cDNA Microarray Analysis of Gene Expression Profiles Associated with Cervical Cancer

The molecular pathology of cervical cancers associated with human papillomavirus infection is presently unclear. In an effort to clarify this issue, the gene expression profiles and pathogenic cellular processes of cervical cancer lesions were investigated.

Cervical cancer biopsies were obtained from patients at the Department of Obstetrics and Gynecology, The Catholic University of Korea. The disease status was assigned according to the International Federation of Gynecology and Obstetrics. The tissue samples of 11 patients (invasive cancer stage Ib- IIIa) were investigated by a cDNA microarray of 4, 700 genes, hierarchical clustering and the Gene Ontology (GO). Total RNA from cervical cancer and non-lesional tissues were labeled with Cy5 and Cy3. The HaCaT human epithelial keratinocyte cell line was used as a negative control cell. The stages of invasive cancer were Ib to IIIb. All specimens were obtained by punch-biopsies and frozen in liquid nitrogen until required.

74 genes, showing more than a 2 fold difference in their expressions, were identified in at least 8 of the 11 patients. Of these genes, 33 were up-regulated and 41 were down-regulated. The gene expression profiles were classified into 345 mutually dependent function sets, resulting in 611 cellular processes according to their GO. The GO analysis showed that cervical carcinogenesis underwent complete down-regulation of cell death, protein biosynthesis and nucleic acid metabolism. The genes related to nucleic acid binding and structural molecule activity were also significantly down-regulated. In contrast, significant up-regulation was shown in the skeletal development, immune response and extracellular activity.

These data are suggestive of potentially significant pathogenetic cellular processes, and showed that the down-regulated functional profiling has an important impact on the discovery of pathogenic pathways in cervical carcinogenesis. GO analysis can also overcome the complexity of the expression profiles of the cDNA microarray via a cellular process level approach. Thereby, a valuable prognostic candidate gene, with real relevance to disease-specific pathogenesis, can be found at the cellular process levels.