Genome wide expression analysis in HPV16 Cervical Cancer: identification of altered metabolic pathways

<p>Abstract</p> <p>Background</p> <p>Cervical carcinoma (CC) is a leading cause of death among women worldwide. Human papilloma virus (HPV) is a major etiological factor in CC and HPV 16 is the more frequent viral type present. Our aim was to characterize metabolic pathways altered in HPV 16 tumor samples by means of transcriptome wide analysis and bioinformatics tools for visualizing expression data in the context of KEGG biological pathways.</p> <p>Results</p> <p>We found 2,067 genes significantly up or down-modulated (at least 2-fold) in tumor clinical samples compared to normal tissues, representing ~3.7% of analyzed genes. Cervical carcinoma was associated with an important up-regulation of Wnt signaling pathway, which was validated by in situ hybridization in clinical samples. Other up-regulated pathways were those of calcium signaling and MAPK signaling, as well as cell cycle-related genes. There was down-regulation of focal adhesion, TGF-β signaling, among other metabolic pathways.</p> <p>Conclusion</p> <p>This analysis of HPV 16 tumors transcriptome could be useful for the identification of genes and molecular pathways involved in the pathogenesis of cervical carcinoma. Understanding the possible role of these proteins in the pathogenesis of CC deserves further studies.</p

Characterization of the global profile of genes expressed in cervical epithelium by Serial Analysis of Gene Expression (SAGE)

BACKGROUND: Serial Analysis of Gene Expression (SAGE) is a new technique that allows a detailed and profound quantitative and qualitative knowledge of gene expression profile, without previous knowledge of sequence of analyzed genes. We carried out a modification of SAGE methodology (microSAGE), useful for the analysis of limited quantities of tissue samples, on normal human cervical tissue obtained from a donor without histopathological lesions. Cervical epithelium is constituted mainly by cervical keratinocytes which are the targets of human papilloma virus (HPV), where persistent HPV infection of cervical epithelium is associated with an increase risk for developing cervical carcinomas (CC). RESULTS: We report here a transcriptome analysis of cervical tissue by SAGE, derived from 30,418 sequenced tags that provide a wealth of information about the gene products involved in normal cervical epithelium physiology, as well as genes not previously found in uterine cervix tissue involved in the process of epidermal differentiation. CONCLUSION: This first comprehensive and profound analysis of uterine cervix transcriptome, should be useful for the identification of genes involved in normal cervix uterine function, and candidate genes associated with cervical carcinoma

Microarray comparative genomic hybridization detection of chromosomal imbalances in uterine cervix carcinoma

BACKGROUND: Chromosomal Comparative Genomic Hybridization (CGH) has been applied to all stages of cervical carcinoma progression, defining a specific pattern of chromosomal imbalances in this tumor. However, given its limited spatial resolution, chromosomal CGH has offered only general information regarding the possible genetic targets of DNA copy number changes. METHODS: In order to further define specific DNA copy number changes in cervical cancer, we analyzed 20 cervical samples (3 pre-malignant lesions, 10 invasive tumors, and 7 cell lines), using the GenoSensor microarray CGH system to define particular genetic targets that suffer copy number changes. RESULTS: The most common DNA gains detected by array CGH in the invasive samples were located at the RBP1-RBP2 (3q21-q22) genes, the sub-telomeric clone C84C11/T3 (5ptel), D5S23 (5p15.2) and the DAB2 gene (5p13) in 58.8% of the samples. The most common losses were found at the FHIT gene (3p14.2) in 47% of the samples, followed by deletions at D8S504 (8p23.3), CTDP1-SHGC- 145820 (18qtel), KIT (4q11-q12), D1S427-FAF1 (1p32.3), D9S325 (9qtel), EIF4E (eukaryotic translation initiation factor 4E, 4q24), RB1 (13q14), and DXS7132 (Xq12) present in 5/17 (29.4%) of the samples. CONCLUSION: Our results confirm the presence of a specific pattern of chromosomal imbalances in cervical carcinoma and define specific targets that are suffering DNA copy number changes in this neoplasm

KEGG-Cellular Pathways integrating our expression data of WNT-signalling pathways

<p><b>Copyright information:</b></p><p>Taken from "Genome wide expression analysis in HPV16 Cervical Cancer: identification of altered metabolic pathways"</p><p>http://www.infectagentscancer.com/content/2/1/16</p><p>Infectious Agents and Cancer 2007;2():16-16.</p><p>Published online 6 Sep 2007</p><p>PMCID:PMC2034543.</p><p></p> Yellow boxes indicates a down regulation of expression in tumor cervices samples. Red boxes indicates a higher gene expression in cervical carcinoma samples. Blue boxes indicates that a member of indicated gene family is expressed in normal tissues, and other member in tumors. Green boxes indicate that the gene was not altered

KEGG-based metabolic pathways identified to be altered in cervical carcinomas

<p><b>Copyright information:</b></p><p>Taken from "Genome wide expression analysis in HPV16 Cervical Cancer: identification of altered metabolic pathways"</p><p>http://www.infectagentscancer.com/content/2/1/16</p><p>Infectious Agents and Cancer 2007;2():16-16.</p><p>Published online 6 Sep 2007</p><p>PMCID:PMC2034543.</p><p></p> To know cellular pathways involved and the extent of alteration in CC, we imported a list of significantly up and down-regulated genes to Pathway Express. Then the Impact Factor obtained was graphed

Genome wide expression analysis in HPV16 Cervical Cancer: identification of altered metabolic pathways-0

<p><b>Copyright information:</b></p><p>Taken from "Genome wide expression analysis in HPV16 Cervical Cancer: identification of altered metabolic pathways"</p><p>http://www.infectagentscancer.com/content/2/1/16</p><p>Infectious Agents and Cancer 2007;2():16-16.</p><p>Published online 6 Sep 2007</p><p>PMCID:PMC2034543.</p><p></p>ss. Genes with expression levels that are statistically beyond delta in either direction are plotted either above (induced, red) or below (repressed, green) the control group. Genes which expression level did not change more than the set delta in either direction were considered to be not statistically significantly different at the set false discovery rate. Cluster analysis of cDNA microarray data. Microarray data were analyzed by the Eisen Hierarchical Cluster program and visualized with TreeView. The cluster shows 2,836 genes. Each row represents a gene, whereas each column corresponds to a tissue sample, the color line below tissue samples indicates, a) green: normal samples and b) red: tumor samples. The relative abundance of each gene in the tissue correlates with color intensity (red induced; green, repressed; black, no change). On the dendogram, all eight invasive cervical cancers clustered together such as two of the tree normal samples (N and N1) cluster indicating their similarity based on expression profile