For the past twenty years, large epidemiologic natural history studies have played a crucial role in achieving our current understanding of cervical neoplasia. We now know that human papillomavirus (HPV) infection is necessary but not sufficient cause of cervical cancer. Cervical pathogenesis evolves as follows: normal 'yields' oncogenic HPV infection 'yields' precancer 'yields' invasive cancer. The majority of women with oncogenic HPV infections will not develop cancer, and most HPV infections, even those with associated cellular changes, regress in 1-2 years, probably eradicated or controlled by cellular immune response. Morevoer, while invasive cancer and precancer are histologically well-defined, the histological classification of low-grade lesions, now better defined as HPV infection, is very heterogeneous and poorly reproducible. Identifying women at highest risk for cancer prior to neoplastic progression is therefore a challenge. At present, we are unable to predict with any accuracy which HPV infections will progress and which are among the majority that regress. Currently, cytologic, histologic, and to some extent, HPV DNA assays are the basis for triage, treatment, and follow-up. While this approach has permitted successful cervical cancer prevention efforts, millions of women are diagnosed each year with HPV infections, and because of the inability to distinguish those who will progress from those who will regress, many women are over-treated as a result. It is therefore of etiologic interest and of public health benefit to develop a method for identifying the HPV-infected women at risk for progressing to precancer and invasion. To develop an accurate and reproducible division of precursor lesions (HPV infection and precancer) will require gaining knowledge about the molecular distinctions at each progressive disease state. Our goal is to therefore comprehensively assess biomarkers of risk for progressive cervical neoplasia, and thus develop a new set of biomarkers that can distinguish those at highest risk of cervical cancer from those with benign infection. Specifically, we will initially implement a cross-sectional study to develop a comprehensive list of potential risk biomarkers by examining cervical tissues of women with normal, HPV infection, precancer, and cancer. They will measure gene expression profiles to gain an accurate and comprehensive in vivo picture of cervical neoplasia carcinogenesis. We propose to then validate the most promising identified candidate biomarkers in a prospective design by assessing their predictive values for key outcomes related to progression (HPV persistence, diagnosis of precancer) or non-progression (HPV clearance).