A Novel NGS-Based Algorithm for Precise HPV Genotyping and Co-infection Detection in QCMD Samples and FFPE Tissues

Accurate genotyping of Human papillomavirus (HPV) is essential for cervical cancer screening, prognostic risk assessment, and epidemiological surveillance. Conventional methods, such as Sanger sequencing and hybridization-based assays, often fail to detect mixed infections, particularly in cases involving DNA from formalin-fixed paraffin-embedded (FFPE) tissues. In this protocol, we present an optimized next-generation sequencing (NGS) based pipeline for comprehensive HPV genotyping. Our workflow includes a curated HPV reference database of 229 HPV genotypes and a proportional read-mapping algorithm. We validated our method using 30 samples from the Quality Control for Molecular Diagnostics (QCMD) proficiency testing panel and were able to fully replicate the expected outcomes-including detecting the defined co-infection with HPV16/18. We then applied our approach to 50 clinical FFPE samples, identifying 44 HPV-positive samples, including a co-infection scenario that traditional diagnostic assays might have missed. This low-cost, open-source NGS-based pipeline improves the sensitivity and accuracy of HPV detection from archival FFPE tissue specimens, cervical screening specimens, and other fresh tissue, and successfully closes the gap between research applications and clinical usage. © 2025 Wiley Periodicals LLC. Basic Protocol 1: DNA isolation Basic Protocol 2: PCR amplification Basic Protocol 3: NGS Basic Protocol 4: Data analysis.