Migrating cells do not proliferate and vice versa, but the mechanism involved remains unknown. Ghosh et al. reveal how this cellular decision is made by showing that a Gαi–GIV molecular complex interacts with EGF receptor and programs growth factor signaling, triggering migration when assembled and favoring mitosis when assembly is prevented.

Despite impressive progress, more than 50% of patients treated with CD19-targeting chimeric antigen receptor T cells (CAR19) experience progressive disease. Ten of 16 patients with large B cell lymphoma (LBCL) with progressive disease after CAR19 treatment had absent or low CD19. Lower surface CD19 density pretreatment was associated with progressive disease. To prevent relapse with CD19− or CD19lo disease, we tested a bispecific CAR targeting CD19 and/or CD22 (CD19-22.BB.z-CAR) in a phase I clinical trial (NCT03233854) of adults with relapsed/refractory B cell acute lymphoblastic leukemia (B-ALL) and LBCL. The primary end points were manufacturing feasibility and safety with a secondary efficacy end point. Primary end points were met; 97% of products met protocol-specified dose and no dose-limiting toxicities occurred during dose escalation. In B-ALL (n = 17), 100% of patients responded with 88% minimal residual disease-negative complete remission (CR); in LBCL (n = 21), 62% of patients responded with 29% CR. Relapses were CD19−/lo in 50% (5 out of 10) of patients with B-ALL and 29% (4 out of 14) of patients with LBCL but were not associated with CD22−/lo disease. CD19/22-CAR products demonstrated reduced cytokine production when stimulated with CD22 versus CD19. Our results further implicate antigen loss as a major cause of CAR T cell resistance, highlight the challenge of engineering multi-specific CAR T cells with equivalent potency across targets and identify cytokine production as an important quality indicator for CAR T cell potency.

During migration, cells must couple direction sensing to signal transduction and actin remodeling. We previously identified GIV/Girdin as a Gαi3 binding partner. We demonstrate that in mammalian cells Gαi3 controls the functions of GIV during cell migration. We find that Gαi3 preferentially localizes to the leading edge and that cells lacking Gαi3 fail to polarize or migrate. A conformational change induced by association of GIV with Gαi3 promotes Akt-mediated phosphorylation of GIV, resulting in its redistribution to the plasma membrane. Activation of Gαi3 serves as a molecular switch that triggers dissociation of Gβγ and GIV from the Gi3–GIV complex, thereby promoting cell migration by enhancing Akt signaling and actin remodeling. Gαi3–GIV coupling is essential for cell migration during wound healing, macrophage chemotaxis, and tumor cell migration, indicating that the Gαi3–GIV switch serves to link direction sensing from different families of chemotactic receptors to formation of the leading edge during cell migration.

A reduced peripheral blood absolute lymphocyte count with an elevated neutrophil count has been a consistent observation in hospitalized coronavirus disease 2019 (COVID‐19) patients. In this brief meta‐analysis, the reduction of lymphocyte subset counts in COVID‐19 patients was investigated across 20 peer‐reviewed studies meeting criteria for reporting lymphocyte subset counts and COVID‐19 disease severity. CD4+ T cell, CD8+ T cell, B cell, NK cell, and total lymphocyte cell counts all showed statistically significant reduction in patients with severe/critical COVID‐19 disease compared to mild/moderate disease. T‐cell subsets showed the largest standardized magnitude of change. In some studies, multivariate analysis has shown that CD4 and/or CD8 T‐cells counts are independently predictive of patient outcomes. © 2020 International Society for Advancement of Cytometry

Slit diaphragms are essential components of the glomerular filtration apparatus, as changes in these junctions are the hallmark of proteinuric diseases. Slit diaphragms, considered specialized adherens junctions, contain both unique membrane proteins (e.g., nephrin, podocin, and Neph1) and typical adherens junction proteins (e.g., P-cadherin, FAT, and catenins). Whether slit diaphragms also contain tight junction proteins is unknown. Here, immunofluorescence, immunogold labeling, and cell fractionation demonstrated that rat slit diaphragms contain the tight junction proteins JAM-A (junctional adhesion molecule A), occludin, and cingulin. We found these proteins in the same protein complexes as nephrin, podocin, CD2AP, ZO-1, and Neph1 by cosedimentation, coimmunoprecipitation, and pull-down assays. PAN nephrosis increased the protein levels of JAM-A, occludin, cingulin, and ZO-1 several-fold in glomeruli and loosened their attachment to the actin cytoskeleton. These data extend current information about the molecular composition of slit diaphragms by demonstrating the presence of tight junction proteins, although slit diaphragms lack the characteristic morphologic features of tight junctions. The contribution of these proteins to the assembly of slit diaphragms and potential signaling cascades requires further investigation.

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Heterotrimeric G protein signaling is regulated by signaling modules composed of heterotrimeric G proteins, active G proteincoupled receptors (Rs), which activate G proteins, and GTPaseactivating proteins (GAPs), which deactivate G proteins. We term these modules GTPase-cycle modules. The local concentrations of these proteins are spatially regulated between plasma membrane microdomains and between the plasma membrane and cytosol, but no data or models are available that quantitatively explain the effect of such regulation on signaling. We present a computational model of the GTPase-cycle module that predicts that the interplay of local G protein, R, and GAP concentrations gives rise to 16 distinct signaling regimes and numerous intermediate signaling phenomena. The regimes suggest alternative modes of the GTPasecycle module that occur based on defined local concentrations of the component proteins. In one mode, signaling occurs while G protein and receptor are unclustered and GAP eliminates signaling; in another, G protein and receptor are clustered and GAP can rapidly modulate signaling but does not eliminate it. Experimental data from multiple GTPase-cycle modules is interpreted in light of these predictions. The latter mode explains previously paradoxical data in which GAP does not alter maximal current amplitude of G protein-activated ion channels, but hastens signaling. The predictions indicate how variations in local concentrations of the component proteins create GTPase-cycle modules with distinctive phenotypes. They provide a quantitative framework for investigating how regulation of local concentrations of components of the GTPase-cycle module affects signaling.T he timing and amplitude of signaling in cellular signaling networks depends on the local concentrations and kinetics of component proteins. The complexity of these networks has precluded comprehensive quantitative analysis of signaling. However, the networks can be divided into discrete signaling modules that can be quantitatively modeled and analyzed independently (1-5). Later, such models of modules can be experimentally verified and then reconnected to build larger signaling networks.G protein-mediated signaling networks (6) are ideal for such quantitative analysis. A key signaling module in these networks is the GTPase-cycle module, which controls signaling by regulating G protein activity. This module consists of a heterotrimeric G protein, a guanine nucleotide exchange factor (GEF) such as agonist-bound and active G protein-coupled receptor, a GTPase-activating protein (GAP) such as regulator of G protein signaling (RGS) protein or phospholipase C-␤, GTP, GDP, and P i . The extent of G protein activation reflects the balance between the rates of GDP͞GTP exchange, which activates the G protein, and GTP hydrolysis, which deactivates it (7-9). GEFs facilitate GDP͞GTP exchange (9), and GAPs accelerate GTP hydrolysis (10, 11). Additional roles of GEFs (12) and GAPs (10,11,13,14) are not included in this module. At present, we lack quantitativ...

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