Systems medicine of melanoma and autoimmunity in the context of immunotherapy

Immune-checkpoint inhibitors have shown clinical activity in advanced melanoma, with significant survival benefit and response rates for anti-CTLA-4 (19%), anti-PD-1 (36-44%) and combined therapy (58-61%). While responses can be durable, a significant proportion of patients show autoimmune side effects, including autoimmune colitis, hepatitis and musculoskeletal side effects. In about one third of cases patients exhibit side effects in more than one organ system. In a fraction of the patients autoimmunity is present prior the therapy and may exacerbate. To be able to predict the risk of appearance of these severe autoimmune side effects would enable physicians to personalize the anticancer treatment to the patient and understanding mechanisms of these autoimmune reactions could improve therapy.
The aim of the project is to improve our understanding of the molecular and cellular mechanisms underlying the interplay between autoimmunity and cancer, with an interest on the role of predisposing factors in the appearance or exacerbation of autoimmunity under immunotherapy. The project uses melanoma, inflammatory bowel and rheumatoid diseases as models. Under the systems medicine paradigm, we will generate in vivo/patient data-based molecular networks and multi-level models accounting for the mechanisms behind the immune activation involved in the autoimmunity-cancer-immunotherapy axis. Combining data and network analysis, computer simulations and model experimentation, we will generate molecular and phenotypic signatures accounting for the emergence or enhancement of autoimmunity under checkpoint inhibitor therapy, and will correlate these signatures with published and de novo patient data. We expect the project to pave the way towards the translation into clinical practice of systems medicine-based methods for monitoring autoimmunity in melanoma patients receiving immunotherapy and establish a basis for rationale treatment approaches for autoimmunity in cancer patients.

Top: factors influencing tumor response and autoimmunity of cancer patients. Bottom: concept of data integration in the project

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