# Metabolic determinants of metastatic heterogeneity: quantitative experiments and mathematical models

> **NIH NIH F32** · SLOAN-KETTERING INST CAN RESEARCH · 2021 · $70,458

## Abstract

Project Summary/Abstract
 It is critically important to establish the causes of organ-specific metastasis; without this knowledge,
prevention and timely treatment of metastatic cancer progression will likely remain limited. The proposed
project aims to identify how metabolic gradients in the primary tumor can maintain diverse lineages with
specific metabolic adaptations, and how these adaptations contribute to organ-specific metastasis in breast
cancer. The central hypothesis is 1) that metabolic adaptations are key to the match between the seed (the
disseminated cell) and the soil (the distal site) in metastatic breast cancer, and 2) that the metabolic
microenvironment in a primary tumor drives metabolically diverse subpopulations. The hypothesis has been
formulated based on 1) published data detailing metabolic heterogeneity and that metabolic adaptations can
promote metastasis, 2) preliminary data and analysis of RNA expression, metabolomics, and flux
measurements, revealing different metabolic adaptations in breast tumor cells that home to different tissues,
and 3) preliminary data showing that metastatic lineages respond differently to hypoxia and nutrient gradients,
indicating a role for the metabolic microenvironment in maintaining diverse subpopulations within the same
heterogeneous primary tumor.
 The proposed aims will be accomplished using a combination of experimental and computational
biology. Integrated flux balance models of metastatic lineages will identify perturbed metabolic pathways in
each lineage. Knocking down or overexpressing key nodes in these pathways and assessing tropism in vivo
will determine the role of metabolic adaptations in organ-specific metastatic selection. The ability of
spontaneous nutrient gradients in the primary tumor to affect spatial segregation of lineages with distinct
metabolic adaptations will be investigated using custom MEMIC tissue mimetic plates. Mathematical models
will be used to study the ecological interactions between cell lines and their microenvironment that lead to
coexistence of metabolically distinct pre-metastatic subpopulations in the primary tumor.
 Joao Xavier will provide excellent mentorship for this project and the candidate’s career goals of
leading an independent research program, with a combination of hands-on teaching and freedom for
independent discovery. The current project will form the foundation of the candidate’s future independent
research. The training plan also includes meetings with a co-sponsor and collaborators, facilitating a
comprehensive education and ensuring a high probability of success for the project. The environment at
MSKCC provides further resources important for the completion of the proposed project, as well as career
development support as the candidate transitions to an independent career.

## Key facts

- **NIH application ID:** 10231357
- **Project number:** 1F32CA260841-01
- **Recipient organization:** SLOAN-KETTERING INST CAN RESEARCH
- **Principal Investigator:** Deepti Mathur
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $70,458
- **Award type:** 1
- **Project period:** 2021-07-31 → 2024-07-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10231357

## Citation

> US National Institutes of Health, RePORTER application 10231357, Metabolic determinants of metastatic heterogeneity: quantitative experiments and mathematical models (1F32CA260841-01). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10231357. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*