Single-cell Multi-omic Profiling of Drug Responses Using Pooled iPSC-CM Differentiation

Stanford University, Stanford CA

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Abstract

PROJECT SUMMARY Cardiovascular complications of cancer therapy significantly contribute to the global burden of cardiovascular diseases. Although remarkable progress has been made in understanding the genetic basis of doxorubicin- induced cardiotoxicity (DIC), we cannot predict which patients will be affected by DIC or protect patients at risk for suffering from DIC adequately. Here, we will use a novel multiplexing methodology of creating a "cell village" by pooling multiple patients' induced pluripotent stem cell (iPSC) lines in a dish to map the genetic basis of inter- individual differences in response to doxorubicin. In Aim 1, we will co-culture 100 iPSC lines in 10 distinct "cell villages," where each "cell village" contains ten independent patient-specific iPSC lines. Next, we will differentiate each "cell village" into iPSC-derived cardiomyocytes (iPSC-CMs). Finally, we will perform a single-cell multi- omics sequencing analysis of the "cell villages" to understand the impact of genetic variability on cardiomyocyte gene regulation and functions at baseline. In Aim 2, we will employ a single-cell multi-omic approach to uncover and validate the role of response eQTL in DIC prediction. We will treat iPSC-CMs in each "cell village" with doxorubicin at various doses. Next, we will perform single-cell multi-omics profiling to model the contribution of genetics to variability in responses to doxorubicin treatment. In Aim 3, we will employ 3D engineered heart tissues (EHTs) and CRISPR/cas9 genome-editing to comprehensively study the functional role of two candidate doxorubicin response genes. All in all, the proposed experiments will serve as a proof-of- principle in using the "cell village" model as a high throughput personalized drug screening platform.