Abstract 150: Single cell mRNA quantification from 1000s of cells in healthy and malignant tumor samples using a high-throughput droplet-based system

Abstract Advances in single cell RNA quantification techniques have enabled comprehensive study of subpopulations of cells within a heterogeneous population. The application of single cell quantification techniques to oncology is helping to elucidate the complex variability in genetic and epigenetic interactions that occur within tumor cells and their microenvironment. However, current single cell RNA-sequencing methods are limited by their reliance on costly infrastructure and laborious experimental protocols. We developed the GemCode Platform, which combines microfluidics with molecular barcoding and custom bioinformatics software to enable 3’ mRNA counting from thousands of single cells. Here we utilized the GemCode Platform to profile primary cells from healthy donors and cancer patients. Cell lines and cancer samples were obtained from commercial sources. Single cells, reagents and a single gel bead containing barcoded oligonucleotides were encapsulated into picoliter-sized droplets using the 10X Genomics GemCode Platform. The platform achieved extremely high cell loading efficiency (> 50%), enabling the creation of libraries from precious samples. Lysis and barcoded reverse transcription of RNAs from single cells were performed inside each droplet. High quality next generation sequencing libraries were finished in a single bulk reaction. The GemCode software suite was utilized for processing, interactive analysis and visualization of single cell gene expression data. We demonstrated single cell behavior through mouse- and human cell mixing experiments with a low doublet rate of <1%, making the platform suitable for profiling of rare cancer cell populations. We profiled >40,000 peripheral blood mononuclear cells from healthy donors and detected all major subpopulations (i.e., B cells, CD4+ T cells, CD8+ T cells, NK cells, dendritic cells, monocytes) in similar proportions to those previously reported in the literature. Notably, the high-throughput nature of the platform enabled resolution of finer sub-structures such as CD4+ effector memory cells and CD4+ central memory cells. Experiments comparing cells isolated from patients with hematologic malignancies (such as CLL, AML and CML) with whole bone marrow from healthy donors further demonstrate the power of single cell profiling for characterizing disease-associated changes in complex tissues. We demonstrate the ability to perform high-throughput gene expression profiling of mRNAs in single cells. The high-throughput platform enables detection of rare cells in a heterogeneous tumor population. Moreover, efficient cell loading enables analysis of clinically relevant sample types with limited cell input. An integrated single cell mRNA analysis will lead to novel insights into the molecular characteristics of individual cancer cells and provide targets for therapeutic intervention. Citation Format: Grace X.y. Zheng, Tarjei Mikkelsen, Jessica Terry, Phillip Belgrader, Paul Ryvkin, Ryan Wilson, Tobias D. Wheeler, Zachary Bent, Geoff McDermott, Solongo Ziraldo, Alexander Wong, Michael Schnall-Levin, Ben Hindson. Single cell mRNA quantification from 1000s of cells in healthy and malignant tumor samples using a high-throughput droplet-based system. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 150.