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Abstract 4706: Temperature-dependent transcription artifacts and cell population biases in scRNAseq data are minimized by tissue dissociation at low temperatures

Authors :
Samuel Aparicio
Kieran R Campbell
Farhia Kabeer
Jamie Lim
Sohrab P. Shah
Ciara H. O'Flanagan
Allen W. Zhang
Source :
Cancer Research. 79:4706-4706
Publication Year :
2019
Publisher :
American Association for Cancer Research (AACR), 2019.

Abstract

Single cell RNA sequencing (scRNAseq) is a powerful tool, particularly for studying complex biological systems, such as tumor heterogeneity and the tumor microenvironment, which may not be resolved by sequencing of bulk material. Nonetheless, it is not without limitations, which include the technical challenges of generating a high quality single cell suspension. Dissociation of tissue to single cell suspension requires mechanical and enzymatic disruption, and the effect of these methods on gene expression or cellular population bias has not been established. In this study, we examined the effects of enzymatic dissociation on cell population capture and transcriptional changes at single cell resolution in breast and ovarian cancer patient samples, patient-derived breast cancer xenografts and cultured cell lines. scRNAseq data showed that enzymatic dissociation of tissues at 37oC with collagenase resulted in significant induction of heat shock, stress and immediate response genes, which was conserved across all tissues. This gene expression induction was not observed when tissues were dissociated at 6oC with a protease derived from a Himalayan glacier soil bacterium. Moreover, dissociation of patient tumors at low temperature enhanced the abundance of rare cell populations, including B-cells, T-Cells and cytotoxic T-cells, which were significantly depleted following dissociation at 37oC. These biases resulting from standard sample preparation methods could significantly affect biological interpretation of scRNAseq data, and can be minimized by dissociation of tissues at low temperature. Note: This abstract was not presented at the meeting. Citation Format: Ciara H. O'Flanagan, Kieran R. Campbell, Farhia Kabeer, Allen Zhang, Jamie Lim, Sohrab P. Shah, Samuel Aparicio. Temperature-dependent transcription artifacts and cell population biases in scRNAseq data are minimized by tissue dissociation at low temperatures [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4706.

Details

ISSN :
15387445 and 00085472
Volume :
79
Database :
OpenAIRE
Journal :
Cancer Research
Accession number :
edsair.doi...........adf2eb55a6086985357bda44f7bc0500
Full Text :
https://doi.org/10.1158/1538-7445.am2019-4706