Histological Severity Risk Factors Identification in Juvenile-Onset Recurrent Respiratory Papillomatosis: How

Charles Lépine1,2, Paul Klein3, Thibault Voron1

  • 1INSERM-U970, PARCC, Université de Paris, Paris, France.

Frontiers in Oncology
|March 25, 2021
PubMed

Insights

Juvenile-onset recurrent respiratory papillomatosis (JoRRP) severity can be predicted using p63 antibody immunostaining. This biomarker shows potential for identifying children at risk for severe JoRRP, aiding in early intervention.

Area of Science:

  • Pediatric Otolaryngology
  • Oncology
  • Digital Pathology

Background:

  • Juvenile-onset recurrent respiratory papillomatosis (JoRRP) presents unpredictably in children, ranging from mild symptoms to aggressive disease requiring extensive medical intervention.
  • Identifying histologic risk factors is crucial for predicting JoRRP severity and tailoring patient management.

Purpose of the Study:

  • To identify histologic severity risk factors in pediatric patients diagnosed with JoRRP.
  • To evaluate the utility of deep learning and machine learning in analyzing digital slides and immunohistochemistry for predicting JoRRP severity.

Main Methods:

  • Retrospective analysis of 48 pediatric patients with JoRRP from two French centers.
  • Hematoxylin and eosin (HE) slide analysis using deep learning to identify morphological patterns.
  • Immunohistochemistry for p53 and p63, quantified using machine learning and deep learning workflows.

Main Results:

  • Deep learning analysis of HE slides did not yield significant results for predicting severity.
  • Immunohistochemistry for p63 showed a significant correlation with JoRRP severity, with higher p63 staining intensity in severe cases (p=0.041 to 0.048 for machine learning, p=0.045 for deep learning).
  • No significant differences in p53 staining were observed between mild and severe JoRRP groups.

Conclusions:

  • p63 immunostaining is a potential biomarker for predicting the severity of Juvenile-onset recurrent respiratory papillomatosis.
  • Automated image analysis, particularly using machine learning and deep learning, can effectively quantify immunohistochemical staining for biomarker assessment in JoRRP.

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