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The antigen specificity and long serum half-life of monoclonal antibodies have made them a critical part of modern therapeutics. These properties have been coopted in a number of synthetic formats, such as antibody-drug conjugates, bispecific antibodies, or Fc-fusion proteins to generate novel biologic drug modalities. Historically, these new therapies have been generated by covalently linking multiple molecular moieties through chemical or genetic methods. This irreversible fusion of different components means that the function of the molecule is static, as determined by the structure. Here, we report the development of a technology for switchable assembly of functional antibody complexes using chemically induced dimerization domains. This approach enables control of the antibody's intended function in vivo by modulating the dose of a small molecule. We demonstrate this switchable assembly across three therapeutically relevant functionalities in vivo, including localization of a radionuclide-conjugated antibody to an antigen-positive tumor, extension of a cytokine's half-life, and activation of bispecific, T cell-engaging antibodies.

BackgroundDiffuse midline gliomas (DMG) are highly malignant incurable pediatric brain tumors. A lack of effective treatment options highlights the need to investigate novel therapeutic strategies. This includes the use of immunotherapy, which has shown promise in other hard-to-treat tumors. To facilitate preclinical immunotherapeutic research, immunocompetent mouse models that accurately reflect the unique genetic, anatomical, and histological features of DMG patients are warranted.MethodsWe established cell cultures from primary DMG mouse models (C57BL/6) that were generated by brainstem targeted intra-uterine electroporation (IUE). We subsequently created allograft DMG mouse models by orthotopically implanting these tumor cells into syngeneic mice. Immunohistochemistry and -fluorescence, mass cytometry, and cell-viability assays were then used to verify that these murine tumors recapitulated human DMG.ResultsWe generated three genetically distinct allograft models representing histone 3 wildtype (H3WT) and K27M-mutant DMG (H3.3K27M and H3.1K27M). These allograft models recapitulated the histopathologic phenotype of their human counterparts, including their diffuse infiltrative growth and expression of DMG-associated antigens. These murine pontine tumors also exhibited an immune microenvironment similar to human DMG, characterized by considerable myeloid cell infiltration and a paucity of T-lymphocytes and NK cells. Finally, we show that these murine DMG cells display similar sensitivity to histone deacetylase (HDAC) inhibition as patient-derived DMG cells.ConclusionsWe created and validated an accessible method to generate immunocompetent allograft models reflecting different subtypes of DMG. These models adequately recapitulated the histopathology, immune microenvironment, and therapeutic response of human DMG, providing useful tools for future preclinical studies.

BackgroundGlioblastoma (GBM) is refractory to immune checkpoint inhibitor (ICI) therapy. We sought to determine to what extent this immune evasion is due to intrinsic properties of the tumor cells versus the specialized immune context of the brain, and if it can be reversed.MethodsWe used CyTOF mass cytometry to compare the tumor immune microenvironments (TIME) of human tumors that are generally ICI-refractory (GBM and sarcoma) or ICI-responsive (renal cell carcinoma), as well as mouse models of GBM that are ICI-responsive (GL261) or ICI-refractory (SB28). We further compared SB28 tumors grown intracerebrally versus subcutaneously to determine how tumor site affects TIME and responsiveness to dual CTLA-4/PD-1 blockade. Informed by these data, we explored rational immunotherapeutic combinations.ResultsICI-sensitivity in human and mouse tumors was associated with increased T cells and dendritic cells (DCs), and fewer myeloid cells, in particular PD-L1+ tumor-associated macrophages. The SB28 mouse model of GBM responded to ICI when grown subcutaneously but not intracerebrally, providing a system to explore mechanisms underlying ICI resistance in GBM. The response to ICI in the subcutaneous SB28 model required CD4 T cells and NK cells, but not CD8 T cells. Recombinant FLT3L expanded DCs, improved antigen-specific T cell priming, and prolonged survival of mice with intracerebral SB28 tumors, but at the cost of increased Tregs. Targeting PD-L1 also prolonged survival, especially when combined with stereotactic radiation.ConclusionsOur data suggest that a major obstacle for effective immunotherapy of GBM is poor antigen presentation in the brain, rather than intrinsic immunosuppressive properties of GBM tumor cells. Deep immune profiling identified DCs and PD-L1+ tumor-associated macrophages as promising targetable cell populations, which was confirmed using therapeutic interventions in vivo.

