首页|University of Leuven (KU Leuven) Reports Findings in Carcinomas (A spatial archi tecture-embedding HLA signature to predict clinical response to immunotherapy in renal cell carcinoma)
University of Leuven (KU Leuven) Reports Findings in Carcinomas (A spatial archi tecture-embedding HLA signature to predict clinical response to immunotherapy in renal cell carcinoma)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Oncology - Carcinomas is the subject of a report. According to news reporting originating from Leuven, Belgium, by NewsRx correspondents, research stated, “An important challenge in the real-world management of patients with advanced clear-cell renal cell carcin oma (aRCC) is determining who might benefit from immune checkpoint blockade (ICB ). Here we performed a comprehensive multiomics mapping of aRCC in the context o f ICB treatment, involving discovery analyses in a real-world data cohort follow ed by validation in independent cohorts.” Our news editors obtained a quote from the research from the University of Leuve n (KU Leuven), “We cross-connected bulk-tumor transcriptomes across > 1,000 patients with validations at single-cell and spatial resolutions, revealin g a patient-specific crosstalk between proinflammatory tumor-associated macropha ges 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 sign ature correlated with positive outcome following ICB treatment in both real-worl d data and independent clinical cohorts. In experiments using the RENCA-tumor mo use model, CD40 agonism combined with PD1 blockade potentiated both proinflammat ory tumor-associated macrophages and CD8 T cells, thereby achieving maximal anti tumor efficacy relative to other tested regimens.”
LeuvenBelgiumEuropeCancerCarcino masCyborgsDrugs and TherapiesEmerging TechnologiesHealth and MedicineI mmunotherapyKidneyMachine LearningNephrologyOncology
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