FOXO1 is a master regulator of memory programming in CAR T cells.

A major limitation of chimeric antigen receptor (CAR) T cell therapies is the poor persistence of these cells in vivo1. The expression of memory-associated genes in CAR T cells is linked to their long-term persistence in patients and clinical efficacy2-6, suggesting that memory programs may underpin durable CAR T cell function. Here we show that the transcription factor FOXO1 is responsible for promoting memory and restraining exhaustion in human CAR T cells. Pharmacological inhibition or gene editing of endogenous FOXO1 diminished the expression of memory-associated genes, promoted an exhaustion-like phenotype and impaired the antitumour activity of CAR T cells. Overexpression of FOXO1 induced a gene-expression program consistent with T cell memory and increased chromatin accessibility at FOXO1-binding motifs. CAR T cells that overexpressed FOXO1 retained their function, memory potential and metabolic fitness in settings of chronic stimulation, and exhibited enhanced persistence and tumour control in vivo. By contrast, overexpression of TCF1 (encoded by TCF7) did not enforce canonical memory programs or enhance the potency of CAR T cells. Notably, FOXO1 activity correlated with positive clinical outcomes of patients treated with CAR T cells or tumour-infiltrating lymphocytes, underscoring the clinical relevance of FOXO1 in cancer immunotherapy. Our results show that overexpressing FOXO1 can increase the antitumour activity of human CAR T cells, and highlight memory reprogramming as a broadly applicable approach for optimizing therapeutic T cell states.

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.

BPG: Seamless, automated and interactive visualization of scientific data.

BACKGROUND: We introduce BPG, a framework for generating publication-quality, highly-customizable plots in the R statistical environment. RESULTS: This open-source package includes multiple methods of displaying high-dimensional datasets and facilitates generation of complex multi-panel figures, making it suitable for complex datasets. A web-based interactive tool allows online figure customization, from which R code can be downloaded for integration with computational pipelines. CONCLUSION: BPG provides a new approach for linking interactive and scripted data visualization and is available at http://labs.oicr.on.ca/boutros-lab/software/bpg or via CRAN at https://cran.r-project.org/web/packages/BoutrosLab.plotting.general.

Polyketide and nonribosomal peptide retro-biosynthesis and global gene cluster matching.

Polyketides (PKs) and nonribosomal peptides (NRPs) are profoundly important natural products, forming the foundations of many therapeutic regimes. Decades of research have revealed over 11,000 PK and NRP structures, and genome sequencing is uncovering new PK and NRP gene clusters at an unprecedented rate. However, only ∼10% of PK and NRPs are currently associated with gene clusters, and it is unclear how many of these orphan gene clusters encode previously isolated molecules. Therefore, to efficiently guide the discovery of new molecules, we must first systematically de-orphan emergent gene clusters from genomes. Here we provide to our knowledge the first comprehensive retro-biosynthetic program, generalized retro-biosynthetic assembly prediction engine (GRAPE), for PK and NRP families and introduce a computational pipeline, global alignment for natural products cheminformatics (GARLIC), to uncover how observed biosynthetic gene clusters relate to known molecules, leading to the identification of gene clusters that encode new molecules.

Assembly and clustering of natural antibiotics guides target identification.

Antibiotics are essential for numerous medical procedures, including the treatment of bacterial infections, but their widespread use has led to the accumulation of resistance, prompting calls for the discovery of antibacterial agents with new targets. A majority of clinically approved antibacterial scaffolds are derived from microbial natural products, but these valuable molecules are not well annotated or organized, limiting the efficacy of modern informatic analyses. Here, we provide a comprehensive resource defining the targets, chemical origins and families of the natural antibacterial collective through a retrobiosynthetic algorithm. From this we also detail the directed mining of biosynthetic scaffolds and resistance determinants to reveal structures with a high likelihood of having previously unknown modes of action. Implementing this pipeline led to investigations of the telomycin family of natural products from Streptomyces canus, revealing that these bactericidal molecules possess a new antibacterial mode of action dependent on the bacterial phospholipid cardiolipin.

The molecular basis of breast cancer pathological phenotypes.

