Sunny, SP and Ravindra, DR and Hariharan, A and Mukhia, N and Gurudath, S and Keerthi, G and Raghavan, S and Kolur, T and Shetty, V and Vidya Bushan, R and Surolia, A and Satyajit, T and Chandrashekhar, P and Nisheena, R and Pandya, HJ and Pillai, V and Praveen Birur, N and Kuriakose, MA and Suresh, A (2023) CD44-SNA1 integrated cytopathology for delineation of high grade dysplastic and neoplastic oral lesions. In: PLoS ONE, 18 (9 Sept).
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Abstract
The high prevalence of oral potentially-malignant disorders exhibits diverse severity and risk of malignant transformation, which mandates a Point-of-Care diagnostic tool. Low patient compliance for biopsies underscores the need for minimally-invasive diagnosis. Oral cytology, an apt method, is not clinically applicable due to a lack of definitive diagnostic criteria and subjective interpretation. The primary objective of this study was to identify and evaluate the efficacy of biomarkers for cytology-based delineation of high-risk oral lesions. A comprehensive systematic review and meta-analysis of biomarkers recognized a panel of markers (n: 10) delineating dysplastic oral lesions. In this observational cross sectional study, immunohistochemical validation (n: 131) identified a four-marker panel, CD44, Cyclin D1, SNA-1, and MAA, with the best sensitivity (>75; AUC>0.75) in delineating benign, hyperplasia, and mild-dysplasia (Low Risk Lesions; LRL) from moderate-severe dysplasia (High Grade Dysplasia: HGD) along with cancer. Independent validation by cytology (n: 133) showed that expression of SNA-1 and CD44 significantly delineate HGD and cancer with high sensitivity (>83). Multiplex validation in another cohort (n: 138), integrated with a machine learning model incorporating clinical parameters, further improved the sensitivity and specificity (>88). Additionally, image automation with SNA-1 profiled data set also provided a high sensitivity (sensitivity: 86). In the present study, cytology with a two-marker panel, detecting aberrant glycosylation and a glycoprotein, provided efficient risk stratification of oral lesions. Our study indicated that use of a two-biomarker panel (CD44/SNA-1) integrated with clinical parameters or SNA-1 with automated image analysis (Sensitivity >85) or multiplexed two-marker panel analysis (Sensitivity: >90) provided efficient risk stratification of oral lesions, indicating the significance of biomarker-integrated cytopathology in the development of a Point-of-care assay. © 2023 Sunny et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
| Item Type: | Journal Article |
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| Publication: | PLoS ONE |
| Publisher: | Public Library of Science |
| Additional Information: | The copyright for this article belongs to the Authors. |
| Keywords: | biological marker; glycoprotein; Hermes antigen; hydrocortisone; transcription factor Sox2; CD44 protein, human; hyaluronic acid binding protein, alternative RNA splicing; area under the curve; Article; artificial intelligence; cancer grading; cell differentiation; comparative effectiveness; convolutional neural network; cytopathology; drug efficacy; dysplasia; female; fluorescence in situ hybridization; glycosylation; human; image analysis; immunohistochemistry; logistic regression analysis; machine learning; male; malignant transformation; mouth lesion; patient compliance; pluripotent stem cell; predictive value; protein expression; proteomics; random forest; receiver operating characteristic; risk assessment; sensitivity analysis; sensitivity and specificity; syndrome delineation; systematic review (topic); automation; bioassay; biopsy; hyperplasia; meta analysis; observational study, Automation; Biological Assay; Biopsy; Glycosylation; Humans; Hyaluronan Receptors; Hyperplasia; Observational Studies as Topic |
| Department/Centre: | Division of Biological Sciences > Molecular Biophysics Unit Division of Electrical Sciences > Electronic Systems Engineering (Formerly Centre for Electronic Design & Technology) |
| Date Deposited: | 03 Dec 2023 06:10 |
| Last Modified: | 03 Dec 2023 06:10 |
| URI: | https://eprints.iisc.ac.in/id/eprint/83441 |
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