, Chengdu University, Chengdu, Sichuan, China
4. Department of Gastroenterology, South China Hospital, Health Science Center, Shenzhen University, Shenzhen, Guangdong, China
† Contributed equally to this work

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
Citation:
Hu W, Chen ZM, Li XX, Lu L, Yang GH, Lei ZX, You LJ, Cui XB, Lu SC, Zhai ZY, Zeng ZY, Chen Y, Huang SL, Gong W. Faecal microbiome and metabolic signatures in rectal neuroendocrine tumors. Theranostics 2022; 12(5):2015-2027. doi:10.7150/thno.66464. Available from https://www.thno.org/v12p2015.htm

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Abstract

Graphic abstract

Background: The prevalence of rectal neuroendocrine tumors (RNET) has increased substantially over the past decades. Little is known on mechanistic alteration in the pathogenesis of such disease. We postulate that perturbations of human gut microbiome-metabolome interface influentially affect the development of RNET. The study aims to characterize the composition and function of faecal microbiome and metabolites in RNET individuals.

Methods: We performed deep shotgun metagenomic sequencing and untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomic profiling of faecal samples from the discovery cohort (18 RNET patients, 40 controls), and validated the microbiome and metabolite-based classifiers in an independent cohort (15 RNET participants, 19 controls).

Results: We uncovered a dysbiotic gut ecological microenvironment in RNET patients, characterized by aberrant depletion and attenuated connection of microbial species, and abnormally aggregated lipids and lipid-like molecules. Functional characterization based on our in-house and Human Project Unified Metabolic Analysis Network 2 (HUMAnN2) pipelines further indicated a nutrient deficient gut microenvironment in RNET individuals, evidenced by diminished activities such as energy metabolism, vitamin biosynthesis and transportation. By integrating these data, we revealed 291 robust associations between representative differentially abundant taxonomic species and metabolites, indicating a tight interaction of gut microbiome with metabolites in RNET pathogenesis. Finally, we identified a cluster of gut microbiome and metabolite-based signatures, and replicated them in an independent cohort, showing accurate prediction of such neoplasm from healthy people.

Conclusions: Our current study is the first to comprehensively characterize the perturbed interface of gut microbiome and metabolites in RNET patients, which may provide promising targets for microbiome-based diagnostics and therapies for this disorder.

Keywords: Rectal neuroendocrine tumor, Gut microbiota, Metabolite, Shotgun metagenomic sequencing, Untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics.