4.6 Article

Development of a sensitive droplet digital PCR according to the HPV infection specificity in Chinese population

Journal

BMC CANCER
Volume 23, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s12885-023-11529-3

Keywords

Human papillomavirus; Infection specificity; Droplet digital PCR; Viral load

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HPV genotypes 16 and 18 are correlated with cervical carcinogenesis, but their prevalence varies according to region, nationality, and environment. This study developed a reliable droplet digital PCR method to detect and quantify HPV genotypes accurately. The method showed high accuracy, sensitivity, and specificity compared to traditional quantitative real-time PCR and supplemented the detection of HPV genotypes in the Chinese population.
HPV16 and 18 are positively correlated with cervical carcinogenesis. However, HPV prevalence tends to vary according to region, nationality, and environment. The most prevalent high-risk (HR) HPV genotypes are HPV16, 52, 58, 56, 18, 33, and 45), while the low-risk (LR) genotypes are HPV6 and 11 in the Chinese population. Importantly, undetectable low-copy HPV DNA could be an important indicator of integration into the human genome and may be a precursor to cancer progression. The HPV viral load changes dramatically, either increasing or decreasing rapidly during carcinogenesis, and traditional quantitative real-time PCR (qPCR) cannot accurately capture this subtle change. Therefore, in this study, a reliable droplet digital PCR (ddPCR) method was developed to simultaneously detect and quantify HPV genotypes. The ddPCR quantitative results showed high accuracy, sensitivity, and specificity compared to qPCR results employing the same clinical specimens and supplemented the ddPCR assay for HPV52/56/58/6 genotypes according to the infection specificity of the Chinese population. In summary, this procedure is valuable for quantifying HPV DNA, especially under conditions of low template copy number in cervical intraepithelial neoplasia (CIN) and/or cervical cancer. Additionally, this method can dynamically observe the prognosis and outcome of HPV infection and thus be used as an effective means for real-time monitoring of tumor load.

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