{Reference Type}: Journal Article
{Title}: A spatial architecture-embedding HLA signature to predict clinical response to immunotherapy in renal cell carcinoma.
{Author}: Kinget L;Naulaerts S;Govaerts J;Vanmeerbeek I;Sprooten J;Laureano RS;Dubroja N;Shankar G;Bosisio FM;Roussel E;Verbiest A;Finotello F;Ausserhofer M;Lambrechts D;Boeckx B;Wozniak A;Boon L;Kerkhofs J;Zucman-Rossi J;Albersen M;Baldewijns M;Beuselinck B;Garg AD;
{Journal}: Nat Med
{Volume}: 30
{Issue}: 6
{Year}: 2024 Jun 21
{Factor}: 87.241
{DOI}: 10.1038/s41591-024-02978-9
{Abstract}: An important challenge in the real-world management of patients with advanced clear-cell renal cell carcinoma (aRCC) is determining who might benefit from immune checkpoint blockade (ICB). Here we performed a comprehensive multiomics mapping of aRCC in the context of ICB treatment, involving discovery analyses in a real-world data cohort followed by validation in independent cohorts. We cross-connected bulk-tumor transcriptomes across >1,000 patients with validations at single-cell and spatial resolutions, revealing a patient-specific crosstalk between proinflammatory tumor-associated macrophages and (pre-)exhausted CD8+ T cells that was distinguished by a human leukocyte antigen repertoire with higher preference for tumoral neoantigens. A cross-omics machine learning pipeline helped derive a new tumor transcriptomic footprint of neoantigen-favoring human leukocyte antigen alleles. This machine learning signature correlated with positive outcome following ICB treatment in both real-world data and independent clinical cohorts. In experiments using the RENCA-tumor mouse model, CD40 agonism combined with PD1 blockade potentiated both proinflammatory tumor-associated macrophages and CD8+ T cells, thereby achieving maximal antitumor efficacy relative to other tested regimens. Thus, we present a new multiomics and spatial map of the immune-community architecture that drives ICB response in patients with aRCC.