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

> **NIH NIH R01** · STANFORD UNIVERSITY · 2024 · $597,054

## 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.

## Key facts

- **NIH application ID:** 10817129
- **Project number:** 5R01HL145676-06
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** MARK MERCOLA
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $597,054
- **Award type:** 5
- **Project period:** 2019-05-01 → 2027-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10817129

## Citation

> US National Institutes of Health, RePORTER application 10817129, Single-cell Multi-omic Profiling of Drug Responses Using Pooled iPSC-CM Differentiation (5R01HL145676-06). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10817129. Licensed CC0.

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