In this application we propose to develop the in vivo native contrast endoscopic imaging system that can identify cellular composition of the esophageal cancer tumors and their microenvironment in order to determine the optimal course of cancer therapy. Esophageal cancer is one of the deadliest forms of cancers with an overall 14% five-year survival rate. The survival rate among operable cancers is 22%, which increases to 37% with the use of chemotherapy prior to surgery as a neoadjuvant therapy. Currently, there are several FDA-approved chemotherapy drugs, which can be used in various combinations. Each of these drugs targets particular cancer cell types. Because tumors are almost always composed of several cancer cell types, combinatorial therapies are most effective. The only existing way of determining the cell type of the cancer is histopathology, which samples a small proportion of the tumor and, given the large heterogeneity between different tumor areas, is prone to biopsy errors. Additionally, there is no good way of determining the cancer responsiveness to the chemotherapy, which is closely related to the types of cells composing the tumor and the tumor microenvironment. Thus, the largest impediment for determining optimal targeted therapies for esophageal cancer treatment is the absence of the in vivo imaging method that can identify cancer cell types, tumor microenvironment, and are able to closely monitor treatment progress. Due to its ability to sense cellular organization of tumors and identify cell types, while providing gross anatomical imaging, light scattering spectroscopy (LSS) based imaging would be uniquely equipped to address the problem of identifying the cytotypes and cytotype distributions of cancer tumors. We propose to complement LSS information with diffuse reflectance spectroscopy (DRS) information which is sensitive to the microenvironment of the tumor, such as degree of angiogenesis and connective tissue density. Therefore, the purpose of this program is to extend the LSS and DRS technologies and develop native contrast real time dual mode endoscopic spectral imaging system (DMESIS) and test it in clinical experiments in patients with suspected esophageal cancer by comparing to histopathology results from tumor biopsies.
Esophageal cancer is one of the deadliest forms of cancers. The largest impediment for determining optimal targeted therapies for esophageal cancer treatment is the absence of an in vivo imaging method that can identify cancer cell types, tumor microenvironment, and is able to closely monitor the treatment progress. Therefore, the purpose of this program is to develop the native contrast real time in vivo imaging technology that will improve esophageal cancer survival rates through optimized and personalized treatment.
| Turzhitsky, Vladimir; Zhang, Lei; Horowitz, Gary L et al. (2018) Picoanalysis of Drugs in Biofluids with Quantitative Label-Free Surface-Enhanced Raman Spectroscopy. Small 14:e1802392 |
| Zhang, Lei; Pleskow, Douglas K; Turzhitsky, Vladimir et al. (2017) Light scattering spectroscopy identifies the malignant potential of pancreatic cysts during endoscopy. Nat Biomed Eng 1: |
