Evidence map›Paper›PMID 36091722›Full record

ArticleSaudi journal of biological sciences2022

Exploration of metabolic responses towards hypoxia mimetic DMOG in cancer cells by using untargeted metabolomics.

Mohammad Imran Khan

Open access · hybridAbstract read
In one paragraph

Article in Saudi journal of biological sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 39% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
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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

1 author at 1 institution in 1 country.

Mohammad Imran KhanDepartment of Biochemistry, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
King Abdulaziz University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hypoxia is considered as one of the most crucial elements of tumor microenvironment. The hypoxia inducible transcription factors (HIF-1/2) are used by the cancer cells to adapt hypoxic microenvironment through regulating the expression of various target genes, including metabolic enzymes. Dimethyloxalylglycine (DMOG), a hypoxic mimetic used for HIF stabilisation in cell and animal models, also demonstrates multiple metabolic effects. In past, it was shown that in cancer cells, DMOG treatment alters mitochondrial ATP production, glycolysis, respiration etc. However, a global landscape of metabolic level alteration in cancer cells during DMOG treatment is still not established. In the current work, the metabolic landscape of cancer cells during DMOG treatment is explored by using untargeted metabolomics approach. Results showed that DMOG treatment primarily alters the one carbon and lipid metabolism. The levels of one-carbon metabolism related metabolites like serine, ornithine, and homomethionine levels significantly altered during DMOG treatment. Further, DMOG treatment reduces the global fatty acyls like palmitic acids, stearic acids, and arachidonic acid levels in cancer cell lines. Additionally, we found an alteration in glycolytic metabolites known to be regulated by hypoxia in cancer cell lines. Collectively, the results provided novel insights into the metabolic impact of DMOG on cancer cells and showed that the use of DMOG to induce hypoxia yields similar metabolic features relative to physiological hypoxia.

Indexed as

Dimethyloxalylglycine (DMOG)Fatty acylsHypoxiaLipidomicsUntargeted Metabolomics

Identifiers

PMID36091722
PMCPMC9460158
OpenAlexW4292622419

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.