The histopathological evaluation of morphological features in breast tumours provides prognostic information to guide therapy. Adjunct molecular analyses provide further diagnostic, prognostic and predictive information. However, there is limited knowledge of the molecular basis of morphological phenotypes in invasive breast cancer. This study integrated genomic, transcriptomic and protein data to provide a comprehensive molecular profiling of morphological features in breast cancer. Fifteen pathologists assessed 850 invasive breast cancer cases from The Cancer Genome Atlas (TCGA). Morphological features were significantly associated with genomic alteration, DNA methylation subtype, PAM50 and microRNA subtypes, proliferation scores, gene expression and/or reverse-phase protein assay subtype. Marked nuclear pleomorphism, necrosis, inflammation and a high mitotic count were associated with the basal-like subtype, and had a similar molecular basis. Omics-based signatures were constructed to predict morphological features. The association of morphology transcriptome signatures with overall survival in oestrogen receptor (ER)-positive and ER-negative breast cancer was first assessed by use of the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset; signatures that remained prognostic in the METABRIC multivariate analysis were further evaluated in five additional datasets. The transcriptomic signature of poorly differentiated epithelial tubules was prognostic in ER-positive breast cancer. No signature was prognostic in ER-negative breast cancer. This study provided new insights into the molecular basis of breast cancer morphological phenotypes. The integration of morphological with molecular data has the potential to refine breast cancer classification, predict response to therapy, enhance our understanding of breast cancer biology, and improve clinical management. This work is publicly accessible at www.dx.ai/tcga_breast. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

A Crowdsourcing Approach to Developing and Assessing Prediction Algorithms for AML Prognosis.

Acute Myeloid Leukemia (AML) is a fatal hematological cancer. The genetic abnormalities underlying AML are extremely heterogeneous among patients, making prognosis and treatment selection very difficult. While clinical proteomics data has the potential to improve prognosis accuracy, thus far, the quantitative means to do so have yet to be developed. Here we report the results and insights gained from the DREAM 9 Acute Myeloid Prediction Outcome Prediction Challenge (AML-OPC), a crowdsourcing effort designed to promote the development of quantitative methods for AML prognosis prediction. We identify the most accurate and robust models in predicting patient response to therapy, remission duration, and overall survival. We further investigate patient response to therapy, a clinically actionable prediction, and find that patients that are classified as resistant to therapy are harder to predict than responsive patients across the 31 models submitted to the challenge. The top two performing models, which held a high sensitivity to these patients, substantially utilized the proteomics data to make predictions. Using these models, we also identify which signaling proteins were useful in predicting patient therapeutic response.

Tetravalent anti-CD20/CD3 bispecific antibody for the treatment of B cell lymphoma.

Bispecific antibodies (bsAbs) are second generation antibodies for therapeutic application in immunotherapy. One of the major strategies of the bsAb platform is the recruitment of immune effector T cells by incorporating an anti-CD3 domain. A bispecific T-cell engager (BiTE), with one end having an affinity for CD3 and the other end with affinity for CD19, has been approved in the US and Europe for the treatment of acute lymphoblastic leukemia. However, due to their small size and lack of Fc region, these single-chain variable fragment (scFv) bsAbs have short half-lives in vivo. Additionally, poor solubility, structural instability, and low production yields have also become major challenges in the bulk production process. To overcome these challenges, we have engineered a tetravalent bsAb with bivalent binding specificity for the CD20 and CD3 antigen in an immunoglobulin G (IgG) format. The fusion of the anti-CD3 scFvs to the CD20 antibody via a linker-hinge domain (LHD) results in improved antibody stabilization and properties. Here we demonstrate this antibody's highly efficient cancer cell elimination in a dose-dependent manner in a CD20-expressing B lymphoblastoid cell line in vitro. Our data suggest the potential clinical application of this bsAb for the treatment of CD20-expressing B cell malignancies.

Hedgehog signaling in neonatal and adult lung.

