Available for download

Single cell RNA-seq with FFPE tissue:

Demonstrated Protocol

 
 
Block 1
editable text

Bring single cell research to FFPE tissue

Formalin-fixed paraffin-embedded (FFPE) tissue blocks are invaluable sources for biotech research, drug discovery, and retrospective gene studies, but, until recently, it was thought to be impossible to generate single cell RNA-seq data from these samples. We are providing a Demonstrated Protocol with guidance on how to dissociate FFPE samples with the Miltenyi GentleMACS Octo Dissociator, enabling compatibility with our Chromium Single Cell Gene Expression Flex assay.

We tested this novel approach in house and observed exciting results in generating single cell gene expression data.

The results so far

Our internal testing included 50 human tissue blocks, ranging in age from 1 to 19 years, using 25 to 100 μm tissue sections.*

Data analysis† yielded good quality data from 32 of these tissue blocks, with overall data quality varying in accordance with FFPE sample quality and block ages. In general, blocks more than 10 years old were less likely to generate high-quality data.

We invite you to be a part of this journey to advance scientific research with single cell RNA sequencing of FFPE tissue.You can start by signing up to download the Demonstrated Protocol.

Please note that this  protocol is recommended for researchers who are experienced with single cell sequencing and willing to optimize and perform pilot studies prior to committing to larger experiments. If you’re new to single cell RNA-seq, we highly recommend checking out the Chromium Single Cell Gene Expression Flex page instead to learn more. 

Additionally, you may already be familiar with Gene Expression Flex—it was first made available as Chromium Single Cell Fixed RNA Profiling, and all kitted reagents and protocols retain the Fixed RNA name.

*A full list of tissues tested can be found in the Demonstrated Protocol.

†Assessment of data quality was based on maximizing singlet (%), barcode rank plot, t-SNE clustering, annotation, and complexity.

 


Download now