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PloS one · 2012

Development of a bead-based multiplex genotyping method for diagnostic characterization of HPV infection.

СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Chung Mee Young, Kim Yong-Wan, Bae Su Mi, Kwon Eun Hye, Chaturvedi Pankaj Kumar, Battogtokh Gantumur, Ahn Woong Shick

Аннотация

The accurate genotyping of human papillomavirus (HPV) is clinically important because the oncogenic potential of HPV is dependent on specific genotypes. Here, we described the development of a bead-based multiplex HPV genotyping (MPG) method which is able to detect 20 types of HPV (15 high-risk HPV types 16, 18, 31, 33, 35, 39, 45, 51, 52, 53, 56, 58, 59, 66, 68 and 5 low-risk HPV types 6, 11, 40, 55, 70) and evaluated its accuracy with sequencing. A total of 890 clinical samples were studied. Among these samples, 484 were HPV positive and 406 were HPV negative by consensus primer (PGMY09/11) directed PCR. The genotyping of 484 HPV positive samples was carried out by the bead-based MPG method. The accuracy was 93.5% (95% CI, 91.0-96.0), 80.1% (95% CI, 72.3-87.9) for single and multiple infections, respectively, while a complete type mismatch was observed only in one sample. The MPG method indiscriminately detected dysplasia of several cytological grades including 71.8% (95% CI, 61.5-82.3) of ASCUS (atypical squamous cells of undetermined significance) and more specific for high grade lesions. For women with HSIL (high grade squamous intraepithelial lesion) and SCC diagnosis, 32 women showed a PPV (positive predictive value) of 77.3% (95% CI, 64.8-89.8). Among women >40 years of age, 22 women with histological cervical cancer lesions showed a PPV of 88% (95% CI, 75.3-100). Of the highest risk HPV types including HPV-16, 18 and 31 positive women of the same age groups, 34 women with histological cervical cancer lesions showed a PPV of 77.3% (95% CI, 65.0-89.6). Taken together, the bead-based MPG method could successfully detect high-grade lesions and high-risk HPV types with a high degree of accuracy in clinical samples.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты