Abstract A04: Unique Raman spectroscopic fingerprints of Burkitt non-Hodgkin lymphoma
Authors: Natalie Kamada, Robert Oda, Tiffany Shieh, Melissa Agsalda-Garcia, Tayro Acosta-Maeda, Anupam Misra, So Yung Choi, Eunjung Lim, Bruce Shiramizu
Journal: Cancer Research (2018)

Abstract Purpose: Raman spectroscopy (RS) is a noninvasive laser-based technique that provides a very high level of confidence in detecting various molecules through their vibrational modes. A monochromatic laser is used to excite a sample, and inelastic scattered light generated by the sample is used to measure Raman spectra of the sample. Because vibration modes of a molecule are very unique to the molecule, RS is sensitive and highly selective to the molecular composition of various chemicals including biologic tissues and cells. By using micro-Raman systems capable of measuring Raman spectra of single biologic cell, the objective of the study focused on identifying molecular differences between normal B-cells and Burkitt non-Hodgkin lymphoma (BNHL) cells, hypothesizing that unique RS fingerprints of BL could be identified with the overall goal to apply the information for novel diagnostic or treatment strategies. Methods: Normal B-cells were isolated from peripheral blood using a negative selection Robosep kit (EasySep Human B-Cell Isolation Kit, Stemcell Technologies, Cambridge, MA). BNHL cell lines (Ramos and CA46, ATCC, Manassas, VA), were cultured, washed, and resuspended in a 0.9% saline solution at a concentration of 1 x 106 cells/mL. The cells were mounted on a clean aluminum reflective slide and single cells were analyzed with a micro-Raman system utilizing a 785-nm laser excitation and an automated xyz microscope stage. Asymmetric Least Squares (AsLS) was applied to the spectral data (n=20 spectra per cell type) to obtain baseline spectra. Principal Component Analysis (PCA) followed by k-nearest neighboring (KNN) method was applied to analyze the variance in the spectral data and assess the diagnostic accuracy of the loadings from PCA. Results: The Raman fingerprints of normal B-cells and BNHL cells identified characteristic peak differences between the cell types, ranging from DNA/protein concentrations to saccharide bonds. These were further analyzed using AsLS and PCA. AsLS informed the PCA, which identified variances in the peaks that formed distinct clusters to differentiate normal B-cells from BL NHL cells. PCA effectively compiles the peaks, demonstrating that the first three components accounted for 97.45% of variance in the data. Several peaks were identified as the major contributors to the loadings, and some (e.g., 831, 1083, 1210, 1257, 1360, 1578, 1658 cm-1) were also reported as biomarkers of BNHL. The KNN on the PCs revealed that diagnostic accuracy was 100% and specificity was 100%. Conclusions: Raman fingerprints of normal B-cells versus BNHL cells demonstrated unique clustering of molecular changes that could potentially distinguish neoplastic cells from normal cells. As a novel and innovative tool, RS could contribute towards diagnostic resources and new paradigms for intervention for BNHL and other diseases. This study was supported by the St. Baldrick’s and McCabe Foundations and in part by NIH U54MD007584. Citation Format: Natalie Kamada, Robert Oda, Tiffany Shieh, Melissa Agsalda-Garcia, Tayro Acosta-Maeda, Anupam Misra, So Yung Choi, Eunjung Lim, Bruce Shiramizu. Unique Raman spectroscopic fingerprints of Burkitt non-Hodgkin lymphoma [abstract]. In: Proceedings of the AACR Special Conference: Pediatric Cancer Research: From Basic Science to the Clinic; 2017 Dec 3-6; Atlanta, Georgia. Philadelphia (PA): AACR; Cancer Res 2018;78(19 Suppl):Abstract nr A04.