A Healthier Wisconsin

Personalized Breast Cancer Treatment

Developing a PDX breast cancer library to serve as platform for patient-specific hypotheses related to personalized treatment strategies

Full Project Name:The MCW Program for Personalized Breast Cancer Treatment (PBCT)Principal Investigator:Michael J. Flister, PhD, PhysiologyCo-Investigator:Hallgeir Rui, MD, PhD, PathologyAward Amount:$200,000
Award Date
Project Duration:24 months

Project Description Narrative:

Over 230,000 new cases of breast cancer are diagnosed each year in the U.S. More than 40,000 patients die annually from metastatic breast cancer that is resistant to available therapies. In most of these cases, the mechanisms by which tumors resist therapy are unknown and possibly differ between individuals.

One strategy used to identify the mechanisms of therapy resistance has been to study a patient's transplanted tumor sample in an animal, which is referred to as a patient-derived xenograft (PDX) model. However, the PDX model has limitations that can make it difficult to aid patient treatment. For instance, PDX models take months to generate and so are often too slow to impact a patient's treatment. In addition, very few PDX models exist for estrogen receptor positive (ER+) breast cancer, which makes up 70-80% of cases. New approaches are needed to address these limitations and increase understanding to support personalized breast cancer treatment.

This award aims to develop a PDX breast cancer library that will serve as clinical avatars for new breast cancer patients. The PDX breast cancer avatars will capture the majority of genetic diversity in Wisconsin breast cancer patients and will serve as platforms to test patient-specific hypotheses related to personalized treatment strategies.

Outcomes & Lessons Learned:

  • Established that the humanized prolactin NSG mouse is a novel and superior host for patient-derived breast cancer zenografts, which is a paradigm shifting research tool that enables the study of all subtypes of breast cancer that was previously unattainable
  • A total of 15 therapy resistant metastatic breast cancer PDX models were sequenced
  • Multiple novel therapeutic targets have been identified for validation in future studies
  • Through this study, the researchers gained new and important insight into the underlying drivers of therapy resistance in breast cancer that will help the development of more effective strategies for treatment
  • Published three manuscripts in cancer and bioinformatic journals

Project Updates:

  • Performed genomic characterization of multiple patient-derived breast cancer models, leading to the discovery of several new mechanisms of therapy resistance. As a result, multiple therapeutics (e.g., Herceptin and Parp inhibitors) that are FDA approved were identified, but have not yet been used to for preventing/curing tamoxifen-resistant metastatic breast cancer. Thus, these findings will potentially lead to repurposing these drugs for treating patients with tamoxifen-resistant breast cancer
  • Increased team's ability to generate human patient-derived xenograft (PDX) models that have enabled the study of the development of therapy resistance, resulting in unprecedented access to PDX models of breast cancer which are being studied using DNA and RNA sequencing techniques to identify mechanisms of acquired therapy resistance in human breast cancer patients
  • Using team's unique breast cancer PDX models, began to identify genetic and molecular pathways that cancer cells use to develop therapy resistance

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