ProNetView-ccRCC

ProNetView-ccRCC provides interactive 3D visualization of phosphopeptide co-expression networks derived from clear cell renal cell carcinoma (ccRCC) proteogenomic data to enable exploration of molecular interactions and associations with clinical variables such as tumor grade.

Key Features:

• Interactive 3D Visualization: WebGL-based three-dimensional visual representation of phosphopeptide co-expression networks for exploration of network topology.
• Phosphoprotein Co-expression Network: A network encompassing 3,614 genes constructed from phospho-peptide data derived from 103 ccRCC samples.
• Pathway-Enriched Modules: Identification and presentation of 30 functional pathway-enriched modules within the phosphoprotein network.
• Clinical Association: Linking network components to clinical variables, including tumor grade, to support association analyses.
• CPTAC Integration: Integration with proteogenomic datasets and analyses produced under the NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC).

Scientific Applications:

• Molecular Research: Investigation of phosphoproteomic profiles and network-level regulatory mechanisms in ccRCC.
• Clinical Insights: Identification of proteogenomic features associated with tumor grade and potential biomarkers for prognosis.
• Collaborative Studies: Enabling shared analysis of ccRCC proteogenomic networks across oncology, proteomics, and genomics research groups.

Methodology:

Construction of gene/protein regulatory networks from phospho-peptide data from 103 ccRCC samples, identification of 30 pathway-enriched modules, and interactive 3D visualization implemented with WebGL; data and analyses integrated from CPTAC proteogenomic studies.