Cited by 1,924Gut microbiota and healthDrug Transport and Resistance MechanismsCholangiocarcinoma and Gallbladder Cancer Studies

Bile acid-microbiota crosstalk in gastrointestinal inflammation and carcinogenesis

Open access
Jia, Wei, Xie, Guoxiang, Jia, Weiping·2018·Nature Reviews Gastroenterology & Hepatology

Abstract

Emerging evidence points to a strong association between the gut microbiota and the risk, development and progression of gastrointestinal cancers such as colorectal cancer (CRC) and hepatocellular carcinoma (HCC). Bile acids, produced in the liver, are metabolized by enzymes derived from intestinal bacteria and are critically important for maintaining a healthy gut microbiota, balanced lipid and carbohydrate metabolism, insulin sensitivity and innate immunity. Given the complexity of bile acid signalling and the direct biochemical interactions between the gut microbiota and the host, a systems biology perspective is required to understand the liver-bile acid-microbiota axis and its role in gastrointestinal carcinogenesis to reverse the microbiota-mediated alterations in bile acid metabolism that occur in disease states. An examination of recent research progress in this area is urgently needed. In this Review, we discuss the mechanistic links between bile acids and gastrointestinal carcinogenesis in CRC and HCC, which involve two major bile acid-sensing receptors, farnesoid X receptor (FXR) and G protein-coupled bile acid receptor 1 (TGR5). We also highlight the strategies and cutting-edge technologies to target gut-microbiota-dependent alterations in bile acid metabolism in the context of cancer therapy.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/nrgastro.2017.119

Cites

215 of 215 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Gut bacteria produce a large array of metabolites that serve as important signaling factors and energy substrates, such as bile acids, choline, neurotransmitters, and short-chain fatty acids.

    “These bacteria produce a large array of metabolites that serve as important signaling factors and energy substrates, such as bile acids (BA), choline, neurotransmitters, and short-chain fatty acids (SCFA) [213].”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 7

  1. [41]Hylemon PB Bile acids as regulatory molecules J Lipid Res 50 1509 1520 2009 19346331 PMC2724047
  2. [120]Bernstein H Bernstein C Payne CM Dvorak K Bile acids as endogenous etiologic agents in gastrointestinal cancer World J Gastroenterol 15 3329 3340 2009 19610133 PMC2712893
  3. [142]Calmus Y Poupon R Shaping macrophages function and innate immunity by bile acids: Mechanisms and implication in cholestatic liver diseases Clin Res Hepatol Gastroenterol 38 550 556 2014 25176586
  4. [152]Gerard P Metabolism of cholesterol and bile acids by the gut microbiota Pathogens 3 14 24 2013 25437605 PMC4235735
  5. [188]Hohenester S A biliary HCO3− umbrella constitutes a protective mechanism against bile acid-induced injury in human cholangiocytes Hepatology 55 173 183 2012 21932391
  6. [203]Martin FPJ A top-down systems biology view of microbiome-mammalian metabolic interactions in a mouse model Molecular Systems Biology 3 112 2007 17515922 PMC2673711
  7. [225]Pellicciari R Discovery of 6alpha-ethyl-23(S)-methylcholic acid (S-EMCA, INT-777) as a potent and selective agonist for the TGR5 receptor, a novel target for diabesity Journal of medicinal chemistry 52 7958 2009 20014870

Cited by

Sorted by citations

Authors
Jia, W., Xie, G., & Jia, W.
Affiliations
Shanghai Jiao Tong University (CN)
Corresponding author
Jia, Wei
Venue
Nature Reviews Gastroenterology & Hepatology
Published
2017-10-11
Volume
15
Issue
2
Pages
111-128
ISSN
  • 1759-5045 (ISSN-L)
  • 1759-5053
OpenAlex
W2761145411
Cited by
1,924
References
215
Citations by year
2026: 263 · 2025: 285 · 2024: 320 · 2023: 292 · 2022: 305 · 2021: 208 · 2020: 142 · 2019: 74 · 2018: 34
FWCI
6.45
Type
journal article
Language
en
Open access
Locations
  • Nature Reviews Gastroenterology & Hepatology (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
Funders
National Cancer Institute (U01CA188387, P30CA071789)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Health Sciences › Medicine › Oncology › Drug Transport and Resistance Mechanisms
  • Health Sciences › Medicine › Surgery › Cholangiocarcinoma and Gallbladder Cancer Studies
Keywords
bile acids, gut microbiota, gastrointestinal inflammation, gastrointestinal carcinogenesis, colorectal cancer, hepatocellular carcinoma, farnesoid X receptor, TGR5, bile acid metabolism
MeSH terms
Gastrointestinal Microbiome, Bile Acids and Salts, Biological Transport, Digestive System Neoplasms, Gastroenteritis, Hepatitis, Carcinoma, Hepatocellular, Humans, Liver Neoplasms, Signal Transduction, Carcinogenesis

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review