Evidence map›Paper›PMID 27358718›Full record

ReviewComputational and structural biotechnology journal2016

MicroRNAs and oncogenic transcriptional regulatory networks controlling metabolic reprogramming in cancers.

Pannapa Pinweha, Khanti Rattanapornsompong, Varodom Charoensawan, Sarawut Jitrapakdee

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Computational and structural biotechnology journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 1 pooled it
4.8field-weighted citation impact, top 4% 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

52 citing papers in PubMed, 1 synthesis or guideline pooled it, 74 citations in OpenAlex.

  1. Pooled it
  2. New insights into the ACLY-mediated metabolic and epigenetic interplay in macrophages.Journal of enzyme inhibition and medicinal chemistry · 2026
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  10. MicroRNAs in metabolism for precision treatment of lung cancer.Cellular & molecular biology letters · 2024
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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 at 1 institution in 1 country.

Pannapa PinwehaDepartment of Biochemistry, Faculty of Science, Mahidol University, Bangkok 10400, Thailand.
Khanti RattanapornsompongDepartment of Biochemistry, Faculty of Science, Mahidol University, Bangkok 10400, Thailand.
Varodom CharoensawanDepartment of Biochemistry, Faculty of Science, Mahidol University, Bangkok 10400, Thailand; Integrative Computational BioScience (ICBS) Center, Mahidol University, Nakhon Pathom 73170, Thailand.
Sarawut JitrapakdeeDepartment of Biochemistry, Faculty of Science, Mahidol University, Bangkok 10400, Thailand.
Mahidol University · TH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Altered cellular metabolism is a fundamental adaptation of cancer during rapid proliferation as a result of growth factor overstimulation. We review different pathways involving metabolic alterations in cancers including aerobic glycolysis, pentose phosphate pathway, de novo fatty acid synthesis, and serine and glycine metabolism. Although oncoproteins, c-MYC, HIF1α and p53 are the major drivers of this metabolic reprogramming, post-transcriptional regulation by microRNAs (miR) also plays an important role in finely adjusting the requirement of the key metabolic enzymes underlying this metabolic reprogramming. We also combine the literature data on the miRNAs that potentially regulate 40 metabolic enzymes responsible for metabolic reprogramming in cancers, with additional miRs from computational prediction. Our analyses show that: (1) a metabolic enzyme is frequently regulated by multiple miRs, (2) confidence scores from prediction algorithms might be useful to help narrow down functional miR-mRNA interaction, which might be worth further experimental validation. By combining known and predicted interactions of oncogenic transcription factors (TFs) (c-MYC, HIF1α and p53), sterol regulatory element binding protein 1 (SREBP1), 40 metabolic enzymes, and regulatory miRs we have established one of the first reference maps for miRs and oncogenic TFs that regulate metabolic reprogramming in cancers. The combined network shows that glycolytic enzymes are linked to miRs via p53, c-MYC, HIF1α, whereas the genes in serine, glycine and one carbon metabolism are regulated via the c-MYC, as well as other regulatory organization that cannot be observed by investigating individual miRs, TFs, and target genes.

Indexed as

2-HG, 2-hydroxyglutarateACC, acetyl-CoA carboxylaseACL, ATP-citrate lyaseBRCA1, breast cancer type 1 susceptibility proteinCancerc-MYC, V-myc avian myelocytomatosis viral oncogene homologFAS, fatty acid synthaseFH, fumarate hydrataseG6PD, glucose-6-phosphate dehydrogenaseGDH, glutamate dehydrogenaseGLS, glutaminaseGLUT, glucose transporterHIF1α, hypoxia inducible factor 1αHK, hexokinaseIDH, isocitrate dehydrogenaseMCT, monocarboxylic acid transporterME, malic enzymeMetabolismMicroRNAmiR/miRNA, LDH, lactate dehydrogenase micro RNAOncogenep53, tumor protein p53PC, pyruvate carboxylasePDH, pyruvate dehydrogenasePDK, pyruvate dehydrogenase kinasePEPCK, phosphoenolpyruvate carboxykinasePEP, phosphoenolpyruvatePFK, phosphofructokinasePGK, phosphoglycerate kinase (PGK)PHGDH, phosphoglycerate dehydrogenasePKM, muscle-pyruvate kinasePPP, pentose phosphate pathwayPSAT, phosphoserine aminotransferasePSPH, phosphoserine phosphataseSDH, succinate dehydrogenaseSHMT, serine hydroxymethyl transferaseSREBP1, sterol regulatory element binding protein 1TCA, tricarboxylic acidTFs, transcription factorsTranscriptional regulation network

Identifiers

PMID27358718
PMCPMC4915959
OpenAlexW2416158141

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.