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

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.