OncoProExp: An interactive shiny web application for comprehensive cancer proteomics and phosphoproteomics analysis

Area of Science:

• Proteomics and Bioinformatics
• Cancer Biology
• Computational Biology

Background:

• Mass spectrometry (MS)-based proteomics revolutionized cancer research by enabling large-scale protein profiling.
• Lack of user-friendly platforms for integrative analysis hinders efficient data exploration, biomarker discovery, and translational insights in cancer research.

Purpose of the Study:

• To develop OncoProExp, an interactive web application for comprehensive cancer proteomic and phosphoproteomic data analysis.
• To provide robust workflows for data preprocessing, visualization, differential expression, survival analysis, and predictive modeling.
• To enhance translational utility through features like user data upload, pathway enrichment, and drug relevance evaluation.

Main Methods:

• Developed OncoProExp, a Shiny-based interactive web application.
• Implemented workflows for data preprocessing, PCA, hierarchical clustering, heatmaps, and gene set enrichment analysis (GSEA).
• Integrated differential expression, survival analysis, pan-cancer exploration, and predictive models (SVMs, Random Forests, ANNs) with SHAP for interpretability.

Main Results:

• OncoProExp offers comprehensive tools for in-depth cancer proteomic and phosphoproteomic analyses.
• The application facilitates biomarker and therapeutic target discovery through differential expression analysis.
• Predictive models and SHAP enhance cancer classification and interpretability, demonstrated with CPTAC datasets.

Conclusions:

• OncoProExp provides a user-friendly, comprehensive platform for translational cancer research.
• It integrates diverse analytical tools for exploring proteomic and phosphoproteomic data.
• Freely accessible and deployable via Docker, OncoProExp supports scalable and flexible integration for researchers.