Quantitative Phase Microscopy for Real-Time Clinical Determination of Drug Therapy Response in Primary and Metastatic Breast Cancer

Abstract

There are no biomarkers that can accurately predict chemotherapy response in advanced cancer patients and less than 10 percent of patients with a detected targetable mutation are eligible for a clinical trial. There is a need for new diagnostic methods that can accurately stratify high-risk patients to effective, FDA-approved therapies. Our current patient-derived models for assessing tumor drug response involve expanding patient tumor cells as 3D patient derived organoids (PDO) in Matrigel or using in vivo drug sensitivity studies with patient-derived xenograft models (PDX). These experimental models typically exhibit the same phenotype and molecular alterations in vivo and ex vivo and have the same drug responses as in the patient. However, these methods require 1-8 months to obtain drug sensitivity profiles making this impractical for patient care. In this project, we will develop a functional assay with the new capability to predict cancer cell response to therapy for both cell population response and single-cell heterogeneity. In year 3, we completed the technical validation of the QPM platform using established cell lines and FDA-approved therapies. This work is under review for publication. In addition, we have begun using organoid breast cancer models to show analytic validity of drug response/resistance. Overall, our project will provide real-time feedback to oncologists on overall drug sensitivity/resistance and resistant subpopulations.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2022
Accession Number
AD1173828

Entities

People

  • Phillip S. Bernard

Organizations

  • University of Utah

Tags

DTIC Thesaurus Topics

  • Biomedical Research
  • Breast Cancer
  • Cell Line
  • Cells
  • Chemical Engineering
  • Culture Techniques
  • Data Analysis
  • Data Visualization
  • Engineering
  • Genetic Techniques
  • Infectious Diseases
  • Medical Personnel
  • Neoplasms
  • Physicians
  • Pleural Diseases
  • Resistance
  • Standards
  • Students
  • Therapy
  • United States

Fields of Study

  • Biology
  • Medicine

Readers

  • Computational Modeling and Simulation
  • Oncology