Sonic Hedgehog (Shh) signaling is essential during embryonic lung development, but its role in postnatal lung development and adult lung are not known. Using Gli1(nlacZ) reporter mice to identify cells with active Hh signaling, we found that Gli1(nlacZ)-positive mesenchymal cells are densely and diffusely present up to 2 weeks after birth and decline in number thereafter. In adult mice, Gli1(nlacZ)-positive cells are present around large airways and vessels and are sparse in alveolar septa. Hh-stimulated cells are mostly fibroblasts; only 10% of Gli1(nlacZ)-positive cells are smooth muscle cells, and most smooth muscle cells do not have activation of Hh signaling. To assess its functional relevance, we influenced Hh signaling in the developing postnatal lung and adult injured lung. Inhibition of Hh signaling during early postnatal lung development causes airspace enlargement without diminished alveolar septation. After bleomycin injury in the adult lung, there are abundant Gli1(nlacZ)-positive mesenchymal cells in fibrotic lesions and increased numbers of Gli1(nlacZ)-positive cells in preserved alveolar septa. Inhibition of Hh signaling with an antibody against all Hedgehog isoforms does not reduce bleomycin-induced fibrosis, but adenovirus-mediated overexpression of Shh increases collagen production in this model. Our data provide strong evidence that Hh signaling can regulate lung stromal cell function in two critical scenarios: normal development in postnatal lung and lung fibrosis in adult lung.

Biventricular Takotsubo Cardiomyopathy Secondary to COVID-19.

Takotsubo cardiomyopathy (TCM) is a heart failure syndrome characterized by acute and transient dysfunction of the apical segment of the left ventricle. Since the emergence of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the diagnosis of TCM has increased in prevalence. Here we present an intriguing case of a patient who initially presented to the hospital with respiratory failure and received a diagnosis of COVID-19. During the patient's hospital course, he was also diagnosed with biventricular TCM and subsequently experienced complete resolution of TCM before discharge. Providers should be cognizant of the potential cardiovascular complications of COVID-19 and consider those heart failure syndromes, including TCM, could be causing some of the respiratory dysfunction in these patients.

Characterization of Leukemic Resistance to CD19-Targeted CAR T-cell Therapy through Deep Genomic Sequencing.

Chimeric antigen receptor (CAR) T-cell therapy targeting CD19 has been a clinical breakthrough for pediatric B-cell acute lymphoblastic leukemia (B-ALL), and loss of the CD19 target antigen on leukemic cells represents a major mechanism of relapse. Previous studies have observed CD19 mutations specific to CD19- relapses, and we sought to clarify and strengthen this relationship using deep whole-exome sequencing in leukemic cells expanded in a patient-derived xenograft. By assessing pre-treatment and relapse cells from 13 patients treated with CAR T-cell therapy, 8 of whom developed CD19- relapse and 5 of whom developed CD19+ relapse, we demonstrate that relapse-specific single-nucleotide variants and small indels with high allele frequency combined with deletions in the CD19 gene in a manner specific to those patients with CD19- relapse. Before CAR T-cell infusion, one patient was found to harbor a pre-existing CD19 deletion in the context of genomic instability, which likely represented the first hit leading to the patient's subsequent CD19- relapse. Across patients, preexisting mutations and genomic instability were not significant predictors of subsequent CD19- relapse across patients, with sample size as a potential limiting factor. Together, our results clarify and strengthen the relationship between genomic events and CD19- relapse, demonstrating this intriguing mechanism of resistance to a targeted cancer immunotherapy.

Identification and targeting of treatment resistant progenitor populations in T-cell Acute Lymphoblastic Leukemia.

