# Project 1: Patterned Heterogeneity in Colon Cancer

> **NIH NIH U54** · UNIVERSITY OF CALIFORNIA-IRVINE · 2021 · $440,558

## Abstract

In many solid malignancies, molecular and cellular heterogeneity within a single tumor confounds our ability to
understand tumorigenesis and to design effective therapies. Much effort has focused on genetic variants, the
forces that lead to clonal outgrowth, and the relevance these clones have to the development of drug
resistance. However it is the highly dynamic forms of non-genetic heterogeneity that are thought to enable
adaptation to the rapidly changing stresses that confront the tumor as it grows and wounds the surrounding
environment. Little is understood about non-genetic heterogeneity, whether it reflects a random
epiphenomenon or mutualistic cooperation among cancer cells to benefit the tumor as a whole. Here we
address these questions using a systems biology approach to mathematically model a pattern of non-genetic
heterogeneity in xenografted colon tumors. Our studies of Wnt-β-signaling and its regulation of glycolysis have
led us to discover a striking quasi-regular array of cell clusters (spots). Cells clusters are identified by high
levels of Wnt (β-catenin and its target LEF1) and we identify a similar spotted pattern using markers of
glycolysis. Manipulation of the levels of Wnt signaling in these xenografts changes the spotted pattern and
reduces tumor growth. Whether the growth defect is functionally linked to the changes in pattern and
heterogeneity is a fundamental unknown we wish to address. The overarching goal of this project therefore is
to identify molecules and strategies that create pattern in this system, to ask how these strategies influence
tumor growth, and to determine whether these mechanisms are involved in drug resistance. Aim 1 will use
high-resolution single cell RNA-seq (scRNA-seq) and tumor imaging to build on our existing mathematical
model and to explain the relationships between tumor heterogeneity, growth and invasion. Data from
experiments wherein expression of candidate regulators and cell populations have been manipulated will be
used to validate and refine the predictive power of our model. Work in Aim 2 will build a general model(s) that
can explain how overt differences in tumor growth, heterogeneity, and metabolism arise as emergent
behaviors of non-linearly interacting networks that qualitatively and quantitatively affect the Wnt pathway. In
Aim 3 we use xenograft models that develop resistance to the anti-angiogenic drug bevacizumab and single
cell RNA-seq approaches to examine the changes in cellular heterogeneity and patterning that accompany
acquisition of resistance. Mathematical modeling will identify the most likely resistance mechanisms:
mutualistic metabolic symbiosis, metabolic/population rewiring, mutualistic non-metabolic symbiosis, or none of
the above. Modeling predictions of strategies that re-establish drug sensitivity will be tested via genetic
engineering (CRISPR/Cas9) or small molecule drug therapies.

## Key facts

- **NIH application ID:** 10136546
- **Project number:** 5U54CA217378-04
- **Recipient organization:** UNIVERSITY OF CALIFORNIA-IRVINE
- **Principal Investigator:** Marian L Waterman
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $440,558
- **Award type:** 5
- **Project period:** 2018-04-01 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10136546

## Citation

> US National Institutes of Health, RePORTER application 10136546, Project 1: Patterned Heterogeneity in Colon Cancer (5U54CA217378-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10136546. Licensed CC0.

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