Abstract Glucocorticoid-induced TNFR family related protein (GITR, CD357 or TNFRSF18) is a member of the tumor necrosis factor receptor superfamily (TNFRSF). Like other T cell co-stimulatory TNFR family members, GITR utilizes multiple oligomerization states to regulate the initiation of downstream signaling during T cell activation by antigen presenting cells (APCs). The formation of receptor superclusters, comprised of two or more trimeric molecules, has been defined for multiple TNFRs as a means of regulating downstream signal amplification. For co-stimulatory TNFRs, like GITR, CD137 and OX40, signaling outcomes in T cells are primarily mediated via the NFκB pathway that promotes cell survival and effector cell activities in response to suboptimal T cell receptor (TCR) stimulation. It has been hypothesized that the manipulation of the oligomeric states of co-stimulatory TNFRs using antibodies may have therapeutic utility in enhancing the activity of tumor-reactive T cells, either as single agents or in combination with other immunomodulatory or immune education strategies. Here we describe a structure-based analysis of two functionally distinct classes of anti-human GITR antibodies that stabilize unique conformational states of the receptor. INCAGN1876, a human IgG1 monoclonal anti-GITR antibody, was found to engage a conformational epitope located within a β-turn of the extracellular domain of GITR. This antibody binding site modified the equilibrium of GITR monomer, dimer and trimers to promote receptor oligomerization, resulting in downstream NFκB signaling. Notably, this mode of INCAGN1876 receptor engagement enabled it to effectively activate the GITR pathway in recently primed T cells. By contrast, a second reference anti-GITR antibody required concomitant TCR co-engagement in order to modulate the GITR pathway. High content confocal analysis was used to evaluate the kinetics of GITR clustering by both classes of anti-GITR antibody, confirming our T cell functional analysis. The ability of INCAGN1876 to engage and effectively activate GITR on recently primed T cells may enable them to overcome suppressive features of the tumor microenvironment. Notably, INCAGN1876 was shown to promote T cell co-stimulation both as a single agent and in combination with other antibodies targeting PD-1, CTLA-4 and OX40. Finally, we compared the pharmacologic activity of INCAGN1876 to Fc variants of this antibody with diminished binding to the inhibitory Fcγ receptor (FcγR), CD32B. The superiority of an IgG1 antibody in these assays was consistent with the potential to achieve optimal GITR clustering by FcγRs, while maintaining the potential for FcγR-mediated effector cell activity directed toward intratumoral GITRhigh regulatory T cells. INCAGN1876 is currently under evaluation in Phase 1/2 studies in subjects with advanced metastatic solid tumors (NCT02697591). Citation Format: Ana M. Gonzalez, Mariana L. Manrique, Lukasz Swiech, Thomas Horn, Jeremy Waight, Yuqi Liu, Shiwen Lin, Dennis Underwood, Ekaterina Breous, Olivier Leger, Volker Seibert, Taha Merghoub, Roberta Zappasodi, Gerd Ritter, David Schaer, Kevin N. Heller, Kimberli Brill, Peggy Scherle, Gregory Hollis, Reid Huber, Marc van Dijk, Jennifer Buell, Robert Stein, Nicholas S. Wilson. INCAGN1876, a unique GITR agonist antibody that facilitates GITR oligomerization [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3643. doi:10.1158/1538-7445.AM2017-3643
Anti-PD-1 therapies have achieved durable clinical responses in a wide range of malignancies, but responses are limited to a small subset of patients. Expression of PD-L1 on tumor cells by immunohistochemistry (IHC) has been applied as a companion diagnostic for anti-PD-1 therapy. However, recent studies have called in to question the reliability of this method to predict response.
Methods
Here we developed a novel platform that integrates in vitro pharmacogenomic and functional data with clinical pharmacodynamic responses to immunotherapy using proprietary in silico approaches. The data originate from a long-term co-culture of primary antigen-specific T cells and cancer cells which drives T cells to a terminally dysfunctional, PD-1 refractory state. T cell effector functions and gene expression changes were monitored in the presence or absence of anti-PD-1 antibody or genetic knockouts. RNA expression signatures were refined with a randomized sliding window approach to generate a deep learning neural network for PD-1 response prediction.
Results
We defined five T cell states associated with distinct phenotypic and molecular features - naïve, active, effector, transition and dysfunction. Among the genes that were selectively expressed in the dysfunction state, we identified a 96-gene signature that is closely associated with clinical outcomes to anti-PD-1 therapy. In PD-1 treated patients across multiple solid tumor indications, this signature correlates with objective response rate and outperforms traditional metrics such as tumor mutation burden or PD-L1 IHC signal. Moreover, this signature combines with tumor sequencing data to generate a powerful machine-learning model that predicts anti-PD-1 responses in metastatic melanoma patients with significantly higher accuracy than PD-L1 IHC. Having established that the T cell states in our co-culture relate to clinical outcomes, we leveraged the system to investigate the molecular basis for PD-1 responses. Single cell mapping of transition state T cells in the presence of anti-PD-1 revealed an expanded population of T cells that co-expresses PD-1, TIGIT and activation markers. Likewise, PD-L1 knockout on cancer cells identified the TIGIT ligand, CD155, as a potential tumor escape mechanism to anti-PD-1 therapy. Consistent with this, the combination of PD-1 and TIGIT blockade enhanced T cell cytotoxicity of tumor cells relative to monotherapies.
