Thursday, 20 September 2018 | 12:00 noon
Center for Genome Research, Department of Life Sciences, University of Modena and Reggio Emilia, Modena, ITALY
Integrative analysis of genomics data to investigate transcriptional programs in cancer cells
(Host: F. Benvenuti)
Transcriptional profiling has been extensively used to detect patterns in gene expression that stem from regulatory interactions. Seminal studies demonstrated that the synergistic use of high-throughput techniques and bioinformatics analysis of genomic data might not only further the understanding of pathological phenotypes, but also provide lists of genes to dissect a disease into distinct groups, with different molecular or clinical characteristics.
Nonetheless, optimism for gene expression-based technologies as clinical tools has suffered both perceptual and real setbacks. Criticism is largely on the grounds of general non-reproducibility of gene signatures and on the limited inference about the molecular mechanisms underlying pathological traits.
Here, we describe how to integrate large collection of gene expression data with clinical information and the impact of bioinformatics analyses in the investigation of transcriptional programs of cancer cells. Specifically, several applicative examples will be used to illustrate a bioinformatics strategy that integrating multiple, independently generated datasets allows a thorough analysis of signaling pathways driving tumorigenesis and tumor heterogeneity in human breast cancer.