Elisabeth Sivy Nginamau

Background: Oral squamous cell carcinoma (OSCC) is increasing at an alarming rate particularly in low-income countries. This urges for research into noninvasive, user-friendly diagnostic tools that can be used in limited-resource settings. This study aims to test and validate the feasibility of e-nose technology for detecting OSCC in the limited-resource settings of the Sudanese population. Methods: Two e-nose devices (Aeonose™, eNose Company, Zutphen, The Netherlands) were used to collect breath samples from OSCC (n = 49) and control (n = 35) patients. Patients were divided into a training group for building an artificial neural network (ANN) model and a blinded control group for model validation. The Statistical Package for the Social Sciences (SPSS) software was used for the analysis of baseline characteristics and regression. Aethena proprietary software was used for data analysis using artificial neural networks based on patterns of volatile organic compounds. Results: A diagnostic accuracy of 81% was observed, with 88% sensitivity and 71% specificity. Conclusions: This study demonstrates that e-nose is an efficient tool for OSCC detection in limited-resource settings, where it offers a valuable cost-effective strategy to tackle the burden posed by OSCC.

Micro-RNAs (miRs) are emerging as important players in carcinogenesis. Their stromal expression has been less investigated in part due to lack of methods to accurately differentiate between tumor compartments. This study aimed to establish a robust method for dual visualization of miR and protein (pan-cytokeratin) by combining chromogen-based in situ hybridization (ISH) and immunohistochemistry (IHC), and to apply it to investigate stromal expression of miR204 as a putative prognostic biomarker in oral squamous cell carcinoma (OSCC). Four different combinations of methods were tested and ImageJ and Aperio ImageScope were used to quantify miR expression. All four dual ISH-IHC methods tested were comparable to single ISH in terms of positive pixel area percentage or integrated optical density of miRs staining. Based on technical simplicity, one of the methods was chosen for further investigation of miR204 on a cohort of human papilloma virus (HPV)-negative primary OSCC (n = 169). MiR204 stromal expression at tumor front predicted recurrence-free survival (p = 0.032) and overall survival (p = 0.036). Multivariate Cox regression further confirmed it as an independent prognostic biomarker in OSCC. This study provides a methodological platform for integrative biomarker studies based on simultaneous detection and quantification of miRs and/or protein and reveals stromal miR204 as a prognostic biomarker in OSCC.