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<p>Oral mucosal abnormalities considered to have malignant potential may involve a large area of mucosa. Standard care histopathological investigation is invasive, limited to site selection and subject to variation in assessment between pathologists. A quantitative, minimally invasive, rapidly collected, oral mucosal site-specific assessment will assist in decision making and increase diagnostic precision. This study aimed to validate a workflow to analyse oral scrape derived cancer-associated microRNA analysis for mucosal site-specific assessment as a surrogate biomarker to histopathological diagnosis. Forty-one oral scrapes were collected from 33 patients undergoing investigation at the Royal Dental Hospital of Melbourne before mucosal biopsy. RNA from oral scrapes was used to investigate ten cancer-associated microRNAs. An algorithm for categorical high or low-risk based on histopathological diagnosis was developed. The novel risk stratification algorithm utilised two microRNAs and categorised all cases of carcinoma and severe dysplasia as high-risk and accurately distinguished all non-potentially malignant disorders as low-risk lesions. This study provides proof-of-concept that oral scrapes can be predictably collected in a clinical workflow to assess the expression of cancer-associated microRNA specific to an oral mucosal site with minimal invasiveness.</p>

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Oral mucosal scrapes capture cancer associated microRNA expression consistent with histopathology

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月25日

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  • Nadia Kaunein,
  • Michael McCullough,
  • Catherine Butler,
  • Nirav Bhatia,
  • Ivy Tan,
  • Caroline Moore,
  • Christopher Angel,
  • Tami Yap

摘要

Oral mucosal abnormalities considered to have malignant potential may involve a large area of mucosa. Standard care histopathological investigation is invasive, limited to site selection and subject to variation in assessment between pathologists. A quantitative, minimally invasive, rapidly collected, oral mucosal site-specific assessment will assist in decision making and increase diagnostic precision. This study aimed to validate a workflow to analyse oral scrape derived cancer-associated microRNA analysis for mucosal site-specific assessment as a surrogate biomarker to histopathological diagnosis. Forty-one oral scrapes were collected from 33 patients undergoing investigation at the Royal Dental Hospital of Melbourne before mucosal biopsy. RNA from oral scrapes was used to investigate ten cancer-associated microRNAs. An algorithm for categorical high or low-risk based on histopathological diagnosis was developed. The novel risk stratification algorithm utilised two microRNAs and categorised all cases of carcinoma and severe dysplasia as high-risk and accurately distinguished all non-potentially malignant disorders as low-risk lesions. This study provides proof-of-concept that oral scrapes can be predictably collected in a clinical workflow to assess the expression of cancer-associated microRNA specific to an oral mucosal site with minimal invasiveness.