Analysis of Pan-omics Data in Human Interactome Network (APODHIN)

Area of Science:

• Systems Biology
• Bioinformatics
• Computational Biology

Background:

• Cancer involves complex molecular interconnections.
• Understanding these interactions requires integrating diverse omics data (genomics, transcriptomics, proteomics, metabolomics).
• Existing platforms may not offer comprehensive analysis of these integrated networks.

Purpose of the Study:

• To present the Analysis of Pan-omics Data in Human Interactome Network (APODHIN) platform.
• To enable integrative analysis of multi-omics data for identifying key molecular players and their interconnections in biological scenarios, particularly cancer.
• To identify potential diagnostic, prognostic, and therapeutic targets through network topology analysis.

Main Methods:

• Development of a meta-interactome network integrating protein-protein interactions (PPIs), miRNA-target gene, and transcription factor-target gene regulatory relationships.
• Application of graph theory for network topology analysis to identify Topologically Important Nodes (TINs).
• Implementation of mathematical modeling to identify cross-pathway regulatory and PPI links.

Main Results:

• The APODHIN platform successfully maps omics data onto a meta-interactome network.
• Identification of TINs and cross-pathway links connecting regulatory components to metabolic enzymes.
• Demonstration of the platform's utility with example analyses of cervical, ovarian, and breast cancer datasets.

Conclusions:

• APODHIN provides a valuable tool for integrative pan-omics data analysis in cancer research.
• Identified TINs and cross-pathway links can serve as potential biomarkers and therapeutic targets.
• The platform facilitates a deeper understanding of molecular reprogramming in cancer.