Immunoexpression of oral brush biopsy enhances the accuracy of diagnosis for oral lichen planus and lichenoid lesions

Abstract

Background: This study assessed the efficacy of using oral liquid-based brush cytology (OLBC) coupled with immunostained cytology-derived cell-blocks, quantified using machine-learning, in the diagnosis of oral lichen planus (OLP).Methods: Eighty-two patients diagnosed clinically with either OLP or oral lichenoid lesion (OLL) were included. OLBC samples were obtained from all patients before undergoing surgical biopsy. Liquid-based cytology slides and cell-blocks were prepared and assessed by cytomorphology and immunocytochemistry for four antibodies (Ki-67, BAX, NF-κB-p65, and AMACR). For comparison purposes, a sub-group of 31 matched surgical biopsy samples were selected randomly and assessed by immunohistochemistry. Patients were categorized according to their definitive diagnoses into OLP, OLL, and clinically lichenoid, but histopathologically dysplastic lesions (OEDL). Machine-learning was utilized to provide automated quantification of positively stained protein expression.Results: Cytomorphological assessment was associated with an accuracy of 77.27% in the distinction between OLP/OLL and OEDL. A strong concordance of 92.5% (κ = 0.84) of immunostaining patterns was evident between cell-blocks and tissue sections using machine-learning. A diagnostic index using a Ki-67-based model was 100% accurate in detecting lichenoid cases with epithelial dysplasia. A BAX-based model demonstrated an accuracy of 92.16%. The accuracy of cytomorphological assessment was greatly improved when it was combined with BAX immunoreactivity (95%).Conclusions: Cell-blocks prepared from OLBC are reliable and minimally-invasive alternatives to surgical biopsies to diagnose OLLs with epithelial dysplasia when combined with Ki-67 immunostaining. Machine-learning has a promising role in the automated quantification of immunostained protein expression.

Automated immunohistochemical quantification of hypoxia biomarkers shows correlation with dysplastic epithelial changes

“…Therefore, our study employed machine learning for objective and reproducible assessment of IHC data. This approach has been validated previously while defining the ROI as the total epithelial thickness of the WSI minimising human intervention 19 …”

“…This approach has been validated previously while defining the ROI as the total epithelial thickness of the WSI minimising human intervention. 19 The angiogenic switch is a discrete step that can commence at different stages during the carcinogenesis process. 14 Currently, however, there is no reliable tool to detect the occurrence of the angiogenic switch.…”

“…For five antibodies (Glut‐1, Glut‐3, VEGF, HIF‐1α, and STAT3), the region of interest (ROI) was defined as the total epithelial thickness of the entire WSI excluding the keratin layer of not less than 250 000 μm 2 19 …”

“…For five antibodies (Glut-1, Glut-3, VEGF, HIF-1α, and STAT3), the region of interest (ROI) was defined as the total epithelial thickness of the entire WSI excluding the keratin layer of not less than 250 000 μm 2 . 19 A licenced multiple-module image analysis platform (QuantCenter ® , Version 2.3, 3DHistech, Budapest, Hungary) was used for immunostain quantification through integrated CellQuant ® algorithms. These algorithms were customised using a set of 10 slides for each antibody to develop a customised automated immunostaining scenario.…”

Salivary-Based Cell-Free Mitochondrial DNA Level Is an Independent Prognostic Biomarker for Patients with Head and Neck Squamous Cell Carcinoma

“…Recent research in molecular pathology has identified thousands of biomarkers related to HNSCC. While promising outcomes have been reported when employing molecular biomarkers to detect and diagnose oral cancers and potentially malignant oral disorders [ 11 , 12 ], the reliability of prognostic biomarkers in HNSCC is uncertain due to the unsatisfactory quality levels of relevant studies and the heterogeneity of reporting [ 13 ]. Liquid biopsies, however, are reliable sources of certain body-fluid-based biomarkers, such as cell-free nuclear DNA (cf-nDNA) and cell-free mitochondrial DNA (cf-mtDNA) [ 14 ].…”