# Advanced development and validation of an in vitro platform to phenotype brain metastatic tumor cells using artificial intelligence

> **NIH NIH R33** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2024 · $369,018

## Abstract

Abstract
Metastasis from the primary tumor site to the brain is the most lethal complication of advanced breast cancer
and is experienced by approximately 20% of breast cancers worldwide. There is at present no approach to
detect if a tumor has brain metastatic potential, no markers that predict successful future metastasis, and thus
no therapies to target any of the processes involved. These gaps are difficult to bridge due to a lack of
technology that can elucidate the underlying mechanisms by classifying a cancer cell based on its brain
metastatic potential. Current in vivo murine models are slow to manifest metastasis and do not have the
capability of capturing single cell morphology and dynamics; and current in vitro models are short lived and
lack software support therefore, we propose an in vitro blood brain niche (µm-BBN) on-a-chip to measure the
phenotypic differences between cancer cells and normal cells and amongst cancer cells as they transit through
the model niche and to assign them a brain metastatic potential. Moreover, we propose capturing the cells that
transit through the BBN for further analysis.
This system is composed of the µm-BBN, an integrated piezo pump and controller, automated phenotyping
software and a classification algorithm. The µm-BBN has two chambers which form a vessel (human brain
endothelial cells and brain stroma (ECM and Normal Human Astrocytes (NHA), Microglia and Pericytes)
separated by a 5µm porous membrane coated with Matrigel. The goal is to culture cancer cells in the device
for up to 20 days using the integrated pump. Expanding on previous work, the cellular phenotype and
migratory behavior of a library of patient cells will be recorded. Generation of phenotypic measures for
individual cancer cells, micro-metastasis and the tumor micro-environment will enable automated profiling of
the metastatic signature of tumor cells. After culture the cells will be recovered and fixed or analyzed to create
a multi-omic readout enabling a complimentary cellular and molecular signature for single cells and sub-
populations of metastatic cancer cells.
This work will enable improved understanding of the underlying mechanisms of brain metastasis and,
downstream from it, in a more robust set of targetable pathways for prevention of brain metastasis.

## Key facts

- **NIH application ID:** 10839801
- **Project number:** 5R33CA261696-03
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Jianping Fu
- **Activity code:** R33 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $369,018
- **Award type:** 5
- **Project period:** 2022-06-01 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10839801

## Citation

> US National Institutes of Health, RePORTER application 10839801, Advanced development and validation of an in vitro platform to phenotype brain metastatic tumor cells using artificial intelligence (5R33CA261696-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10839801. Licensed CC0.

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