Spots Global Cancer Trial Database for Identifying Biomarkers for Early Detection of Cancer in Patients With Cervical Dysplasia or Carcinoma in Situ of the Cervix

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Trial Identification

Brief Title: Identifying Biomarkers for Early Detection of Cancer in Patients With Cervical Dysplasia or Carcinoma in Situ of the Cervix

Official Title: Genomics Approach to Id Novel Targets & Markers for Early Detection And Intervention In Cancer (Cervical)

Study ID: NCT00601601

Conditions

Cervical Cancer

Precancerous Condition

Interventions

Study Description

Brief Summary: RATIONALE: Studying the genes expressed in samples of tissue from patients with abnormal cells may help doctors identify biomarkers related to cancer. PURPOSE: This clinical trial is identifying biomarkers for early detection of cancer in women with cervical dysplasia or carcinoma in situ of the cervix.

Detailed Description: OBJECTIVES: Primary * To identify and catalogue genetic alterations and protein changes associated with developmental stages of cervical cancer. * To identify a ranked list of candidate genes that drive the transformation of premalignant lesions to tumors for further study and validation as molecular targets for novel early detection and treatment design. Secondary * To complete genome scans at high density and analysis of gene and protein expression to identify recurrent genetic and protein changes in cancer. * To confirm changes clustered to specific chromosomal regions which harbor tumor suppressors or oncogenes. OUTLINE: Patients undergo biopsy of cervical tissue followed by loop electrocautery excision procedure (LEEP) (removing all of the tissue surrounding and under the area biopsied). RNA, DNA, and protein is extracted from the cells to provide material for the construction of libraries for Serial Analysis of Gene Expression (SAGE analysis); for hybridization against Bacterial Artificial Chromosome Comparative Genome Hybridization arrays (BAC CGH arrays); and for analysis using protein chip arrays and proteomics. Resulting data from coded samples provide gene expression and protein profiles. The coded molecular datasets are linked, analyzed, and compared using a variety of statistical software to identify putative genes, gene alterations, and proteins of interest. Some samples may be banked for future studies.