• A cluster of cooperating tumor-suppressor gene candidates in chromosomal deletions.

      Xue, Wen; Kitzing, Thomas; Roessler, Stephanie; Zuber, Johannes; Krasnitz, Alexander; Schultz, Nikolaus; Revill, Kate; Weissmueller, Susann; Rappaport, Amy R; Simon, Janelle; et al. (2012-05-22)
      The large chromosomal deletions frequently observed in cancer genomes are often thought to arise as a "two-hit" mechanism in the process of tumor-suppressor gene (TSG) inactivation. Using a murine model system of hepatocellular carcinoma (HCC) and in vivo RNAi, we test an alternative hypothesis, that such deletions can arise from selective pressure to attenuate the activity of multiple genes. By targeting the mouse orthologs of genes frequently deleted on human 8p22 and adjacent regions, which are lost in approximately half of several other major epithelial cancers, we provide evidence suggesting that multiple genes on chromosome 8p can cooperatively inhibit tumorigenesis in mice, and that their cosuppression can synergistically promote tumor growth. In addition, in human HCC patients, the combined down-regulation of functionally validated 8p TSGs is associated with poor survival, in contrast to the down-regulation of any individual gene. Our data imply that large cancer-associated deletions can produce phenotypes distinct from those arising through loss of a single TSG, and as such should be considered and studied as distinct mutational events.
    • Integrative analyses for omics data: a Bayesian mixture model to assess the concordance of ChIP-chip and ChIP-seq measurements.

      Schäfer, Martin; Lkhagvasuren, Otgonzul; Klein, Hans-Ulrich; Elling, Christian; Wüstefeld, Torsten; Müller-Tidow, Carsten; Zender, Lars; Koschmieder, Steffen; Dugas, Martin; Ickstadt, Katja; et al. (2012)
      The analysis of different variations in genomics, transcriptomics, epigenomics, and proteomics has increased considerably in recent years. This is especially due to the success of microarray and, more recently, sequencing technology. Apart from understanding mechanisms of disease pathogenesis on a molecular basis, for example in cancer research, the challenge of analyzing such different data types in an integrated way has become increasingly important also for the validation of new sequencing technologies with maximum resolution. For this purpose, a methodological framework for their comparison with microarray techniques in the context of smallest sample sizes, which result from the high costs of experiments, is proposed in this contribution. Based on an adaptation of the externally centered correlation coefficient ( Schäfer et al. 2009 ), it is demonstrated how a Bayesian mixture model can be applied to compare and classify measurements of histone acetylation that stem from chromatin immunoprecipitation combined with either microarray (ChIP-chip) or sequencing techniques (ChIP-seq) for the identification of DNA fragments. Here, the murine hematopoietic cell line 32D, which was transduced with the oncogene BCR-ABL, the hallmark of chronic myeloid leukemia, was characterized. Cells were compared to mock-transduced cells as control. Activation or inhibition of other genes by histone modifications induced by the oncogene is considered critical in such a context for the understanding of the disease.