Final Activity Report Summary - CANCEROMICS (Canceromics)
In the research program, we focussed on the development and application of novel microarray technologies at the molecular, cellular and patient level, and their application in cancer research and therapy development. Our laboratory is now world-wide unique in having access to a large number of different high-throughput technologies for cancer profiling and analysis. In particular, we have developed cell microarray technology for rapid functional analysis of genes in living cells at a genomic scale. Integrated analysis of canceromics data ('canceromics' or cancer systems biology) has been the main overall goal of the canceromics MC-EXT program. We believe that the canceromics team, in collaboration with the host institutes, has established itself as a major European site for the development and application of these technologies. The current state of art with some of the technologies is summarised below:
1) High-resolution array-CGH analyses: We are now using 244 000 oligo-array elements, allowing the identification of even sub-gene (exon-level) copy number changes. This has revealed a number of individual gene targets involved in genetic rearrangements. This will soon be complemented with the analysis using next-generation whole-genome genomic sequencing technologies.
2) HTS and lysate arrays: We have established a state-of-the-art cell-based High Throughput Screening (HTS) system. The primary focus is at screening for the identification of druggablöe targets for cancer using siRNA and miRNA libraries and for genome-scale cancer/cell biology research. We are also routinely screening for compounds against specific druggable targets or cellular processes (chemical biology). Over 30 000 cell biological experiments can be performed at a time, with the lysate microarray technology allowing us to profile up to dozens cellular endpoints simultaneously.
3) uHTS with cell arrays: We have developed a unique ultra-high density cell microarray screening system enables 100-1000x screening throughput compared to 384-well-based assays with a corresponding reduction in reagent consumption. Currently, we print arrays of 7 000 individual siRNAs / slide or 20 000 / plate, and can measure many endpoints such as cell proliferation, apoptosis and mitotic index, as well as individual protein markers.
4) Gene and miRNA expression arrays: We are using the industry-standard Affymetrix U133 series platform (1.3 M oligos) and the new Affymetrix exon microarrays. These latter ones contain 5.5 Million oligos, essentially at least one probe set for each exon of each human gene. This provides with an opportunity to identify genes that are alternatively spliced or that are rearranged by genetic alterations. We have also set up array profiling of human miRNAs.
5) Bioinformatic data analysis and integration: Microarray and HTS data are routinely normalized, QC controlled and analysed by hierarchical clustering, principal component analysis, self-organising-maps (SOM), significance analysis of microarrays (SAM) and gene-set enrichment analysis (GSEA). We have also created an extensive set of bioinformatic methods for high-throughput data integration. Matlab, the R programming language and Bioconductor packages are used to build data integration, analysis and visualisation capabilities. In addition, web-based data analysis and display software are used to enable biologists to analyse and interpret the data.
6) Meta-analysis of transcriptional profiles in clinical cancers: We have set up a large publicly available gene expression database http://www.genesapiens.org based on roughly 10 000 samples profiled using the Affymetrix microarray platform. Every sample has been carefully annotated according to pathological and clinical patient data. This allows, for the first time, a comprehensive analysis of gene functions across all human healthy tissues and most cancer types.
1) High-resolution array-CGH analyses: We are now using 244 000 oligo-array elements, allowing the identification of even sub-gene (exon-level) copy number changes. This has revealed a number of individual gene targets involved in genetic rearrangements. This will soon be complemented with the analysis using next-generation whole-genome genomic sequencing technologies.
2) HTS and lysate arrays: We have established a state-of-the-art cell-based High Throughput Screening (HTS) system. The primary focus is at screening for the identification of druggablöe targets for cancer using siRNA and miRNA libraries and for genome-scale cancer/cell biology research. We are also routinely screening for compounds against specific druggable targets or cellular processes (chemical biology). Over 30 000 cell biological experiments can be performed at a time, with the lysate microarray technology allowing us to profile up to dozens cellular endpoints simultaneously.
3) uHTS with cell arrays: We have developed a unique ultra-high density cell microarray screening system enables 100-1000x screening throughput compared to 384-well-based assays with a corresponding reduction in reagent consumption. Currently, we print arrays of 7 000 individual siRNAs / slide or 20 000 / plate, and can measure many endpoints such as cell proliferation, apoptosis and mitotic index, as well as individual protein markers.
4) Gene and miRNA expression arrays: We are using the industry-standard Affymetrix U133 series platform (1.3 M oligos) and the new Affymetrix exon microarrays. These latter ones contain 5.5 Million oligos, essentially at least one probe set for each exon of each human gene. This provides with an opportunity to identify genes that are alternatively spliced or that are rearranged by genetic alterations. We have also set up array profiling of human miRNAs.
5) Bioinformatic data analysis and integration: Microarray and HTS data are routinely normalized, QC controlled and analysed by hierarchical clustering, principal component analysis, self-organising-maps (SOM), significance analysis of microarrays (SAM) and gene-set enrichment analysis (GSEA). We have also created an extensive set of bioinformatic methods for high-throughput data integration. Matlab, the R programming language and Bioconductor packages are used to build data integration, analysis and visualisation capabilities. In addition, web-based data analysis and display software are used to enable biologists to analyse and interpret the data.
6) Meta-analysis of transcriptional profiles in clinical cancers: We have set up a large publicly available gene expression database http://www.genesapiens.org based on roughly 10 000 samples profiled using the Affymetrix microarray platform. Every sample has been carefully annotated according to pathological and clinical patient data. This allows, for the first time, a comprehensive analysis of gene functions across all human healthy tissues and most cancer types.