Junyangdikul Pairoj, Tanchotsrinon Watcharaporn, Chansaenroj Jira, Nilyaimit Pornjarim, Lursinsap Chidchanok, Poovorawan Yong
Department of Pathology, Samitivej Srinakharin Hospital, Bangkok Hospital Group Thailand, Bangkok, Thailand.
Asian Pac J Cancer Prev. 2013;14(2):903-7. doi: 10.7314/apjcp.2013.14.2.903.
Primary screening by HPV DNA testing is an effective method for reducing cervical cancer and has proven more sensitive than cytology. To advance this approach, many molecular methods have been developed. Hybrid capture 2 provides semi-quantitative results in ratios of relative light units and positive cutoff values (RLU/ PC). Twenty-five thousand and five patients were included in this study to analyze the correlation between the ratio of RLU/PC and stage of cervical dysplasia. The results show that the RLU/PC ratios ranged from 0-3500 while almost normal cases, ASC-US and ASC-H, had values below 200. Of those samples negative for cytology markers, 94.6% were normal and their RLU/PC ratios were less than 4. With an RLU/PC ratio greater than 4 and less than or equal to 300, the percentages in all age groups were normal 53.6%, LSIL 20.2%, ASC-US 17.2%, HSIL 6.13%, ASC-H 2.72%, and AGC 0.11%, respectively. In contrast, 64.0% of samples with a RLU/ PC ratio greater than 300 and less than or equal to 3500 were LSIL. These results should contribute to cost effective cervical cancer management strategies. Further studies of associations with particular HPV genotypes would be useful to predict the risk of progression to cancer.
通过人乳头瘤病毒(HPV)DNA检测进行初筛是降低宫颈癌发病率的有效方法,且已被证明比细胞学检查更具敏感性。为推进这一方法,已开发出多种分子方法。杂交捕获2法以相对光单位与阳性临界值之比(RLU/PC)提供半定量结果。本研究纳入了25005例患者,以分析RLU/PC比值与宫颈发育异常分期之间的相关性。结果显示,RLU/PC比值范围为0至3500,而几乎所有正常病例、非典型鳞状细胞不能明确意义(ASC-US)和非典型鳞状细胞不排除高度鳞状上皮内病变(ASC-H)的RLU/PC值均低于200。在细胞学标志物为阴性的样本中,94.6%为正常样本,其RLU/PC比值小于4。当RLU/PC比值大于4且小于或等于300时,各年龄组中正常样本的比例为53.6%,低度鳞状上皮内病变(LSIL)为20.2%,ASC-US为17.2%,高度鳞状上皮内病变(HSIL)为6.13%,ASC-H为2.72%,非典型腺细胞(AGC)为0.11%。相比之下,RLU/PC比值大于300且小于或等于3500的样本中,64.0%为LSIL。这些结果应有助于制定具有成本效益的宫颈癌管理策略。进一步研究与特定HPV基因型的关联,对于预测癌症进展风险将是有用的。