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

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.

Hsa-Mir-320c, Hsa-Mir-200c-3p, and Hsa-Mir-449c-5p as Potential Specific miRNA Biomarkers of COPD: A Pilot Study

“…This overlap of miR-200c and miR-449c between COPD and asthma is probably due to their role in regulating key inflammatory responses in both diseases. In relation to other lung diseases, COPD is known to be a risk factor for developing lung cancer, especially for non-small cell lung cancer (NSCLC), and a common miRNA signature has been identified between both diseases by “miRNA set enrichment analysis” [ 35 ]. Of note, our three-miRNA signature (miR-200c-3p, miR-449c-5p, and miR-320c) is not present in that COPD-NSCLC panel, thus highlighting their potential use as biomarkers specifics of COPD only.…”

Altered Differentiation and Inflammation Profiles Contribute to Enhanced Innate Responses in Severe COPD Epithelium to Rhinovirus Infection

“…It is worth noting that changes in respiratory epigenetic profiles such as DNA methylation, histone modification and microRNAs (miRNA) are likely to contribute to the altered differentiation and pro-inflammatory response in severe COPD. Perturbations in histone acetylation (HAT)/histone deacetylase (HDAC), methyltransferase (HMT) and histone demethylase (HDM) activities have been demonstrated to regulate many chromatin-dependent processes, including transcription, recombination and DNA repair (48)(49)(50). In COPD, cigarette smoke, accelerated aging and other environmental factors such as diet-modulated oxidative stress play a role in the pathogenesis of severe COPD (48,49).…”

“…In COPD, cigarette smoke, accelerated aging and other environmental factors such as diet-modulated oxidative stress play a role in the pathogenesis of severe COPD (48,49). Consequently, oxidativeg genome-wide epigenetic profiles in severe COPD airway epithelium would provide a great platform for potential the stress can regulate the activity of HATs and HDACs and enhance NF-B-dependent pro-inflammatory gene transcription such as IL-8 and TNFα (48)(49)(50). MiRNA-125a and -b have been shown to inhibit A20 and MAVS.…”

Weighted Gene Coexpression Network Analysis Identifies Crucial Genes Involved in Coronary Atherosclerotic Heart Disease

“…The prevention and cure of CHD are facing severe problems and challenges. Therefore, there is an urgent need to With the innovation and development of DNA sequencing and chip technology, bioinformatics methods have been extensively employed for research related to the various chronic diseases, such as non-small-cell lung cancer [18], gastric cancer [19], sepsis [20], pressure hydrocephalus [21], amyotrophic lateral sclerosis [22], schizophrenia [23], hypertension [24], hypertrophic cardiomyopathy [25], and pulmonary artery high-pressure disease [26]. In the current study, we have used multiple bioinformatics methods to determine the potential biological mechanisms of CHD.…”