Evidence map›Paper›PMID 24958139›Full record

ArticleMetabolites2013

A review of applications of metabolomics in cancer.

Richard D Beger

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Metabolites, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03736993 (Towards Better Therapy for Resectable Lung Cancer), which is not on this map. Cited by 137 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
137citing papers in PubMed, 1 pooled it
6.7field-weighted citation impact, top 2% 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.

NCT03736993 nacompletednot on this mapstarted 2018, after this paper: background citation

Towards Better Therapy for Resectable Lung Cancer: Metabolomics Predict Therapy Response

TypeinterventionalSponsorHasselt UniversityRan2018 to 2022Enrolled160ConditionsNSCLC, Stage IIIAArmsAdditional blood sampling
3 · Its place in the literature

Who cites it

137 citing papers in PubMed, 1 synthesis or guideline pooled it, 295 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Review
  10. Article
  11. Review
  12. Review
  13. Review
  14. Review
  15. Article
  16. Review
  17. Article
  18. Article
  19. Review
  20. Article

77 more citing papers are in PubMed but not listed here.

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

1 author at 1 institution in 1 country.

Richard D BegerNational Center for Toxicological Research, US Food and Drug Administration, 3900 NCTR Road, Jefferson, AR 72079, USA. Richard.Beger@fda.hhs.gov.
National Center for Toxicological Research · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is a devastating disease that alters the metabolism of a cell and the surrounding milieu. Metabolomics is a growing and powerful technology capable of detecting hundreds to thousands of metabolites in tissues and biofluids. The recent advances in metabolomics technologies have enabled a deeper investigation into the metabolism of cancer and a better understanding of how cancer cells use glycolysis, known as the "Warburg effect," advantageously to produce the amino acids, nucleotides and lipids necessary for tumor proliferation and vascularization. Currently, metabolomics research is being used to discover diagnostic cancer biomarkers in the clinic, to better understand its complex heterogeneous nature, to discover pathways involved in cancer that could be used for new targets and to monitor metabolic biomarkers during therapeutic intervention. These metabolomics approaches may also provide clues to personalized cancer treatments by providing useful information to the clinician about the cancer patient's response to medical interventions.

Identifiers

PMID24958139
PMCPMC3901293
OpenAlexW2065342065

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.