Overall Goals- Breast conserving surgery (BCS) is a mainstay of treatment in patients with early stage breast cancer, and requires tumor removal with clear margins in order to reduce the risk local recurrences and improve survival. Numerous methods of intraoperative margin evaluation have been investigated, however none have been proven to be of clinical utility in terms of sensitivity, specificity, timeliness and cost; the curent technique for standard margin assessment remains postoperative histopathology. Given the lack of intra- operative margin assessment, re-excision surgery ranges between approaches 20-40% nationwide. A technique capable of distinguishing breast tumor from healthy tissue which could be used as an intraoperative tool for investigating BCS margins in an accurate and timely manner would be revolutionizing for the field of breast surgery and drastically improve breast patient care by ultimately reducing current BCS re-excision rates. Objectives and Approach- In this project, desorption electrospray ionization (DESI) and liquid extraction surface analysis (LESA) mass spectrometry (MS) will be investigated as tools for reliably distinguishing between breast cancer and healthy tissue. The approach relies on metabolic differences in cancerous and healthy tissue and allows researchers to obtain spatially resolved molecular profiles of hundreds of molecules in a matter of minutes. DESI MS has previously been successful in delineating margins from brain tumor specimens, and has had initial success in the limited ex vivo evaluation of mastectomy specimens. This project seeks to develop and refine a reference system composed of DESI, LESA, and matrix assisted laser desorption ionization (MALDI) MS data acquired from breast tissue samples and use this information to generate MS biomarkers and classification models for breast tumor subtypes and healthy breast tissue. The models will be validated on breast tissue samples in an ex vivo laboratory environment by comparing results to those of standard histopathology analysis. DESI and LESA MS will also be utilized intraoperatively to investigate tissue samples taken from lumpectomy specimens of patients undergoing BCS in an operating room designated by the National Cancer Institute Center for Image Guided Therapeutics, called the Advanced Multimodal Image Guided Operating Suite (AMIGO), which will allow the MS data to be spatially registered with intraoperative Magnetic Resonance Imaging (iMRI). The timeliness of intraoperative MS results will be measured and accuracy will be established by comparing results to the standard histopathology results. It is anticipated that the results of this study will lead to changes in the intraoperative management of breast cancer patients by allowing for real-time margin assessment, and ultimately improve patient based care in terms of timeliness of therapy, cost, infection by reducing re-excision rates.

Public Health Relevance

Molecular characterization of breast cancer tissue during surgery with mass spectrometry will be investigated as a technique to distinguish between breast cancer and healthy tissue, and diagnosis. It is anticipated that the results of this study wll lead to changes in the intraoperative management of breast cancer patients by allowing real-time margin assessment, and ultimately improve patient based care in terms of timeliness of therapy, cost, infection by reducing re-excision rates.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA201469-04
Application #
9605728
Study Section
Medical Imaging Study Section (MEDI)
Program Officer
Lively, Tracy Lugo
Project Start
2015-01-06
Project End
2020-11-30
Budget Start
2018-12-01
Budget End
2019-11-30
Support Year
4
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
02115
Basu, Sankha S; Randall, Elizabeth C; Regan, Michael S et al. (2018) In Vitro Liquid Extraction Surface Analysis Mass Spectrometry (ivLESA-MS) for Direct Metabolic Analysis of Adherent Cells in Culture. Anal Chem 90:4987-4991
Kurreck, Annika; Vandergrift, Lindsey A; Fuss, Taylor L et al. (2018) Prostate cancer diagnosis and characterization with mass spectrometry imaging. Prostate Cancer Prostatic Dis 21:297-305