Single-Cell RNA Sequencing of Cardiac Organoids to Determine the Genetic Basis for Cell-Specific Responses to Anticancer Drugs

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PROJECT SUMMARY Anticancer drug-induced cardiovascular toxicity (CT) is a major side effect for many patients undergoing treatment for oncological disorders. CT symptoms vary widely across individuals, both in presentation and in time to onset. Risk of CT complicates treatment protocols and places cancer patients under additional duress. Genetic background is broadly understood to be a component of CT susceptibility, but specific variants and mechanisms remain largely unknown. To understand the genetic basis for drug-induced CT, we need to understand how anticancer drugs stimulate transcriptomic responses in multiple cardiovascular cell types from individuals of different genetic backgrounds. Inter-individual variability in response to anticancer drugs is mediated by genetic variants that affect gene regulation in a drug-dependent manner (response eQTLs). In other words, genetic variants respond to anticancer drugs by regulating the activity of specific genes. Notably, different cell types can vary in their response eQTLs to anticancer drugs. I propose to determine the genetic basis for transcriptomic responses to the anticancer drugs doxorubicin (DOX), 5-fluorouracil (5-FU), and bevacizumab (BVC) in multiple cardiac cell types from a genetically diverse panel of 70 individuals. Identification of CT-associated response eQTLs necessitates a high-throughput model system comprised of multiple cardiac cell types. For Aim 1 of my proposal, I have developed a culture environment and guided differentiation protocol conducive to cardiac lineage and supporting cell types. This procedure reproducibly transforms induced pluripotent stem cell (iPSC)-derived embryoid bodies (EBs) into cardiac organoids. Preliminary data demonstrate that the cardiac organoids harbor cardiomyocytes, fibroblasts, vascular endothelial cells, and other mesodermal cell types. In Aim 2, I will perform single-cell RNA sequencing (scRNA-seq) on a panel of 70 cardiac organoids cultured in control and drug-treated conditions. Repeating this experiment across multiple individuals will allow me to identify the response eQTLs that regulate how different cardiovascular cell types respond to each drug. In Aim 3, I will quantify gene expression levels and identify response eQTLs that regulate transcriptional changes to each anticancer drug in cardiovascular cell types. Response eQTLs (which are anchored by genotype) provide a catalog of loci that interact either directly or indirectly with the treatment. These response eQTLs may reveal specific genes and pathways important for normal cardiovascular function. Elucidating the genetic architecture underlying CT risk will provide intuition on cardiotoxic mechanisms and associated genes and inform future studies that aim to classify individual patient susceptibility.