Optical sensing techniques for detection of disease metabolites and rare circulating tumor cells

Abstract

In recent years, there have been significant efforts to develop biomedical devices for non-invasive detection and monitoring of disease. This work focuses on two methods in this field: (1) development of biomimetic sensor arrays to detect disease metabolites using Raman spectroscopy and spectral analysis, and (2) detection and enumeration of rare circulating tumor cells in mice, specifically to study the effects of radiation therapy on metastasis. While the first discusses sensor optimization and pattern recognition for future biological applications, the second highlights the potential of novel optical sensing methods to uncover mechanisms of disease. Currently, the development of non-invasive, accurate devices for early disease diagnosis remains challenging. Presented herein is a cross-reactive sensor array based on spectroscopically self-encoded polymers. The array was analyzed by Raman spectroscopy before and after exposure to organic liquid and vapor analytes. The changes in the polymers' vibrational fingerprints were quantified, and multivariate data analysis was then performed to evaluate sensor selectivity. Multivariate data analysis methods were performed for optimized detection of specific analytes. Results indicated that the polymer-based sensors provide a unique and reproducible pattern for each analyte and have the potential to be used in the fabrication of a novel electronic nose (vapor) or tongue (liquid) device. There is significant clinical and pre-clinical evidence that radiation therapy (RT) may promote the metastatic spread of cancer to other organs. In this work, Diffuse in vivo Flow Cytometry (DiFC) was used to investigate the influence of RT on CTC shedding, and its possible role in RTIM. First, a subcutaneous LLC model was established in mice, and CTC shedding was monitored throughout the study. Second, CTC kinetics and lung metastasis were compared in both radiated and non-radiated mice. While DiFC data from both studies show a large variation in CTC shedding rates across all mice, RT mice had a significantly higher lung tumor burden (determined by cryo-macrotome imaging), and number of CTC clusters detected. This supports previous hypotheses in the literature that CTC clusters play a significant role in metastasis, and this work represents an important step in uncovering the kinetics of RTIM.