Literature DB >> 34635059

Identification of common microRNA between COPD and non-small cell lung cancer through pathway enrichment analysis.

Amirhossein Fathinavid1, Mohadeseh Zarei Ghobadi2, Ali Najafi3, Ali Masoudi-Nejad4.   

Abstract

BACKGROUND: Different factors have been introduced which influence the pathogenesis of chronic obstructive pulmonary disease (COPD) and non-small cell lung cancer (NSCLC). COPD as an independent factor is involved in the development of lung cancer. Moreover, there are certain resemblances between NSCLC and COPD, such as growth factors, activation of intracellular pathways, as well as epigenetic factors. One of the best approaches to understand the possible shared pathogenesis routes between COPD and NSCLC is to study the biological pathways that are activated. MicroRNAs (miRNAs) are critical biomolecules that implicate the regulation of several biological and cellular processes. As such, the main goal of this study was to use a systems biology approach to discover common dysregulated miRNAs between COPD and NSCLC, one that targets most genes within common enriched pathways.
RESULTS: To reconstruct the miRNA-pathways for each disease, we used the microarray miRNA expression data. Then, we employed "miRNA set enrichment analysis" (MiRSEA) to identify the most significant joint miRNAs between COPD and NSCLC based on the enrichment scores. Overall, our study revealed the involvement of the targets of miRNAs (such as has-miR-15b, hsa-miR-106a, has-miR-17, has-miR-103, and has-miR-107) in the most important common biological pathways.
CONCLUSIONS: According to the promising results of the pathway analysis, the identified miRNAs can be utilized as the new potential signatures for therapy through understanding the molecular mechanisms of both diseases.
© 2021. The Author(s).

Entities:  

Keywords:  COPD; Non-small cell lung Cancer; Pathway analysis; miRNA

Mesh:

Substances:

Year:  2021        PMID: 34635059      PMCID: PMC8507163          DOI: 10.1186/s12863-021-00986-z

Source DB:  PubMed          Journal:  BMC Genom Data        ISSN: 2730-6844


  58 in total

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