Oral cancer is the 6th most common cancer worldwide. Despite the easy accessibility of the oral cavity for screening, oral cancer has one of the lowest 5-year survival rates of all cancers. Oral cancer is thought to arise as a result of fied cancerization, where, often in response to tobacco and alcohol exposure, wide areas of the mucosal surface develop subclinical carcinogenetic changes. The poor outcomes of oral cancer arise primarily because: (1) most patients are diagnosed at a late stage since the molecular changes that put patients at risk of neoplasia often do not give rise to clinically visible lesions and (2) a large fraction of patients treated for oral cancer develop subsequent cancers because areas of field cancerization persist following treatment and are not clinically visible. The development and progression of oral cancer is ultimately a molecular process, reflecting a complex succession of genetic changes within the field-at-risk. Ultimately tumor-initiating stem cells give rise to aggressive clones within a mucosal field-at-risk, resulting in malignant progression. While much progress has been made to understand the molecular alterations associated with oral cancer progression, this research has not yet led to improvements in early detection mainly because molecular analysis methods are costly and can only be carried out with tissues obtained from invasive biopsies. There is increasing evidence to suggest that key molecular alterations result in phenotypic changes that can be measured clinically at the point-of-care. Recent studies by our group and others suggest that multi-modal optical imaging can image changes in tissue fluorescence and nuclear morphometry to identify high grade oral precancer and early cancer with significantly improved sensitivity and specificity compared to visual examination; moreover, changes in optical properties correlate strongly with molecular markers associated with neoplastic progression. The goal of this proposal is to validate the ability of multimodal optical imaging to improve early detection and to determine whether risk-related optical markers (RROMs) can be used to predict the likelihood of malignant progression. We will perform longitudinal studies in patients with oral lesions using cutting edge autofluorescence and microendoscopy technology with automated diagnostic algorithms. In an animal model of oral cancer, we will combine optical imaging and novel tissue preparation techniques, which render tissue optically transparent and macromolecular permeable, to assess the temporal and spatial correlations of molecular alterations to phenotypic changes during development and progression of oral cancer. With this data, we propose to develop and validate predictive models relating RROMs to malignant transformation.

Public Health Relevance

600,000 patients will be diagnosed with oral cancer worldwide this year; only 40-50% of newly diagnosed patients are expected to survive more than 5 years. Prognosis is poor because oral cancer is often diagnosed at a late stage. Optical properties can be measured at the point-of-care to provide earlier, more reliable diagnosis and prognosis of oral neoplasia.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA185207-02
Application #
8912436
Study Section
Special Emphasis Panel (ZCA1-RPRB-0 (J1))
Program Officer
Tandon, Pushpa
Project Start
2014-09-01
Project End
2018-08-31
Budget Start
2015-09-01
Budget End
2016-08-31
Support Year
2
Fiscal Year
2015
Total Cost
$640,656
Indirect Cost
$113,482
Name
Rice University
Department
Biomedical Engineering
Type
Schools of Engineering
DUNS #
050299031
City
Houston
State
TX
Country
United States
Zip Code
77005
Yang, Eric C; Schwarz, Richard A; Lang, Alexander K et al. (2018) In Vivo Multimodal Optical Imaging: Improved Detection of Oral Dysplasia in Low-Risk Oral Mucosal Lesions. Cancer Prev Res (Phila) 11:465-476
Yang, Eric C; Tan, Melody T; Schwarz, Richard A et al. (2018) Noninvasive diagnostic adjuncts for the evaluation of potentially premalignant oral epithelial lesions: current limitations and future directions. Oral Surg Oral Med Oral Pathol Oral Radiol 125:670-681
Quang, Timothy; Tran, Emily Q; Schwarz, Richard A et al. (2017) Prospective Evaluation of Multimodal Optical Imaging with Automated Image Analysis to Detect Oral Neoplasia In Vivo. Cancer Prev Res (Phila) 10:563-570