PLoS ONE (Jan 2023)

CD44-SNA1 integrated cytopathology for delineation of high grade dysplastic and neoplastic oral lesions.

  • Sumsum P Sunny,
  • Ravindra D R,
  • Aditi Hariharan,
  • Nirza Mukhia,
  • Shubha Gurudath,
  • Keerthi G,
  • Subhashini Raghavan,
  • Trupti Kolur,
  • Vivek Shetty,
  • Vidya Bushan R,
  • Avadhesha Surolia,
  • Satyajit T,
  • Pavithra Chandrashekhar,
  • Nisheena R,
  • Hardik J Pandya,
  • Vijay Pillai,
  • Praveen Birur N,
  • Moni A Kuriakose,
  • Amritha Suresh

DOI
https://doi.org/10.1371/journal.pone.0291972
Journal volume & issue
Vol. 18, no. 9
p. e0291972

Abstract

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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.