Leveraging T cell receptor signaling heterogeneity for improved adoptive cell therapies
Adoptive T cell therapies rely on promoting the tumor-killing capacity of a cancer patient’s T cells. These therapies are revolutionizing cancer treatment and have demonstrated remarkable efficiency for some cancer types. However, their effectiveness is still limited; a restricted number of patients (<4%) with advanced or metastatic cancers benefit from these state-of-the-art therapies, and significant efforts are being made to refine current protocols and develop novel ACT strategies.
Focusing on the dynamics of T cell receptor (TCR) signaling, using imaging, artificial intelligence, and T cell functionality assays, we propose to identify patients who will benefit most from ACT and improve the efficacy of these treatments. We hypothesize that studying the heterogeneity of TCR signaling dynamics during T cell activation can be valuable to predict T cell states at the single cell level.
Objectives:
1) We monitor Ca signaling dynamics to provide a functional characterization of the Tumor Infiltrating Lymphhocytes CD8 T cell population, in attempt to develop novel biomarkers to find patients that will most benefit from TIL therapies.
2) We curate T cell activation dynamics which lead to optimal tumor control and artificially expose TCR- or Chimeric Antigen Receptor-transduced T cells to these patterns of stimulation, to evaluate if they promote similar function on ACT products.
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Funding
Cancer Research Society (CRS) - Next Generation of Scientists Award start-up grant
Biomarker discovery in the context of mRNA-based in vivo CAR T cell therapy
In vivo Chimeric Antigen Receptor (CAR) T cell therapy, rely on the in situ modification of immune cells through lipid nanoparticle (LNP) delivery of CAR mRNA. Engineering of the LNP, through antibody decoration or biochemical modification, allows for the targeted delivery of the CAR mRNA to CD8 T cells or myeloid antigen-presenting cells (e.g., macrophages). Critically, the targeted populations are highly heterogeneous in vivo; there are not only many distinct subsets of each immune cells but also varying levels of dysfunctional phenotypes linked to cancer immunosuppressive microenvironment and previous treatments. We hypothesize that CAR-expressing immune cells following in vivo mRNA delivery will display important cell-to-cell heterogeneity in their effector function.
We investigate this functional heterogeneity of in vivo CAR transduced cells; comparing highly vs weakly functional cells may allow for the discovery of novel biomarkers associated with improved therapeutic efficacy. These biomarkers could be leveraged into better targeting strategies (i.e., target mRNA delivery to highly functional cells) or to promote specific effector function in CAR-expressing immune cells (i.e., enhancing specific pathway through combination therapy).
Funding
DNA to RNA (D2R) New Faculty start-up funds
Identifying actionable pathways to control long-term T cell fate
Engagement of individual T cells with antigen presenting cells induces a multitude of signaling pathways downstream of the T cell receptor (TCR) complex but also downstream of costimulation molecules, cytokine receptors, and/or other microenvironmental cues. The dynamics of TCR signaling contains information about the state of individual T cells upon antigen recognition. However, predicting complex T cell states, such as T cell exhaustion, from early TCR signaling remains a significant challenge. A better understanding of the signaling cascade downstream of antigen recognition has the potential to greatly advance the field of adoptive T cell therapies and T cell immunity. However, a more comprehensive approach that monitors multiple components of the T cell signaling cascade simultaneously, through time, and at the single cell level is required.
We aim to engineer reporters for TCR and related signaling pathways and use them in combination with methods to measure metabolic state and T cell:antigen presenting cell contact to enable high-throughput, time-resolved, multimodal imaging of T cell activation. Using higher dimension imaging modalities, we evaluate the predictive power of T cell activation dynamics for determining complex T cell states and fates. Furthermore, we aim to quantify the contribution of individual signaling pathways and their interactions in shaping effector functions, identifying the most actionable pathways to manipulate T cell fate.
Intracellular calcium dynamics as a predictor of TCR affinity for cognate antigen
The strength of antigen recognition by the T cell receptor (TCR) dictates T cell fate and function. However, existing methods to quantify TCR avidity for cognate antigen at the single cell level are limited. We developed a microscopy-based method based on intracellular calcium (Ca ) oscillations, an early functional readout of TCR engagement, to monitor the quality of TCR signaling following T cell activation. We have generated a large dataset of images and Ca signaling temporal dynamics; this dataset is used to train deep-learning models to predict T cell avidity at the single cell level. This includes approach for the extraction of relevant image-based parameters for T cell activation (Ca levels, morphology, migration, etc.) as well as video-based classification.
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