Immunotherapy has revolutionized cancer treatment, but predicting patient
response remains challenging. Here, we presented Intelligent Predicting
Response to cancer Immunotherapy through Systematic Modeling (iPRISM), a
novel network-based model that integrates multiple data types to predict
immunotherapy outcomes. It incorporates gene expression, biological
functional network, tumor microenvironment characteristics, immune-related
pathways, and clinical data to provide a comprehensive view of factors
influencing immunotherapy efficacy. By identifying key genetic and
immunological factors, it provides an insight for more personalized
treatment strategies and combination therapies to overcome resistance
mechanisms.