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Updated: Sep 28, 2025

Studying Triple Negative Breast Cancer Using Orthotopic Breast Cancer Model
Published on: March 20, 2020
Therapeutic Targeting of Stromal-Tumor HGF-MET Signaling in an Organotypic Triple-Negative Breast Tumor Model
Sunil Singh1, Astha Lamichhane1, Pouria Rafsanjani Nejad1
1Department of Biomedical Engineering, The University of Akron, Akron, Ohio.
Abstract:
The tumor microenvironment (TME) promotes proliferation, drug resistance, and invasiveness of cancer cells. Therapeutic targeting of the TME is an attractive strategy to improve outcomes for patients, particularly in aggressive cancers such as triple-negative breast cancer (TNBC) that have a rich stroma and limited targeted therapies. However, lack of preclinical human tumor models for mechanistic understanding of tumor-stromal interactions has been an impediment to identify effective treatments against the TME. To address this need, we developed a three-dimensional organotypic tumor model to study interactions of patient-derived cancer-associated fibroblasts (CAF) with TNBC cells and explore potential therapy targets. We found that CAFs predominantly secreted hepatocyte growth factor (HGF) and activated MET receptor tyrosine kinase in TNBC cells. This tumor-stromal interaction promoted invasiveness, epithelial-to-mesenchymal transition, and activities of multiple oncogenic pathways in TNBC cells. Importantly, we established that TNBC cells become resistant to monotherapy and demonstrated a design-driven approach to select drug combinations that effectively inhibit prometastatic functions of TNBC cells. Our study also showed that HGF from lung fibroblasts promotes colony formation by TNBC cells, suggesting that blocking HGF-MET signaling potentially could target both primary TNBC tumorigenesis and lung metastasis. Overall, we established the utility of our organotypic tumor model to identify and therapeutically target specific mechanisms of tumor-stromal interactions in TNBC toward the goal of developing targeted therapies against the TME.
Implications:
Leveraging a state-of-the-art organotypic tumor model, we demonstrated that CAFs-mediated HGF-MET signaling drive tumorigenic activities in TNBC and presents a therapeutic target.
Insights
Targeting cancer-associated fibroblasts (CAFs) and their HGF-MET signaling in triple-negative breast cancer (TNBC) can inhibit tumor growth and metastasis. This study developed a 3D model to identify effective combination therapies against the tumor microenvironment.
Area of Science:
- Oncology
- Cancer Biology
- Translational Research
Background:
- The tumor microenvironment (TME) fuels cancer progression, especially in triple-negative breast cancer (TNBC), which lacks targeted therapies.
- Understanding tumor-stromal interactions is crucial for developing effective treatments, but preclinical models are limited.
- Cancer-associated fibroblasts (CAFs) within the TME significantly influence cancer cell behavior.
Purpose of the Study:
- To develop a 3D organotypic tumor model for studying TNBC and CAF interactions.
- To identify therapeutic targets within the TME for TNBC treatment.
- To explore effective drug combinations against prometastatic functions.
Main Methods:
- Developed a three-dimensional organotypic tumor model using patient-derived CAFs and TNBC cells.
- Investigated the role of hepatocyte growth factor (HGF) and MET receptor tyrosine kinase signaling.
- Assessed the efficacy of monotherapies and drug combinations in inhibiting tumor cell functions.
Main Results:
- CAFs secrete HGF, activating MET signaling in TNBC cells, promoting invasiveness and epithelial-to-mesenchymal transition.
- TNBC cells develop resistance to monotherapy.
- Blocking HGF-MET signaling showed potential in targeting primary TNBC and lung metastasis.
Conclusions:
- The developed organotypic model is effective for studying TME interactions in TNBC.
- Targeting HGF-MET signaling represents a promising therapeutic strategy for TNBC.
- Combination therapies are necessary to overcome monotherapy resistance and inhibit metastasis.