Refractoriness to initial chemotherapy and relapse after remission are the main obstacles to cure in T-cell Acute Lymphoblastic Leukemia (T-ALL). Biomarker guided risk stratification and targeted therapy have the potential to improve outcomes in high-risk T-ALL; however, cellular and genetic factors contributing to treatment resistance remain unknown. Previous bulk genomic studies in T-ALL have implicated tumor heterogeneity as an unexplored mechanism for treatment failure. To link tumor subpopulations with clinical outcome, we created an atlas of healthy pediatric hematopoiesis and applied single-cell multiomic (CITE-seq/snATAC-seq) analysis to a cohort of 40 cases of T-ALL treated on the Children's Oncology Group AALL0434 clinical trial. The cohort was carefully selected to capture the immunophenotypic diversity of T-ALL, with early T-cell precursor (ETP) and Near/Non-ETP subtypes represented, as well as enriched with both relapsed and treatment refractory cases. Integrated analyses of T-ALL blasts and normal T-cell precursors identified a bone-marrow progenitor-like (BMP-like) leukemia sub-population associated with treatment failure and poor overall survival. The single-cell-derived molecular signature of BMP-like blasts predicted poor outcome across multiple subtypes of T-ALL within two independent patient cohorts using bulk RNA-sequencing data from over 1300 patients. We defined the mutational landscape of BMP-like T-ALL, finding that NOTCH1 mutations additively drive T-ALL blasts away from the BMP-like state. We transcriptionally matched BMP-like blasts to early thymic seeding progenitors that have low NR3C1 expression and high stem cell gene expression, corresponding to a corticosteroid and conventional cytotoxic resistant phenotype we observed in ex vivo drug screening. To identify novel targets for BMP-like blasts, we performed in silico and in vitro drug screening against the BMP-like signature and prioritized BMP-like overexpressed cell-surface (CD44, ITGA4, LGALS1) and intracellular proteins (BCL-2, MCL-1, BTK, NF-κB) as candidates for precision targeted therapy. We established patient derived xenograft models of BMP-high and BMP-low leukemias, which revealed vulnerability of BMP-like blasts to apoptosis-inducing agents, TEC-kinase inhibitors, and proteasome inhibitors. Our study establishes the first multi-omic signatures for rapid risk-stratification and targeted treatment of high-risk T-ALL.

B cell targeting in CAR T cell therapy: Side effect or driver of CAR T cell function?

Chimeric antigen receptor (CAR) T cell therapies targeting CD19 and CD22 have been successful for treating B cell cancers, but CAR T cells targeting non-B cell cancers remain unsuccessful. We propose that rather than being strictly a side effect of therapy, the large number of CAR interactions with normal B cells may be a key contributor to clinical CAR T cell responses.

Network Analysis Reveals Synergistic Genetic Dependencies for Rational Combination Therapy in Philadelphia Chromosome-Like Acute Lymphoblastic Leukemia.

PURPOSE: Systems biology approaches can identify critical targets in complex cancer signaling networks to inform new therapy combinations that may overcome conventional treatment resistance. EXPERIMENTAL DESIGN: We performed integrated analysis of 1,046 childhood B-ALL cases and developed a data-driven network controllability-based approach to identify synergistic key regulator targets in Philadelphia chromosome-like B-acute lymphoblastic leukemia (Ph-like B-ALL), a common high-risk leukemia subtype associated with hyperactive signal transduction and chemoresistance. RESULTS: We identified 14 dysregulated network nodes in Ph-like ALL involved in aberrant JAK/STAT, Ras/MAPK, and apoptosis pathways and other critical processes. Genetic cotargeting of the synergistic key regulator pair STAT5B and BCL2-associated athanogene 1 (BAG1) significantly reduced leukemia cell viability in vitro. Pharmacologic inhibition with dual small molecule inhibitor therapy targeting this pair of key nodes further demonstrated enhanced antileukemia efficacy of combining the BCL-2 inhibitor venetoclax with the tyrosine kinase inhibitors ruxolitinib or dasatinib in vitro in human Ph-like ALL cell lines and in vivo in multiple childhood Ph-like ALL patient-derived xenograft models. Consistent with network controllability theory, co-inhibitor treatment also shifted the transcriptomic state of Ph-like ALL cells to become less like kinase-activated BCR-ABL1-rearranged (Ph+) B-ALL and more similar to prognostically favorable childhood B-ALL subtypes. CONCLUSIONS: Our study represents a powerful conceptual framework for combinatorial drug discovery based on systematic interrogation of synergistic vulnerability pathways with pharmacologic inhibitor validation in preclinical human leukemia models.

Integrative Bulk and Single-Cell Profiling of Premanufacture T-cell Populations Reveals Factors Mediating Long-Term Persistence of CAR T-cell Therapy.

