Abstract 5782: Sample management for enabling successful single-cell RNAseq processing

Abstract

Abstract Background: Single cell analysis allows the profiling of biomolecules on a cell-by-cell basis, revealing insights into how cellular heterogeneity impacts biological mechanisms. Drug discovery and development have greatly benefited from the comparative, longitudinal, and causal information single cell analysis provides, transforming our ability to understand disease. Many preclinical and clinical studies leveraging single cell resolution have already played a crucial role in target identification and biomarker discovery. From collection through analysis, proper sample management is a crucial and challenging aspect of large-scale clinical research studies and directly influences specimen quality and the ability to interrogate specific cell populations of interest. Methods: We sought to determine the effect of collection and storage conditions for PBMCs enriched from whole blood prior to downstream processing using our scRNAseq workflow. PBMCs were freshly isolated from whole blood collected in EDTA tubes or following storage at various timepoints and temperatures until PBMC isolation. Samples were then cryopreserved after the conclusion of each isolation stage and later processed to assess impact of cryopreservation. All PBMC samples were processed using the Chromium Single Cell Immune Profiling kit to compare gene expression and immune repertoire profiling across all storage conditions. Results: We found that gene expression data were highly correlated across all storage conditions tested. We also found that the clustering and annotation of PBMC libraries were comparable across all conditions tested, but certain subsets were more sensitive to these conditions, indicated by an elevation in cell stress and apoptosis markers. Conclusions: When planning future studies, it is imperative to consider collection and storage conditions in the workflow of processing for enabling high quality samples for single cell analysis, especially with regard to sensitive and rare cell types of interest. Citation Format: Priya J. Halvorsen, Caitlin W. Britton, Hiba Shaban, Fernando Torres, Douglas Wilson, Joseph Modarelli. Sample management for enabling successful single-cell RNAseq processing [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 5782.