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Integrating Molecular Diagnostics into Cervical Cancer Screening: A Workflow Using FFPE Tissue Samples.

Serena Varesano1, Giulia Ciccarese2, Paola Parente3

  • 1Hygiene Unit, IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi 10, 16132 Genoa, Italy.

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|September 29, 2025
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Summary
This summary is machine-generated.

Integrating molecular human papillomavirus (HPV) testing with FFPE histology improves cervical cancer screening accuracy. This method enhances risk stratification and reduces overdiagnosis by detecting HPV presence and viral load in cervical specimens.

Keywords:
HPV from formalin-fixed paraffin-embedded blocks (FFPE)HPV genotypingHPV screeningItalycervical cancerhuman papillomavirusmolecular diagnosticsviral load assessmentworkflow

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Area of Science:

  • Gynecology
  • Oncology
  • Molecular Diagnostics

Background:

  • Cervical cancer screening is vital for early detection of high-grade lesions.
  • Traditional methods struggle to distinguish transient HPV infections from progressive ones.
  • There is a need for improved diagnostic precision in cervical cancer screening.

Purpose of the Study:

  • To assess the feasibility of integrating molecular HPV testing into histopathological workflows.
  • To improve diagnostic precision in cervical cancer screening using FFPE samples.
  • To evaluate the utility of HPV genotyping and viral load quantification.

Main Methods:

  • Retrospective analysis of 55 FFPE cervical specimens.
  • Automated DNA extraction and real-time PCR-based HPV genotyping (Seegene Anyplex II HPV28 assay).
  • Correlation of molecular findings with histopathological diagnoses.

Main Results:

  • HPV DNA detected in 56.4% of samples, with 21 genotypes identified.
  • High viral loads correlated significantly with high-grade cervical lesions.
  • Molecular testing reduced potential overdiagnosis in HPV-negative, morphologically suspicious lesions.

Conclusions:

  • An automated molecular workflow for FFPE samples enhances cervical cancer screening.
  • Integration of HPV viral load and genotyping improves risk stratification and patient management.
  • The method shows potential for broader implementation and validation in multicenter settings.