Abstract 2181: Establishing a multi-modal, cell therapy characterization workflow to identify cell subsets with heightened cytotoxicity
Authors: Richard Yau, Shreya Deshmukh, JangKeun Kim, Jiwoon Park, Yanping Yang, Makenzie Sacca, Shan Sabri, Teresa Ai, Pier Federico Gherardini, Gary Schroth, Christopher E. Mason, Moonsoo M. Jin
Journal: Cancer Research (2025)

Cell therapies have been groundbreaking for B-cell lymphomas but optimizing efficacy for solid tumors remains challenging. Lack of consensus on potency measures, unknowns about novel engineering strategies, and product heterogeneity drive extensive characterization to discover product-specific mechanisms of action (MoAs). This process is costly and limited by variable results from simple molecular assays and need to infer relationships between data from disparate technologies. Thus, we created a multi-modal technology with which to establish a multi-functional, longitudinal cellular characterization workflow. With a single sample input, this workflow evaluates multiple live phenotypes from the same individual cells across tens of thousands of cells at once. We leveraged TALL-104 cells before validating compatibility with clinical-stage cell therapies with AIC100 - a Phase 1 CAR-T product targeting thyroid cancer (NCT04420754). Cellanome’s technology enables multi-modal evaluation of live, cellular behavior at the resolution of single cells or single-cell interactions. Within an 8-lane flow cell, tens of thousands of single TALL-104 cells were enclosed with K562 target cells in bio-compatible hydrogel compartments called CellCage™ enclosures (CCEs). These CCEs enable longitudinal monitoring of single TALL-104 cells interacting with K562 cells for hours to days with time-lapse imaging. During this period, imaging-based evaluation of surface markers, cytokine secretion, and cytotoxicity are integrated from the same single T-cells. Our analysis pipeline links target cell death to single T cells in CCEs, enabling cell killing to be studied with unprecedented resolution. Similar to flow cytometry via CD107 as a surrogate for killing, with Cellanome’s technology, we could identify cytotoxic T cells (∼85%). Uniquely, we can directly evaluate killing by single TALL-104 cells and further segment them into groups. Group 1 consists of strong killers (killing 100% of targets), Group 2 of medium killers (50-99%), and Group 3 of weaker killers (0-49%). We next characterized single AIC100 cells enclosed with HeLa as targets and observed that, unlike TALL-104 cells where Group 2 was the largest, for AIC100, Group 3 was the largest, suggesting distinct killing mechanisms. Thus, we asked whether AIC100’s heterogeneous composition of CD4 / 8 cells impacts product efficacy. We configured this workflow to test killing by ∼100 combinations of CD4:CD8 AIC100 cells in a single experiment. Preliminarily, more killing occurred in CCEs containing a mixture of CD4 and CD8 T cells relative to CCEs containing only CD4 or CD8 cells. We are continuing to identify the optimal CD4:CD8 compositions for greater potency. We envision multi-modal characterization of clinical products with our platform, pre and post-patient infusion, will inform efforts to advance cell therapies for solid tumors. Citation Format: Richard Yau, Shreya Deshmukh, JangKeun Kim, Jiwoon Park, Yanping Yang, Makenzie Sacca, Shan Sabri, Teresa Ai, Pier Federico Gherardini, Gary Schroth, Christopher E. Mason, Moonsoo M. Jin. Establishing a multi-modal, cell therapy characterization workflow to identify cell subsets with heightened cytotoxicity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2181.