The landscape of pharmacogenomic interactions in human cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE68379 | GEO | 2016/07/05
SECONDARY ACCESSION(S): PRJNA282584
REPOSITORIES: GEO
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Project description: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.
2016-07-05 | E-GEOD-68379 | biostudies-arrayexpress
Project description:Basal expression profiles of 1,000 human cancer cell lines in the Genomics of Drug Sensitivity in Cancer (GDSC) panel [upcoming version], profiled using a diverse collection of 265 compounds. We have carried out an extensive computational exploration of the data to determine (1) to what extent does the mutational landscape of cancer cell lines recapitulate that seen in primary tumours, (2) what effect the status of these genomic features have on the variation in drug response; (3) whether genomic alterations acting in concert explain more of the variation in drug response; and (4) what is the predictive ability of these individual data-omics and at what extent this is improved when they are combined. [See publication]
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Project description:The goal of this study was to characterize and classify pulmonary neuroendocrine tumors based on Array Comparative Genomic Hybridization (aCGH). Using aCGH, we performed karyotype analysis of 33 small cell lung cancer (SCLC) tumors, 13 SCLC cell lines, 19 bronchial carcinoids, and 9 gastrointestinal (GI) carcinoids. In contrast to the relatively stable karyotypes of carcinoid tumors, the karyotypes of SCLC tumors and cell lines were highly aberrant. High copy number (CN) gains were detected in SCLC tumors and cell lines in cytogenetic bands encoding JAK2, FGFR1, and MYC family members. In some of those samples, the CN of these genes exceeded 100, suggesting that they could represent driver alterations and potential drug targets in subgroups of SCLC patients. Recurrent CN alterations of a total of 203 genes, including the RB1 gene, and 59 microRNAs, most of which locate in the DLK1-DIO3 domain, were observed in SCLC tumors, bronchial carcinoids and carcinoids of GI origin; in contrast, CN alterations of the TP53 gene and the MYC family members were observed more frequently in SCLC. These findings suggest the existence of partially shared tumor-specific CN alterations in these tumors. Furthermore, we demonstrated that the aCGH profile of SCLC cell lines highly resemble that of clinical SCLC specimens. Finally, by analyzing potential drug targets, we provide a genomics based rationale for targeting the AKT-mTOR and apoptosis pathways in SCLC.
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