Real-world evaluation of deep learning algorithms to classify functional pathogenic germline variants.

Deep learning models for variant pathogenicity prediction can recapitulate expert-curated annotations, but their performance remains unexplored on actual disease phenotypes in a real-world setting. Here, we apply three state-of-the-art pathogenicity prediction models to classify hereditary breast cancer gene variants in the UK Biobank. Predicted pathogenic variants in BRCA1, BRCA2 and PALB2, but not ATM and CHEK2, were associated with increased breast cancer risk. We explored gene-specific score thresholds for variant pathogenicity, finding that they could improve model performance. However, when specifically tasked with classifying variants of uncertain significance, the deep learning models were generally of limited clinical utility.

In vivo AAV-SB-CRISPR screens of tumor-infiltrating primary NK cells identify genetic checkpoints of CAR-NK therapy.

Natural killer (NK) cells have clinical potential against cancer; however, multiple limitations hinder the success of NK cell therapy. Here, we performed unbiased functional mapping of tumor-infiltrating NK (TINK) cells using in vivo adeno-associated virus (AAV)-SB (Sleeping Beauty)-CRISPR (clustered regularly interspaced short palindromic repeats) screens in four solid tumor mouse models. In parallel, we characterized single-cell transcriptomic landscapes of TINK cells, which identified previously unexplored subpopulations of NK cells and differentially expressed TINK genes. As a convergent hit, CALHM2-knockout (KO) NK cells showed enhanced cytotoxicity and tumor infiltration in mouse primary NK cells and human chimeric antigen receptor (CAR)-NK cells. CALHM2 mRNA reversed the CALHM2-KO phenotype. CALHM2 KO in human primary NK cells enhanced their cytotoxicity, degranulation and cytokine production. Transcriptomics profiling revealed CALHM2-KO-altered genes and pathways in both baseline and stimulated conditions. In a solid tumor model resistant to unmodified CAR-NK cells, CALHM2-KO CAR-NK cells showed potent in vivo antitumor efficacy. These data identify endogenous genetic checkpoints that naturally limit NK cell function and demonstrate the use of CALHM2 KO for engineering enhanced NK cell-based immunotherapies.