Abstract
Current methods for the intraoperative determination of breast cancer margins commonly suffer from the insufficient accuracy, specificity and/or low speed of analysis, increasing the time and cost of operation as well the risk of cancer recurrence. The purpose of this study is to develop a method for the rapid and accurate determination of breast cancer margins using direct molecular profiling by mass spectrometry (MS). Direct molecular fingerprinting of tiny pieces of breast tissue (approximately 1 × 1 × 1 mm) is performed using a home-built tissue spray ionization source installed on a Maxis Impact quadrupole time-of-flight mass spectrometer (qTOF MS) (Bruker Daltonics, Hamburg, Germany). Statistical analysis of MS data from 50 samples of both normal and cancer tissue (from 25 patients) was performed using orthogonal projections onto latent structures discriminant analysis (OPLS-DA). Additionally, the results of OPLS classification of new 19 pieces of two tissue samples were compared with the results of histological analysis performed on the same tissues samples. The average time of analysis for one sample was about 5 min. Positive and negative ionization modes are used to provide complementary information and to find out the most informative method for a breast tissue classification. The analysis provides information on 11 lipid classes. OPLS-DA models are created for the classification of normal and cancer tissue based on the various datasets: All mass spectrometric peaks over 300 counts; peaks with a statistically significant difference of intensity determined by the Mann–Whitney U-test (p < 0.05); peaks identified as lipids; both identified and significantly different peaks. The highest values of Q2 have models built on all MS peaks and on significantly different peaks. While such models are useful for classification itself, they are of less value for building explanatory mechanisms of pathophysiology and providing a pathway analysis. Models based on identified peaks are preferable from this point of view. Results obtained by OPLS-DA classification of the tissue spray MS data of a new sample set (n = 19) revealed 100% sensitivity and specificity when compared to histological analysis, the “gold” standard for tissue classification. “All peaks” and “significantly different peaks” datasets in the positive ion mode were ideal for breast cancer tissue classification. Our results indicate the potential of tissue spray mass spectrometry for rapid, accurate and intraoperative diagnostics of breast cancer tissue as a means to reduce surgical intervention.
Highlights
Breast cancer ranks first in the incidence of malignant neoplasms among the female population
A study is performed on biopsy materials of breast cancer from patients treated at the National Medical Research Center for Obstetrics, Gynecology and Perinatology named after Academician V.I
The data on a sample molecular composition are obtained by tissue spray mass spectrometry [24,25,26]
Summary
Breast cancer ranks first in the incidence of malignant neoplasms among the female population. 60–80% of newly detected cases of breast cancer are treated with organ-preserving surgery [1,2]. Several large randomized trials clearly showed that there were no statistically significant differences in the rates of disease-free and overall survival among patients who underwent either mastectomy or organ-preserving operation [3,4,5]. The risk of local recurrence after organ-preserving surgeries remains higher than after mastectomy, and is an average of 0.5% per year. “Positive” margins of resection are the reason for performing repeated surgical interventions in 20–25% of breast cancer patients after performing organ-preserving surgeries [6,7]. It is extremely important to provide the surgeon with the most accurate information regarding the margins of resection during the operation and thereby reduce the risk of repeated surgical interventions
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