Abstract P1-20-04: Advanced development of the MasSpec Pen technology to aid in breast cancer surgical margin evaluation and diagnosis during surgery
Authors: Garza Kyana Y , Zhang Jialing , Lin John Q , Carter Stacey , Suliburk James , Nagi Chandandeep , Eberlin Livia S 
Published: March 2020

Complete tumor removal during breast conserving surgery (BCS) remains a challenge for even the most experienced surgeons due to difficulties associated with detecting residual disease at the margin. Additionally, there is limited technology to evaluate resected tissue while the patient is under anesthesia. Mass spectrometry (MS) has been previously used for rapid molecular characterization of healthy and diseased tissue and has shown potential for intraoperative use. We have developed an MS-based technology that couples a handheld and biocompatible device, the MasSpec Pen, to a mass spectrometer for non-destructive ex vivo and in vivo analysis of cancer tissue in a matter of seconds. We have used the MasSpec Pen with multivariate statistical analysis to discriminate the molecular patterns of normal breast and lymph node from invasive cancer tissue, achieving accuracies over 88%. Our results showcase the potential of the MasSpec Pen to provide surgical guidance during BCS. A total of 213 banked human tissues including normal breast and lymph node, IDC, and IDC to lymph node were obtained from the Cooperative Human Tissue Network and stored at -80°C prior to analysis. Samples were then thawed and analyzed using a mass spectrometer coupled to the MasSpec Pen. During MasSpec Pen analysis, a single water droplet is held in contact with the tissue to extract molecules that are then analyzed by a mass spectrometer, yielding a molecular fingerprint. The molecular information obtained is analyzed by the statistical model to provide a predictive diagnosis in seconds. The least absolute shrinkage and selection operator (Lasso) statistical method was used to generate predictive models comprised of molecular features indicative of healthy and diseased tissue. Analyzed regions of tissue were demarcated with a surgical ink marker, snap frozen, and sectioned at a thickness of 5µm. Tissue sections were H&E stained for pathological evaluation. The MasSpec Pen was used to analyze 79 normal and 64 breast cancer tissues. Various molecular species involved in cell metabolism, including metabolites, fatty acids, and glycerophospholipids were observed in the mass spectra. For example, glutamate was detected at a high relative abundance in breast cancer tissue while hexose was detected at a high abundance in normal breast tissue. The primary breast cancer model yielded a sensitivity and specificity over 95% for the training set (n=68) and validation set (n=22). The diagnostic capabilities of the model were further evaluated by predicting on an independent test set of samples (n=53). A sensitivity and specificity of 83.9% and 100% were achieved, demonstrating the ability of the MasSpec Pen to discriminate between normal and cancerous breast tissue. The MasSpec Pen was used to detect metastatic breast cancer in lymph node. Normal lymph nodes (n=26) and nodes with metastatic disease (n=44) were analyzed with the MasSpec Pen. For the metastatic breast cancer model, overall accuracies of 88.7% and 94.1% were achieved for the training set (n=46) and validation set (n=17), respectively. We envision the MasSpec Pen to be used in the operating room (OR) for the in vivo analysis of breast cancer. Recently, we have implemented the MasSpec Pec in the OR to evaluate the feasibility of this technology for intraoperative analysis of breast and lymph node tissue. Similar molecular species are detected in spectra obtained from the in vivo and ex vivo analysis of human breast and lymph node tissue when compared to spectra obtained from banked tissue. Continuous effort is being made to continue patient accrual and testing of the technology. Collectively, these results showcase the capability of the MasSpec Pen for breast cancer detection and its potential as an intraoperative tool for rapid breast cancer diagnosis and surgical margin evaluation during BCS.

Citation Format: Kyana Y Garza, Jialing Zhang, John Q Lin, Stacey Carter, James Suliburk, Chandandeep Nagi, Livia S Eberlin. Advanced development of the MasSpec Pen technology to aid in breast cancer surgical margin evaluation and diagnosis during surgery [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-20-04.