Evidence map›Paper›PMID 41244072›Full record

ArticleBioMed research international2025

The LBX2-AS1-miR-491-5p-PKM2 Positive Feedback Loop Promotes Radiation Resistance of Esophageal Cancer by Enhancing Glycolysis.

Fuhui Zhang, Zhiwu Wang, Xuemin Yao, Qingyu Zhang

Abstract read
In one paragraph

Article in BioMed research international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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

1 citing paper in PubMed.

  1. Article
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.

Fuhui ZhangDepartment of Gastroenterology, Tianjin Medical University General Hospital, Tianjin, China, tjmugh.com.cn.ORCID https://orcid.org/0009-0007-3253-1243
Zhiwu WangDepartment of Radiation and Chemotherapy Division, Tangshan People's Hospital, Tangshan, China, tsrmyy.cn.ORCID https://orcid.org/0000-0003-3904-4513
Xuemin YaoDepartment of Radiation and Chemotherapy Division, North China University of Science and Technology Affiliated Hospital, Tangshan, China, ncst.edu.cn.ORCID https://orcid.org/0009-0007-7265-6040
Qingyu ZhangDepartment of Gastroenterology, Tianjin Medical University General Hospital, Tianjin, China, tjmugh.com.cn.ORCID https://orcid.org/0009-0007-8438-7124

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objective: Radioresistance is a significant factor affecting the therapeutic efficacy of radiotherapy. This study is aimed at investigating the molecular mechanism by which LBX2-AS1 regulates pyruvate kinase M2 (PKM2) to influence radioresistance and its potential as a biomarker for radioresistance in esophageal cancer. Methods and Key Findings: Radioresistant sub-cell lines, KYSE150R, were established in KYSE150 cells, and PKM2, cyclin D1, HIF-1 Conclusion and Clinical Implications: LBX2-AS1-miR-491-5p-PKM2 positive feedback loop enhances the radioresistance of esophageal cancer cells by altering the cell cycle and enhancing glycolysis. High level of LBX2-AS1 in serum was correlated with worse DCR, lymphatic metastasis, worse overall survival, and progression-free survival.

Indexed as

Carrier ProteinsEsophageal NeoplasmsGlycolysisMembrane ProteinsMicroRNAsRadiation ToleranceRNA, Long NoncodingThyroid HormonesCell Line, TumorCell ProliferationCyclin D1Feedback, PhysiologicalGene Expression Regulation, NeoplasticHumansHypoxia-Inducible Factor 1, alpha SubunitThyroid Hormone-Binding ProteinsCarrier ProteinsCyclin D1HIF1A protein, humanHypoxia-Inducible Factor 1, alpha SubunitMembrane ProteinsMicroRNAsRNA, Long NoncodingThyroid Hormone-Binding ProteinsThyroid Hormonesesophageal cancerglycolysisLBX2-AS1PKM2radiotherapy

Identifiers

PMID41244072
PMCPMC12612690

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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.