Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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The landscape of pharmacogenomic interactions in human cancer

ABSTRACT: Systematic studies of the cancer genome are providing unprecedented insights into the molecular nature of human cancer. Using this information to guide the development and application of therapies in the clinic remains challenging. Here we report how cancer driving alterations detected in 11,215 tumors and 29 different tissues (integrating multiple omics) correlate with response to 265 compounds profiled in 1,001 cancer cell lines. We find that cell lines faithfully resemble tumours on the domain of these alterations, and numerous examples of altered genes and pathways conferring drug sensitivity and resistance. Significantly, logic-based modeling improves our ability to identify drug sensitive sub-types and machine-learning methods enable us to investigate the predictive ability of the different data-omics. We provide a comprehensive analysis of how somatic alterations identified from the large-scale analysis of primary tumors impact on drug response. This represents a rich resource to help identify therapeutic options for selected cancer populations. DNA was quantified by Quant-iT PicoGreen dsDNA Reagent (Invitrogen) and the integrity was analyzed in a 1.3% agarose gel. Bisulfite conversion of 600 ng of each sample was perform according to the manufacturer's recommendation for Illumina Infinium Assay. Effective bisulphite conversion was checked for three controls that were converted simultaneously with the samples. 4 ul of bisulfite converted DNA were used to hybridize on Infinium HumanMethylation 450 BeadChip, following Illumina Infinium HD Methylation protocol. Chip analysis was performed using Illumina HiScan SQ fluorescent scanner. The intensities of the images are extracted using GenomeStudio (2011.2) Methylation module (1.8.5) software. Methylation score of each CpG is represented as beta value. The cell lines are not treated with any drug or coumpound.

ORGANISM(S): Homo sapiens

SUBMITTER: Sebastian Moran

PROVIDER: E-GEOD-68379 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Human aging implies many phenotypic modifications and an increased susceptibility to many common diseases, phenomena that cannot be fully explained by the constrained genetic setting. An alternative pathway that could explain the age-associated alterations is epigenetic drifts. To address this issue, we performed Whole Genome Bisulfite Sequencing (WGBS) of a newborn and of a centenarian. The centenarian DNA exhibited a significant loss in DNA methylation and a poor correlation in the methylation status of neighboring CpGs throughout the genome. From a gene-regulatory region standpoint, we observed that the DNA hypomethylation events occurred mainly at CpG-poor promoters and in tissue-specific genes, whereas a greater level of DNA methylation was observed in CpG island promoters. Most importantly, we extended the study to a larger cohort of newborn and nonagenarian samples using a 450,000 CpG-site DNA methylation microarray. The 450K DNA methylation approach enabled validation of the WGBS data and revealed additional age-related DNA methylation events. Interestingly, we also observed the DNA methylation fingerprint characteristic of a healthy aged cell in samples from patients with premature-aging disorders such as Hutchinson-Gilford progeria and Werner syndrome. Overall, we suggest that defects in the physiological DNA methylation profile contribute to the process of human aging. As the disease associated cells were immortalized B cells, the effect of EBV immortalization was determined in advance to the study using immortalized and naive B cells. DNA was quantified by Quant-iT PicoGreen dsDNA Reagent (Invitrogen) and the integrity was analyzed in a 1.3% agarose gel. Bisulfite conversion of 600 ng of each sample was perform according to the manufacturer's recommendation for Illumina Infinium Assay. Effective bisulphite conversion was checked for three controls that were converted simultaneously with the samples. 4 ul of bisulfite converted DNA were used to hybridize on Infinium HumanMethylation 450 BeadChip, following Illumina Infinium HD Methylation protocol. Chip analysis was performed using Illumina HiScan SQ fluorescent scanner. The intensities of the images are extracted using GenomeStudio (2010.3) Methylation module (1.8.5) software. Methylation score of each CpG is represented as beta value.

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The landscape of pharmacogenomic interactions in human cancer

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