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T cell therapies, such as chimeric antigen receptor (CAR) T cells and T cell receptor (TCR) T cells, are a growing class of anti-cancer treatments. However, expansion to novel indications and beyond last-line treatment requires engineering cells' dynamic population behaviors. Here we develop the tools for cellular behavior analysis of T cells from live-cell imaging, a common and inexpensive experimental setup used to evaluate engineered T cells. We first develop a state-of-the-art segmentation and tracking pipeline, Caliban , based on human-in-the-loop deep learning. We then build the Occident pipeline to collect a catalog of phenotypes that characterize cell populations, morphology, movement, and interactions in co-cultures of modified T cells and antigen-presenting tumor cells. We use Caliban and Occident to interrogate how interactions between T cells and cancer cells differ when beneficial knock-outs of RASA2 and CUL5 are introduced into TCR T cells. We apply spatiotemporal models to quantify T cell recruitment and proliferation after interactions with cancer cells. We discover that, compared to a safe harbor knockout control, RASA2 knockout T cells have longer interaction times with cancer cells leading to greater T cell activation and killing efficacy, while CUL5 knockout T cells have increased proliferation rates leading to greater numbers of T cells for hunting. Together, segmentation and tracking from Caliban and phenotype quantification from Occident enable cellular behavior analysis to better engineer T cell therapies for improved cancer treatment.

Genetic perturbation of T cell receptor (TCR) T cells is a promising method to unlock better TCR T cell performance to create more powerful cancer immunotherapies, but understanding the changes to T cell behavior induced by genetic perturbations remains a challenge. Prior studies have evaluated the effect of different genetic modifications with cytokine production and metabolic activity assays. Live-cell imaging is an inexpensive and robust approach to capture TCR T cell responses to cancer. Most methods to quantify T cell responses in live-cell imaging data use simple approaches to count T cells and cancer cells across time, effectively quantifying how much space in the 2D well each cell type covers, leaving actionable information unexplored. In this study, we characterize changes in TCR T cell's interactions with cancer cells from live-cell imaging data using explainable artificial intelligence (AI). We train convolutional neural networks to distinguish behaviors in TCR T cell with CRISPR knock outs of CUL5, RASA2, and a safe harbor control knockout. We use explainable AI to identify specific interaction types that define different knock-out conditions. We find that T cell and cancer cell coverage is a strong marker of TCR T cell modification when comparing similar experimental time points, but differences in cell aggregation characterize CUL5KO and RASA2KO behavior across all time points. Our pipeline for discovery in live-cell imaging data can be used for characterizing complex behaviors in arbitrary live-cell imaging datasets, and we describe best practices for this goal.

Hypodiploid acute lymphoblastic leukemia (ALL) is an aggressive blood cancer with a poor prognosis despite intensive chemotherapy or stem cell transplant. Children and adolescents with positive end-of-induction minimal residual disease have an overall survival lower than 30%. However, data regarding therapeutic alternatives for this disease is nearly nonexistent, emphasizing the critical need for new or adjunctive therapies that can improve outcomes. We previously reported on the therapeutic efficacy of venetoclax (ABT-199) in hypodiploid B-lineage ALL but with limitations as monotherapy. In this study, we set out to identify drugs enhancing the anti-leukemic effect of venetoclax in hypodiploid ALL. Using a highthroughput drug screen, we identified dinaciclib, a cyclin-dependent kinase inhibitor that worked synergistically with venetoclax to induce cell death in hypodiploid cell lines. This combination eradicated leukemic blasts within hypodiploid ALL patient-derived xenografts mice with low off-target toxicity. Our findings suggest that dual inhibition of BCL-2 (venetoclax) and CDK9/MCL-1 (dinaciclib) is a promising therapeutic approach in hypodiploid ALL, warranting further investigation to inform clinical trials in this high-risk patient population.

