A majority of triple-negative breast cancer (TNBC) patients die because of the metastasis of their tumors. Due to the lack of targetable receptors in the tumors, chemotherapy remains the only therapeutic option. Chemotherapy drugs must be given at high concentrations, which are harmful to normal, healthy cells, and the clinical outcomes are very unpredictable. Patients often suffer from side effects or even mortality because of the treatments. When used as drug carriers, nanoparticles can reduce dose-limiting toxicities but only present an anti-tumor activity comparable to that of free drugs. This is because nanoparticles must bypass various physiological barriers, e.g., being captured by the reticuloendothelial system. They must also penetrate tumors to be effective. Once inside the tumors, they are susceptible to clearance by the lymphatic system. There is a demand for a delivery approach that will make chemotherapy safer and more effective. Our long-term goal is to overcome physical and biological barriers and thus deliver more drugs to tumor sites. Our immediate objective is to investigate the delivery efficiency and therapeutic efficacy of a novel peptide nanofiber platform (NFP) for the treatment of metastatic TNBC. We hypothesize that NFP can carry more drugs to tumors via a multiplexed delivery approach and thus improve treatment outcomes. This hypothesis is formulated based on our preliminary data: NFP has unique tumor-preferential uptake, infiltration, and retention properties. When used as a drug carrier, it displays superior therapeutic efficacy and toxicity profiles compared to free drugs in terms of eradicating solid tumors. NFP can target metastatic tumors in the lungs.
Two specific aims will be pursued: (1) investigating the delivery of treatment to metastatic TNBC tumors via NFP and (2) evaluating the therapeutic efficacy of drug-loaded nanofibers in improving the survival rate. NFP will be used to deliver aldoxorubicin, a prodrug of doxorubicin that was shown to improve the survival rate of TNBC patients. In the first effort, the tumor uptake and retention of an 89Zr-labeld and drug-loaded NFP (aldox-NFP) will be monitored via PET/CT imaging of mice with mTNBC tumors in their lungs. The pharmacokinetics and biodistribution of aldox-NFP will be determined. The tumor penetration will be studied via confocal and transmission electron microscopic analysis of the tumor sections and validated in 3D cell cultures. In the second effort, experiments will be conducted to assess the therapeutic efficacy. The Kaplan-Meier survival rate of the NFP-treated animals will be determined. The toxicity profile will be evaluated via clinical pathology and blood chemistry. The results will be compared to aldoxorubicin and the clinically used nanoparticle, Doxil. The rationale behind this research is that a technology such as NFP may represent a more robust, sensitive, and effective therapy; reduce the required administration dosage; and thus minimize chemotherapy-associated morbidity and mortality. NFP is innovative; it utilizes a combination of shape-controlled tumoral uptake, infiltration, and retention approach. NFP advances will allow it to carry other drugs for the treatment of various cancers.

Public Health Relevance

The current methods to deliver chemotherapy faces many challenges including unfavorable body distributions, leading to insufficient therapeutic drug concentration at tumor sites and off-targeting toxicity. This application describes a novel multiplexed drug approach, NFP, to overcome physiological barriers of tumoral delivery, for achieving safer and more precise and effective treatment of metastatic breast cancer.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Small Research Grants (R03)
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Special Emphasis Panel (ZCA1)
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Fu, Yali
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Weill Medical College of Cornell University
Schools of Medicine
New York
United States
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Bellat, Vanessa; Ting, Richard; Southard, Teresa L et al. (2018) Functional Peptide Nanofibers with Unique Tumor Targeting and Enzyme-Induced Local Retention Properties. Adv Funct Mater 28: