Next-Generation Molecular Histology Using Highly Multiplexed Ion-Beam Imaging (MIBI) of Breast Cancer Tissue Specimens for Enhanced Clinical Guidance

Abstract

The ability to visualize the presence, abundance, location and functional state of many proteins at once in cells and tissues with preserved morphology has long been a goal. This proposal seeks to optimize recently demonstrated mass-spec-based imaging methods that can, when fully developed, detect as many as 40 to 100+ molecular targets in cells and tissues using simultaneously applied mass-tag-labeled antibodies, with outstanding morphology. Preliminary data using a highly focused, scanning oxygen ion beam and 10 antibodies applied simultaneously to clinical breast cancer tissues demonstrate histology-like images that reveal bound antibody location with subcellular resolution. The present project will address: reliable pre analytical sample preparation methods and labeling techniques for protein analytes; ion-beam imaging method improvements based on current and projected instrumentation; powerful, easy-to-use software for equipment control, display and analysis; and validation in several important biological test cases. Going forward, we would like to optimize sensitivity and reliability, with the goal of making this a standard, high performance, imaging approach for basic and translational science discovery, drug development, and possible clinical deployment.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2018
Accession Number
AD1063914

Entities

People

  • Alexander Borowsky

Organizations

  • University of California, Davis

Tags

DTIC Thesaurus Topics

  • Allergy And Immunology
  • Breast Cancer
  • Cells
  • Chemical Synthesis
  • Chemistry
  • Computational Biology
  • Detectors
  • Immune System
  • Ion Beams
  • Mass Spectra
  • Mass Spectrometers
  • Mass Spectrometry
  • Medical Personnel
  • Neoplasms
  • Proteins
  • Spectrometry
  • Systems Biology

Fields of Study

  • Physics

Readers

  • Medical Imaging.
  • Oncology and Biomarker-Based Cancer Detection.
  • Systems Analysis and Design