Evidence map›Paper›PMID 28412757›Full record

ReviewOncotarget2017

Fatty acid metabolism in breast cancer subtypes.

Marie E Monaco

Open access · diamondAbstract readReview
In one paragraph

Review in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 126 papers.

0numbers the graph read from it
0cells of the map it votes in
126citing papers in PubMed
5.6field-weighted citation impact, top 3% 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

126 citing papers in PubMed, 204 citations in OpenAlex.

  1. Trial
  2. Toward targeted therapeutics for lobular breast cancer.The Journal of clinical investigation · 2026
    Review
  3. NMR in biomedicine · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Lipid Droplets in Cancer: New Insights and Therapeutic Potential.International journal of molecular sciences · 2026
    Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. Article
  19. Review
  20. Article

66 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.

Marie E MonacoDepartment of Neuroscience & Physiology, New York University School of Medicine, New York, NY, USA.
VA NY Harbor Healthcare System · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dysregulation of fatty acid metabolism is recognized as a component of malignant transformation in many different cancers, including breast; yet the potential for targeting this pathway for prevention and/or treatment of cancer remains unrealized. Evidence indicates that proteins involved in both synthesis and oxidation of fatty acids play a pivotal role in the proliferation, migration and invasion of breast cancer cells. The following essay summarizes data implicating specific fatty acid metabolic enzymes in the genesis and progression of breast cancer, and further categorizes the relevance of specific metabolic pathways to individual intrinsic molecular subtypes of breast cancer. Based on mRNA expression data, the less aggressive luminal subtypes appear to rely on a balance between de novo fatty acid synthesis and oxidation as sources for both biomass and energy requirements, while basal-like, receptor negative subtypes overexpress genes involved in the utilization of exogenous fatty acids. With these differences in mind, treatments may need to be tailored to individual subtypes.

Indexed as

Breast NeoplasmsFatty AcidsFemaleHumansMaleFatty Acidsbreast cancerfatty acid metabolismmolecular subtype

Identifiers

PMID28412757
PMCPMC5438746
OpenAlexW2589411605

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.