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Chimeric antigen receptor (CAR) T cells are ineffective against solid tumors with immunosuppressive microenvironments. To overcome suppression, we engineered circuits in which tumor-specific synNotch receptors locally induce production of the cytokine IL-2. These circuits potently enhance CAR T cell infiltration and clearance of immune-excluded tumors, without systemic toxicity. The most effective IL-2 induction circuit acts in an autocrine and T cell receptor (TCR)- or CAR-independent manner, bypassing suppression mechanisms including consumption of IL-2 or inhibition of TCR signaling. These engineered cells establish a foothold in the target tumors, with synthetic Notch–induced IL-2 production enabling initiation of CAR-mediated T cell expansion and cell killing. Thus, it is possible to reconstitute synthetic T cell circuits that activate the outputs ultimately required for an antitumor response, but in a manner that evades key points of tumor suppression.

Binary expression systems like the LexA-LexAop system provide a powerful experimental tool kit to study gene and tissue function in developmental biology, neurobiology, and physiology. However, the number of well-defined LexA enhancer trap insertions remains limited. In this study, we present the molecular characterization and initial tissue expression analysis of nearly 100 novel StanEx LexA enhancer traps, derived from the StanEx 1 index line. This includes 76 insertions into novel, distinct gene loci not previously associated with enhancer traps or targeted LexA constructs. Additionally, our studies revealed evidence for selective transposase-dependent replacement of a previously-undetected KP element on chromosome III within the StanEx 1 genetic background during hybrid dysgenesis, suggesting a molecular basis for the over-representation of LexA insertions at the NK7.1 locus in our screen. Production and characterization of novel fly lines were performed by students and teachers in experiment-based genetics classes within a geographically diverse network of public and independent high schools. Thus, unique partnerships between secondary schools and university-based programs have produced and characterized novel genetic and molecular resources in Drosophila for open-source distribution, and provide paradigms for development of science education through experience-based pedagogy.

◥Purpose: Between 30%-40% of patients with prostate cancer experience disease recurrence following radical prostatectomy. Existing clinical models for recurrence risk prediction do not account for population-based variation in the tumor phenotype, despite recent evidence suggesting the presence of a unique, more aggressive prostate cancer phenotype in African American (AA) patients. We investigated the capacity of digitally measured, population-specific phenotypes of the intratumoral stroma to create improved models for prediction of recurrence following radical prostatectomy.Experimental Design: This study included 334 radical prostatectomy patients subdivided into training (V T , n ¼ 127), validation 1 (V 1 , n ¼ 62), and validation 2 (V 2 , n ¼ 145). Hematoxylin and eosin-stained slides from resected prostates were digitized, and 242 quantitative descriptors of the intratumoral stroma were calculated using a computational algorithm. Machine learning and elastic net Cox regression models were constructed using V T to predict biochemical recurrence-free survival based on these features. Performance of these models was assessed using V 1 and V 2 , both overall and in population-specific cohorts.Results: An AA-specific, automated stromal signature, AAstro, was prognostic of recurrence risk in both independent validation datasets [V 1,AA : AUC ¼ 0.87, HR ¼ 4.71 (95% confidence interval (CI), 1.65-13.4), P ¼ 0.003; V 2,AA : AUC ¼ 0.77, HR ¼ 5.7 (95% CI, 1.48-21.90), P ¼ 0.01]. AAstro outperformed clinical standard Kattan and CAPRA-S nomograms, and the underlying stromal descriptors were strongly associated with IHC measurements of specific tumor biomarker expression levels.Conclusions: Our results suggest that considering populationspecific information and stromal morphology has the potential to substantially improve accuracy of prognosis and risk stratification in AA patients with prostate cancer.

Chimeric antigen receptor (CAR) costimulatory domains derived from native immune receptors steer the phenotypic output of therapeutic T cells. We constructed a library of CARs containing ~2,300 synthetic costimulatory domains, built from combinations of 13 signaling motifs. These CARs promoted diverse cell fates, which were sensitive to motif combinations and configurations. Neural networks trained to decode the combinatorial grammar of CAR signaling motifs allowed extraction of key design rules. For example, non-native combinations of motifs which bind tumor necrosis factor receptor-associated factors (TRAFs) and phospholipase C gamma 1 (PLCγ1) enhanced cytotoxicity and stemness associated with effective tumor killing. Thus, libraries built from minimal building blocks of signaling, combined with machine learning, can efficiently guide engineering of receptors with desired phenotypes.

Rubicon is a potent negative regulator of autophagy and a potential target for autophagy-inducing therapeutics. Rubicon-mediated inhibition of autophagy requires the interaction of the C-terminal Rubicon homology (RH) domain of Rubicon with Rab7–GTP. Here we report the 2.8-Å crystal structure of the Rubicon RH domain in complex with Rab7–GTP. Our structure reveals a fold for the RH domain built around four zinc clusters. The switch regions of Rab7 insert into pockets on the surface of the RH domain in a mode that is distinct from those of other Rab–effector complexes. Rubicon residues at the dimer interface are required for Rubicon and Rab7 to colocalize in living cells. Mutation of Rubicon RH residues in the Rab7-binding site restores efficient autophagic flux in the presence of overexpressed Rubicon, validating the Rubicon RH domain as a promising therapeutic target.

Functional imaging using fluorescent indicators has revolutionized biology but additional sensor scaffolds are needed to access properties such as bright, far-red emission. We introduce a new platform for 'chemigenetic' fluorescent indicators, utilizing the self-labeling HaloTag protein conjugated to environmentally sensitive synthetic fluorophores. This approach affords bright, far-red calcium and voltage sensors with highly tunable photophysical and chemical properties, which can reliably detect single action potentials in neurons. Fluorescent sensors enable noninvasive measurement of cellular function. Although this field began with small-molecule fluorescent dyes, functional imaging in biology rapidly switched to protein-based sensors after the discovery of green fluorescent protein (GFP). Protein-based indicators allow cell-specific expression and take advantage of evolved molecular recognition motifs found in nature. In particular, genetically encoded calcium and voltage indicators (GECIs and GEVIs) have become powerful tools for monitoring neuronal activity in living systems. 1, 2Commonly used GECIs and GEVIs, such as GCaMP 3, 4 and ASAP 5 , rely on the use of a circularly permuted (cp) GFP fused to sensor protein domains like calmodulin (CaM) or a voltage sensitive

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