Predicting response and resistance to immune checkpoint blockade and surgery in melanoma patients.

Melanoma remains a formidable clinical challenge, claiming the lives of 60,000 patients annually. Current therapeutic modalities encompass surgical intervention and immune checkpoint inhibitors (ICB). Nevertheless, the efficacy of ICB varies, necessitating the need to anticipate response and resistance outcomes, while also considering alternative approaches, such as surgical interventions coupled with autologous skin grafts. In pursuit of these objectives, we conducted a comprehensive analysis involving seven melanoma patient cohorts subjected to four distinct ICB treatments. Remarkably, our findings revealed varying response rates: 29% for Nivolumab, 43% for Pembrolizumab, 20% for Ipilimumab, and an encouraging 62.5% for the combination of Pembrolizumab and Ipilimumab. This underscores the superior clinical outcomes associated with anti-PD1+anti-CTLA4 therapy. Intriguingly, responders to Pembrolizumab and Ipilimumab exhibited distinct immunological characteristics, characterized by an augmentation in Th1 and M1 macrophages, alongside a reduction in CD4+ T cell infiltration. This phenomenon coincided with the upregulation of antigen presentation genes (HLA, CD80), heightened pro-inflammatory cytokine production (CCL5, CXCL9, CXCL10), and enhanced T cell responses. Furthermore, based on these response profiles, we have developed predictive software to forecast individual patient responses to available checkpoint inhibitor combinations. This innovative tool also facilitates precise calculations for the extent of melanoma resection required during surgery, graft sizing, and the determination of the necessary autologous skin cell resources. In conclusion, our approach advocates for tailored therapies, leveraging patient-specific attributes and computational predictions to enhance clinical outcomes following immunotherapy and surgical interventions. This strategy holds promise for advancing melanoma treatment paradigms.