Specific Detection of Cervical Cancers Using Cytometry-Based Molecular Diagnostic

描述（由申请人提供）：宫颈癌是仅次于乳腺癌的最常见的恶性肿瘤，在全球范围内的妇女的发病率和死亡率。在美国和其他工业化国家，宫颈癌的发病率和死亡率急剧下降，这与宫颈细胞学筛查（巴氏试验）在人口中的广泛应用有关。尽管取得了这一成功，宫颈病变的细胞学诊断仍受到一个持续存在的问题的困扰，即对低级别细胞学异常患者中具有临床意义的高级别病变的特异性低。因此，每年有400多万妇女接受细胞学诊断，需要进一步评估以排除高度异型增生或癌症的可能性。在大多数情况下，进一步的评估不能识别低级别细胞学异常患者的潜在高级别病变。虽然HPV检测可以在一些患者的分诊中发挥重要作用，但它对几种细胞学诊断没有用处。使情况复杂化的是，高危HPV的简单检测并不能预测潜在的高级别病变，因为感染并不表明有临床意义的宫颈病变。该项目的长期目标是应用新兴技术开发具有适当特异性的高通量基于细胞的分析，以识别宫颈粘膜的高级别癌前病变和恶性病变。本项目中使用的方法将采用、测试和验证基于细胞计数的分子诊断方法，以检测假阴性宫颈标本。在前一个资助阶段的幌子下，应用高通量流式细胞术和细胞分选技术检测p16INK4a和Mcm5（宫颈癌生物标志物）的蛋白表达，以识别和捕获宫颈标本中的罕见癌细胞。此外，已经实施了多重HPV基因分型测定来分析在这种方法中分离的稀有细胞。重要的是，工作流程已经使用常见的样品制备与当前的病理学测试协议来实现。本应用中应用的技术和方法将使用集成的工作流程来实施，具有实质性的自动化，以评估进一步翻译的可行性，以满足临床需求并提高全球护理标准。最终目标是建立一种有可能取代基于载玻片的宫颈细胞学检查的主要检测方法，其灵敏度更高，主观性更低，劳动强度更低。 公共卫生相关性：这项拟议的项目将采用新技术，检测异常子宫颈细胞，从以前的巴氏试验的临床样本。我们将使用细胞蛋白质含量的自动分析来分离异常细胞，之后自动DNA分析将确定是否存在致癌的人乳头瘤病毒类型。这些结果将与相同样本的巴氏涂片和活检结果进行比较，以确定我们的测试可以检测出宫颈癌的早期阶段。

DESCRIPTION (provided by applicant): Cervical cancer is second to breast cancer as the most common form of malignancy in both incidence and mortality for women worldwide. The population-wide utilization of screening cervical cytology (Pap tests) has been associated with a dramatic decrease in morbidity and mortality from cervical cancer in the United States and in other industrialized nations. Despite this success, the cytologic diagnosis of cervical lesions is plagued by a persistent problem of low specificity for clinically significant high-grade lesions in patients with low-grade cytologic abnormalities. As a result, over four million women each year receive a cytologic diagnosis that requires further evaluation to rule out the possibility of high-grade dysplasia or cancer. In most cases, further evaluation does not identify underlying high-grade lesions in patients with low-grade cytologic abnormalities. Although HPV testing can play an important role for the triage of some patients, it is not useful for several cytologic diagnoses. Complicating the situation is that simple detection of high risk HPVs does not predict an underlying high grade lesion, since infections do not indicate clinically significant cervical lesions. The long-term goal of this project is to apply emerging technology to develop a high-throughput cell-based analysis with suitable specificity to identify high grade premalignant and malignant lesions of the cervical mucosa. The methods to be used in this project will employ, test and validate the approach of cytometry-based molecular diagnostics to detect false negative cervical specimens. Under the guise of the previous grant phase, an application of protein expression of p16INK4a and Mcm5 (cervical cancer biomarkers) with high- throughput flow cytometry and cell sorting has been used to identify and capture the rare cancerous cells in cervical specimens. Furthermore, a multiplexed HPV genotyping assay has been implemented to analyze the rare cells isolated in this approach. Importantly, the work flow has been implemented using common sample preparation with current pathology testing protocols. The technology and methodology being applied in this application will be implemented using an integrated workflow, with substantial automation, to assess feasibility of further translation to accommodate clinical need and to improve the standard of care worldwide. The ultimate goal is to establish a primary assay with potential to supplant slide based cervical cytology with greater sensitivity, less subjectivity, and less labor intensiveness. PUBLIC HEALTH RELEVANCE: This proposed project will apply new technology, for detection of abnormal cervical cells, to clinical samples from previous Pap tests. We will use automated analysis of protein content of cells to isolate abnormal cells, after which automated DNA analysis will determine whether cancer-causing human papillomavirus types are present. These results will be compared to the Pap smear and biopsy results of the same samples in order to determine how well our test can detect early stages of cervical cancer.