# Tracking Therapy-Resistant Alterations in Childhood Acute Lymphoblastic Leukemia

> **NIH NIH R01** · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · 2022 · $444,265

## Abstract

PROJECT SUMMARY/ABSTRACT
Relapsed ALL is associated with poor outcome and remains the leading cause of cancer-related death among
all childhood cancer. Current therapies are toxic and can result in high incidence of late effects such as infertility
and heart failure. Thus, it has been a standard practice to allocate newly diagnosed patients to therapies based
on predicted risk of relapse. The presence of residual cancer cells after induction chemotherapy, known as
minimal residual disease (MRD), is a highly significant prognostic variable. However, many patients not
considered to be “high risk” still experience relapse. There is an unmet need to develop novel risk models
with enhanced accuracy to enable allocation of patients to risk-adapted therapies to reduce the
likelihood of future relapse. Our prior genomics studies on relapsed ALL in protein-coding regions (~2% of the
human genome) have revealed novel insights on the drivers of resistance to therapy. While these findings have
potential for developing novel molecular risk models, significant knowledge gaps remain. First, more than 50%
of relapsed cases lack any known resistance drivers. Second, the known resistance drivers are derived from
retrospective studies of relapsed specimens and it is unclear how to apply such information prospectively from
initial diagnosis to decrease the likelihood of relapse. Our goal is to develop novel molecular risk models by
tracking resistance drivers at diagnosis. Our central hypothesis is that resistance drivers, when detected at
diagnosis, will be informative for allocation of patients to risk-adapted therapies. We will test our hypothesis in
three aims. In Aim 1, we will identify comprehensive resistance drivers from both protein-coding and non-coding
regions by leveraging a large cohort of 669 relapsed childhood ALL cases from a recently completed cooperative
clinical trial with genome and transcriptome sequencing data available. We hypothesize that unexplored non-
coding regions will harbor novel resistance drivers and that the large cohort size will empower the discovery of
rare resistance drivers. In Aim 2, we will backtrack the resistance drivers at diagnosis by using ultra-deep
sequencing coupled with state-of-the-art computational error suppression that will enable detection of rare
variants with frequency as low as 0.01%. In Aim 3, we will investigate if resistance drivers pre-exist in an
independent cohort of patients at diagnosis. We will develop novel molecular risk models by comparing
prevalence profiles of resistance drivers detected at initial diagnosis between patients who have relapsed and
those who are cured. Successful completion of our project aims will deliver 1) comprehensive knowledge of
drivers of resistance to therapy, 2) the full spectrum of pre-existing resistance drivers at diagnosis, and 3) novel
molecular risk models for decreasing the risk of relapse. Our deliverables will form the basis for future clinical
trials and for de...

## Key facts

- **NIH application ID:** 10504566
- **Project number:** 1R01CA273326-01
- **Recipient organization:** ST. JUDE CHILDREN'S RESEARCH HOSPITAL
- **Principal Investigator:** Xiaotu Ma
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $444,265
- **Award type:** 1
- **Project period:** 2022-08-01 → 2027-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10504566

## Citation

> US National Institutes of Health, RePORTER application 10504566, Tracking Therapy-Resistant Alterations in Childhood Acute Lymphoblastic Leukemia (1R01CA273326-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10504566. Licensed CC0.

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