Stratified analysis identifies HIF-2α as a therapeutic target for highly immune-infiltrated melanomas
Amy Y. HuangiD, Kelly P. BurkeiD, Ryan M. PorteriD, Lynn Meiger, Peter R. FatourosiD, Jiekun YangiD, Emily J. RobitschekiD, Natalie I. VokesiD, Cora A. RickeriD, Valeria Rosado, Giuseppe TarantinoiD, Jiajia CheniD, Tyler J. ApratiiD, Marc GlettigiD, Yiwen HeiD, Cassia Wang, Doris FuiD, Li‐Lun Ho, Kyriaki Galani, Gordon James FreemaniD, Elizabeth Iannotti BuchbinderiD, Frank Stephen HodiiD, M KellisiD, Genevieve Marie BolandiD, Arlene H. SharpeiD, David LiuiD
Abstract
While immune-checkpoint blockade (ICB) has revolutionized treatment of metastatic melanoma over the last decade, the identification of broadly applicable robust biomarkers has been challenging, driven in large part by the heterogeneity of ICB regimens and patient and tumor characteristics. To disentangle these features, we performed a standardized meta-analysis of eight cohorts of patients treated with anti-PD-1 (n=290), anti-CTLA-4 (n=175), and combination anti-PD-1/anti-CTLA-4 (n=51) with RNA sequencing of pre-treatment tumor and clinical annotations. Stratifying by immune-high vs -low tumors, we found that surprisingly, high immune infiltrate was a biomarker for response to combination ICB, but not anti-PD-1 alone. Additionally, hypoxia-related signatures were associated with non-response to anti-PD-1, but only amongst immune infiltrate-high melanomas. In a cohort of scRNA-seq of patients with metastatic melanoma, hypoxia also correlated with immunosuppression and changes in tumor-stromal communication in the tumor microenvironment (TME). Clinically actionable targets of hypoxia signaling were also uniquely expressed across different cell types. We focused on one such target, HIF-2, which was specifically upregulated in endothelial cells and fibroblasts but not in immune cells or tumor cells. HIF-2 inhibition, in combination with anti-PD-1, enhanced tumor growth control in pre-clinical models, but only in a more immune-infiltrated melanoma model. Our work demonstrates how careful stratification by clinical and molecular characteristics can be leveraged to derive meaningful biological insights and lead to the rational discovery of novel clinical targets for combination therapy.
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