Abstract 2927: Optimization of sample preparation for single-cell RNA-sequencing using accumulated collection of preclinical and clinical specimens

Abstract Background: The heterogeneity of tumors became apparent with the introduction of single-cell RNA-sequencing technology, enabling the discovery of rare and novel cell types that were not attainable with bulk RNA-sequencing. Numerous papers have been published, and the data from single-cell RNA-sequencing are publicly available. While current literatures provide detailed guidance on effectively analyzing single-cell RNA sequencing data, documentation for sample preparations is less frequently reported in easily accessible protocols. Additionally, researchers hold diverse opinions on sample handling and practical information is scattered across multiple sources. Method: A total of 233 cases were included in the study, comprising 150 cases of clinical and 83 cases of preclinical samples. Among the 150 clinical samples, 58 were freshly obtained (32 biopsies and 26 surgical resections), and 92 were frozen. Of the 83 preclinical samples, 70 were fresh, and 13 were frozen. Sample preparations for 10X Genomics Chromium single-cell RNA-sequencing were carried out using the methods of 'Red blood cell lysis', 'Straining', and 'Dead cell removal using magnetic beads' with clinical specimens. Each method was applied based on specific situations involving the presence of red blood cells, cell aggregates, dead cells and debris. Results: There was a variation in the usage of red blood cell lysis, straining, and dead cell removal methods across different sample types. Specifically, 40. 6% of clinical biopsy samples were primarily conducted with red blood cell lysis and/or straining without the removal of dead cells. Whereas, 96. 2% of clinical surgical resections and 100% of clinical frozen samples predominantly utilized dead cell removal. The frequency of a double application of dead cell removal was higher in frozen samples, at 34. 8% due to low viability as expected. For surgical resections, in comparison, only 15. 4% required a second round of dead cell removal. In preclinical samples, both fresh and frozen, removal of dead cells was essential and implemented in 100% of cases. Among these, 62. 9% of the fresh preclinical samples and 76. 9% of the frozen preclinical samples underwent a second round of dead cell removal. Conclusions: The utilization of the methods red blood cell lysis, straining, and dead cell removal proved to be adequate in meeting the stipulated criteria of the 10x Genomics guidelines, demonstrating efficiency in terms of time. We have outlined a workflow for each sample type, accompanied by images illustrating pre- and post-conditions for plausible occurrences. Additionally, approximate cell numbers required, or percentages of cell loss are provided for each situation. We anticipate that this protocol will be beneficial for those new to the field, enabling them to generate samples for single-cell RNA-sequencing independently. Citation Format: Kyumin Lim, JuHyeon Lee, Kyoung-Ho Pyo, Byoung Chul Cho. Optimization of sample preparation for single-cell RNA-sequencing using accumulated collection of preclinical and clinical specimens abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 2927.