Evidence map›Paper›PMID 42445401›Full record

ArticleTranslational cancer research2026

DDR1 in esophageal squamous cell carcinoma: bioinformatics discovery and experimental validation.

Yamen Ahmad Muad, Linxiang Zhang, Weiyan Peng, Lin Ye

Abstract read
In one paragraph

Article in Translational cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yamen Ahmad MuadDepartment of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.ORCID https://orcid.org/0009-0007-6156-9013
Linxiang ZhangDepartment of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.ORCID https://orcid.org/0009-0003-8318-6989
Weiyan PengChongqing Key Laboratory of Molecular Oncology and Epigenetics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.ORCID https://orcid.org/0000-0002-9480-5787
Lin YeDepartment of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.ORCID https://orcid.org/0000-0002-4495-5955

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Esophageal squamous cell carcinoma accounts for almost 90% of all esophageal cancer cases. Recent progress in understanding tumor biology, early diagnosis, and surgical techniques has contributed to the improvements in incidence and mortality. However, the discovery of novel biomarkers remains essential for further reducing disease burden and improving clinical outcomes. The study focuses on investigating the function of DDR1 and its potential clinical utility as a biomarker in esophageal squamous cell carcinoma (ESCC). Methods: Five gene expression datasets were included in the study, and a meta-analysis of differentially expressed genes (DEGs) was conducted. Genes identified by three feature selection algorithms were intersected and used for predictive modeling and experimental validation. Clinical validation included reverse transcription quantitative polymerase chain reaction (RT-qPCR) on 40 paired ESCC tumors and adjacent tissues. TE-7 ESCC cells were transfected with anti-miR-199a-5p or pre-miR-199a-5p and analyzed by RT-qPCR and western blotting. Results: DDR1 was significantly upregulated across datasets [pooled average log fold change (FC) =1.06, pooled P<0.05]. A generalized linear model trained using the gene exhibited good performance in classifying tumor and non-tumor samples across four external validation sets. In 40 paired clinical samples, RT-qPCR revealed significantly higher DDR1 and lower miR-199a-5p levels in tumors compared to non-tumor samples (both P<0.001). Anti-miR-199a-5p produced a significant reduction in miR-199a-5p (P=0.041) and a significant increase in DDR1 (P=0.01). MiR-199a-5p inhibition increased DDR1, STAT3, pSTAT3, mesenchymal markers [N-cadherin (CDH2), vimentin (VIM)], and decreased epithelial marker [E-cadherin (CDH1)]. The opposite pattern was observed following miR-199a-5p overexpression (all P<0.05). Conclusions: DDR1 is a candidate biomarker for ESCC. Modulating miR-199a-5p alters DDR1, STAT3 activation, and epithelial-mesenchymal transition (EMT) marker profiles, making miR-199a-5p/DDR1/STAT3/EMT pathway a potential therapeutic target in ESCC.

Indexed as

bioinformaticsDDR1Esophageal squamous cell carcinoma (ESCC)polymerase chain reaction (PCR)Western blot

Identifiers

PMID42445401
PMCPMC13357071

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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.