# High-Dimensional Profiling of Physiological Signaling Responses to Identify Relapse-Driving Cells in Acute Myeloid Leukemia

> **NIH NIH R21** · BAYLOR COLLEGE OF MEDICINE · 2020 · $236,030

## Abstract

Despite aggressive chemotherapy and often stem cell transplant, 40% of pediatric AML patients still relapse,
and most of those patients will die of refractory disease. It is well established that the microenvironment provided
by stromal cells in the bone marrow niche confers a strong survival advantage to some AML cells. Recent studies
have shown that AML cells recovered from bone marrow after treatment with chemotherapy are different from
the untreated bulk disease population in their metabolic activities, gene expression profiles, and interactions with
the microenvironment. Currently, chemoresistant AML cells cannot be distinguished from the chemosensitive
bulk population at diagnosis because there is no reliable biomarker that identifies them prospectively. However,
because chemoresistant cells interact differently with the microenvironment, it is likely that they have a distinct
environment-induced signaling profile that can be leveraged for targeted therapeutics. The ultimate goal of our
research is to identify the mechanisms by which AML cells survive chemotherapy, and by disabling those
mechanisms, to achieve a meaningful advance in AML treatment. Toward that goal, the objective of this
application is to identify and block the soluble factor-induced signaling pathways that specifically enable a subset
of AML blasts in the bone marrow niche to survive chemotherapy. We have shown that many AML cases contain
subpopulations of blasts that respond differently to the cytokines and growth factors in the bone marrow
environment. For example, subpopulations with features of leukemia stem cells have more robust inducible
STAT3 pathway activation, compared to bulk AML cells. Our central hypothesis is that relapse-driving AML cells
respond to their microenvironment differently from chemosensitive cells. Therefore, the resistant cells can be
identified by high-dimensional functional profiling methods such as mass cytometry, and they can be targeted
by appropriate signaling pathway inhibitors. We will test this hypothesis with two Specific Aims. In Aim 1, we will
study primary AML samples collected prior to treatment and stimulated with stroma-conditioned medium (CM)
as a physiological source of bone marrow cytokines and growth factors. We will use mass cytometry to
differentiate the capacity of distinct subpopulations to activate downstream pathways, and we will test the effects
of inhibitors of these pathways on functions such as self-renewal in vitro and leukemia initiation in vivo. In Aim
2, we will study end of induction samples from the same patients, selected for known minimal residual disease.
By mass cytometry, we will identify therapeutic vulnerabilities of chemoresistant cells by determining the CM-
induced signaling profiles of the residual AML cells. We will test the efficacy of adding targeted inhibitors to
chemotherapy in our in vitro and in vivo chemoresistance assays. By generating high-dimensional protein profiles
of physiologically st...

## Key facts

- **NIH application ID:** 9878490
- **Project number:** 1R21CA234529-01A1
- **Recipient organization:** BAYLOR COLLEGE OF MEDICINE
- **Principal Investigator:** Michele S. Redell
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $236,030
- **Award type:** 1
- **Project period:** 2019-12-01 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9878490

## Citation

> US National Institutes of Health, RePORTER application 9878490, High-Dimensional Profiling of Physiological Signaling Responses to Identify Relapse-Driving Cells in Acute Myeloid Leukemia (1R21CA234529-01A1). Retrieved via AI Analytics 2026-06-11 from https://api.ai-analytics.org/grant/nih/9878490. Licensed CC0.

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