Evidence map›Paper›PMID 24954394›Full record

ArticleBMC systems biology2014

Metabolomics of ApcMin/+ mice genetically susceptible to intestinal cancer.

Jean-Eudes J Dazard, Yana Sandlers, Stephanie K Doerner, Nathan A Berger, Henri Brunengraber

Open access · diamondAbstract read
In one paragraph

Article in BMC systems biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 32% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Pleiotropic effects of DCLK1 in cancer and cancer stem cells.Frontiers in molecular biosciences · 2022
    Review
  5. ApcScientific reports · 2020
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Jean-Eudes J DazardCenter for Proteomics and Bioinformatics, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA. jxd101@case.edu.
Yana Sandlers
Stephanie K Doerner
Nathan A Berger
Henri Brunengraber
Case Western Reserve University · USUniversity School · USKennedy Krieger Institute · US

Funding

TUMOR METABOLISM PROGRAMP30CA043703 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI MARK R CHANCE · 1987 to 2026
$142.3M
Transdisciplinary Research on Energetics and CancerU54CA116867 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI BERGER, NATHAN A. · 2005 to 2010
$11.3M
MOUSE GENETIC RESOURCES FOR MULTIGENIC DISEASE ANALYSIS: AIDSP40RR012305 · NCRR · CASE WESTERN RESERVE UNIVERSITY · PI BERGER, NATHAN A. · 1996 to 2011
$6.8M
Dynamic Metabolomics via Isotopomer Analysis(RMI)R33DK070291 · NIDDK · CASE WESTERN RESERVE UNIVERSITY · PI BRUNENGRABER, HENRI · 2004 to 2006
$3.3M
NCI NIH HHS 5U54CA116867NCI NIH HHS P30 CA043703NCI NIH HHS P30-CA043703NCI NIH HHS U54 CA116867NCRR NIH HHS 5P40RR12305NCRR NIH HHS P40 RR012305NIDDK NIH HHS 5R33DK070291NIDDK NIH HHS R33 DK070291
6 · The paper itself

Abstract

backgroundTo determine how diets high in saturated fat could increase polyp formation in the mouse model of intestinal neoplasia, ApcMin/+, we conducted large-scale metabolome analysis and association study of colon and small intestine polyp formation from plasma and liver samples of ApcMin/+ vs. wild-type littermates, kept on low vs. high-fat diet. Label-free mass spectrometry was used to quantify untargeted plasma and acyl-CoA liver compounds, respectively. Differences in contrasts of interest were analyzed statistically by unsupervised and supervised modeling approaches, namely Principal Component Analysis and Linear Model of analysis of variance. Correlation between plasma metabolite concentrations and polyp numbers was analyzed with a zero-inflated Generalized Linear Model.

resultsPlasma metabolome in parallel to promotion of tumor development comprises a clearly distinct profile in ApcMin/+ mice vs. wild type littermates, which is further altered by high-fat diet. Further, functional metabolomics pathway and network analyses in ApcMin/+ mice on high-fat diet revealed associations between polyp formation and plasma metabolic compounds including those involved in amino-acids metabolism as well as nicotinamide and hippuric acid metabolic pathways. Finally, we also show changes in liver acyl-CoA profiles, which may result from a combination of ApcMin/+-mediated tumor progression and high fat diet. The biological significance of these findings is discussed in the context of intestinal cancer progression.

conclusionsThese studies show that high-throughput metabolomics combined with appropriate statistical modeling and large scale functional approaches can be used to monitor and infer changes and interactions in the metabolome and genome of the host under controlled experimental conditions. Further these studies demonstrate the impact of diet on metabolic pathways and its relation to intestinal cancer progression. Based on our results, metabolic signatures and metabolic pathways of polyposis and intestinal carcinoma have been identified, which may serve as useful targets for the development of therapeutic interventions.

Indexed as

Genetic Predisposition to DiseaseAdenomatous Polyposis Coli ProteinAnimalsDiet, High-FatGenotypeHumansIntestinal NeoplasmsIntestinal PolypsLiverMaleMass SpectrometryMetabolomicsMiceAdenomatous Polyposis Coli Protein

Identifiers

PMID24954394
PMCPMC4099115
OpenAlexW2131060845

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.