TGF-β-responsive CAR-T cells promote anti-tumor immune function.

A chimeric antigen receptor (CAR) that responds to transforming growth factor beta (TGF-β) enables the engineering of T cells that convert this immunosuppressive cytokine into a potent T-cell stimulant. However, clinical translation of TGF-β CAR-T cells for cancer therapy requires the ability to productively combine TGF-β responsiveness with tumor-targeting specificity. Furthermore, the potential concern that contaminating, TGF-β?producing regulatory T (Treg) cells may preferentially expand during TGF-β CAR-T cell manufacturing and suppress effector T (Teff) cells demands careful evaluation. Here, we demonstrate that TGF-β CAR-T cells significantly improve the anti-tumor efficacy of neighboring cytotoxic T cells. Furthermore, the introduction of TGF-β CARs into mixed T-cell populations does not result in the preferential expansion of Treg cells, nor do TGF-β CAR-Treg cells cause CAR-mediated suppression of Teff cells. These results support the utility of incorporating TGF-β CARs in the development of adoptive T-cell therapy for cancer

Boosting Operational DNN Testing Efficiency through Conditioning

With the increasing adoption of Deep Neural Network (DNN) models as integral parts of software systems, efficient operational testing of DNNs is much in demand to ensure these models' actual performance in field conditions. A challenge is that the testing often needs to produce precise results with a very limited budget for labeling data collected in field. Viewing software testing as a practice of reliability estimation through statistical sampling, we re-interpret the idea behind conventional structural coverages as conditioning for variance reduction. With this insight we propose an efficient DNN testing method based on the conditioning on the representation learned by the DNN model under testing. The representation is defined by the probability distribution of the output of neurons in the last hidden layer of the model. To sample from this high dimensional distribution in which the operational data are sparsely distributed, we design an algorithm leveraging cross entropy minimization. Experiments with various DNN models and datasets were conducted to evaluate the general efficiency of the approach. The results show that, compared with simple random sampling, this approach requires only about a half of labeled inputs to achieve the same level of precision.Comment: Published in the Proceedings of the 27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2019

The heme-p53 interaction: Linking iron metabolism to p53 signaling and tumorigenesis

Recently, we reported that heme binds to tumor suppressor p53 protein (TP53, best known as p53) and promotes its nuclear export and cytosolic degradation, whereas iron chelation stabilizes p53 protein and suppresses tumors in a p53-dependent manner. This not only provides mechanistic insights into tumorigenesis associated with iron excess, but also helps guide the administration of chemotherapy based on iron deprivation in the clinic

Degradation of the Separase-cleaved Rec8, a Meiotic Cohesin Subunit, by the N-end Rule Pathway

The Ate1 arginyltransferase (R-transferase) is a component of the N-end rule pathway, which recognizes proteins containing N-terminal degradation signals called N-degrons, polyubiquitylates these proteins, and thereby causes their degradation by the proteasome. Ate1 arginylates N-terminal Asp, Glu, or (oxidized) Cys. The resulting N-terminal Arg is recognized by ubiquitin ligases of the N-end rule pathway. In the yeast Saccharomyces cerevisiae, the separase-mediated cleavage of the Scc1/Rad21/Mcd1 cohesin subunit generates a C-terminal fragment that bears N-terminal Arg and is destroyed by the N-end rule pathway without a requirement for arginylation. In contrast, the separase-mediated cleavage of Rec8, the mammalian meiotic cohesin subunit, yields a fragment bearing N-terminal Glu, a substrate of the Ate1 R-transferase. Here we constructed and used a germ cell-confined Ate1−/− mouse strain to analyze the separase-generated C-terminal fragment of Rec8. We show that this fragment is a short-lived N-end rule substrate, that its degradation requires N-terminal arginylation, and that male Ate1−/− mice are nearly infertile, due to massive apoptotic death of Ate1−/− spermatocytes during the metaphase of meiosis I. These effects of Ate1 ablation are inferred to be caused, at least in part, by the failure to destroy the C-terminal fragment of Rec8 in the absence of N-terminal arginylation

Incidence, clinical characteristics and prognosis of tumor lysis syndrome following B-cell maturation antigen-targeted chimeric antigen receptor-T cell therapy in relapsed/refractory multiple myeloma

