AccScience Publishing / GPD / Online First / DOI: 10.36922/gpd.2937
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ORIGINAL RESEARCH ARTICLE

Deciphering novel molecular gene expression signatures and pathways in cystic fibrosis through integrative bioinformatics strategies

Mamun Mia1 ,  Arafat Rahman Oany2,3* ,  Tahmina Pervin4,5 ,  Syeda Sharmin Duza6
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1 Department of Psychology, Division of Sciences, University of Otago, Dunedin, New Zealand
2 Department of Veterinary Physiology and Pharmacology, College of Veterinary Medicine & Biomedical Sciences, Texas A&M University, College Station, Texas, United States of America
3 Aristopharma Limited, Dhaka, Bangladesh
4 Biotechnology and Genetic Engineering Discipline, Life Science School, Khulna University, Khulna, Bangladesh
5 Department of Biology, College of Arts and Sciences, Texas A&M University, College Station, Texas, United States of America
6 Environmental, and Occupational Health, School of Public Health, Texas A&M University, College Station, Texas, United States of America
GPD 2024, 3(2), 2937 https://doi.org/10.36922/gpd.2937
Submitted: 15 February 2024 | Accepted: 29 April 2024 | Published: 10 June 2024
© 2024 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Cystic fibrosis (CF), a fatal autosomal recessive disorder, is triggered by a genetic alteration of the CF transmembrane conductance regulator (CFTR) gene. On a global scale, around one in 3000 live births are affected with CF annually. While diagnosis and therapy are available for CF patients with non-specific and rare mutations, the current research is dedicated to exploring customized biomarkers, genes, signaling networks, and therapy for improving the management of CF. Although still in the early stages of development and validation, mRNA and gene-based treatment strategies are aimed to target patients who are resistant to CFTR gene restoration therapies. In this study, we utilized the systems biology approaches integrated with gene expression analysis to identify novel biomarkers and pathways for CF treatment. At first, out of 54,676 differentially expressed genes, we identified 104 upregulated and 107 downregulated genes. The upregulated genes were largely concentrated on Glutamatergic synapses, and the downregulated genes were enriched in ubiquitin-mediated proteolysis. Utilizing the enrichment analysis, we explored deeper into the pathways linked to these genes, with emphasis on relevant pathways involving bronchial epithelial cells. Following the enrichment analysis, we identified six essential genes: WWP2, RNASEL, CUL1, CDC42, HDAC4, and UBA2. Furthermore, the discovered genes were evaluated using expression profile analysis. Finally, our data indicate that the WWP2 gene has a critical role in CF management. The current findings provide a coherent theoretical foundation for future experiments to further explore the WWP2 gene as a unique and prognostic target for developing an effective CF therapeutic approach.

Keywords
Cystic fibrosis
Cystic fibrosis transmembrane conductance regulator
Differentially expressed genes
Upregulated gene
Downregulated gene
Biomarkers
Gene Expression Omnibus
Funding
None.
Conflict of interest
The authors declare that they have no competing interests.
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