'Cytology-on-a-chip' based sensors for monitoring of potentially malignant oral lesions.

UNLABELLED: Despite significant advances in surgical procedures and treatment, long-term prognosis for patients with oral cancer remains poor, with survival rates among the lowest of major cancers. Better methods are desperately needed to identify potential malignancies early when treatments are more effective. OBJECTIVE: To develop robust classification models from cytology-on-a-chip measurements that mirror diagnostic performance of gold standard approach involving tissue biopsy. MATERIALS AND METHODS: Measurements were recorded from 714 prospectively recruited patients with suspicious lesions across 6 diagnostic categories (each confirmed by tissue biopsy -histopathology) using a powerful new 'cytology-on-a-chip' approach capable of executing high content analysis at a single cell level. Over 200 cellular features related to biomarker expression, nuclear parameters and cellular morphology were recorded per cell. By cataloging an average of 2000 cells per patient, these efforts resulted in nearly 13 million indexed objects. RESULTS: Binary "low-risk"/"high-risk" models yielded AUC values of 0.88 and 0.84 for training and validation models, respectively, with an accompanying difference in sensitivity+specificity of 6.2%. In terms of accuracy, this model accurately predicted the correct diagnosis approximately 70% of the time, compared to the 69% initial agreement rate of the pool of expert pathologists. Key parameters identified in these models included cell circularity, Ki67 and EGFR expression, nuclear-cytoplasmic ratio, nuclear area, and cell area. CONCLUSIONS: This chip-based approach yields objective data that can be leveraged for diagnosis and management of patients with PMOL as well as uncovering new molecular-level insights behind cytological differences across the OED spectrum.

Application of programmable bio-nano-chip system for the quantitative detection of drugs of abuse in oral fluids.

OBJECTIVE: There is currently a gap in on-site drug of abuse monitoring. Current detection methods involve invasive sampling of blood and urine specimens, or collection of oral fluid, followed by qualitative screening tests using immunochromatographic cartridges. While remote laboratories then may provide confirmation and quantitative assessment of a presumptive positive, this instrumentation is expensive and decoupled from the initial sampling making the current drug-screening program inefficient and costly. The authors applied a noninvasive oral fluid sampling approach integrated with the in-development chip-based Programmable bio-nano-chip (p-BNC) platform for the detection of drugs of abuse. METHOD: The p-BNC assay methodology was applied for the detection of tetrahydrocannabinol, morphine, amphetamine, methamphetamine, cocaine, methadone and benzodiazepines, initially using spiked buffered samples and, ultimately, using oral fluid specimen collected from consented volunteers. RESULTS: Rapid (∼10min), sensitive detection (∼ng/mL) and quantitation of 12 drugs of abuse was demonstrated on the p-BNC platform. Furthermore, the system provided visibility to time-course of select drug and metabolite profiles in oral fluids; for the drug cocaine, three regions of slope were observed that, when combined with concentration measurements from this and prior impairment studies, information about cocaine-induced impairment may be revealed. CONCLUSIONS: This chip-based p-BNC detection modality has significant potential to be used in the future by law enforcement officers for roadside drug testing and to serve a variety of other settings, including outpatient and inpatient drug rehabilitation centers, emergency rooms, prisons, schools, and in the workplace.