Differential gene expression and network analysis in head and neck squamous cell carcinoma

Discovering Promising Biomarkers and Therapeutic Targets for Duchenne Muscular Dystrophy: a Multiomics Meta-Analysis Approach

Duchenne muscular dystrophy (DMD) is a genetic disorder that causes muscle weakness and degeneration. In this study, we identified potential biomarkers and drug targets for DMD through a comprehensive meta-analysis of mRNA profiles. We conducted an in-depth analysis of three microarray datasets from the GEO database, utilizing the Affymetrix platform. A rigorous data pre-processing pipeline encompassed background correction, normalization, log2 transformation and probe-to-gene symbol mapping. Robust multi-array average method followed by Limma package in R was employed to ensure differential expression analysis within individual datasets, yielding gene-specific p-values. We identified 63 genes exhibiting statistically significant differential expression across the three datasets (p < 0.05) and an absolute log fold change > 1.5. Functional enrichment analyses of these differentially expressed genes were done, followed by pathway analyses. Our results suggested pertinent biological processes, molecular functions and cellular components associated with DMD. Finally, eight hub genes-COL6A3, COL1A1, COL3A1, COL1A2, POSTN, TIMP1, THBS2 and SPP1-were pinpointed as central players in the network. Two differentially expressed genes with substantial absolute log-fold changes, namely, DMD, downregulated and MYH3, upregulated, were identified as potential therapeutic candidates. In light of these findings, our work contributes not only to understanding DMD at the molecular level but also presents potential targets for therapeutic strategies. Finally, our study facilitates the development of therapeutic interventions that can effectively control and mitigate the impact of DMD.

Exploring the mechanism of action bitter melon in the treatment of breast cancer by network pharmacology

BACKGROUND

Bitter melon has been used to stop the growth of breast cancer (BRCA) cells. However, the underlying mechanism is still unclear.

AIM

To predict the therapeutic effect of bitter melon against BRCA using network pharmacology and to explore the underlying pharmacological mechanisms.

METHODS

The active ingredients of bitter melon and the related protein targets were taken from the Indian Medicinal Plants, Phytochemistry and Therapeutics and SuperPred databases, respectively. The GeneCards database has been searched for BRCA-related targets. Through an intersection of the drug's targets and the disease's objectives, prospective bitter melon anti-BRCA targets were discovered. Gene ontology and kyoto encyclopedia of genes and genomes enrichment analyses were carried out to comprehend the biological roles of the target proteins. The binding relationship between bitter melon's active ingredients and the suggested target proteins was verified using molecular docking techniques.

RESULTS

Three key substances, momordicoside K, kaempferol, and quercetin, were identified as being important in mediating the putative anti-BRCA effects of bitter melon through the active ingredient-anti-BRCA target network study. Heat shock protein 90 AA, proto-oncogene tyrosine-protein kinase, and signal transducer and activator of transcription 3 were found to be the top three proteins in the protein-protein interaction network study. The several pathways implicated in the anti-BRCA strategy for an active component include phosphatidylinositol 3-kinase/protein kinase B signaling, transcriptional dysregulation, axon guidance, calcium signaling, focal adhesion, janus kinase-signal transducer and activator of transcription signaling, cyclic adenosine monophosphate signaling, mammalian target of rapamycin signaling, and phospholipase D signaling.

CONCLUSION

Overall, the integration of network pharmacology, molecular docking, and functional enrichment analyses shed light on potential mechanisms underlying bitter melon's ability to fight BRCA, implicating active ingredients and protein targets, as well as highlighting the major signaling pathways that may be altered by this natural product for therapeutic benefit.

Unveiling Potential Targeted Therapeutic Opportunities for Co-Overexpressed Targeting Protein for Xklp2 and Aurora-A Kinase in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the most prevalent and leading causes of cancer deaths globally, with limited diagnostic and clinically significant therapeutic targets. Identifying the genes and processes involved in developing and progressing LUAD is crucial for developing effective targeted therapeutics and improving patient outcomes. Therefore, the study aimed to explore the RNA sequencing data of LUAD from The Cancer Genome Atlas (TCGA) and gene expression profile datasets involving GSE10072, GSE31210, and GSE32863 from the Gene Expression Omnibus (GEO) databases. The differential gene expression and the downstream analysis determined clinically significant biomarkers using a network-based approach. These therapeutic targets predominantly enriched the dysregulation of mitotic cell cycle regulation and revealed the co-overexpression of Aurora-A Kinase (AURKA) and Targeting Protein for Xklp2 (TPX2) with high survival risk in LUAD patients. The hydrophobic residues of the AURKA-TPX2 interaction were considered as the target site to block the autophosphorylation of AURKA during the mitotic cell cycle. The tyrosine kinase inhibitor (TKI) dacomitinib demonstrated the strong binding potential to hinder TPX2, shielding the AURKA destabilization. This in silico study lays the foundation for repurposing targeted therapeutic options to impede the Protein-Protein Interactions (PPIs) in LUAD progression and aid in future translational investigations.