Dissociation of tumor tissue samples for single-cell genomics

Unraveling the diversity of cell types and understanding the complexity of the tumor microenvironment are critical milestones to advance cancer research and the development of both diagnostics and therapeutics for cancer.

Within the tumor microenvironment there are numerous cells types, such as infiltrating immune cells, inflammatory cells, cancer-associated fibroblasts, vascular cells, stromal cells, extracellular matrix, and tumor cells. Tumor cells are highly evasive due to their elasticity and ability to adapt to environmental modifications. As a result of these properties, improving our understanding of a tumor’s dynamic cellular composition and gene expression profile will enhance the research community’s ability to develop more effective diagnostics and treatments for cancer.

In recent years, single-cell RNA sequencing (scRNA-seq) has become a popular analytical tool to significantly augment characterization of the tumor microenvironment. In contrast to RNA sequencing of bulk cell populations, scRNA-seq allows for the transcriptomic profiling of hundreds, thousands, or potentially millions of individual cells. The ability to detect transcriptomic signatures unique to an individual cell greatly increases the diversity of transcripts that can be detected in a sample. This is in comparison to bulk sequencing, whereby the average signal across the entire sample obscures transcripts from rare cell populations. As a result, the use of scRNA-seq has the potential to facilitate advances, such as the discovery of new cell subpopulations and the identification of clonal tumor cell subsets responsible for resistance to treatment.

The dissociation of a tumor in order to release intact individual cells is a critical step in every scRNA-seq experiment. Ideally, the sample for a scRNA-seq experiment is a suspension consisting of fully dissociated, intact, viable cells. Attributes of a poor quality sample include clumps, dead or dying cells, extracellular debris, and ambient free-floating RNA. These cellular and molecular contaminants can negatively impact data quality and increase overall sequencing costs. Therefore, it is important to consider the sample preparation process and utilize an approach that does not produce a low-quality sample that adversely impacts scRNA-seq data.

To address this challenge, Miltenyi Biotec and 10x Genomics designed a collaborative study to demonstrate the impact of sample preparation on scRNA-seq. For this work, our research teams combined methodologies for sample storage, tumor tissue dissociation, and sample cleanup from Miltenyi Biotec, with the 10x Genomics technology for single-cell sequencing. As a result, we validated an end-to-end workflow for preparing solid tumor tissue for single-cell RNA sequencing. For this study, solid tumors from syngeneic mouse models were collected and preserved in MACS^® Tissue Storage Solution, then dissociated using the gentleMACS™ Octo Dissociator with Heaters and the Tumor Dissociation Kit, mouse. Following dissociation, a series of steps was performed to remove debris, red blood cells (RBCs), and dead cells prior to analysis of the samples using the 10x Genomics Chromium System and an Illumina sequencing platform.

Starting with the MACS Tissue Storage Solution for tumor sample collection and transport, followed by sample processing with gentleMACS Octo Dissociator with Heaters and the Tumor Dissociation kit, mouse, we were able to produce high quality single-cell suspensions with adequate performance in scRNA-seq. However, additional cleanup steps including RBCs and dead cell removal significantly improved different quality metrics for single-cell gene expression data generated using the 10x Genomics Chromium Platform. Our data indicates that the reduction of RBCs and dead cells from the dissociated tumor tissue samples leads to:

• An increased number of reads confidently mapped back to one cell
• A higher number of genes detected per cell
• Maximal cell recovery with the 10x Chromium System
   

For all the details on this collaboration, please use the QR code below.