Comparative analysis of different PCR-based strategies for HPV detection and genotyping from cervical samples.

BACKGROUND: Human papillomavirus (HPV) is the main cause of cervical cancer. Polymerase chain reaction (PCR)-based techniques are associated with accurate results with respect to HPV detection and genotyping, being able to identify viral DNA at low levels. However, differences in primer design influence their sensibility and specificity, depending on the HPV type assessed. OBJECTIVE: The aim of the study was to comparatively evaluate the effectiveness of three different PCR-based strategies for HPV detection and genotyping from cervical samples. STUDY DESIGN: The procedures were based on different primer design strategies, using MY09/MY11, EntroA, and type specific multiplex PCR primers. RESULTS: Out of 411 samples of cervical scrapings, 45 (10.9%), 50 (12.2%), and 117 (28.5%) were positive for MY09/MY11, EntroA, and multiplex PCR, respectively. For MY09/MY11 positive samples, 36 were negative for EntroA and 23 for multiplex PCR. For EntroA positive samples, 40 were negative for MY09/MY11 and 26 for multiplex PCR. For multiplex PCR positive samples, 96 were negative for MY09/MY11 and 94 for EntroA. MY09/MY11 identified 12 different HPV types, EntroA detected eight types and multiplex PCR detected 11 HPV types. EntroA primers were able to detect HPV in more samples than MY09/MY11, while multiplex PCR, despite the limited targeted HPV types, presented higher sensibility than the other methods. CONCLUSIONS: The three methods presented different advantages and disadvantages, and the present study reinforces the need to use more than one molecular strategy for HPV detection and genotyping, and the development of novel methods which could overcome the limitations of the existing tests.

Application of an entropy-based computational strategy to identify genomic markers for molecular detection and typing of human papillomavirus.

Human papillomavirus (HPV) is a diverse group of double-stranded DNA viruses that present high tropism for the epithelium and infect keratinocytes. Currently, over 200 viral types have been identified, and almost 40 types preferentially infect the epithelial cells of the genital tract. Infections caused by HPV are the most prevalent viral infections that are sexually transmitted in the world. Given how HPV infection is one of the key factors in the development of cervical cancer, we need to develop more effective diagnostic methods to correctly diagnose patients. The significance of our research is that we have developed and applied a novel computational approach based on entropy to identify phylogenetically informative genomic regions that could be used as markers for the detection and typing of HPV. We have demonstrated that our strategy is capable of finding phylogenetically informative L1 regions to design a primer set that can be used to accurately detect and genotype HPV isolates.