Abstract 2259: Single-cell multi-omics analysis of SNV, CNV, and protein expression

Abstract

Abstract Recent advancements in precision medicine, while highly promising, presents a major technical challenge to researchers due to disease heterogeneity. The emergence of single-cell technologies has greatly refined the resolution in which sample diversity can be investigated, enhancing the efficiency of selecting appropriate molecular targets. Additionally, applying multi-omics analysis on single cells would further improve the understanding of cell-to-cell heterogeneity by providing unique insights on cellular and genetic composition. Using a two-step droplet microfluidic technology, the Mission Bio Tapestri Platform enables multiplex-PCR based high-throughput targeted DNA sequencing in single cells to obtain single-nucleotide variation (SNV) and copy number variation (CNV) information. By leveraging this technology, a new workflow is developed to detect protein expression in addition to DNA genotype in the same single cells. In this approach, cells are labeled with a pool of oligonucleotide-conjugated antibodies prior to loading the cells into the Tapestri Instrument. Sequencing libraries are then prepared from both antibody oligonucleotides and the amplified DNA sequences, followed by identification of single-cell DNA genotypes and protein signatures from the sequencing readout. The number of protein targets can be in the range from 6 to over 40, which is beyond the limit for a single flow cytometry run. This method has been successfully performed on cell lines, fresh and frozen PBMCs, as well as clinical samples. In an acute myeloid leukemia (AML) sample, combined single-cell SNV, CNV, and protein expression data illustrated the heterogeneity within the sample. The data clearly identified CD3+ T cells and CD19+ B cells without pathogenic SNVs and CNVs. CD34hiCD11blo and CD34loCD11bhi subpopulations were also identified within the cells carrying the same pathogenic SNVs and CNVs. We believe that this novel multi-omics technology will facilitate new discoveries in the complex relationship between genotype and phenotype, enable a better understanding of disease biology, and subsequently improve the design of diagnostics and therapies. Citation Format: Aik Ooi, Dalia Dhingra, Adam Sciambi, Kate Thompson, Jacqueline Marin, Saurabh Parikh, Mani Manivannan, David Ruff. Single-cell multi-omics analysis of SNV, CNV, and protein expression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2259.