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Biomarker Expression in Multifocal Vulvar High-Grade Squamous Intraepithelial Lesions
Nikki B Thuijs1, Willemijn A M Schonck1, Linde L J Klaver1
1Department of Pathology, Cancer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands.
Cancers
|November 27, 2021
Summary
Multifocal high-grade squamous intraepithelial lesions (HSIL) of the vulva show biomarker heterogeneity. This exploratory study reveals variations in HPV genotype and DNA methylation between lesions, suggesting potential for refined diagnostics.
Area of Science:
- Gynecologic Oncology
- Molecular Pathology
- Virology
Background:
- Multifocal high-grade squamous intraepithelial lesion (HSIL) of the vulva is common in patients with high-risk human papillomavirus (HPV).
- Understanding biomarker expression in these multifocal lesions is crucial for accurate diagnosis and prognosis.
Purpose of the Study:
- To investigate the biomarker expression profiles in multifocal HSIL of the vulva.
- To explore potential heterogeneity in HPV genotype, p16INK4a, Ki-67, and DNA methylation across multiple lesions within individual patients.
Main Methods:
- Analysis of 27 lesions from 12 patients with HPV-positive multifocal HSIL.
- Testing for HPV genotype, p16INK4a and Ki-67 expression, and DNA methylation of six genes.
- Comparison of biomarker profiles within and between lesions from the same patient.
Main Results:
- HPV16 was the predominant genotype (77.8%).
- HPV genotype differed between lesions in 16.4% of patients.
- While p16INK4a staining was mostly diffuse, significant heterogeneity in DNA methylation profiles was observed between lesions within patients and across patients.
Conclusions:
- This study is the first to demonstrate significant heterogeneity of individual lesions in multifocal HSIL of the vulva.
- Biomarker profiles, particularly DNA methylation, show variability that may impact prognostic and predictive diagnostics.
- Further prospective, longitudinal studies are warranted to explore biomarker profiles for improved patient management.
