Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

MCGH of cervical cancer

ABSTRACT: Genomic alteration of cervical cancer samples. Analysis by CGH array. Array spotted at AECOM (NY) with human ESTs. Analysis as in Bourdon et al. Cancer Res. 2002 Nov 1;62(21):6218-23

ORGANISM(S): Homo sapiens

SUBMITTER: Veronique Bourdon

PROVIDER: E-GEOD-1715 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Gene dosage alterations revealed by cDNA microarray analysis in cervical cancer: identification of candidate amplified and overexpressed genes.

Narayan Gopeshwar G Bourdon Veronique V Chaganti Seeta S Arias-Pulido Hugo H Nandula Subhadra V SV Rao Pulivarthi H PH Gissmann Lutz L Dürst Matthias M Schneider Achim A Pothuri Bhavana B Mansukhani Mahesh M Basso Katia K Chaganti R S K RS Murty Vundavalli V VV

Genes, chromosomes & cancer 20070401 4

Cervical cancer (CC) cells exhibit complex karyotypic alterations, which is consistent with deregulation of numerous critical genes in its formation and progression. To characterize this karyotypic complexity at the molecular level, we used cDNA array comparative genomic hybridization (aCGH) to analyze 29 CC cases and identified a number of over represented and deleted genes. The aCGH analysis revealed at least 17 recurrent amplicons and six common regions of deletions. These regions contain sev ...[more]

PMID: 17243165

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Project description: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.

Dataset Information

MCGH of cervical cancer

Publications

Gene dosage alterations revealed by cDNA microarray analysis in cervical cancer: identification of candidate amplified and overexpressed genes.

Similar Datasets

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