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.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Exploratory/Developmental Grants Phase II (R33)
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Special Emphasis Panel (ZCA1-SRLB-Q (M1))
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Patriotis, Christos F
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Purdue University
Other Basic Sciences
Schools of Veterinary Medicine
West Lafayette
United States
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Escobar-Hoyos, Luisa F; Yang, Jie; Zhu, Jiawen et al. (2014) Keratin 17 in premalignant and malignant squamous lesions of the cervix: proteomic discovery and immunohistochemical validation as a diagnostic and prognostic biomarker. Mod Pathol 27:621-30
Robinson, J Paul; Patsekin, Valery; Holdman, Cheryl et al. (2013) High-throughput secondary screening at the single-cell level. J Lab Autom 18:85-98
Robinson, J Paul; Rajwa, Bartek; Patsekin, Valery et al. (2012) Computational analysis of high-throughput flow cytometry data. Expert Opin Drug Discov 7:679-93