Evidence map›Paper›PMID 39156867›Full record

ArticleInternational journal of molecular and cellular medicine2024

Gene Expression of Glycolysis Enzymes in MCF-7 Breast Cancer Cells Exposed to Warburg Effect and Hypoxia.

Irem Bayar, Gamze Sevri Ekren Asici, Ayşegül Bildik, Funda Kiral

Abstract read
In one paragraph

Article in International journal of molecular and cellular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Potential Strategies Applied byPathogens (Basel, Switzerland) · 2025
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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

4 authors.

Irem BayarSelcuk University Faculty of Veterinary, Department of Biochemistry Konya, Turkey.
Gamze Sevri Ekren AsiciAdnan Menderes University Faculty of Veterinary, Department of Biochemistry Aydın, Turkey.
Ayşegül BildikAdnan Menderes University Faculty of Veterinary, Department of Biochemistry Aydın, Turkey.
Funda KiralAdnan Menderes University Faculty of Veterinary, Department of Biochemistry Aydın, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hypoxia can cause significant changes in the glucose metabolism of cancer cells that prefer aerobic glycolysis for energy production instead of the conventional oxidative phosphorylation mechanism. In this study, breast cancer cells (MCF-7) were exposed to glucose (0-5.5-15-55 mM), during specific incubation periods (3, 6, 12, or 24 hours) under normoxic and hypoxic conditions. The expression levels of hypoxia-inducible factor-1α (HIF-1α), glucose transporter-1 (GLUT-1), and glycolytic enzymes at varying glucose concentrations in cells were investigated in the different oxygen environments. It was determined that glycolytic enzymes [Hexokinase 2 (HK2), Pyruvate Kinase M2 (PKM2), Glucose-6-phosphate dehydrogenase (G6PD), Lactate Dehydrogenase A (LDHA), Glyceraldehyde-3-phosphate Dehydrogenase (GAPDH), and Phosphofructokinase M (PFKM)] increased at the transcriptional level, especially in the first hours. This increase indicates that major metabolic reprogramming in response to hypoxia probably occurs over a short period of time. The increase in G6PD gene expression under high glucose and hypoxia conditions suggests that the pentose phosphate pathway (PPP) is used by cancer cells to synthesize necessary precursors for the cell. The results of the study showed that there is a significant interaction between hypoxia and glycolytic metabolism in cancer cells. It is thought that metabolic pathways activated by hypoxia and related genes located in these pathways will contribute to the literature by offering the potential to be target molecules for therapeutic purposes.

Indexed as

gene expressionGlucoseglycolysishypoxiaMCF-7normoxia

Identifiers

PMID39156867
PMCPMC11329934

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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.