Evidence map›Paper›PMID 28340574›Full record

ArticleJournal of translational medicine2017

Myocyte enhancer factor 2D provides a cross-talk between chronic inflammation and lung cancer.

Hai-Xing Zhu, Lin Shi, Yong Zhang, Yi-Chun Zhu, Chun-Xue Bai, Xiang-Dong Wang, Jie-Bai Zhou

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 28% 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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.

  1. Pooled it
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  7. MEF2D Functions as a Tumor Suppressor in Breast Cancer.International journal of molecular sciences · 2024
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  10. Comprehensive bioinformatics analysis forTranslational cancer research · 2022
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  20. Comparison of microRNA Profiles between Bovine Mammary Glands Infected withInternational journal of biological sciences · 2018
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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

7 authors at 3 institutions in 1 country.

Hai-Xing ZhuDepartment of Pulmonary Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Lin ShiDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
Yong ZhangDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
Yi-Chun ZhuDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
Chun-Xue BaiDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
Xiang-Dong WangInstitute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai, China.
Jie-Bai ZhouDepartment of Pulmonary Medicine, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China. zhou.jiebai@zs-hospital.sh.cn.
Fudan University · CNZhongshan Hospital · CNRuijin Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung cancer is the leading cause of cancer-related morbidity and mortality worldwide. Patients with chronic respiratory diseases, such as chronic obstructive pulmonary disease (COPD), are exposed to a higher risk of developing lung cancer. Chronic inflammation may play an important role in the lung carcinogenesis among those patients. The present study aimed at identifying candidate biomarker predicting lung cancer risk among patients with chronic respiratory diseases.

methodsWe applied clinical bioinformatics tools to analyze different gene profile datasets with a special focus on screening the potential biomarker during chronic inflammation-lung cancer transition. Then we adopted an in vitro model based on LPS-challenged A549 cells to validate the biomarker through RNA-sequencing, quantitative real time polymerase chain reaction, and western blot analysis.

resultsBioinformatics analyses of the 16 enrolled GSE datasets from Gene Expression Omnibus online database showed myocyte enhancer factor 2D (MEF2D) level significantly increased in COPD patients coexisting non-small-cell lung carcinoma (NSCLC). Inflammation challenge increased MEF2D expression in NSCLC cell line A549, associated with the severity of inflammation. Extracellular signal-regulated protein kinase inhibition could reverse the up-regulation of MEF2D in inflammation-activated A549. MEF2D played a critical role in NSCLC cell bio-behaviors, including proliferation, differentiation, and movement.

conclusionsInflammatory conditions led to increased MEF2D expression, which might further contribute to the development of lung cancer through influencing cancer microenvironment and cell bio-behaviors. MEF2D might be a potential biomarker during chronic inflammation-lung cancer transition, predicting the risk of lung cancer among patients with chronic respiratory diseases.

Indexed as

A549 CellsCarcinoma, Non-Small-Cell LungExtracellular Signal-Regulated MAP KinasesGene Expression Regulation, NeoplasticHumansInflammationLipopolysaccharidesLung NeoplasmsMEF2 Transcription FactorsPulmonary Disease, Chronic ObstructiveRNA, MessengerSignal TransductionUp-RegulationExtracellular Signal-Regulated MAP KinasesLipopolysaccharidesMEF2 Transcription FactorsRNA, MessengerBiomarkerClinical bioinformaticsInflammationLung cancerMyocyte enhancer factor 2D

Identifiers

PMID28340574
PMCPMC5366127
OpenAlexW2598704805

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Registered trials

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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.