# Combating Subclonal Evolution of Resistant Cancer Phenotypes

> **NIH NIH U54** · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · 2021 · $2,195,349

## Abstract

Overall abstract
Our Cancer Systems Biology Center of HoPE (Heterogeneity of Phenotypic Evolution) will develop
a suite of
systems-based methodologies to understand how genomic diversity, clonal evolution, and phenotypic change
 . To evaluate their potential for
translation, we will integrate these dynamic models with clinical trials that will evaluate whether these
phenotypic changes can be targeted for therapy. We hypothesize that acquired resistance emerges from
selection acting on phenotypes during tumor evolution, and that simultaneously measuring and
modeling subclone genotypes and phenotypes will identify new, and testable, therapeutic targets.
Selective pressures from therapy and the tumor microenvironment can propel subclones from every patient's
tumor along an evolutionary trajectory that leads to resistance. Indeed, our data shows that both genetic and
phenotypic diversity among tumor subclones evolves as cancer cells progress to a resistant state. However, it
is not yet known the specific phenotypes that promote that resistant state, the interactions among them, and
how they converge to common resistant phenotypes seen in late stage cancer. To address these and other
questions, we will develop a new class of dynamical systems models of subclone evolution to characterize the
changes and development of key cell states that arise during acquired chemo-resistance and metastasis using
our unique patient cohorts. These mechanistic models will identify points of therapeutic vulnerability that we will
test in clinical trials aimed at blocking evolution to a resistant state by targeting critical resistant phenotypes.
Our Center is comprised of an Administrative, Education/Outreach, Translational, and Computational Cores, in
addition to two complementary projects. The synergies are derived from: 1) the convergent parameterization of
the evolutionary models drawn from deep longitudinal patient progression studies (Project 1) and broad
multisite metastatic tumor analyses (Project 2), resulting in a robust model to identify resistant states for clinical
targeting; and 2) an integrated computational and experimental framework and resources for dissecting tumor
heterogeneity and evolution that will contribute to an improved capacity for personalized cancer therapy. Our
multidisciplinary team of systems biologists, bioinformaticians, tumor biologists, pharmacologists, mathematical
biologists, and clinicians will tackle these scientific challenges. We will create programs to educate the next
generation of scientists in systems biology and inform the community about the latest scientific advances and
their impact on treatment strategies. And we will provide state of the art tools for the analysis of patient
samples and tumor genomic complexity. These studies move beyond prior research by integrating cell
population dynamics and cellular phenotypes with cellular genotypes, and will deliver approaches and a
knowledge base to block or reverse the transiti...

## Key facts

- **NIH application ID:** 10207524
- **Project number:** 5U54CA209978-06
- **Recipient organization:** BECKMAN RESEARCH INSTITUTE/CITY OF HOPE
- **Principal Investigator:** ANDREA Hope BILD
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $2,195,349
- **Award type:** 5
- **Project period:** 2017-05-15 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10207524

## Citation

> US National Institutes of Health, RePORTER application 10207524, Combating Subclonal Evolution of Resistant Cancer Phenotypes (5U54CA209978-06). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10207524. Licensed CC0.

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