Abstract 4899: Identification of epigenomics biomarkers for early detection and progression of cervical carcinogenesis
Authors: Brebi Priscilla , Ili-Gangas Carmen , Leal-Rojas Pamela , García Patricia , Ostrow Kimberly , Perez Jimena , Guerrero-Preston Rafael , Soudry Ethan , Roa Juan C. , Sidransky David 
Published: February 2011

Introduction: Pap smears and HPV infection tests have been the most widely used tools to detect cytological abnormalities and women's risk of developing cervical cancer. However, they do not distinguish between lesions that will progress to an invasive carcinoma and those that will not. Epigenetic biomarkers may prove to be useful early detection and progression markers for cervical carcinoma.

Objective: To identify epigenetic biomarkers for early detection and monitor progression of premalignant lesions in cervical cancer.

Materials and Methods: A total of 221 samples were analyzed: 25 normal, 66 Low Grade Lesions (LSIL), 91 High Grade Lesions (HSIL) and 39 cervical cancers (CC). The Reverse Line Blot technique was used for viral detection and HPV genotyping. DNA isolated from 12 normal samples and 7 cervical cancers was enriched with Methylated DNA Immunoprecipitation (MeDIP) and hybridized to Nimblegen 385K CpG Islands plus Promoter arrays. Bioinformatics strategies were used for background correction, array normalization and data analysis of differentially methylated genomic regions between tumor and normal tissue. Methylation Specific PCR (MSP) validated promoter methylation frequency in the 221 genotyped samples. Correlation analyses, and Receiver Characteristic Operator Curves (ROC) were used to determine the association between HPV infection, DNA methylation, and cancer status.

Results. Infection by single and multiple HPV subtypes was observed in normal (4%), LSIL (80.3%), HSIL (93.4%) and cervical cancer (92.3%) samples. HPV16 was the most frequent genotype across sample histology: LSIL (45.3%), HSIL (47.1%) and CC (55.6%). Multiple HPV infections were more frequent in cancer samples (31%). Five hypermethylated genes were identified as potential biomarkers after validation by MSP. The methylation frequency for all five genes was higher in tumor, Gene 1 (100%); Gene 2 (98%); Gene 3 (96%); Gene 4 (100%) and Gene 5 (98%); than in normal samples: Gene 1 (12%): Gene 2 (12%); Gene 3 (16%); Gene 4 (40%); and Gene 5 (44%). The methylation status of Gene 2 and Gene 4 showed a progression in methylation frequency from normal samples to invasive carcinoma. The correlation of cancer status with of Gene 1 (0.90) methylation was higher than with HPV infection (0.87), Gene 2 (0.87), Gene 3 (0.81), Gene 4 (0.69) and Gene 5 (0.62) methylation. All correlations were statistically significant at the 95th percentile. The Receiver Characteristic Operator Curves (ROC) for HPV and individual genes revealed Area Under the Curve values of: HPV (0.94), Gene 1 (0.94), Gene 2 (0.93), Gene 3 (0.89), Gene 4 (0.80), Gene 5 (0.77).

Conclusions: A panel combining HPV infection status and methylation in one of the five candidate genes identified had a higher predictive value than HPV infection or genotype and methylation status of any one candidate gene. Validation of these markers in a case-control cohort is warranted.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4899.