Targeting the IL1ß Pathway for Cancer Immunotherapy Remodels the Tumor Microenvironment and Enhances Antitumor Immune Responses.

High levels of IL1ß can result in chronic inflammation, which in turn can promote tumor growth and metastasis. Inhibition of IL1ß could therefore be a promising therapeutic option in the treatment of cancer. Here, the effects of IL1ß blockade induced by the mAbs canakinumab and gevokizumab were evaluated alone or in combination with docetaxel, anti-programmed cell death protein 1 (anti-PD-1), anti-VEGFα, and anti-TGFß treatment in syngeneic and humanized mouse models of cancers of different origin. Canakinumab and gevokizumab did not show notable efficacy as single-agent therapies; however, IL1ß blockade enhanced the effectiveness of docetaxel and anti-PD-1. Accompanying these effects, blockade of IL1ß alone or in combination induced significant remodeling of the tumor microenvironment (TME), with decreased numbers of immune suppressive cells and increased tumor infiltration by dendritic cells (DC) and effector T cells. Further investigation revealed that cancer-associated fibroblasts (CAF) were the cell type most affected by treatment with canakinumab or gevokizumab in terms of change in gene expression. IL1ß inhibition drove phenotypic changes in CAF populations, particularly those with the ability to influence immune cell recruitment. These results suggest that the observed remodeling of the TME following IL1ß blockade may stem from changes in CAF populations. Overall, the results presented here support the potential use of IL1ß inhibition in cancer treatment. Further exploration in ongoing clinical studies will help identify the best combination partners for different cancer types, cancer stages, and lines of treatment.

Decade-long leukaemia remissions with persistence of CD4+ CAR T cells.

The adoptive transfer of T lymphocytes reprogrammed to target tumour cells has demonstrated potential for treatment of various cancers1-7. However, little is known about the long-term potential and clonal stability of the infused cells. Here we studied long-lasting CD19-redirected chimeric antigen receptor (CAR) T cells in two patients with chronic lymphocytic leukaemia1-4 who achieved a complete remission in 2010. CAR T cells remained detectable more than ten years after infusion, with sustained remission in both patients. Notably, a highly activated CD4+ population emerged in both patients, dominating the CAR T cell population at the later time points. This transition was reflected in the stabilization of the clonal make-up of CAR T cells with a repertoire dominated by a small number of clones. Single-cell profiling demonstrated that these long-persisting CD4+ CAR T cells exhibited cytotoxic characteristics along with ongoing functional activation and proliferation. In addition, longitudinal profiling revealed a population of gamma delta CAR T cells that prominently expanded in one patient concomitant with CD8+ CAR T cells during the initial response phase. Our identification and characterization of these unexpected CAR T cell populations provide novel insight into the CAR T cell characteristics associated with anti-cancer response and long-term remission in leukaemia.

High-Dimensional Immune Monitoring for Chimeric Antigen Receptor T Cell Therapies.

PURPOSE OF REVIEW: High-dimensional flow cytometry experiments have become a method of choice for high-throughput integration and characterization of cell populations. Here, we present a summary of state-of-the-art R-based pipelines used for differential analyses of cytometry data, largely based on chimeric antigen receptor (CAR) T cell therapies. These pipelines are based on publicly available R libraries, put together in a systematic and functional fashion, therefore free of cost. RECENT FINDINGS: In recent years, existing tools tailored to analyze complex high-dimensional data such as single-cell RNA sequencing (scRNAseq) have been successfully ported to cytometry studies due to the similar nature of flow cytometry and scRNAseq platforms. Existing environments like Cytobank (Kotecha et al., 2010), FlowJo (FlowJo™ Software) and FCS Express (https://denovosoftware.com) already offer a variety of these ported tools, but they either come at a premium or are fairly complicated to manage by an inexperienced user. To mitigate these limitations, experienced cytometrists and bioinformaticians usually incorporate these functions into an RShiny (https://shiny.rstudio.com) application that ultimately offers a user-friendly, intuitive environment that can be used to analyze flow cytometry data. Computational tools and Shiny-based tools are the perfect answer to the ever-growing dimensionality and complexity of flow cytometry data, by offering a dynamic, yet user-friendly exploratory space, tailored to bridge the space between the lab experimental world and the computational, machine learning space.

TGFß-blockade uncovers stromal plasticity in tumors by revealing the existence of a subset of interferon-licensed fibroblasts.