The adoptive transfer of chimeric antigen receptor (CAR) T cells represents a breakthrough in clinical oncology, yet both between- and within-patient differences in autologously derived T cells are a major contributor to therapy failure. To interrogate the molecular determinants of clinical CAR T-cell persistence, we extensively characterized the premanufacture T cells of 71 patients with B-cell malignancies on trial to receive anti-CD19 CAR T-cell therapy. We performed RNA-sequencing analysis on sorted T-cell subsets from all 71 patients, followed by paired Cellular Indexing of Transcriptomes and Epitopes (CITE) sequencing and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) on T cells from six of these patients. We found that chronic IFN signaling regulated by IRF7 was associated with poor CAR T-cell persistence across T-cell subsets, and that the TCF7 regulon not only associates with the favorable naïve T-cell state, but is maintained in effector T cells among patients with long-term CAR T-cell persistence. These findings provide key insights into the underlying molecular determinants of clinical CAR T-cell function. SIGNIFICANCE: To improve clinical outcomes for CAR T-cell therapy, there is a need to understand the molecular determinants of CAR T-cell persistence. These data represent the largest clinically annotated molecular atlas in CAR T-cell therapy to date, and significantly advance our understanding of the mechanisms underlying therapeutic efficacy.This article is highlighted in the In This Issue feature, p. 2113.

Overexpression and activation of epidermal growth factor receptor in hemangioblastomas.

Hemangioblastomas frequently develop in patients with von Hippel-Lindau (VHL) disease, an autosomal dominant genetic disorder. The tumors are characterized by a dense network of blood capillaries, often in association with cysts. Although activation of receptor tyrosine kinase (RTK) signaling, including epidermal growth factor receptor (EGFR) has been implicated in the development of malignant brain tumors such as high-grade gliomas, little is known about the role of RTK signaling in hemangioblastomas. To address this issue, we examined hemangioblastoma tumor specimens using receptor tyrosine kinase (RTK) activation profiling and immunohistochemistry. Six human hemangioblastomas were analyzed with a phospho-RTK antibody array, revealing EGFR phosphorylation in all tumors. EGFR expression was confirmed by immunohistochemistry in all tumors analyzed and downstream effector pathway activation was demonstrated by positive staining for phospho-AKT. Our findings suggest that, in primary hemangioblastomas, RTK upregulation and signaling predominantly involves EGFR, providing an attractive molecular target for therapeutic intervention.

Dissecting the Tumor-Immune Landscape in Chimeric Antigen Receptor T-cell Therapy: Key Challenges and Opportunities for a Systems Immunology Approach.

The adoptive transfer of genetically engineered chimeric antigen receptor (CAR) T cells has opened a new frontier in cancer therapy. Unlike the paradigm of targeted therapies, the efficacy of CAR T-cell therapy depends not only on the choice of target but also on a complex interplay of tumor, immune, and stromal cell communication. This presents both challenges and opportunities from a discovery standpoint. Whereas cancer consortia have traditionally focused on the genomic, transcriptomic, epigenomic, and proteomic landscape of cancer cells, there is an increasing need to expand studies to analyze the interactions between tumor, immune, and stromal cell populations in their relevant anatomical and functional compartments. Here, we focus on the promising application of systems biology to address key challenges in CAR T-cell therapy, from understanding the mechanisms of therapeutic resistance in hematologic and solid tumors to addressing important clinical challenges in biomarker discovery and therapeutic toxicity. We propose a systems biology view of key clinical objectives in CAR T-cell therapy and suggest a path forward for a biomedical discovery process that leverages modern technological approaches in systems biology.

Diverse noncoding mutations contribute to deregulation of cis-regulatory landscape in pediatric cancers.

Interpreting the function of noncoding mutations in cancer genomes remains a major challenge. Here, we developed a computational framework to identify putative causal noncoding mutations of all classes by joint analysis of mutation and gene expression data. We identified thousands of SNVs/small indels and structural variants as putative causal mutations in five major pediatric cancers. We experimentally validated the oncogenic role of CHD4 overexpression via enhancer hijacking in B-ALL. We observed a general exclusivity of coding and noncoding mutations affecting the same genes and pathways. We showed that integrated mutation profiles can help define novel patient subtypes with different clinical outcomes. Our study introduces a general strategy to systematically identify and characterize the full spectrum of noncoding mutations in cancers.