iCancerLab is a research platform we are developing for cancer systems immunology. The platform will include tools capable of integrating large sets of heterogeneous and context-specific information to describe the time-dependent relationships of cancer, immunity, and immunotherapies. The suite of tools is being built using evidence in public databases, almost in real-time, and will include five specific tools:
- miRNAs (iMIRLab) to explore immune gene targets of microRNAs
- SNP2Strucutre to identify the impact of mutations on immunoprotein structures
- Significant Intratumor Genomic Heterogenity (SIGH) to look at tumor heterogeneity in the context of immune response
- Differential Dependence Network (DDN) to look at differential biological networks in inflamed versus non-inflamed tumors
- Compositional Data Mining (CDM) to create stories by connecting a wide variety of data and text to generate patterns. These tools will enhance immunotherapy development by identifying optimal target antigens and improving immunotherapy trials by determining biomarker signatures to predict immune responsiveness, ultimately making immunotherapy discovery and development faster, cheaper and more effective.