Conclusions
Agenus' T cell dysfunction platform combines deep in vitro profiling and AI-based approaches to predict clinical outcomes. Here, we defined a predictive biomarker signature that outperforms standard PD-L1 IHC. Further, we identified known (TIGIT) and potentially novel combination partners predicted to enhance the durability of anti-PD-1 responses.
Tuberous sclerosis complex (TSC) is a genetic disease resulting from mutation in TSC1 or TSC2 and subsequent hyperactivation of mammalian Target of Rapamycin (mTOR). Common TSC features include brain lesions, such as cortical tubers and subependymal giant cell astrocytomas (SEGAs). However, the current treatment with mTOR inhibitors has critical limitations. We aimed to identify new targets for TSC pharmacotherapy. The results of our shRNA screen point to glutamate-cysteine ligase catalytic subunit (GCLC), a key enzyme in glutathione synthesis, as a contributor to TSC-related phenotype. GCLC inhibition increased cellular stress and reduced mTOR hyperactivity in TSC2-depleted neurons and SEGA-derived cells. Moreover, patients' brain tubers showed elevated GCLC and stress markers expression. Finally, GCLC inhibition led to growth arrest and death of SEGA-derived cells. We describe GCLC as a part of redox adaptation in TSC, needed for overgrowth and survival of mutant cells, and provide a potential novel target for SEGA treatment.
Mammalian target of rapamycin (mTOR) is a serine/threonine protein kinase known to merge extracellular instructions with information about cellular metabolic resources and control the rate of anabolic and catabolic processes accordingly. In neurons, mTOR has been implicated in several aspects of development and physiology. The major problems with studying mTOR functions in neurons are caused by the restricted knowledge of downstream mTOR effectors and relatively poor tools for studying this particular kinase. In this chapter, we describe the materials and methods routinely used in our laboratory to study mTOR function and activity and the binding partners of mTOR in neurons.
Single-cell RNA sequencing (RNA-Seq) provides rich information about cell types and states. However, it is difficult to capture rare dynamic processes, such as adult neurogenesis, because isolation of rare neurons from adult tissue is challenging and markers for each phase are limited. Here, we develop Div-Seq, which combines scalable single-nucleus RNA-Seq (sNuc-Seq) with pulse labeling of proliferating cells by 5-ethynyl-2'-deoxyuridine (EdU) to profile individual dividing cells. sNuc-Seq and Div-Seq can sensitively identify closely related hippocampal cell types and track transcriptional dynamics of newborn neurons within the adult hippocampal neurogenic niche, respectively. We also apply Div-Seq to identify and profile rare newborn neurons in the adult spinal cord, a noncanonical neurogenic region. sNuc-Seq and Div-Seq open the way for unbiased analysis of diverse complex tissues.
Abstract Therapeutic antibodies targeting T cell co-inhibitory pathways, such as cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and programmed cell death protein-1 (PD-1), have emerged as an important class of cancer therapies. Insights into how different IgG isotypes modulate biological activities of antibodies have opened new avenues to enhance their therapeutic effects. For example, Fc-FcγR interactions have been shown to enhance antibody-directed effector cell activities, as well as antibody-dependent forward signaling into target cells via receptor clustering. Here, we describe a novel FcγR-dependent mechanism for antibodies targeting CTLA-4. Our findings suggest that selective Fc-FcγR binding dramatically improves the quality of the immune synapse, which in turn modifies apical T cell receptor signaling events to increase effector T cell activity. Our data also suggest that subsets of antigen-presenting cells (APCs), expressing FcγRIV in mice and FcγRIIIA in humans are important mediators of this effect. Importantly, we find this mechanism to be independent of regulatory T cell (Treg) depletion. Altogether, we describe a novel mechanism of action that provides a foundation for a new class of Fc-engineered antibodies to enhance antitumor immune responses. Citation Format: Jeremy D. Waight, Dhan Chand, Sylvia Dietrich, Randi Gombos, Thomas Horn, Ana M. Gonzalez, Mariana Manrique, Antoine Tanne, Christopher Dupont, Lukasz Swiech, Ben A. Croker, Jennifer S. Buell, Robert Stein, Alex Duncan, David A. Savitsky, Nicholas S. Wilson. Selective FcγR engagement by CTLA-4 antibodies results in increased functional activity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2721.
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