# IMAT-ITCR Collaboration: Engineering model-based systems to monitor and steer subclonal dynamics

> **NIH NIH R21** · H. LEE MOFFITT CANCER CTR & RES INST · 2024 · $75,785

## Abstract

PROJECT SUMMARY
Ongoing cancer genomic studies have documented numerous mutations across all tumor types. Most cancer
mutations have not been functionally characterized, as conducting experiments with individual cell line models
for each mutation is neither scalable nor practical. Moreover, primary tumors and cancer cell lines exhibit
extensive genetic and transcriptional heterogeneity, with multiple subclones coexisting within the same cancer
population. Each subclone possesses different biological properties. Therefore, it is crucial to closely monitor
this heterogeneity to achieve clear and reproducible results.
There is a lack of integrated experimental systems and computational approaches capable of analyzing the
genomic complexity of subclonal populations. To address this need, we will integrate two distinct approaches—
one genomic and one bioinformatic—to engineer, track, and study the impact of various mutations on the
subclonal properties of cancer, including growth. Transcript-informed single-cell CRISPR sequencing (TISCC-
seq), developed by the Ji group at Stanford, can experimentally model cancer mutations of interest at single-cell
resolution by leveraging CRISPR engineering and single-cell RNA sequencing (scRNA-seq). CLONEID,
developed by the Andor group at Moffitt Cancer Center, is a computational tool for monitoring heterogeneous
cell populations by taking daily microscopic cell images and incorporating various assays, including single-cell
sequencing. Using this integrated system, we will characterize the functional consequences of mutations in
clinically relevant genes (TP53, PTEN, and MET) in gastric cancers by monitoring and modeling subclonal
dynamics over time.
The objective of this project is to develop an integrated system combining TISCC-seq for single-cell mutation
analysis with the CLONEID framework to evaluate the functional consequences of introduced mutations by
monitoring and modeling subclonal dynamics. We have two specific aims: 1) adapting the CLONEID framework
for TISCC-seq single cell clonal tracking and readouts and 2) Single cell longitudinal monitoring of TISCC-seq
engineered clonal growth phenotypes. This project aims to demonstrate how an integrated system can provide
accurate and reproducible insights into the functional consequences of known cancer mutations.

## Key facts

- **NIH application ID:** 11137295
- **Project number:** 3R21CA269415-02S1
- **Recipient organization:** H. LEE MOFFITT CANCER CTR & RES INST
- **Principal Investigator:** Noemi Andor
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $75,785
- **Award type:** 3
- **Project period:** 2024-09-01 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11137295

## Citation

> US National Institutes of Health, RePORTER application 11137295, IMAT-ITCR Collaboration: Engineering model-based systems to monitor and steer subclonal dynamics (3R21CA269415-02S1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/11137295. Licensed CC0.

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