# Developing high-throughput genetic perturbation strategies for single cells in cancer organoids

> **NIH NIH U01** · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · 2022 · $922,170

## Abstract

PROJECT SUMMARY
 To address the complexity of heterogeneous cancers that are resistant to chemotherapy and frequently recur
or metastasize, we propose to develop a set of tools based on multidisciplinary innovations combining Synthetic
Biology, Cancer Organoid Technology, and Bioinformatics. These Synthetic Tools to Annotate Reporter
Organoids for Cancer Heterogeneity and Recurrence Development (StarOrchard) include: Synthetic Promoter
Activated Recombination of Kaleidoscopic Organoids (SPARKO), Combinatorial Genetics En
Masse (CombiGEM), and single-cell RNA sequencing panorama (Scanorama). SPARKO can annotate
heterogeneous cancer populations in living cells via fluorescent protein expression libraries to make multi-
colored tumor organoids. CombiGEM can rapidly identify potential therapeutic targets via large-scale,
massively parallel, and unbiased combinatorial genetic screens. Scanorama can integrate the analysis
of large datasets of single-cell transcriptomics via sophisticated bioinformatics algorithms. These tools
focus on barcoding strategies to enable accurate tracking and analysis of individual tumor cells that harbor
distinct genetic aberrations, and substantially expand the utility of the Next Generation Cancer Models
(NGCMs) for cancer mechanistic investigations or therapeutic discovery. The StarOrchard tools enable
targeted genetic perturbations in annotated heterogeneous tumor phenotypes without destroying cells for
sequencing. These tools will be applied to a large number and variety of NGCMs to optimize experimental
protocol. To ensure success, we have convened an outstanding team: PI Timothy K. Lu, MD, PhD, has
made strikingly original contributions to Synthetic Biology tools that enable high-throughput genetic
interrogation of cancer cell drug dependency; PI Ömer Yilmaz, MD, PhD, has extensive expertise in cancers
of the gastrointestinal tract and has developed novel technologies to maintain patient-derived colon cancer
organoids for in vivo modeling; and PI Bonnie Berger, PhD, will use her expertise in bioinformatics and
her Scanorama algorithm to integrate data across all tumor types based on dynamic single cell RNA
sequencing (scRNAseq). We are also supported by leading experts in cancer biology and various cancer
types at both the basic science and clinical oncology frontiers of cancer research. The collective
commitment and multidisciplinary contributions of the entire team ensure the establishment of an openly
distributed investigative tool set that accelerates advancements in cancer biology and therapeutic discovery

## Key facts

- **NIH application ID:** 10455437
- **Project number:** 5U01CA250554-03
- **Recipient organization:** MASSACHUSETTS INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** BONNIE BERGER
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $922,170
- **Award type:** 5
- **Project period:** 2020-07-08 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10455437

## Citation

> US National Institutes of Health, RePORTER application 10455437, Developing high-throughput genetic perturbation strategies for single cells in cancer organoids (5U01CA250554-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10455437. Licensed CC0.

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