Evidence map›Paper›PMID 25632377›Full record

ArticleCurrent Metabolomics2014

Recent Advances in Metabolic Profiling And Imaging of Prostate Cancer.

Roopa Thapar, Mark A Titus

Abstract read
In one paragraph

Article in Current Metabolomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
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

18 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Prostate Cancer Energetics and Biosynthesis.Advances in experimental medicine and biology · 2019
    Review
  11. Article
  12. Article
  13. Review
  14. Review
  15. Review
  16. Review
  17. Article
  18. 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

2 authors.

Roopa ThaparDepartment of Biochemistry and Cell Biology, Rice University, Houston, TX 77251-1892, USA.
Mark A TitusDepartment of Genitourinary Medical Oncology, The University of Texas M.D. Anderson Cancer Center, Houston TX 77030, USA.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
NCI NIH HHS P30 CA016672
6 · The paper itself

Abstract

Cancer is a metabolic disease. Cancer cells, being highly proliferative, show significant alterations in metabolic pathways such as glycolysis, respiration, the tricarboxylic acid (TCA) cycle, oxidative phosphorylation, lipid metabolism, and amino acid metabolism. Metabolites like peptides, nucleotides, products of glycolysis, the TCA cycle, fatty acids, and steroids can be an important read out of disease when characterized in biological samples such as tissues and body fluids like urine, serum, etc. The cancer metabolome has been studied since the 1960s by analytical techniques such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. Current research is focused on the identification and validation of biomarkers in the cancer metabolome that can stratify high-risk patients and distinguish between benign and advanced metastatic forms of the disease. In this review, we discuss the current state of prostate cancer metabolomics, the biomarkers that show promise in distinguishing indolent from aggressive forms of the disease, the strengths and limitations of the analytical techniques being employed, and future applications of metabolomics in diagnostic imaging and personalized medicine of prostate cancer.

Indexed as

BiomarkerCastration-Resistant Prostate CancerMagnetic Resonance SpectroscopyMass SpectrometryMetabolic ImagingMetabolomicsNuclear Magnetic ResonanceProstate Cancer

Identifiers

PMID25632377
PMCPMC4306198

What OpenQuestion holds

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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.