Dr Tarhini on the Utility of a Prognostic Model in Advanced Melanoma Following ICI Treatment

Ahmad Tarhini, MD, PhD, discusses a prognostic model evaluating patients with advanced melanoma treated with immune checkpoint inhibitors.

Ahmad Tarhini, MD, PhD, director, Cutaneous Clinical and Translational Research, leader, Neoadjuvant and Adjuvant Translational Science Program, senior member, Moffitt Cancer Center, Research Institute Departments of Cutaneous Oncology and Immunology; professor, Oncologic Sciences, the University of South Florida Morsani College of Medicine; chair, Scientific Committee, Oncology Research Information Exchange Network (ORIEN); chair, ORIEN ImmunoOncology Research Subcommittee, discusses insights from research presented at the 2024 ASCO Annual Meeting.

This research investigated a prognostic model based on selected cell state and cellular community scores in patients with advanced melanoma treated with immune checkpoint inhibitors (Ecotype-ICI score) as a predictor of ICI immunotherapeutic benefits. In this study, investigators used a machine learning framework to analyze molecular data from patients treated with immune checkpoint inhibitors, Tarhini begins. The goal was to examine the immune cell states and ecosystems within the tumor microenvironment (TME) to refine patient selection for immunotherapy and understand the molecular mechanisms of immune resistance, which may inform future immuno-oncology drug development, Tarhini says. This computational tool profiles gene expression signatures unique to specific cell types and immune cell states. It helps develop an immune cell state atlas, facilitating the resolution of complex immune architecture within the TME created by these immune cells and states.

Tarhini reports that investigators began this research by assessing clinical and transcriptomic data from patients treated with immune checkpoint inhibitors who were enrolled in the Total Cancer Care protocol within a network of specific cancer centers. Initially, investigators developed a predictive survival model for this patient population, he says. They then validated this model in 2 independent external cohorts, he reports. The first cohort was enrolled in the phase 3 E1609 study (NCT01274338) that treated high-risk patients with adjuvant ipilimumab (Yervoy; n = 456), with the control arm receiving interferon alpha, a non-immune checkpoint inhibitor (n = 248). The second cohort consisted of a harmonized group of patients from public datasets treated with PD-1 inhibitor monotherapy (n = 121), CTLA-4 inhibitors (n = 40), and a combination of PD-1 and CTLA-4 inhibitors (n = 66), he concludes.

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