We failed to show an association between the ABCB1 C3435T polymorphism and the risk of drug-resistance suggesting a revision in contribution of this polymorphism in the multi-drug transporters hypothesis of pharmacoresistance to AEDs in epilepsy.

Integrative analyses of multiple genomic datasets for selected samples can provide better insight into the overall data and can enhance our knowledge of cancer. The objective of this study was to elucidate the association between copy number variation (CNV) and gene expression in colorectal cancer (CRC) samples and their corresponding non-cancerous tissues. Sixty-four paired CRC samples from the same patients were subjected to CNV profiling using the Illumina HumanOmni1-Quad assay, and validation was performed using multiplex ligation probe amplification method. Genome-wide expression profiling was performed on 15 paired samples from the same group of patients using the Affymetrix Human Gene 1.0 ST array. Significant genes obtained from both array results were then overlapped. To identify molecular pathways, the data were mapped to the KEGG database. Whole genome CNV analysis that compared primary tumor and non-cancerous epithelium revealed gains in 1638 genes and losses in 36 genes. Significant gains were mostly found in chromosome 20 at position 20q12 with a frequency of 45.31% in tumor samples. Examples of genes that were associated at this cytoband were PTPRT, EMILIN3 and CHD6. The highest number of losses was detected at chromosome 8, position 8p23.2 with 17.19% occurrence in all tumor samples. Among the genes found at this cytoband were CSMD1 and DLC1. Genome-wide expression profiling showed 709 genes to be up-regulated and 699 genes to be down-regulated in CRC compared to non-cancerous samples. Integration of these two datasets identified 56 overlapping genes, which were located in chromosomes 8, 20 and 22. MLPA confirmed that the CRC samples had the highest gains in chromosome 20 compared to the reference samples. Interpretation of the CNV data in the context of the transcriptome via integrative analyses may provide more in-depth knowledge of the genomic landscape of CRC.

BackgroundHistopathological assessment has a low potential to predict clinical outcome in patients with the same stage of colorectal cancer. More specific and sensitive biomarkers to determine patients’ survival are needed. We aimed to determine gene expression signatures as reliable prognostic marker that could predict survival of colorectal cancer patients with Dukes’ B and C.MethodsWe examined microarray gene expression profiles of 78 archived tissues of patients with Dukes’ B and C using the Illumina DASL assay. The gene expression data were analyzed using the GeneSpring software and R programming.ResultsThe outliers were detected and replaced with randomly chosen genes from the 90 % confidence interval of the robust mean for each group. We performed three statistical methods (SAM, LIMMA and t-test) to identify significant genes. There were 19 significant common genes identified from microarray data that have been permutated 100 times namely NOTCH2, ITPRIP, FRMD6, GFRA4, OSBPL9, CPXCR1, SORCS2, PDC, C12orf66, SLC38A9, OR10H5, TRIP13, MRPL52, DUSP21, BRCA1, ELTD1, SPG7, LASS6 and DUOX2. This 19-gene signature was able to significantly predict the survival of patients with colorectal cancer compared to the conventional Dukes’ classification in both training and test sets (p < 0.05). The performance of this signature was further validated as a significant independent predictor of survival using patient cohorts from Australia (n = 185), USA (n = 114), Denmark (n = 37) and Norway (n = 95) (p < 0.05). Validation using quantitative PCR confirmed similar expression pattern for the six selected genes.ConclusionProfiling of these 19 genes may provide a more accurate method to predict survival of patients with colorectal cancer and assist in identifying patients who require more intensive treatment.Electronic supplementary materialThe online version of this article (doi:10.1186/s12920-016-0218-1) contains supplementary material, which is available to authorized users.