Despite the increasing interest in targeting stromal elements of the tumor microenvironment, we still face tremendous challenges in developing adequate therapeutics to modify the tumor stromal landscape. A major obstacle to this is our poor understanding of the phenotypic and functional heterogeneity of stromal cells in tumors. Herein, we perform an unbiased interrogation of tumor mesenchymal cells, delineating the co-existence of distinct subsets of cancer-associated fibroblasts (CAFs) in the microenvironment of murine carcinomas, each endowed with unique phenotypic features and functions. Furthermore, our study shows that neutralization of TGFß in vivo leads to remodeling of CAF dynamics, greatly reducing the frequency and activity of the myofibroblast subset, while promoting the formation of a fibroblast population characterized by strong response to interferon and heightened immunomodulatory properties. These changes correlate with the development of productive anti-tumor immunity and greater efficacy of PD1 immunotherapy. Along with providing the scientific rationale for the evaluation of TGFß and PD1 co-blockade in the clinical setting, this study also supports the concept of plasticity of the stromal cell landscape in tumors, laying the foundation for future investigations aimed at defining pathways and molecules to program CAF composition for cancer therapy.

Tisagenlecleucel cellular kinetics, dose, and immunogenicity in relation to clinical factors in relapsed/refractory DLBCL.

The anti-CD19 chimeric antigen receptor (CAR)-T cell therapy tisagenlecleucel was evaluated in the global, phase 2 JULIET study in adult patients with relapsed/refractory diffuse large B-cell lymphoma (DLBCL). We correlated tisagenlecleucel cellular kinetics with clinical/product parameters in 111 patients treated in JULIET. Tisagenlecleucel persistence in responders and nonresponders, respectively, was demonstrated for 554 and 400 days maximum by flow cytometry and for 693 and 374 days maximum by quantitative polymerase chain reaction (qPCR). No relationships were identified between cellular kinetics (qPCR) and product characteristics, intrinsic/extrinsic factors, dose, or immunogenicity. Most patients with 3-month response had detectable transgene at time of response and continued persistence for ≥6 months. Expansion (maximal expansion of transgene/CAR-positive T-cell levels in vivo postinfusion [Cmax]) was potentially associated with response duration but this did not reach statistical significance (hazard ratio for a twofold increase in Cmax, 0.79; 95% confidence interval, 0.61-1.01). Tisagenlecleucel expansion was associated with cytokine-release syndrome (CRS) severity and tocilizumab use; no relationships were observed with neurologic events. Transgene levels were associated with B-cell levels. Dose was associated with CRS severity, but this was not statistically significant after adjusting for baseline tumor burden. In contrast to the results from B-cell precursor acute lymphoblastic leukemia (B-ALL) and chronic lymphocytic leukemia, similar exposure was observed in DLBCL in this study regardless of response and expansion was lower in DLBCL than B-ALL, likely from differences in cancer location and/or T-cell intrinsic factors. Relationships between expansion and CRS severity, and lack of relationships between dose and exposure, were similar between DLBCL and B-ALL. Tisagenlecleucel cellular kinetics in adult relapsed/refractory DLBCL improve current understanding of in vivo expansion and its relationships with safety/efficacy endpoints. This trial was registered at www.clinicaltrials.gov as #NCT02445248.

B cell maturation antigen-specific CAR T cells are clinically active in multiple myeloma.

BACKGROUND: Chimeric antigen receptor (CAR) T cells are a promising therapy for hematologic malignancies. B-cell maturation antigen (BCMA) is a rational target in multiple myeloma (MM). METHODS: We conducted a phase I study of autologous T cells lentivirally-transduced with a fully-human, BCMA-specific CAR containing CD3ζ and 4-1BB signaling domains (CART-BCMA), in subjects with relapsed/refractory MM. Twenty-five subjects were treated in 3 cohorts: 1) 1-5 x 108 CART-BCMA cells alone; 2) Cyclophosphamide (Cy) 1.5 g/m2 + 1-5 x 107 CART-BCMA cells; and 3) Cy 1.5 g/m2 + 1-5 x 108 CART-BCMA cells. No pre-specified BCMA expression level was required. RESULTS: CART-BCMA cells were manufactured and expanded in all subjects. Toxicities included cytokine release syndrome and neurotoxicity, which were grade 3-4 in 8 (32%) and 3 (12%) subjects, respectively, and reversible. One subject died at day 24 from candidemia and progressive myeloma, following treatment for severe CRS and encephalopathy. Responses (based on treated subjects) were seen in 4/9 (44%) in cohort 1, 1/5 (20%) in cohort 2, and 7/11 (64%) in cohort 3, including 5 partial, 5 very good partial, and 2 complete responses, 3 of which were ongoing at 11, 14, and 32 months. Decreased BCMA expression on residual MM cells was noted in responders; expression increased at progression in most. Responses and CART-BCMA expansion were associated with CD4:CD8 T cell ratio and frequency of CD45RO-CD27+CD8+ T cells in the pre-manufacturing leukapheresis product. CONCLUSION: CART-BCMA infusions with or without lymphodepleting chemotherapy are clinically active in heavily-pretreated MM patients. TRIAL REGISTRATION: NCT02546167. FUNDING: University of Pennsylvania-Novartis Alliance and NIH.

