A pretreatment transcriptomic signature that predicts outcomes of immunotherapy in melanoma

Abstract

Identifying indicators of immunotherapy response are key to clinical treatment decisions. To date, immunotherapy is most widely used in melanoma because of its higher tumor mutation burden compared to other cancer types. However, less than half of melanoma patients can benefit from immune checkpoint inhibitor (ICI) therapy. For this reason, we deciphered pretreatment transcriptomes across a cohort of melanoma patients receiving anti-PD-1 or CTLA-4 alone (sICI) or in combination (cICI). We developed a two-gene signature that could predict the curative effect of ICI in melanoma by using the LASSO method. The pre-ICI signature displayed an equally competitive predictive power as the post-ICI irRECIST assessment that could offer clues regarding long-term ICI therapy response and facilitate risk stratification and treatment strategies.

Keywords

• Immune checkpoint inhibitor
• irRECIST
• Melanoma
• PD-1
• Risk score