# Dissecting Clonal Evolution of Myeloid Malignancies

> **NIH VA I01** · VETERANS HEALTH ADMINISTRATION · 2024 · —

## Abstract

Clonal evolution is cancer is a critical part of disease progression, but it is difficult to understand which clonal
populations are present with bulk sequencing techniques. Myeloid malignancies are increasing among our aging
veteran population and are a group of blood cancers where clonal evolution even prior to inception is apparent.
This proposal uses cutting-edge single-cell DNA sequencing, in addition to other single cell modalities, to better
characterize clonal evolution in signaling mutant MDS and secondary AML. Our preliminary data has identified
patterns of clonal architecture change that are typical of transformation of MDS to sAML. These patterns, defined
as either dynamic or static clonal change, blast increase and are enriched for signaling mutations. We propose
to profile signaling mutant sAML and MDS deeply to trace clonal histories with single cell DNA sequencing
combined with surface marker characterization. We will also sequence mitochondrial DNA from scDNAseq and
scRNAseq data to connect genotype to transcriptome. This represents a powerful tool to better probe cell
ontogeny and clonality in myeloid malignancy. Further we will characterize how mutation status effects cell type
output. Next, we will use single cell RNA sequencing combined with antibody detection of surface markers (CITE-
seq) to identify transcriptional properties of clonal populations, with the focus of distinguishing between signaling
mutant cells and non-mutant cells in the same sample. We will test the hypothesis here that there are common
gene regulatory networks within clonal evolution patterns with both methylation gene mutations (e.g., TET2) and
signaling gene mutations (e.g., FLT3) in MDS and sAML that arises out of MDS. In addition to CITE-seq, we will
perform phospho-specific mass cytometry to find aberrant signaling responses to inflammatory perturbations.
We have used this modality to probe extracellular and intracellular proteins simultaneously in AML and MDS in
the past. Here, we will probe signaling responses by subjecting samples to multiple perturbations. This technique
enables cell type assignment via a large panel of >24 surface markers combined with 10 intracellular signaling
readouts. Ultimately, we propose to computationally align data from the common surface markers in each of the
three single cell modalities to discover correlations between signaling, transcriptional, and clonal identity. In order
to dissect the emergence of signaling mutations more accurately, we will use ex vivo CRISPR/Cas9-edited cells
that model this clonal change. We will investigate the underlying epigenetic alterations that can give rise to
signaling mutant clonal evolution and investigate signaling changes associated with a new signaling mutation.
This proposal will identify molecular mechanisms involved in clonal advantage and potential therapeutic targets.

## Key facts

- **NIH application ID:** 10804451
- **Project number:** 1I01BX005991-01A2
- **Recipient organization:** VETERANS HEALTH ADMINISTRATION
- **Principal Investigator:** PAUL B FERRELL
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2024
- **Award amount:** —
- **Award type:** 1
- **Project period:** 2024-01-01 → 2027-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10804451

## Citation

> US National Institutes of Health, RePORTER application 10804451, Dissecting Clonal Evolution of Myeloid Malignancies (1I01BX005991-01A2). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10804451. Licensed CC0.

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