Data from Integrated Genomic Characterization of the Human Immunome in Cancer

Alterations in immune-related pathways are common hallmarks of cancer. A comprehensive understanding of how cancer mutations rewire immune signaling networks and functional output across cancer types is instrumental to realize the full potential of immunotherapy. Here, we systematically interrogated somatic mutations involved in immune signaling that alter immune responses in patients with cancer. To do so, we developed a Network-based Integrative model to Prioritize Potential immune respondER genes (NIPPER). Identified mutations were enriched in essential protein domains and genes identified by NIPPER were associated with responsiveness to multiple immunotherapy modalities. These genes were used to devise an interactome network propagation framework integrated with drug-associated gene signatures to identify potential immunomodulatory drug candidates. Together, our systems-level analysis results help interpret the heterogeneous immune responses among patients and serve as a resource for future functional studies and targeted therapeutics.

This study demonstrates that integration of multi-omics data can help identify critical molecular determinants for effective targeted therapeutics.