Evidence map›Paper›PMID 34943182›Full record

ArticleBiology2021

Breast Cancer Cell Subtypes Display Different Metabolic Phenotypes That Correlate with Their Clinical Classification.

Consuelo Ripoll, Mar Roldan, Maria J Ruedas-Rama, Angel Orte, Miguel Martin

Abstract read
In one paragraph

Article in Biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Review
  7. Omics-Based Investigations of Breast Cancer.Molecules (Basel, Switzerland) · 2023
    Review
  8. Article
  9. Article
  10. 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.

Consuelo RipollNanoscopy-UGR Laboratory, Departamento de Fisicoquimica, Unidad de Excelencia de Química Aplicada a Biomedicina y Medioambiente, Facultad de Farmacia, Universidad de Granada, Campus Cartuja, 18071 Granada, Spain.
Mar RoldanGENYO, Pfizer-Universidad de Granada-Junta de Andalucia Centre for Genomics and Oncological Research, Avda Ilustracion 114, PTS, 18016 Granada, Spain.
Maria J Ruedas-RamaNanoscopy-UGR Laboratory, Departamento de Fisicoquimica, Unidad de Excelencia de Química Aplicada a Biomedicina y Medioambiente, Facultad de Farmacia, Universidad de Granada, Campus Cartuja, 18071 Granada, Spain.ORCID 0000-0003-0853-187X
Angel OrteNanoscopy-UGR Laboratory, Departamento de Fisicoquimica, Unidad de Excelencia de Química Aplicada a Biomedicina y Medioambiente, Facultad de Farmacia, Universidad de Granada, Campus Cartuja, 18071 Granada, Spain.ORCID 0000-0003-1905-4183
Miguel MartinGENYO, Pfizer-Universidad de Granada-Junta de Andalucia Centre for Genomics and Oncological Research, Avda Ilustracion 114, PTS, 18016 Granada, Spain.

Funding

Spanish Ministry of Science and Innovation, European Regional Development Fund CTQ2017-85658-R
6 · The paper itself

Abstract

Metabolic reprogramming of cancer cells represents an orchestrated network of evolving molecular and functional adaptations during oncogenic progression. In particular, how metabolic reprogramming is orchestrated in breast cancer and its decisive role in the oncogenic process and tumor evolving adaptations are well consolidated at the molecular level. Nevertheless, potential correlations between functional metabolic features and breast cancer clinical classification still represent issues that have not been fully studied to date. Accordingly, we aimed to investigate whether breast cancer cell models representative of each clinical subtype might display different metabolic phenotypes that correlate with current clinical classifications. In the present work, functional metabolic profiling was performed for breast cancer cell models representative of each clinical subtype based on the combination of enzyme inhibitors for key metabolic pathways, and isotope-labeled tracing dynamic analysis. The results indicated the main metabolic phenotypes, so-called 'metabophenotypes', in terms of their dependency on glycolytic metabolism or their reliance on mitochondrial oxidative metabolism. The results showed that breast cancer cell subtypes display different metabophenotypes. Importantly, these metabophenotypes are clearly correlated with the current clinical classifications.

Indexed as

breast cancermetabolic profilingmetabolic reprogrammingtumor metabolism

Identifiers

PMID34943182
PMCPMC8698801

What OpenQuestion holds

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Registered trials

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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.