Determinants of response and resistance to CD19 chimeric antigen receptor (CAR) T cell therapy of chronic lymphocytic leukemia.

Tolerance to self-antigens prevents the elimination of cancer by the immune system1,2. We used synthetic chimeric antigen receptors (CARs) to overcome immunological tolerance and mediate tumor rejection in patients with chronic lymphocytic leukemia (CLL). Remission was induced in a subset of subjects, but most did not respond. Comprehensive assessment of patient-derived CAR T cells to identify mechanisms of therapeutic success and failure has not been explored. We performed genomic, phenotypic and functional evaluations to identify determinants of response. Transcriptomic profiling revealed that CAR T cells from complete-responding patients with CLL were enriched in memory-related genes, including IL-6/STAT3 signatures, whereas T cells from nonresponders upregulated programs involved in effector differentiation, glycolysis, exhaustion and apoptosis. Sustained remission was associated with an elevated frequency of CD27+CD45RO-CD8+ T cells before CAR T cell generation, and these lymphocytes possessed memory-like characteristics. Highly functional CAR T cells from patients produced STAT3-related cytokines, and serum IL-6 correlated with CAR T cell expansion. IL-6/STAT3 blockade diminished CAR T cell proliferation. Furthermore, a mechanistically relevant population of CD27+PD-1-CD8+ CAR T cells expressing high levels of the IL-6 receptor predicts therapeutic response and is responsible for tumor control. These findings uncover new features of CAR T cell biology and underscore the potential of using pretreatment biomarkers of response to advance immunotherapies.

Chimeric Antigen Receptor T Cells in Refractory B-Cell Lymphomas.

BACKGROUND: Patients with diffuse large B-cell lymphoma or follicular lymphoma that is refractory to or that relapses after immunochemotherapy and transplantation have a poor prognosis. High response rates have been reported with the use of T cells modified by chimeric antigen receptor (CAR) that target CD19 in B-cell cancers, although data regarding B-cell lymphomas are limited. METHODS: We used autologous T cells that express a CD19-directed CAR (CTL019) to treat patients with diffuse large B-cell lymphoma or follicular lymphoma that had relapsed or was refractory to previous treatments. Patients were monitored for response to treatment, toxic effects, the expansion and persistence of CTL019 cells in vivo, and immune recovery. RESULTS: A total of 28 adult patients with lymphoma received CTL019 cells, and 18 of 28 had a response (64%; 95% confidence interval [CI], 44 to 81). Complete remission occurred in 6 of 14 patients with diffuse large B-cell lymphoma (43%; 95% CI, 18 to 71) and 10 of 14 patients with follicular lymphoma (71%; 95% CI, 42 to 92). CTL019 cells proliferated in vivo and were detectable in the blood and bone marrow of patients who had a response and patients who did not have a response. Sustained remissions were achieved, and at a median follow-up of 28.6 months, 86% of patients with diffuse large B-cell lymphoma who had a response (95% CI, 33 to 98) and 89% of patients with follicular lymphoma who had a response (95% CI, 43 to 98) had maintained the response. Severe cytokine-release syndrome occurred in 5 patients (18%). Serious encephalopathy occurred in 3 patients (11%); 2 cases were self-limiting and 1 case was fatal. All patients in complete remission by 6 months remained in remission at 7.7 to 37.9 months (median, 29.3 months) after induction, with a sustained reappearance of B cells in 8 of 16 patients and with improvement in levels of IgG in 4 of 10 patients and of IgM in 6 of 10 patients at 6 months or later and in levels of IgA in 3 of 10 patients at 18 months or later. CONCLUSIONS: CTL019 cells can be effective in the treatment of relapsed or refractory diffuse large B-cell lymphoma and follicular lymphoma. High rates of durable remission were observed, with recovery of B cells and immunoglobulins in some patients. Transient encephalopathy developed in approximately one in three patients and severe cytokine-release syndrome developed in one in five patients. (Funded by Novartis and others; ClinicalTrials.gov number, NCT02030834 .).

