Evidence map›Paper›PMID 41671297›Full record

SynthesisPloS one2026

Identifying regulatory driver motifs in non-small cell lung carcinoma via a systematic approach.

Rahul Kumar, Sheersh Massey, Sarah Albogami, Abdulaziz A Aloliqi, Abdulaziz Asiri, Maher M Aljohani, Hashim M Aljohani, Atul Kumar, Kapil Dev

Abstract readMeta-Analysis
In one paragraph

Synthesis in PloS one, 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

9 authors.

Rahul KumarMedical Biotechnology Lab, Department of Biotechnology, Jamia Millia Islamia, New Delhi, India.
Sheersh MasseyHuman Genetics Lab, Department of Biosciences, Jamia Millia Islamia, New Delhi, India.
Sarah AlbogamiDepartment of Biotechnology, College of Science, Taif University, Taif, Saudi Arabia.
Abdulaziz A AloliqiDepartment of Basic Health Sciences, College of Applied Medical Sciences, Qassim University, Buraydah, Al-Qassim, Saudi Arabia.
Abdulaziz AsiriDepartment of Medical Laboratory Sciences, College of Applied Medical Sciences, University of Bisha, Bisha, Saudi Arabia.
Maher M AljohaniDepartment of Basic Medical Sciences, College of Medicine, Taibah University, Medina, Saudi Arabia.
Hashim M AljohaniDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Taibah University, Medina, Saudi Arabia.
Atul KumarMedical Biotechnology Lab, Department of Biotechnology, Jamia Millia Islamia, New Delhi, India.
Kapil DevMedical Biotechnology Lab, Department of Biotechnology, Jamia Millia Islamia, New Delhi, India.ORCID https://orcid.org/0000-0002-3995-2370

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung cancer exhibits highest incidence among all cancer types worldwide and even after rigorous research and advanced treatment strategies, it constitutes a primary cause of cancer-related mortality. Non-small cell lung cancer is the predominant subtype, constituting the majority of lung cancer cases. Therefore, exploring novel biomarkers is crucial for betterment of diagnostic and therapeutic approaches.

methodsThe meta-analysis was performed using GEO datasets, to explore the differentially expressed genes (DEGs) and miRNAs (DEMs) in the non-small cell lung cancer (NSCLC) cases. We explored the ChEA database to extract the relevant transcription factors regulating the expression of our hub genes. Further, based on the highest degree of centrality, the feed-forward loop was identified with highest sub-network motif comprising of gene-TF-miRNA. We used pathway and GO term enrichment analysis to determine the importance of these DEGs in different biological processes.

resultsIn NSCLC, we found 950 differentially expressed miRNAs and 1761 genes were recognized exhibiting the significant change in expression (p < 0.05). Further, we investigated the role of sub-network motif in patient survival, hsa-miR-5010 was found to be significantly linked with patient outcome in Lung Adenocarcinoma (LUAD) (p = 0.033) and Lung Squamous Cell Carcinoma (LUSC) (p = 0.013) while SMAD4 (p < 0.001) and NRG1 (p < 0.001) expression exhibited prognostic significance in LUAD cohort only.

conclusionOur data indicated that NRG1-SMAD4-miR-5010-5p was the most prominent sub-network motif engaged in NSCLC patients based on the degree of centrality. In vitro mechanistic studies will provide better understanding on the role of NRG1-SMAD4-miR-5010-5p motif in NSCLC cases.

Indexed as

Carcinoma, Non-Small-Cell LungGene Expression Regulation, NeoplasticLung NeoplasmsBiomarkers, TumorGene Expression ProfilingGene Regulatory NetworksHumansMicroRNAsBiomarkers, TumorMicroRNAs

Identifiers

PMID41671297
PMCPMC12893602

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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.