Amplification of the epidermal growth factor receptor gene (EGFR) represents one of the most commonly observed genetic lesions in glioblastoma (GBM); however, therapies targeting this signaling pathway have failed clinically. Here, using human tumors, primary patient-derived xenografts (PDX), and a murine model for GBM, we demonstrate that EGFR inhibition leads to increased invasion of tumor cells. Further, EGFR inhibitor-treated GBM demonstrates altered oxidative stress, with increased lipid peroxidation, and generation of toxic lipid peroxidation products. A tumor cell subpopulation with elevated aldehyde dehydrogenase (ALDH) levels was determined to comprise a significant proportion of the invasive cells observed in EGFR inhibitor-treated GBM. Our analysis of the ALDH1A1 protein in newly diagnosed GBM revealed detectable ALDH1A1 expression in 69% (35/51) of the cases, but in relatively low percentages of tumor cells. Analysis of paired human GBM before and after EGFR inhibitor therapy showed an increase in ALDH1A1 expression in EGFR-amplified tumors (P < 0.05, n = 13 tumor pairs), and in murine GBM ALDH1A1-high clones were more resistant to EGFR inhibition than ALDH1A1-low clones. Our data identify ALDH levels as a biomarker of GBM cells with high invasive potential, altered oxidative stress, and resistance to EGFR inhibition, and reveal a therapeutic target whose inhibition should limit GBM invasion.

The advent of mass cytometry (CyTOF®) has permitted simultaneous detection of more than 40 antibody parameters at the single-cell level, although a limited number of metal-labeled antibodies are commercially available. Here we present optimized and scalable protocols for conjugation of lanthanide as well as bismuth ions to immunoglobulin (Ig) using a maleimide-functionalized chelating polymer and for characterization of the conjugate. The maleimide functional group is reactive with cysteine sulfhydryl groups generated through partial reduction of the Ig Fc region. Incubation of Ig with polymer pre-loaded with lanthanide ions produces metal-labeled Ig without disrupting antigen specificity. Antibody recovery rates can be determined by UV spectrophotometry and frequently exceeds 60%. Each custom-conjugated antibody is validated using positive and negative cellular control populations and is titrated for optimal staining at concentrations ranging from 0.1 to 10 μg/mL. The preparation of metal-labeled antibodies can be completed in 4.5 h, and titration requires an additional 3-5 h.

MotivationHigh-parameter single-cell technologies can reveal novel cell populations of interest, but studying or validating these populations using lower-parameter methods remains challenging.ResultsHere, we present GateFinder, an algorithm that enriches high-dimensional cell types with simple, stepwise polygon gates requiring only two markers at a time. A series of case studies of complex cell types illustrates how simplified enrichment strategies can enable more efficient assays, reveal novel biomarkers and clarify underlying biology.Availability and implementationThe GateFinder algorithm is implemented as a free and open-source package for BioConductor: https://nalab.stanford.edu/gatefinder.Supplementary informationSupplementary data are available at Bioinformatics online.

Single-cell barcoding enables the combined processing and acquisition of multiple individual samples as one. This maximizes assay efficiency and eliminates technical variability in both sample preparation and analysis. Remaining challenges are the barcoding of live, unprocessed cells to increase downstream assay performance combined with the flexibility of the approach towards a broad range of cell types. To that end, we developed a novel antibody-based platform that allows the robust barcoding of live human cells for mass cytometry (CyTOF). By targeting both the MHC class I complex (beta-2-microglobulin) and a broadly expressed sodium-potassium ATPase-subunit (CD298) with platinum-conjugated antibodies, human immune cells, stem cells as well as tumor cells could be multiplexed in the same single-cell assay. In addition, we present a novel palladium-based covalent viability reagent compatible with this barcoding strategy. Altogether, this platform enables mass cytometry-based, live-cell barcoding across a multitude of human sample types and provides a scheme for multiplexed barcoding of human single-cell assays in general.

