# Dissecting the complexity of metastasis with mathematical models and quantitative experiments with in zebrafish

> **NIH NIH R01** · SLOAN-KETTERING INST CAN RESEARCH · 2022 · $619,097

## Abstract

Project Summary
Metastasis—a defining feature of advanced cancer—often represents a transition from curable to incurable
disease. The metastatic cascade consists of a series of severe obstacles that cancer cells must overcome,
each one highly inefficient and apparently stochastic; we are presently unable to predict whether, when and
where metastases will occur. We propose to apply an ecological lens to metastasis. Specifically, we will
investigate the processes driving the increased metastatic potential of circulating tumor cell (CTC) clusters
through a combination of mathematical modeling and in vivo quantitative experiments in a zebrafish model of
melanoma. Melanoma, the most lethal of skin cancers, shows a particularly stark difference between the
outcomes of patients with local versus metastatic disease: Patients with CTC clusters in their blood have worse
clinical prognoses. Despite their importance, the mechanisms underlying CTC cluster formation, increased
metastatic capacity, and potential for therapeutic targeting remain understudied—particularly in melanoma. We
take advantage of the zebrafish model of metastatic melanoma, including the ZMEL1 cell line capable of
transplantation into transparent Casper zebrafish, which provides a powerful system to quantitatively
investigate the mechanisms behind increased metastatic potential of CTC clusters from an ecological
perspective. Our three specific aims address how CTC clusters relate to metastatic fitness: (Aim 1) We
hypothesize that the trade-off between group size and number—integral to ecological dispersal—is key in
metastasis formation by CTC clusters; we will we will test this hypothesis with mathematical models to predict
how the success of melanoma clusters varies with size, and we will confront those models with zebrafish data
to quantify the metastatic fitness landscape of melanoma CTC clusters; we will then introduce genetic
perturbations on hypothesized mechanisms of cellular cooperation within-clusters and elucidate the
mechanisms underlying the shape of the cluster fitness landscape. (Aim 2) We hypothesize that high intra-
cluster diversity promotes overall metastatic fitness despite the presence of some cells with lower individual
fitness; we will test this hypothesis by engineering clusters with melanoma-specific forms of genetic
heterogeneity; we will apply quantitative statistical analyses to compare high- and low-diversity clusters
transplanted into zebrafish and evaluate the role of compositional heterogeneity in CTC cluster metastatic
fitness using multi-level selection theory. (Aim 3) We hypothesize that microenvironmental gradients of
diffusible substances determine the success of clusters of extravasated cells; we will test this hypothesis by
investigating gradients in vivo, in vitro and in silico using an agent-based model with partial differential
equations of reaction-diffusion. These aims, coupled with validation in mammalian models, will generate new
insights into ...

## Key facts

- **NIH application ID:** 10471185
- **Project number:** 5R01CA229215-05
- **Recipient organization:** SLOAN-KETTERING INST CAN RESEARCH
- **Principal Investigator:** Richard Mark White
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $619,097
- **Award type:** 5
- **Project period:** 2018-09-01 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10471185

## Citation

> US National Institutes of Health, RePORTER application 10471185, Dissecting the complexity of metastasis with mathematical models and quantitative experiments with in zebrafish (5R01CA229215-05). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10471185. Licensed CC0.

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