Genome-wide analysis of gene expression in Normal Cervical mucosa, Cervical intraepithelial neoplasia and Cervical squamous cell carcinoma

Analysis of various of up-regulated and down-regulated genes in Normal Cervical mucosa, Cervical intraepithelial neoplasia and Cervical squamous cell carcinoma. The report provides a data analysis methodology for identification of co-expressed gene patterns, as emerging clusters, in global transcriptome of cervical mucosal pre-malignant and malignant conditions in comparison to their normal counterparts. Microarray based study of global gene expression is often used to extract molecular signatures underlying cancer progression. Such endeavors endorse self organizing map, a type of artificial neural network to analyze high dimensional pre-processed transcriptome data to segregate hotspot genes in component plane for disease subtypes. This report provides a data analysis methodology for identification of coexpressed gene patterns, as emerging clusters, in global transcriptome of oral and cervical mucosal premalignant and malignant conditions in comparison to their normal counterparts. Four exclusive cluster patterns, each involving 100 − 300 genes, were identified from component planes for oral study groups. Gene expression associated with each pattern belonged to 32 biological processes. Analysis on cervical biopsies, where cancer was compared to cervical interepithelial neoplasia and normal counterpart, it revealed three non-overlapping patterns for each condition. In cervical interepithelial neoplasia an intermediate pattern with nine different dominant functional processes was identified, whereas, in cervical squamous cell carcinoma pattern showed dominance for seven different functions. This analysis demonstrated utility of self organizing map to capture dominant enriched patterns as visual plots and revealed six common biological processes like transcription and RNA processing, cytoskeleton reorganization, angiogenesis, immunity, neuron signalling, and connective tissue remodelling in the pathogenesis of oral and cervical cancers. In fact it could provide an intuitive understanding of molecular course in carcinogenesis and may contribute for combinatorial biomarker discovery. Cervical cancer is among top ten cancers worldwide with mortality rate of 52 % . It goes through a series of pre-malignant stages - Cervical Intraepithelial Neoplasia CIN 1, 2 and 3. However, some CIN2 lesions may develop soon after HPV infection, suggesting that there could be alternate pathways involved. Incisional biopsies from Cervical interepithelial neoplasia (CIN) and Cervical squamous cell carcinoma (OSCC) were collected. All the collected biopsies were divided into two and one half was processed for the purpose of light microscopy evaluation. After histopathological confirmation of disease condition by onco-pathologist, the other half of the tissue was used for microarray analysis. In the inclusion of histopathologically normal cervical biopsies were done from patients undergoing hysterectomy due to prolapsed uterus or uterine polyp or fibroid. The aim of the study is to investigate the differential transcrptomics modulations that are responsible for the transition of normal cervical mucosa to CIN and later its malignant transformation to cancer.