There are increasing studies aimed to reveal genomic hallmarks predictive of immune checkpoint blockade (ICB) treatment response, which generated a large number of data and provided an unprecedented opportunity to identify response-related features and evaluate their robustness across cohorts. However, those valuable data sets are not easily accessible to the research community. To take full advantage of existing large-scale immuno-genomic profiles, we developed Immu-Mela (http://bioinfo.vanderbilt.edu/database/Immu-Mela/), a multidimensional immuno-genomic portal that provides interactive exploration of associations between ICB responsiveness and multi-omics features in melanoma, including genetic, transcriptomics, immune cells, and single-cell populations. Immu-Mela also enables integrative analysis of any two genomic features. We demonstrated the value of Immu-Mela by identifying known and novel genomic features associated with ICB response. In addition, Immu-Mela allows users to upload their data sets (unrestricted to any cancer types) and co-analyze with existing data to identify and validate signatures of interest. Immu-Mela reduces barriers between researchers and complex genomic data, facilitating discoveries in cancer immunotherapy.
All Science Journal Classification (ASJC) codes
- Molecular Biology