The efficacy of adoptive T cell therapies for cancer treatment can be limited by suppressive signals from both extrinsic factors and intrinsic inhibitory checkpoints 1,2 . Targeted gene editing has the potential to overcome these limitations and enhance T cell therapeutic function 3-10 . Here we performed multiple genome-wide CRISPR knock-out screens under different immunosuppressive conditions to identify genes that can be targeted to prevent T cell dysfunction. These screens converged on RASA2, a RAS GTPase-activating protein (RasGAP) that we identify as a signalling checkpoint in human T cells, which is downregulated upon acute T cell receptor stimulation and can increase gradually with chronic antigen exposure. RASA2 ablation enhanced MAPK signalling and chimeric antigen receptor (CAR) T cell cytolytic activity in response to target antigen. Repeated tumour antigen stimulations in vitro revealed that RASA2-deficient T cells show increased activation, cytokine production and metabolic activity compared with control cells, and show a marked advantage in persistent cancer cell killing. RASA2-knockout CAR T cells had a competitive fitness advantage over control cells in the bone marrow in a mouse model of leukaemia. Ablation of RASA2 in multiple preclinical models of T cell receptor and CAR T cell therapies prolonged survival in mice xenografted with either liquid or solid tumours. Together, our findings highlight RASA2 as a promising target to enhance both persistence and effector function in T cell therapies for cancer treatment., (© 2022. The Author(s).)

Competing Interests: The authors have declared that no competing interests exist.

We recently demonstrated the effectiveness of blocking CD49d with anti-functional antibodies or small molecule inhibitors as a rational targeted approach to the treatment of acute leukemia in combination with chemotherapy. Antisense oligonucleotide promises to be no less specific than antibodies and inhibitors, but more interesting for pharmacokinetics and pharmacodynamics. We addressed this using the published CD49d antisense drug ATL1102. In vitro, we incubated/nucleofected the ALL cell line Kasumi-2 with ATL1102. In vivo, immunodeficient hosts were engrafted with primary ALL cells and treated with ATL1102. Changes in expression of CD49d mRNA and CD49d protein, and of cooperating gene products, including ß1 integrin and CXCR4, as well as survival in the mouse experiments were quantified. We observed dose-dependent down-regulation of CD49d mRNA and protein levels and its partner integrin ß1 cell surface protein level and, up-regulation of CXCR4 surface expression. The suppression was more pronounced after nucleofection than after incubation, where down-regulation was significant only at the higher doses. In vivo effects of ATL1102 were not sufficient to translate into "clinical" benefit in the leukemia model. In summary, antisense oligonucleotides are successful tools for specifically modulating gene expression but sufficient delivery to down-regulate CD49d in vivo may be difficult to achieve.

Background: Ana Nova® is a novel-finned press-fit acetabular cup which showed superior biomechanical characteristics in an experimental set-up. Using Einzel Bild Röntgen Analyse (EBRA) measurements should offer the opportunity to predict implant survival at an early stage. The purpose of this study was to assess migration and clinical outcome 2 years after total hip replacement by a novel-finned press-fit acetabular cup., Methods: In this study, migration and clinical results of the implant were prospectively assessed in 67 patients. Clinical outcome was assessed using the Harris hip score (HHS). Migration analyses were performed using the computer assisted EBRA system. Data were analyzed for normal distribution using the Kolmogorov-Smirnov test. Group comparisons were performed using the analysis of variance (ANOVA) test. P-values less than 0.05 were considered statistically significant., Results: At 2 years after surgery, none of the implants needed revision and HHS increased from 39.7 up to 92.2. In contrast to the beneficial clinical outcome, 17 of 44 patients showed increased total migration ( 1 mm/2a)., Conclusions: Adverse migration data in this study might predict aseptic loosening and decreased survival of the implant. According to previous studies, it is possible that this effect occurred because of limited accuracy of the EBRA system. In our opinion, migration analyses may not be recommended as a screening tool in a 2 year follow-up.