Detection of dysregulated protein-association networks by high-throughput proteomics predicts cancer vulnerabilities.

The formation of protein complexes and the co-regulation of the cellular concentrations of proteins are essential mechanisms for cellular signaling and for maintaining homeostasis. Here we use isobaric-labeling multiplexed proteomics to analyze protein co-regulation and show that this allows the identification of protein-protein associations with high accuracy. We apply this 'interactome mapping by high-throughput quantitative proteome analysis' (IMAHP) method to a panel of 41 breast cancer cell lines and show that deviations of the observed protein co-regulations in specific cell lines from the consensus network affects cellular fitness. Furthermore, these aberrant interactions serve as biomarkers that predict the drug sensitivity of cell lines in screens across 195 drugs. We expect that IMAHP can be broadly used to gain insight into how changing landscapes of protein-protein associations affect the phenotype of biological systems.

Landscape of Targeted Anti-Cancer Drug Synergies in Melanoma Identifies a Novel BRAF-VEGFR/PDGFR Combination Treatment.

A newer generation of anti-cancer drugs targeting underlying somatic genetic driver events have resulted in high single-agent or single-pathway response rates in selected patients, but few patients achieve complete responses and a sizeable fraction of patients relapse within a year. Thus, there is a pressing need for identification of combinations of targeted agents which induce more complete responses and prevent disease progression. We describe the results of a combination screen of an unprecedented scale in mammalian cells performed using a collection of targeted, clinically tractable agents across a large panel of melanoma cell lines. We find that even the most synergistic drug pairs are effective only in a discrete number of cell lines, underlying a strong context dependency for synergy, with strong, widespread synergies often corresponding to non-specific or off-target drug effects such as multidrug resistance protein 1 (MDR1) transporter inhibition. We identified drugs sensitizing cell lines that are BRAFV600E mutant but intrinsically resistant to BRAF inhibitor PLX4720, including the vascular endothelial growth factor receptor/kinase insert domain receptor (VEGFR/KDR) and platelet derived growth factor receptor (PDGFR) family inhibitor cediranib. The combination of cediranib and PLX4720 induced apoptosis in vitro and tumor regression in animal models. This synergistic interaction is likely due to engagement of multiple receptor tyrosine kinases (RTKs), demonstrating the potential of drug- rather than gene-specific combination discovery approaches. Patients with elevated biopsy KDR expression showed decreased progression free survival in trials of mitogen-activated protein kinase (MAPK) kinase pathway inhibitors. Thus, high-throughput unbiased screening of targeted drug combinations, with appropriate library selection and mechanistic follow-up, can yield clinically-actionable drug combinations.

Small molecules facilitate rapid and synchronous iPSC generation.

The reprogramming of somatic cells into induced pluripotent stem cells (iPSCs) upon overexpression of OCT4, KLF4, SOX2 and c-MYC (OKSM) provides a powerful system to interrogate basic mechanisms of cell fate change. However, iPSC formation with standard methods is typically protracted and inefficient, resulting in heterogeneous cell populations. We show that exposure of OKSM-expressing cells to both ascorbic acid and a GSK3-ß inhibitor (AGi) facilitates more synchronous and rapid iPSC formation from several mouse cell types. AGi treatment restored the ability of refractory cell populations to yield iPSC colonies, and it attenuated the activation of developmental regulators commonly observed during the reprogramming process. Moreover, AGi supplementation gave rise to chimera-competent iPSCs after as little as 48 h of OKSM expression. Our results offer a simple modification to the reprogramming protocol, facilitating iPSC induction at unparalleled efficiencies and enabling dissection of the underlying mechanisms in more homogeneous cell populations.

Automated annotation of gene expression image sequences via non-parametric factor analysis and conditional random fields.

