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

Abstract

Cancer research has been revolutionized by mass spectrometry (MS)-based proteomics, enabling large-scale profiling of proteins and post-translational modifications (PTMs) to identify critical alterations in cancer signaling pathways. However, the lack of comprehensive, user-friendly platforms for integrative analysis limits efficient data exploration, biomarker discovery, and translational insights. To address this, we developed OncoProExp, a Shiny-based interactive web application for in-depth cancer proteomic and phosphoproteomic analyses. OncoProExp offers robust workflows for data preprocessing, interactive visualizations (PCA, hierarchical clustering, heatmaps, gene set enrichment analysis (GSEA)), and functional annotation of gene expression data. Differential expression analysis facilitates biomarker and therapeutic target discovery, while survival analysis identifies proteins whose expression stratifies overall survival, and pan-cancer exploration integrates clinical proteomic and phosphoproteomic datasets. OncoProExp also incorporates state-of-the-art predictive modeling, including Support Vector Machines (SVMs), Random Forests, and Artificial Neural Networks (ANNs) to classify cancer types from proteomic and phosphoproteomic profiles. These models were enhanced by SHapley Additive exPlanations (SHAP) for interpretability. To enhance its translational utility, OncoProExp supports user-uploaded data, protein-protein interactions, pathway enrichment, drug relevance evaluation, and clinical annotation analysis. OncoProExp is deployable via Docker containers, ensuring flexible and scalable integration into individual servers. Its utility has been demonstrated using Clinical Proteomic Tumor Analysis Consortium (CPTAC) datasets. OncoProExp is freely accessible at https://oncopro.cs.ut.ee/ without login requirements, offering a comprehensive resource for translational cancer research.