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Open Access Publications from the University of California

Scholarly Works (5 results)

  • Article
  • Peer Reviewed
UC Berkeley Previously Published Works (2002)

Background

Microarray technology is increasingly being applied in biological and medical research to address a wide range of problems, such as the classification of tumors. An important statistical problem associated with tumor classification is the identification of new tumor classes using gene-expression profiles. Two essential aspects of this clustering problem are: to estimate the number of clusters, if any, in a dataset; and to allocate tumor samples to these clusters, and assess the confidence of cluster assignments for individual samples. Here we address the first of these problems.

Results

We have developed a new prediction-based resampling method, Clest, to estimate the number of clusters in a dataset. The performance of the new and existing methods were compared using simulated data and gene-expression data from four recently published cancer microarray studies. Clest was generally found to be more accurate and robust than the six existing methods considered in the study.

Conclusions

Focusing on prediction accuracy in conjunction with resampling produces accurate and robust estimates of the number of clusters.
    Cover page: A prediction-based resampling method for estimating the number of clusters in a dataset.
    • Article
    • Peer Reviewed
    Lawrence Berkeley National Laboratory (2007)
      Cover page: Amplification of PVT1 contributes to the pathophysiology of ovarian and breast cancer
      • Article
      • Peer Reviewed
      UC San Francisco Previously Published Works (2006)
      Alterations in DNA methylation are important in cancer, but the acquisition of these alterations is poorly understood. Using an unbiased global screen for CpG island methylation events, we have identified a non-random pattern of DNA hypermethylation acquired in p16-repressed cells. Interestingly, this pattern included loci located upstream of a number of homeobox genes. Upon removal of p16(INK4A) activity in primary human mammary epithelial cells, polycomb repressors, EZH2 and SUZ12, are up-regulated and recruited to HOXA9, a locus expressed during normal breast development and epigenetically silenced in breast cancer. We demonstrate that at this targeted locus, the up-regulation of polycomb repressors is accompanied by the recruitment of DNA methyltransferases and the hypermethylation of DNA, an endpoint, which we show to be dependent on SUZ12 expression. These results demonstrate a causal role of p16(INK4A) disruption in modulating DNA hypermethylation, and identify a dynamic and active process whereby epigenetic modulation of gene expression is activated as an early event in breast tumor progression.
        Cover page: Tumor Suppressor p16INK4A Regulates Polycomb-mediated DNA Hypermethylation in Human Mammary Epithelial Cells*
        • Article
        • Peer Reviewed
        LBL Publications (2007)
          Cover page: Aging Impacts Transcriptome but not Genome of Hormone-dependent Breast Cancers
          • Article
          • Peer Reviewed
          UC San Francisco Previously Published Works (2006)

          Background: Genomic DNA copy number aberrations are frequent in solid tumors, although the underlying causes of chromosomal instability in tumors remain obscure. Genes likely to have genomic instability phenotypes when mutated ( e. g. those involved in mitosis, replication, repair, and telomeres) are rarely mutated in chromosomally unstable sporadic tumors, even though such mutations are associated with some heritable cancer prone syndromes. Methods: We applied array comparative genomic hybridization (CGH) to the analysis of breast tumors. The variation in the levels of genomic instability amongst tumors prompted us to investigate whether alterations in processes/genes involved in maintenance and/or manipulation of the genome were associated with particular types of genomic instability. Results: We discriminated three breast tumor subtypes based on genomic DNA copy number alterations. The subtypes varied with respect to level of genomic instability. We find that shorter telomeres and altered telomere related gene expression are associated with amplification, implicating telomere attrition as a promoter of this type of aberration in breast cancer. On the other hand, the numbers of chromosomal alterations, particularly low level changes, are associated with altered expression of genes in other functional classes (mitosis, cell cycle, DNA replication and repair). Further, although loss of function instability phenotypes have been demonstrated for many of the genes in model systems, we observed enhanced expression of most genes in tumors, indicating that over expression, rather than deficiency underlies instability. Conclusion: Many of the genes associated with higher frequency of copy number aberrations are direct targets of E2F, supporting the hypothesis that deregulation of the Rb pathway is a major contributor to chromosomal instability in breast tumors. These observations are consistent with failure to find mutations in sporadic tumors in genes that have roles in maintenance or manipulation of the genome.

            Cover page: Breast tumor copy number aberration phenotypes and genomic instability
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