Detection of cancer‐related gene expression profiles in severe cervical neoplasia

• Published in: International journal of cancer 2004-10, Vol.112 (1), p.33-43
• Main Authors: Sopov, Igor, Sörensen, Till, Magbagbeolu, Mandy, Jansen, Lars, Beer, Katrin, Kühne‐Heid, Rosemarie, Kirchmayr, Richard, Schneider, Achim, Dürst, Matthias
• Format: Article
• Language: English
• Subjects: Adult; Biological and medical sciences; Biomarkers, Tumor - metabolism; Carcinoma, Squamous Cell - genetics; Carcinoma, Squamous Cell - metabolism; Carcinoma, Squamous Cell - pathology; cervical cancer; cervical intraepithelial neoplasia; Cervical Intraepithelial Neoplasia - genetics; Cervical Intraepithelial Neoplasia - metabolism; Cervical Intraepithelial Neoplasia - pathology; Female; Female genital diseases; gene expression profile; Gene Expression Profiling; Gene Expression Regulation, Neoplastic; Gynecology. Andrology. Obstetrics; Humans; Medical sciences; microdissection; Middle Aged; Oligonucleotide Array Sequence Analysis; Reverse Transcriptase Polymerase Chain Reaction; RNA, Neoplasm - genetics; RNA, Neoplasm - metabolism; Tumors; Uterine Cervical Neoplasms - genetics; Uterine Cervical Neoplasms - metabolism; Uterine Cervical Neoplasms - pathology
• ISSN: 0020-7136; 1097-0215
• DOI: 10.1002/ijc.20351

The molecular signatures of 20 severe cervical intraepithelial neoplasia (CIN3) cases and 10 cervical squamous cell cancers were determined to define cancer‐related gene expression profiles. RNAs extracted from microdissected tissues were amplified by SMART technology and used as probes for hybridization of commercially available cDNA array filters comprising 1,176 cancer‐related genes. Ninety‐two differentially expressed genes were identified by comparison of pooled cDNA from CIN3 vs. cervical cancer. Heterogeneity in expression of this subset of genes was then analyzed for each biopsy using an algorithm for self‐organizing maps. For several gene clusters, the expression pattern for CIN3 differed significantly from that of cancer. Moreover, hierarchical clustering revealed significant differences in distribution of CIN and cancer. Several CIN cases were more strongly related to cancer, suggesting that gene expression profiling may be useful for subdividing pathologically indistinguishable precancers into different biologic entities. This approach also provides a basis for the identification of putative prognostic markers and for targeted molecular therapy. © 2004 Wiley‐Liss, Inc.