# Connecting molecular phenotype with cell fate using single-cell barcoding and RNA FISH

> **NIH NIH F30** · UNIVERSITY OF PENNSYLVANIA · 2020 · $8,935

## Abstract

Project summary
Despite tremendous advances in medical therapy for cancer, current treatments often fail to eradicate disease
completely, allowing the rare cells that survive to proliferate and drive disease progression. Identifying how
these rare cells survive therapy and metastasize is fundamental to our understanding of cancer biology and the
development of better therapeutics. Current approaches attempt to identify molecular drivers of these
processes by characterizing cancer cells ​after​ they become drug resistant or metastatic. However, we and
others have shown that as cancer cells grow and adapt to a drug or new environment, they change radically
and may bear little resemblance to the ​initial​ rare cells that survived treatment and spread. Therefore, even the
most sensitive current approach that profiles individual cancer cells may miss fundamental differences that
matter at the earliest stages of disease. Instead, we need a way to effectively peer back in time and ask: what
was different about those rare cells initially? Here we propose combining high-complexity lineage barcoding,
high-throughput sequencing, and RNA FISH to directly isolate and profile the initial cancer cells that give rise to
drug resistance and metastasis. In our preliminary work, we created a lentivirus library for delivering unique
transcribed barcodes to millions of cells which can be detected by both sequencing and RNA FISH. In parallel,
we developed a technique for exponentially amplifying RNA FISH fluorescence, enabling cell sorting based on
specific transcripts. Combining these tools as described below will allow us to label and isolate a specific cell
lineage based on its future behaviour, such as resistance to drug or invasiveness. In aim one, we plan to
demonstrate this potential by isolating the drug-naive melanoma cells that later give rise to vemurafenib
resistant colonies. By performing RNA-seq and ATAC-seq on the isolated cells, we will identify markers and
epigenetic regulators of these resistance-progenitor cells and validate them functionally using pharmacologic
and CRISPR-based perturbations. In aim 2, we propose taking our method ​in-vivo​ to characterize what is
different about the rare melanoma cells that metastasize in human xenograft and syngeneic mouse models.
First, by tracking barcodes across tissues forward in time we will identity the order, route and tissue preference
of individual metastatic clones. Then, using RNA FISH to label and isolate the ancestors of these clones, we
will look back to determine how past differences in gene expression might underlie these behaviours.
Successful completion of these aims will reveal how therapy resistance and metastasis arises in melanoma
and, more generally, validate a novel method based on FISHable barcodes for studying the origins of rare-cell
phenomena.

## Key facts

- **NIH application ID:** 9932790
- **Project number:** 5F30CA236129-02
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Benjamin Emert
- **Activity code:** F30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $8,935
- **Award type:** 5
- **Project period:** 2019-06-01 → 2020-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9932790

## Citation

> US National Institutes of Health, RePORTER application 9932790, Connecting molecular phenotype with cell fate using single-cell barcoding and RNA FISH (5F30CA236129-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9932790. Licensed CC0.

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