MOTIVATION: Computational approaches for the annotation of phenotypes from image data have shown promising results across many applications, and provide rich and valuable information for studying gene function and interactions. While data are often available both at high spatial resolution and across multiple time points, phenotypes are frequently annotated independently, for individual time points only. In particular, for the analysis of developmental gene expression patterns, it is biologically sensible when images across multiple time points are jointly accounted for, such that spatial and temporal dependencies are captured simultaneously. METHODS: We describe a discriminative undirected graphical model to label gene-expression time-series image data, with an efficient training and decoding method based on the junction tree algorithm. The approach is based on an effective feature selection technique, consisting of a non-parametric sparse Bayesian factor analysis model. The result is a flexible framework, which can handle large-scale data with noisy incomplete samples, i.e. it can tolerate data missing from individual time points. RESULTS: Using the annotation of gene expression patterns across stages of Drosophila embryonic development as an example, we demonstrate that our method achieves superior accuracy, gained by jointly annotating phenotype sequences, when compared with previous models that annotate each stage in isolation. The experimental results on missing data indicate that our joint learning method successfully annotates genes for which no expression data are available for one or more stages.

A microfluidic device and computational platform for high-throughput live imaging of gene expression.

To fully describe gene expression dynamics requires the ability to quantitatively capture expression in individual cells over time. Automated systems for acquiring and analyzing real-time images are needed to obtain unbiased data across many samples and conditions. We developed a microfluidics device, the RootArray, in which 64 Arabidopsis thaliana seedlings can be grown and their roots imaged by confocal microscopy over several days without manual intervention. To achieve high throughput, we decoupled acquisition from analysis. In the acquisition phase, we obtain images at low resolution and segment to identify regions of interest. Coordinates are communicated to the microscope to record the regions of interest at high resolution. In the analysis phase, we reconstruct three-dimensional objects from stitched high-resolution images and extract quantitative measurements from a virtual medial section of the root. We tracked hundreds of roots to capture detailed expression patterns of 12 transgenic reporter lines under different conditions.

Automatic annotation of spatial expression patterns via sparse Bayesian factor models.

Advances in reporters for gene expression have made it possible to document and quantify expression patterns in 2D-4D. In contrast to microarrays, which provide data for many genes but averaged and/or at low resolution, images reveal the high spatial dynamics of gene expression. Developing computational methods to compare, annotate, and model gene expression based on images is imperative, considering that available data are rapidly increasing. We have developed a sparse Bayesian factor analysis model in which the observed expression diversity of among a large set of high-dimensional images is modeled by a small number of hidden common factors. We apply this approach on embryonic expression patterns from a Drosophila RNA in situ image database, and show that the automatically inferred factors provide for a meaningful decomposition and represent common co-regulation or biological functions. The low-dimensional set of factor mixing weights is further used as features by a classifier to annotate expression patterns with functional categories. On human-curated annotations, our sparse approach reaches similar or better classification of expression patterns at different developmental stages, when compared to other automatic image annotation methods using thousands of hard-to-interpret features. Our study therefore outlines a general framework for large microscopy data sets, in which both the generative model itself, as well as its application for analysis tasks such as automated annotation, can provide insight into biological questions.

Hierarchical bayesian modeling of topics in time-stamped documents.

We consider the problem of inferring and modeling topics in a sequence of documents with known publication dates. The documents at a given time are each characterized by a topic and the topics are drawn from a mixture model. The proposed model infers the change in the topic mixture weights as a function of time. The details of this general framework may take different forms, depending on the specifics of the model. For the examples considered here, we examine base measures based on independent multinomial-Dirichlet measures for representation of topic-dependent word counts. The form of the hierarchical model allows efficient variational Bayesian inference, of interest for large-scale problems. We demonstrate results and make comparisons to the model when the dynamic character is removed, and also compare to latent Dirichlet allocation (LDA) and Topics over Time (TOT). We consider a database of Neural Information Processing Systems papers as well as the US Presidential State of the Union addresses from 1790 to 2008.

Infinite hidden Markov models for unusual-event detection in video.

We address the problem of unusual-event detection in a video sequence. Invariant subspace analysis (ISA) is used to extract features from the video, and the time-evolving properties of these features are modeled via an infinite hidden Markov model (iHMM), which is trained using "normal"/"typical" video. The iHMM retains a full posterior density function on all model parameters, including the number of underlying HMM states. Anomalies (unusual events) are detected subsequently if a low likelihood is observed when associated sequential features are submitted to the trained iHMM. A hierarchical Dirichlet process framework is employed in the formulation of the iHMM. The evaluation of posterior distributions for the iHMM is achieved in two ways: via Markov chain Monte Carlo and using a variational Bayes formulation. Comparisons are made to modeling based on conventional maximum-likelihood-based HMMs, as well as to Dirichlet-process-based Gaussian-mixture models.