Evidence map›Paper›PMID 32124270›Full record

ArticleHuman cell2020

MiR-1297 negatively regulates metabolic reprogramming in glioblastoma via repressing KPNA2.

Huibing Li, Honggang Yuan

Abstract read
PubMed Publisher
In one paragraph

Article in Human cell, 2020. 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
1.4field-weighted citation impact, top 20% 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

10 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Metabolic Rewiring in Glioblastoma Cancer:Frontiers in oncology · 2022
    Review
  7. Article
  8. Observational
  9. Article
  10. Review
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

2 authors at 1 institution in 1 country.

Huibing LiThe People's Hospital of Hanchuan City, No. 1 Renmin Road, Xiaogan, Hanchuan, Hubei, China.
Honggang YuanThe People's Hospital of Hanchuan City, No. 1 Renmin Road, Xiaogan, Hanchuan, Hubei, China. yuanhonggang@aliyun.com.
Xiaochang People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer cell growth is characterized by reprogrammed glucose metabolism and subsequent high rate of glycolysis. The metabolic reprogramming is essential for cell proliferation and drug resistance of cancer cells including glioblastoma (GBM). MicroRNAs play pivotal roles during GBM development. In the present study, we discovered a significant downregulation of miR-1297 in GBM. Decreased miR-1297 expression was associated with prolonged overall survival of patients with glioma. Overexpression of miR-1297 promoted cell proliferation and glycolysis in GBM cells. Bioinformatic analysis (TargetScan and miRanda) indicated that miR-1297 might target 3'UTR of KPNA2, a key regulator of glycolysis in GBM. The regulation was confirmed in a dual-luciferase reporter assay in GBM cells. Furthermore, overexpression of KPNA2 could reverse miR-1297 mimic induced cell growth arrest and inhibition of glycolysis in GBM cells. Finally, a negative correlation between miR-1297 and KPNA2 mRNA levels was observed in GBM tissues. Collectively, the data demonstrated that the abnormal metabolic reprogramming was driven by miR-1297 in GBM and suggested miR-1297 as a tumor suppressor.

Indexed as

Genes, Tumor Suppressoralpha KaryopherinsCell ProliferationDrug Resistance, NeoplasmGene ExpressionGlioblastomaGlycolysisHumansMicroRNAsSurvival RateTumor Cells, Culturedalpha KaryopherinsKPNA2 protein, humanMicroRNAsMIRN1297 microRNA, humanGlioblastomaGlycolysisKPNA2miR-1297

Identifiers

PMID32124270
OpenAlexW3009246150

What OpenQuestion holds

Textmetadata
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.