Evidence map›Paper›PMID 36124026›Full record

ReviewDisease markers2022

lncRNAs: Key Regulators of Signaling Pathways in Tumor Glycolysis.

Li Wen, Chang Tan, Shuai Ma, Xinzhi Li

Open access · hybridAbstract readReview
In one paragraph

Review in Disease markers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.5field-weighted citation impact, top 42% 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, 5 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Transcriptional Regulation of De Novo Lipogenesis by SIX1 in Liver Cancer Cells.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  6. 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

4 authors at 1 institution in 1 country.

Li WenDepartment of Orthopedics, Renhe Hospital Affiliated to Three Gorges University, Yichang, China.
Chang TanDepartment of Orthopedics, Renhe Hospital Affiliated to Three Gorges University, Yichang, China.
Shuai MaDepartment of Orthopedics, Renhe Hospital Affiliated to Three Gorges University, Yichang, China.
Xinzhi LiDepartment of Orthopedics, Renhe Hospital Affiliated to Three Gorges University, Yichang, China.ORCID https://orcid.org/0000-0002-3327-6017
China Three Gorges University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In response to overstimulation of growth factor signaling, tumor cells can reprogram their metabolism to preferentially utilize and metabolize glucose to lactate even in the presence of abundant oxygen, which is termed the "Warburg effect" or aerobic glycolysis. Long noncoding RNAs (lncRNAs) are a group of transcripts longer than 200 nucleotides and do not encode proteins. Accumulating evidence suggests that lncRNAs can affect aerobic glycolysis through multiple mechanisms, including the regulation of glycolytic transporters and key rate-limiting enzymes. In addition, maladjusted signaling pathways are critical for glycolysis. Therefore, this article mainly reviews the lncRNAs involved in the regulation of tumor glycolysis key signal pathways in recent years and provides an in-depth understanding of the role of differentially expressed lncRNAs in the key signal pathways of glucose metabolism, which may help to provide new therapeutic targets and new diagnostic and prognostic markers for human cancer.

Indexed as

NeoplasmsRNA, Long NoncodingGlucoseGlycolysisHumansLactic AcidNucleotidesOxygenSignal TransductionGlucoseLactic AcidNucleotidesOxygenRNA, Long Noncoding

Identifiers

PMID36124026
PMCPMC9482549
OpenAlexW4295110306

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.