Computational protocol: Reprogramming human A375 amelanotic melanoma cells by catalase overexpression: Upregulation of antioxidant genes correlates with regression of melanoma malignancy and with malignant progression when downregulated

Similar protocols

Protocol publication

[…] Differential gene expression among human amelanotic melanoma cells, A375, and the two established catalase-overexpressing clones with different phenotypes (A7, melanotic and non-invasive and G10, amelanotic and invasive) was evaluated by the bioinformatic analysis of whole genome microarrays (GeneChip® Human Gene 1.0 ST Array, Affymetrix). A375 and PCDNA3 cells were used as controls.The analysis was performed by using the R programming language (2.12.0) [] and different tools of Bioconductor []. The libraries “affy”, “limma”, “oligo”, “affxparser”, “Iranges”, “gplots”, “Biobase”, “Biostrings”, “cluster”, “hugene10stprobeset.db”, “Go.db”, “preprocess Core”, hugene10sttranscriptcluster.db”, “”, “”, “”, “annotate” and KEGG.db” were used. Background correction and normalization of data were performed by Robust Multi-array Average (rma) both for probe set and core. Differential gene expression was evaluated by Limma package (Linear Models for Microarray Data). Log fold change (lfc) and p value parameters were established. In order to determine those genes to be analyzed for functional classification or qPCR validation a 1 and 2 lfc were used respectively. Both analyses were performed with a p < 0.001.The differential genes obtained were functionally classified by DAVID (Database for Annotation, Visualization and Integrated Discovery) [, ]. DAVID Functional Annotation Clustering tool was performed by using the annotation terms: Disease (OMIM_disease), Gene Ontology (GOTERM_BP_FAT, GOTERM_CC_FAT, GOTERM_MF_FAT), Pathways (BBID, BIOCARTA, KEGG_PATHWAY, REACTOME_PATHWAY) and Tissue Expression (UP_TISSUE). The classification stringency was selected as medium and the options were selected as default.Significant and concordant differences between phenotypes were evaluated by GSEA (Gene Set Enrichment Analysis) [] with a priori defined gene sets collected from Gene Ontology Database [] (131 gene groups) and KEGG (Kyoto Encyclopedia of Genes and Genomes) [–] (19 gene groups). These selected gene sets are associated with cell proliferation, melanoma, cell cycle, melanogenesis, apoptosis, cell adhesion, vascularization, angiogenesis, peroxisome, cell migration, regulation of actin cytoskeleton, autophagy regulation, oxidative stress, invasion, cell motility, DNA damage response, drug exportation, drug metabolism, immune response and inflammation (). An additional set of 111 genes related to the antioxidant system [–] was manually defined, visualized by GeneMANIA database [] and studied under the same criteria (Figure and ). This type of analysis was also performed with 39 bibliographic predictive gene signatures of melanomas, associated with invasion, differentiation, aggressiveness and metastasis [–] (). Coexpressed genes obtained by the analysis were visualized by GeneMANIA database [] via GeneMANIA web or via Cytoscape plugin []. […]

Pipeline specifications

Software tools affy, limma, IRanges, gplots, Biobase, Biostrings,, KEGG.db, DAVID, GSEA, GeneMANIA
Databases OMIM Reactome KEGG KEGG PATHWAY GO.db BioCarta
Applications Drug design, Miscellaneous, Protein interaction analysis
Organisms Homo sapiens
Diseases Melanoma, Neoplasms, Melanoma, Amelanotic, Mastocytosis, Systemic
Chemicals Hydrogen Peroxide, Oxygen