Related Experiment Video
Updated: Jan 15, 2026

Intramucosal Inoculation of Squamous Cell Carcinoma Cells in Mice for Tumor Immune Profiling and Treatment Response Assessment
Published on: April 22, 2019
External Validation of Straticyte™, a Quantitative Biomarker-Based Risk Assay in Predicting Oral Cancer
Jason T K Hwang1, Chad Dammling2, Christina McCord3
1Proteocyte Diagnostics Inc., Toronto, ON Canada.
Introduction:
Current management of oral potentially malignant disorders (OPMDs) based on dysplasia grading is controversial. The malignant transformation rate of OPMDs does not correlate well with dysplasia grading, resulting in non-standardized treatment for patients. A quantitative biomarker-based risk score (qBRS; trade name StraticyteTM) was previously developed to address shortcomings related to the current standard of care. A multicenter, retrospective cohort study consisting of biopsied OPMDs was used to validate qBRS for predicting transformation of OPMDs to OSCC.
Materials & Methods:
Three hundred and two cases were immunostained, imaged, and analyzed via qBRS. A binary prognostic risk was determined using a receiver operating characteristic curve optimizing sensitivity and specificity. Kaplan-Meier analysis was used to estimate the cumulative probability of lack of malignant transformation for patients with elevated or normal biomarker-based risk.
Results:
The results demonstrated very high sensitivity (96.2%) and negative predictive value (96.2%) for qBRS. Elevated risk scores had higher predicted probabilities of transformation to cancer, independent of dysplasia grade.
Conclusions:
qBRS can be a useful clinical adjunct tool to dysplasia grading for the assessment of malignant transformation potential, providing a quantitative metric in OPMDs. The addition of qBRS to current histological techniques should improve early detection rates of OSCC, enhancing the effectiveness of treatment.
More Related Videos
06:46Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025