Although signaling from phosphatidylinositol 3-kinase (PI3K) and AKT to mechanistic target of rapamycin (mTOR) is prominently dysregulated in high-grade glial brain tumors, blockade of PI3K or AKT minimally affects downstream mTOR activity in glioma. Allosteric mTOR inhibitors, such as rapamycin, incompletely block mTORC1 compared with mTOR kinase inhibitors (TORKi). Here, we compared RapaLink-1, a TORKi linked to rapamycin, with earlier-generation mTOR inhibitors. Compared with rapamycin and Rapalink-1, TORKi showed poor durability. RapaLink-1 associated with FKBP12, an abundant mTOR-interacting protein, enabling accumulation of RapaLink-1. RapaLink-1 showed better efficacy than rapamycin or TORKi, potently blocking cancer-derived, activating mutants of mTOR. Our study re-establishes mTOR as a central target in glioma and traces the failure of existing drugs to incomplete/nondurable inhibition of mTORC1.

High-grade gliomas in children are different from those that arise in adults. Recent collaborative molecular analyses of these rare cancers have revealed previously unappreciated connections among chromatin regulation, developmental signaling, and tumorigenesis. As we begin to unravel the unique developmental origins and distinct biological drivers of this heterogeneous group of tumors, clinical trials need to keep pace. It is important to avoid therapeutic strategies developed purely using data obtained from studies on adult glioblastoma. This approach has resulted in repetitive trials and ineffective treatments being applied to these children, with limited improvement in clinical outcome. The authors of this perspective, comprising biology and clinical expertise in the disease, recently convened to discuss the most effective ways to translate the emerging molecular insights into patient benefit. This article reviews our current understanding of pediatric high-grade glioma and suggests approaches for innovative clinical management.

MYC proteins are major drivers of cancer yet are considered undruggable because their DNA binding domains are composed of two extended alpha helices with no apparent surfaces for small-molecule binding. Proteolytic degradation of MYCN protein is regulated in part by a kinase-independent function of Aurora A. We describe a class of inhibitors that disrupts the native conformation of Aurora A and drives the degradation of MYCN protein across MYCN-driven cancers. Comparison of cocrystal structures with structure-activity relationships across multiple inhibitors and chemotypes, coupled with mechanistic studies and biochemical assays, delineates an Aurora A conformation-specific effect on proteolytic degradation of MYCN, rather than simple nanomolar-level inhibition of Aurora A kinase activity.

Insight into the cancer cell populations that are responsible for relapsed disease is needed to improve outcomes. Here we report a single-cell-based study of B cell precursor acute lymphoblastic leukemia at diagnosis that reveals hidden developmentally dependent cell signaling states that are uniquely associated with relapse. By using mass cytometry we simultaneously quantified 35 proteins involved in B cell development in 60 primary diagnostic samples. Each leukemia cell was then matched to its nearest healthy B cell population by a developmental classifier that operated at the single-cell level. Machine learning identified six features of expanded leukemic populations that were sufficient to predict patient relapse at diagnosis. These features implicated the pro-BII subpopulation of B cells with activated mTOR signaling, and the pre-BI subpopulation of B cells with activated and unresponsive pre-B cell receptor signaling, to be associated with relapse. This model, termed 'developmentally dependent predictor of relapse' (DDPR), significantly improves currently established risk stratification methods. DDPR features exist at diagnosis and persist at relapse. By leveraging a data-driven approach, we demonstrate the predictive value of single-cell 'omics' for patient stratification in a translational setting and provide a framework for its application to human cancer., Author(s): Zinaida Good [1, 2, 3, 4]; Jolanda Sarno [5, 6]; Astraea Jager [1, 2, 5]; Nikolay Samusik [1, 2]; Nima Aghaeepour [1, 2]; Erin F Simonds [1, 2]; Leah [...]