Cited by 57Metabolomics and Mass Spectrometry StudiesGut microbiota and healthAdvanced Chemical Sensor Technologies

1H NMR‐based metabolomics reveal overlapping discriminatory metabolites and metabolic pathway disturbances between colorectal tumor tissues and fecal samples

Open access
Lin, Yan, Ma, Changchun, Bezabeh, Tedros, Wang, Zhening, Liang, Jiahao, Huang, Yao, Zhao, Jiayun, Liu, Xinmu +4 more·2019·International Journal of Cancer

Abstract

Previous studies have compared fecal metabolites from healthy and colorectal cancer (CRC) patients to predict the pro‐CRC signatures. However, the systemic mechanistic link between feces and colonic tissues of CRC patients is still limited. The current study was a paralleled investigation of colonic tumor tissues and their normal adjacent tissues alongside patient‐matched feces by using 1H nuclear magnetic resonance spectroscopy combined with pattern recognition to investigate how fecal metabolic phenotypes are linked to the changes in colorectal tumor profiles. A set of overlapping discriminatory metabolites across feces and tumor tissues of CRC were identified, including elevated levels of lactate, glutamate, alanine, succinate and reduced amounts of butyrate. These changes could indicate the networks for metabolic pathway perturbations in CRC potentially involved in the disruptions of glucose and glycolytic metabolism, TCA cycle, glutaminolysis, and short chain fatty acids metabolism. Furthermore, changes in fecal acetate were positively correlated with alterations of glucose and myo‐inositol in colorectal tumor tissues, implying enhanced energy production for rapid cell proliferation. Compared to other fecal metabolites, acetate demonstrated the highest diagnostic performance for diagnosing CRC, with an AUC of 0.843 in the training set, and a good predictive ability in the validation set. Overall, these associations provide evidence of distinct metabolic signatures and metabolic pathway disturbances between the colonic tissues and feces within the same individual, and changes of fecal metabolic signature could reflect the CRC tissue microenvironment, highlighting the significance of the distinct fecal metabolic profiles as potential novel and noninvasive relevant indicators for CRC detection.

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 · 10.1002/ijc.32190

Cites

38 of 38 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?

  • A few cross-sectional studies reported that colorectal cancer patients had a lower abundance of butyrate-producing species and lower fecal butyrate levels than controls.

    “a few cross-sectional studies reported that patients with CRC had a lower abundance of butyrate-producing species and lower fecal levels of butyrate than controls (Table 1).97, 133–135”

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: 5

  1. Siegel R, Naishadham D, Jemal A. Cancer statis- tics, 2013. CA Cancer J Clin 2013;63:11-30.
  2. Quintero E. Chemical or immunological tests for the detection of fecal occult blood in colorectal cancer screening? Gastroenterol Hepatol 2009;32:565-76.
  3. Yanes O, Tautenhahn R, Patti GJ, et al. Expand- ing coverage of the metabolome for global metab- olite profiling. Anal Chem 2011;83:2152-61.
  4. Tian Y, Xu T, Huang J, et al. Tissue Metabonomic Phenotyping for diagnosis and prognosis of human colorectal cancer. Sci Rep 2014;6:20790.
  5. Wang H, Wang L, Zhang H, et al. (1)H NMR- based metabolic profiling of human rectal cancer tissue. Mol Cancer 2013;12:121.

Cited by

Sorted by citations

Authors
Lin, Y., Ma, C., Bezabeh, T., Wang, Z., Liang, J., Huang, Y., Zhao, J., Liu, X., Ye, W., Tang, W., Ouyang, T., & Wu, R.
Affiliations
  • Shantou University (CN)
  • Cancer Hospital of Shantou University Medical College (CN)
  • University of Guam (GU)
  • Department of Radiology Second Affiliated Hospital, Shantou University Medical College Shantou Guangdong Province China
Corresponding author
  • Lin, Yan
  • Wu, Renhua
Venue
International Journal of Cancer
Publisher
Wiley
Published
2019-03-04
Volume
145
Issue
6
Pages
1679-1689
ISSN
  • 0020-7136 (ISSN-L)
  • 1097-0215
OpenAlex
W2911842670
Cited by
57
References
38
Citations by year
2026: 4 · 2025: 6 · 2024: 10 · 2023: 9 · 2022: 8 · 2021: 12 · 2020: 6 · 2019: 2
FWCI
2.32
Type
journal article
Language
en
Open access
Locations
  • International Journal of Cancer (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Natural Science Foundation of China (81471729, 81101102)
  • Department of Education of Guangdong Province (2017KTSCX071)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Physical Sciences › Engineering › Biomedical Engineering › Advanced Chemical Sensor Technologies
Keywords
colorectal cancer, fecal metabolites, tumor microenvironment, short-chain fatty acids, butyrate, lactate, glutamine metabolism, TCA cycle, glycolysis, myo-inositol, non-invasive cancer diagnosis, diagnostic biomarkers
MeSH terms
Feces, Female, Humans, Male, Middle Aged, Biomarkers, Tumor, Colorectal Neoplasms, Case-Control Studies, Early Detection of Cancer, Metabolomics, Proton Magnetic Resonance Spectroscopy

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