# Engineering personalized micro-tumor ecosystems

> **NIH NIH U01** · BRIGHAM AND WOMEN'S HOSPITAL · 2020 · $742,092

## Abstract

Abstract
Cancer is one of the leading causes of death in the United States, accounting for near 1 in every 4 deaths.
However, despite the recent development of subtype-specific personalized therapy based on achievements in
the fields of molecular and genetic profiling, many cancer treatments still have low efficacy which mostly arise
from the limited ability to predict the patient tumor responses to therapeutic agents. The major reason that current
therapeutics often cannot translate into a successful clinical outcomes is because of the complex tumor
microenvironment and heterogeneity that limit the predictive power of the biomarker-guided strategies for
chemotherapy. Therefore, the successful engineering of personalized three-dimensional (3D) tumor ecosystem
that can recapitulate the tumor microenvironment and heterogeneity in vitro is strongly desired to accurately
predict patients’ responses to anti-cancer drugs and thus further improve patient outcome. Here we propose to
develop a personalized breast-cancer-ecosystem-on-a-chip platform for personalized screening of cancer
chemotherapeutics with high accuracy by utilizing patient-derived tumor explant, defined tumor grade-matched
biomaterial matrices and autologous patient serum to mimic patient-specific tumor hallmarks. The proposed
cancer-ecosystem-on-a-chip will also be tightly regulated under physiological fluid dynamics. In this project, we
have hypothesized that 1) the use of tumor explant will embrace the critical components of the tumor
heterogeneity of the patient, 2) the combination of defined tumor grade-matched matrix, autologous patient
serum, and a microfluidic bioreactor will prevent the phenotype alteration of the tumor explant, and 3) the
integration of a machine-learning algorithm with the cancer-ecosystem-on-a-chip platform will provide more
accurate, unbiased prediction of the patient responses to chemotherapeutics based on the data gathered from
the engineered tumor model. Our preliminary results show that the combination of tumor explant culture and
tumor-derived matrix constituents had predicted therapeutic responses with 100% sensitivity. Our preliminary
results show high specificity throughout a range of cancers including breast cancer, colorectal cancer, and head
and neck squamous cell carcinoma, and thus the findings can have broad applications, and can emerge as a
paradigm shift in the management of cancer.

## Key facts

- **NIH application ID:** 9981696
- **Project number:** 5U01CA214411-04
- **Recipient organization:** BRIGHAM AND WOMEN'S HOSPITAL
- **Principal Investigator:** Ali Khademhosseini
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $742,092
- **Award type:** 5
- **Project period:** 2017-09-21 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9981696

## Citation

> US National Institutes of Health, RePORTER application 9981696, Engineering personalized micro-tumor ecosystems (5U01CA214411-04). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/9981696. Licensed CC0.

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