Background aimsB-cell maturation antigen (BCMA)-targeted chimeric antigen receptor-T cell (CAR-T) therapy is used for refractory or relapsed multiple myeloma (r/r MM). However, CAR-T-related tumor lysis syndrome (TLS) has been observed. We aimed to elucidate the incidence, clinical and laboratory characteristics, and prognosis of CAR-T cell-related TLS.MethodsPatients (n=105) with r/r MM treated with BCMA-targeted CAR-T cell therapy were included. Patient characteristics, laboratory parameters, and clinical outcomes were assessed.ResultsEighteen (17.1%) patients developed TLS after BCMA-targeted CAR-T cell therapy. The median time till TLS onset was 8 days. Patients with TLS had steep rise in uric acid (UA), creatinine, and lactate dehydrogenase (LDH) within 6 days following CAR-T cell infusion and presented earlier and persistent escalation of cytokines (C-reactive protein [CRP], interleukin-6 [IL-6], interferon-γ [IFN-γ], and ferritin levels). All 18 patients had cytokine release syndrome (CRS), of which 13 (72.2%) developed grade 3–4 CRS. Three of 18 patients (16.7%) developed immune effector cell-associated neurotoxicity syndrome (ICANS): two patients with grade 1 ICANS and one with grade 2 ICANS. TLS development had a negative effect on the objective response rate (77.8% in the TLS group vs. 95.4% in the non-TLS group, p<0.01). During the median follow-up of 15.1 months, the median PFS was poorer of patients with TLS (median: 3.4 months in the TLS group vs. 14.7 months in the non-TLS group, p<0.001, hazard ratio [HR]=3.5 [95% confidence interval [CI] 1.5–8.5]). Also, TLS development exhibited significant effects on OS (median: 5.0 months in the TLS group vs. 39.8 months in the non-TLS group, p<0.001, hazard ratio [HR]=3.7 [95% CI 1.3–10.3]). TLS was associated with a higher tumor burden, elevated baseline creatinine and UA levels, severe CRS, pronounced CAR-T cell expansion, and corticosteroid use.ConclusionTLS is a frequently observed CAR-T therapy complication and negatively influences clinical response and prognosis. Close monitoring for TLS should be implemented during CAR-T cell therapy, especially for those at high TLS risk

Predictive network modeling in human induced pluripotent stem cells identifies key driver genes for insulin responsiveness.

Insulin resistance (IR) precedes the development of type 2 diabetes (T2D) and increases cardiovascular disease risk. Although genome wide association studies (GWAS) have uncovered new loci associated with T2D, their contribution to explain the mechanisms leading to decreased insulin sensitivity has been very limited. Thus, new approaches are necessary to explore the genetic architecture of insulin resistance. To that end, we generated an iPSC library across the spectrum of insulin sensitivity in humans. RNA-seq based analysis of 310 induced pluripotent stem cell (iPSC) clones derived from 100 individuals allowed us to identify differentially expressed genes between insulin resistant and sensitive iPSC lines. Analysis of the co-expression architecture uncovered several insulin sensitivity-relevant gene sub-networks, and predictive network modeling identified a set of key driver genes that regulate these co-expression modules. Functional validation in human adipocytes and skeletal muscle cells (SKMCs) confirmed the relevance of the key driver candidate genes for insulin responsiveness

Iron Metabolism Regulates p53 Signaling through Direct Heme-p53 Interaction and Modulation of p53 Localization, Stability, and Function

Iron excess is closely associated with tumorigenesis in multiple types of human cancers, with underlying mechanisms yet unclear. Recently, iron deprivation has emerged as a major strategy for chemotherapy, but it exerts tumor suppression only on select human malignancies. Here, we report that the tumor suppressor protein p53 is downregulated during iron excess. Strikingly, the iron polyporphyrin heme binds to p53 protein, interferes with p53-DNA interactions, and triggers both nuclear export and cytosolic degradation of p53. Moreover, in a tumorigenicity assay, iron deprivation suppressed wild-type p53-dependent tumor growth, suggesting that upregulation of wild-type p53 signaling underlies the selective efficacy of iron deprivation. Our findings thus identify a direct link between iron/heme homeostasis and the regulation of p53 signaling, which not only provides mechanistic insights into iron-excess-associated tumorigenesis but may also help predict and improve outcomes in iron-deprivation-based chemotherapy

Identification and selective expansion of functionally superior T cells expressing chimeric antigen receptors

Background: T cells expressing chimeric antigen receptors (CARs) have shown exciting promise in cancer therapy, particularly in the treatment of B-cell malignancies. However, optimization of CAR-T cell production remains a trial-and-error exercise due to a lack of phenotypic benchmarks that are clearly predictive of anti-tumor functionality. A close examination of the dynamic changes experienced by CAR-T cells upon stimulation can improve understanding of CAR–T-cell biology and identify potential points for optimization in the production of highly functional T cells. Methods: Primary human T cells expressing a second-generation, anti-CD19 CAR were systematically examined for changes in phenotypic and functional responses to antigen exposure over time. Multi-color flow cytometry was performed to quantify dynamic changes in CAR-T cell viability, proliferation, as well as expression of various activation and exhaustion markers in response to varied antigen stimulation conditions. Results: Stimulated CAR-T cells consistently bifurcate into two distinct subpopulations, only one of which (CARhi/CD25+) exhibit anti-tumor functions. The use of central memory T cells as the starting population and the resilience—but not antigen density—of antigen-presenting cells used to expand CAR-T cells were identified as critical parameters that augment the production of functionally superior T cells. We further demonstrate that the CARhi/CD25+ subpopulation upregulates PD-1 but is resistant to PD-L1-induced dysfunction. Conclusions: CAR-T cells expanded ex vivo for adoptive T-cell therapy undergo dynamic phenotypic changes during the expansion process and result in two distinct populations with dramatically different functional capacities. Significant and sustained CD25 and CAR expression upregulation is predictive of robust anti-tumor functionality in antigen-stimulated T cells, despite their correlation with persistent PD-1 upregulation. The functionally superior subpopulation can be selectively augmented by careful calibration of antigen stimulation and the enrichment of central memory T-cell type. Electronic supplementary material The online version of this article (doi:10.1186/s12967-015-0519-8) contains supplementary material, which is available to authorized users