Abstract 1970: Single cell proteomic quantification of T cell states using mass cytometry for applications in monitoring immune responses in cancer immunotherapy clinical trials
Authors: Sidiropoulos Dimitrios N. , Phyo Zaw , Gross Nicole , Charmsaz Soren , Xavier Stephanie , Leatherman James , Yarchoan Mark , Jaffee Elizabeth M. , Fertig Elana J. , Ho Won Jin 
Published: June 2022

Although immunotherapies have been established as a successful treatment option for several types of cancers, additional treatment strategies are necessary to broaden the cohorts of patients who may receive clinical benefit. Common immunological profiling for immunotherapy response depends on assessment of the composition of immune cell types in tissue samples and the periphery. Still, the function and state of each of these cells further contributes to the ultimate clinical benefit of immunotherapeutic response. Additionally, our ability to comprehensively study treatment strategies depends on elucidating the temporal effects different immunotherapy regimens have on the immune system of patients. Single-cell proteomics profiling with CyTOF mass cytometry enables robust protein-level profiling of cell types and is also high-dimensional enough to characterize functional states of immune cells. To construct an immunological framework that may feasibly serve to empower functional assessment of immune cell states for clinical trial monitoring strategies using CyTOF, we are employing single cell trajectory inference methods and non-negative matrix factorization (NMF). We demonstrate this approach using peripheral blood derived CyTOF mass cytometry data to model T cell states at the proteomic level. First, we extract T helper (Th) and T cytotoxic (Tc) cell integrated metrics from CyTOF mass cytometry data obtained from diverse cell marker panel designs, immunological states, and diseases to benchmark that these computational pipelines can accurately reflect Th and Tc activation and exhaustion. Next, we develop a new pipeline that enables the use of continuous functional cell-state metrics from continuous pseudotime and NMF pattern weights as immunological profiling markers from CyTOF that can be applied to cancer immunotherapy clinical trials. For instance, we find CyTOF Tc pseudotime and memory pattern weights are higher in PDAC patients with stable disease treated with ipilimumab and a pancreatic cancer-specific vaccine. Thus, our pipeline has the ability to integrate metrics from mass cytometry data to empower translational analyses for determining patient responses in cancer immunotherapy, such as adaptive immune responses to checkpoint inhibitors and cancer vaccines. Moreover, applying this pipeline to peripheral blood samples obtained before and after treatment also enables us to map further temporal cell state transitions in Tc and Th cells resulting from that treatment. Future work will include leveraging CyTOF T cell integrated metrics in larger scale survival analyses to test the predictive potential in a clinical proof of concept.

Citation Format: Dimitrios N. Sidiropoulos, Zaw Phyo, Nicole Gross, Soren Charmsaz, Stephanie Xavier, James Leatherman, Mark Yarchoan, Elizabeth M. Jaffee, Elana J. Fertig, Won Jin Ho. Single cell proteomic quantification of T cell states using mass cytometry for applications in monitoring immune responses in cancer immunotherapy clinical trials [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1970.