Development of a High-Throughput Image Cytometric Screening Method as a Research Tool for Immunophenotypic Characterization of Patient Samples from Clinical Studies

Abstract

Abstract Immune cell characterization from patients undergoing therapeutic treatments in clinical research is critical for understanding disease progression and treatment efficacy. Recently, a novel image cytometry system (Cellaca™ PLX Image Cytometer, Revvity, Inc.) was developed to complement flow cytometry immunophenotyping. Initial studies investigated the feasibility of identifying T-cell, B-cell, NK-cell, and monocyte populations in healthy donors in comparison to flow cytometry. Donor PBMCs were stained with three panels of surface markers: B-cell with CD3-KIRAVIA Blue 520 ™(KB) and CD19-PE; NK-cell with CD3-KB and CD56-PE; and monocyte with CD3-KB and CD14-PE. Stained samples were acquired on the image cytometer and the CytoFLEX (Beckman Coulter, Inc.). Results show similar population percentages within 5%. Furthermore, we tested the screening method using patients enrolled in autoimmunity (rheumatoid arthritis) and oncology (multiple myeloma) disease cohorts. 48 primary PBMC samples were analyzed with Panel 1 of CD3-KB, CD56-PE, and CD14-APC, and Panel 2 of CD3-KB, CD56-PE, and CD19-APC. We validated the image cytometry method by comparing the Cellaca PLX to the Aurora (Cytek™). Results demonstrated comparable CD3, CD14, CD19, and CD56 cell populations between both instruments, showing ~ 5 – 10% differences. The proposed image cytometry method provides a novel high-throughput research tool to streamline the immunophenotyping workflow for patient sample characterization.