Abstract 4967: Leveraging the power of high parameter cell sorting and single-cell multi-omics to profile intratumoral immune cells in a model of B-cell lymphoma
Authors: Baracho Gisele V. , Shi Xhiaoshan , Lin Wai , Sedy John , Lomas Chip , Widmann Stephanie , Tyznik Aaron 
Published: September 2020

Abstract
As for most neoplasms, the pathogenesis and progression of B-cell malignancies is a dynamic process involving reciprocal interactions between malignant cells and surrounding components in the tumor microenvironment. In the case of certain B-cell lymphomas, neoplastic cells migrate to lymphoid sites and prompt the infiltration of non-malignant immune cells. The infiltration of cytotoxic lymphocytes correlates with tumor cell killing and good prognosis. However, most immune cell types in the tumor niche often become unresponsive or end up promoting tumor growth. In this study we present a sorting strategy using the BD FACSymphony™ S6 Cell Sorter that enables concurrent isolation of six cell populations from a tumor niche in a model of B-cell lymphoma. Downstream application of single-cell sequencing was used to unravel the respective roles of each cell subset for the tumor's progression and/or evasion. The six cell subsets were isolated from two groups of mice that had been inoculated with an OVA-expressing B-cell lymphoma cell line and subsequently with either wild-type or BTLA-deficient OVA-specific CD8+ T cells. Prior to sorting, each tissue was labeled with a unique BD™ AbSeq Oligo barcode, allowing us to combine biological replicates (2 mice per group) for a higher throughput. After sorting, cells from both groups were pooled and loaded onto cartridges from the BD™ Rhapsody Single-Cell Analysis System, followed by library preparations for Next-Generation Sequencing. In addition to 34 surface proteins, marked with BD™ AbSeq Oligos, sequencing of 399 target mRNA transcripts enabled a detailed examination of the cellular responses that were triggered in the presence of the tumor. During cell analysis, various algorithms in SeqGeq™ segregated the cells from each individual mouse and identified the sorted populations based on their specific phenotypic and molecular signatures. Importantly, because sequencing is biased toward detecting high frequency proteins and mRNAs, the cell sorting aided more robust single-cell profiling of rare cell subsets within the sorted populations. These analyses also contributed to a better understanding of the conditions underlying the differences between the two mice groups. In sum, we demonstrated a scalable and high-throughput approach that enabled a comprehensive characterization of critical cell populations in tumor responses. Since these cell populations constitute potential targets for the treatment of B-cell lymphomas, this platform, notably through the analysis of protein expression, offers an opportunity for identification of new therapeutic targets.
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Citation Format: Gisele V. Baracho, Xhiaoshan Shi, Wai Lin, John Sedy, Chip Lomas, Stephanie Widmann, Aaron Tyznik. Leveraging the power of high parameter cell sorting and single-cell multi-omics to profile intratumoral immune cells in a model of B-cell lymphoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4967.