Validation of Breast Cancer Margins by Tissue Spray Mass Spectrometry

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.

Comparison of the effectiveness of variable selection method for creating a diagnostic panel of biomarkers for mass spectrometric lipidome analysis

“…The following lipidome data collections (DC) were used in this study 22–24 : (1) blood plasma samples from patients with/without endometriosis (36/24 samples); (2) blood plasma samples from patient with first‐case myoma/recurrent myoma/control (40/59/26 samples); (3) breast tissue samples from patient with breast cancer and with/without lymph node metastasis (48/38 samples); (4) breast cancer tissue samples from patient with/without lymph node metastasis (48/40 samples); (5) cervical tissue samples with/without neoplastic lesions (33/25 samples). DC1–DC4 were obtained by reversed phase liquid chromatography‐mass spectrometry analysis of lipid extract with identification of lipids by Lipid Match scripts 25 .…”

Analytical Platforms for the Determination of Phospholipid Turnover in Breast Cancer Tissue: Role of Phospholipase Activity in Breast Cancer Development

“…In addition, the ROC results were in agreement with PCA, meaning that PCs and TGs can be putative biomarkers for BC diagnosis. Another study obtained significant differences ( p < 0.05) in lipid levels between BC and normal tissues using tissue spray mass spectrometry, for PI, PCs, and SM [ 98 ]. Moreover, the results obtained by orthogonal partial least-squares discriminant analysis (OPLS-DA) classification of the tissue revealed 100% sensitivity and specificity when compared to histological analysis [ 98 ].…”

“…Another study obtained significant differences ( p < 0.05) in lipid levels between BC and normal tissues using tissue spray mass spectrometry, for PI, PCs, and SM [ 98 ]. Moreover, the results obtained by orthogonal partial least-squares discriminant analysis (OPLS-DA) classification of the tissue revealed 100% sensitivity and specificity when compared to histological analysis [ 98 ]. Finally, Cifková et al [ 19 ] correlated the lipidomic profile of cell lines and tissues of BC patients using HILIC/ESI-MS combined with multivariate data analysis (e.g., PCA, OPLS-DA).…”

Alterations in Lipid Profile Upon Uterine Fibroids and Its Recurrence

“…Shotgun lipidomics based on electrospray ionization mass spectrometry (ESI-MS) allows deep molecular profiling of a sample without significant losses of chemical information [26,27]. The high diagnostic potential of lipidomics has been shown in many areas of medicine, particularly in oncology: lung, thyroid gland, breast, stomach, pancreas, colorectal, liver, kidney, prostate, ovarian, and endometrium cancer [28,29,[38][39][40][41][42][43][44][45][46][47]30,[48][49][50][51][31][32][33][34][35][36][37]. MS studies of lipid profiles in tissues and blood plasma have revealed new promising biomarkers of endometriosis (benign gynecological disorder) [26,27,32,33,37,44,47].…”