医学
基因分型
病变
基因型
人乳头瘤病毒
鳞状上皮内病变
内科学
宫颈上皮内瘤变
HPV感染
宫颈癌
妇科
胃肠病学
肿瘤科
病理
癌症
基因
化学
生物化学
作者
Yuanming Shen,Sangsang Tang,Yumei Zhou,Qiuxue Zhang,Tingting Chen,Jingnan Li,Yu Wang,Xiaoyun Wan,Weiguo Lü,Junfen Xu
标识
DOI:10.1097/lgt.0000000000000850
摘要
Objective The aim of the study was to investigate the distribution and association between human papillomavirus (HPV) genotypes and integration as well as their correlation with cervical lesions. Methods Two hundred seven patients diagnosed with high-grade vaginal intraepithelial neoplasia (HG-VaIN) were recruited from the Women's Hospital School of Medicine Zhejiang University between 2015 and 2021 and assayed for HPV genotyping. HPV integration sequencing analysis was conducted using tissues from 53 patients with HG-VaIN and 4 patients with invasive vaginal carcinoma (IVC), along with paired cervical lesion specimens. Results A total of 207 patients with HG-VaIN were categorized as having cervical lesions unrelated to HG-VaIN (group A, 71 patients, 34.30%) or cervical lesion-related HG-VaIN (group B, 136 patients, 65.70%). With an average follow-up of 42.19 months, 12 of 153 patients progressed to IVC and were all from group B. HPV16 infection and the presence of cervical lesions were the 2 main factors associated with disease progression, with cervical lesion coexistence being an independent factor. Compared with group A (5/20, 25%), group B (17/33, 51.52%) showed a higher rate of HPV integration, as demonstrated using HPV integration sequencing analysis, with HPV16 being the most integrated genotype (72.73%). The integration analysis of 4 patients with IVC paired with cervical lesion specimens showed that 3 of the 4 pairs exhibited the same HPV infection and integration sites, indicating a high degree of homology in HPV integration between cervical lesions and HG-VaIN-induced IVC. Conclusions Patients with HG-VaIN associated with cervical lesions exhibited a higher risk of malignant transformation, necessitating more proactive treatment approaches.
科研通智能强力驱动
Strongly Powered by AbleSci AI