Single cell RNA sequencing (scRNA-seq) uncovers tissue heterogeneity by providing gene expression measurements in individual cells within the tissue. This level of resolution allows for a clearer understanding of specific cellular functions, tissue complexity, and is a powerful tool to discover therapeutic targets and novel biomarkers. A current limitation of scRNA-seq is the requirement to isolate viable cells from fresh or cryopreserved solid tumor biopsies, especially given that formalin-fixed paraffin embedded (FFPE) material are ubiquitously utilized for long-term tissue preservation. Though formalin fixation preserves samples for extended periods of time, it also fragments genetic material, which introduces challenges for many RNA-seq methods due to the reduced size of template material. 10x Genomics recently launched the Chromium Single Cell Gene Expression Flex assay, a probe-based solution for scRNA-seq from fixed cells to complement traditional bulk RNA sequencing methodologies. Herein, this discussion describes and characterizes the utilization of prepared single-cells from FFPE blocks of varying tissue types, ages and quality, evaluated using the Single Cell Gene Expression Flex assay. The total number of genes detected was highly reproducible between replicates and ranged between 14,000 and 18,000 per tissue type, indicating robustness of the assay across tissues. While FFPE curl number and size input variables were found to have no significant impact on single-cell QC metrics, the effect of DV200 was observed within each tissue type, indicating a strong driver of metric variability. These combined findings support the use of the 10x Genomics Single Cell Gene Expression Flex assay to obtain high quality single cell gene expression data from FFPE tissues. The data also demonstrate that meaningful gene expression information at single cell resolution is produced by multiple clinically relevant tissue types and input amounts, but samples with the highest DV200 produce the most robust data.

Watch the video of this presentation, given at the 2023 Sanofi Global Analytical Symposium.