Abstract 174: Genomic cytometry characterization of preclinical models for development of immune-oncology therapeutics

Single cell characterization of protein epitopes is usually associated with fluorescent Flow Cytometry, which can be both costly and time consuming to optimize for multiple epitopes. To overcome the limitations of this method, we introduce Genomic Cytometry that utilizes cellular indexing of transcriptomes and protein epitopes by next-generation sequencing (CITE-seq) technology instead of flow. Genomic Cytometry is based on staining cells with antibodies conjugated to unique 15-bp DNA barcodes instead of fluorophores. After sequencing and data analysis the barcode read number can be linked to protein abundance. We utilized Genomic Cytometry to simultaneously analyze over 50 different protein biomarkers in a single scalable workflow. The application is ideal for characterization of heterogeneous cell populations such as tumors including their immune content. In addition to profiling a number cell surface protein markers that exceeds capabilities of traditional flow cytometry the technology allows for assessment of single cell gene expression data to link protein and genomic data sets. Corresponding pre-analytical and 10X Genomics-based analytical workflows were established for human PBMC samples, as well as for solid tissue including tumor specimens derived from mouse syngeneic tumor models. Data analysis pipelines were developed and validated that includes custom scripts. We ran a number of cross-platform validation studies (mouse and human cells) and found that the Genomic Cytometry is highly correlative to fluorescent flow. Multiplex methods were implemented to allow pooling of samples to reduce biases related to sample manipulation. The method enables large-scale single-cell sequencing experiments. In proof of concept experiments, a number of preclinical models, such as MC38 and H22, were deeply analyzed using CITE-seq approach. Genomic Cytometry enables rapid and cost effective characterization of both immune-oncology (I-O) models and modes of action of new I-O molecules in order to develop more differentiated therapeutics. Citation Format: Joon Sang Lee, Shannon McGrath, Emma Wang, Maximilian Rogers-Grazado, Yu-an Zhang, Natalia Malkova, Jack Pollard, Alexei Protopopov. Genomic cytometry characterization of preclinical models for development of immune-oncology therapeutics [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 174.