Potential biomarkers through genome-wide expression analysis of breast cancer samples from Malaysian patients

• Main Authors: Chin, Minning, Norfilza Mohd Mokhtar,, Ezanee Azlina Mohd Haniff,, Norlia Abdullah,, Rohaizak Muhammad,, Nor Aina Emran,, Siti Aishah Che Md Ali,, Rahman Jamal,
• Format: Article
• Language: English
• Published: Pusat Perubatan Universiti Kebangsaan Malaysia 2013
• Online Access: http://journalarticle.ukm.my/13234/1/4-8-1-SM.pdf; http://journalarticle.ukm.my/13234/; http://spaj.ukm.my/apjmm/index.php/apjmm/issue/view/3

Breast cancer is a serious health concern and still a leading cause of death among women in the world. To explore the complexity of this cancer, we performed microarray analysis on highly selective cancer and normal breast tissues. The aim of this study was to identify differentially expressed genes between both tissues and to elucidate further molecular pathways involved in breast cancer carcinogenesis. Genome-wide expression profiling was performed on fifteen cancer and five normal breast tissues using the Affymetrix GeneChip® Human Gene 1.0 ST array. Supervised hierarchical cluster analysis using filtering parameters of -1.5 to 1.5 fold-change and p-value with False Discovery Rate < 0.05 revealed 404 up-regulated and 463 down-regulated genes. Pathway analysis revealed the significant genes were involved in cell cycle regulation, DNA repair, Hedgehog pathway, histone phosphorylation, TRRAP/Tip60 chromatin remodelling and apoptosis regulation. Among the top 10 significantly overexpressed genes were CENPF, DTL and MK167 and these were related to cell cycle regulation. Among the top 10 significant down-regulated genes, HOXA5 and NRG1 were found to be associated with Wnt signalling pathway and ErbB signalling pathway respectively. Aberrations in these genes are likely to promote breast cancer carcinogenesis. Our current findings highlighted the importance of differentially expressed genes in breast cancer and their molecular pathways that linked these genes. Further studies are required to validate our findings using larger sample size.