STATISTICAL METHODS FOR THE ANALYSIS OF CANCER GENOME SEQUENCING DATA

The purpose of cancer genome sequencing studies is to determine the nature and types of alterations present in a typical cancer and to discover genes mutated at high frequencies. In this article we discuss statistical methods for the analysis of data generated in these studies. We place special emphasis on a two-stage study design introduced by Sjoblom et al.[1]. In this context, we describe statistical methods for constructing scores that can be used to prioritize candidate genes for further investigation and to assess the statistical signicance of the candidates thus identfied

Wnt signalling and cancer stem cells

[Abstract] Intracellular signalling mediated by secreted Wnt proteins is essential for the establishment of cell fates and proper tissue patterning during embryo development and for the regulation of tissue homeostasis and stem cell function in adult tissues. Aberrant activation of Wnt signalling pathways has been directly linked to the genesis of different tumours. Here, the components and molecular mechanisms implicated in the transduction of Wnt signal, along with important results supporting a central role for this signalling pathway in stem cell function regulation and carcinogenesis will be briefly reviewed.Ministerio de Ciencia e Innovación; SAF2008-0060

Hyper-recombination and genetic instability in BLM-deficient epithelial cells.

  Genetic instability appears to be required for a normal colorectal epithelial cell to evolve into a cancerous one. Bloom syndrome patients have a strong predisposition to cancer that affects a variety of tissues. The mechanism of disease is attributed to genomic instability, but many questions about the nature of this instability have not yet been answered. To investigate these issues, we used gene-targeting techniques to disrupt the BLM gene in karyotypically stable colorectal cancer epithelial cells. BLM knockout cells showed an increased tendency of sister chromatids to exchange DNA strands and were substantially more likely to undergo homologous recombination at chromosomal loci than parental cells. Surprisingly, BLM-deficient colorectal cancer epithelial cells did not display gross chromosomal rearrangements nor a change in the rates of chromosome gains and losses. However, the enhanced homologous recombination was associated with losses of heterozygosity. These observations define a type of genetic instability that has significant implications for the evolution of cancer

Selective pressures for and against genetic instability in cancer: a time-dependent problem

Genetic instability in cancer is a two-edge sword. It can both increase the rate of cancer progression (by increasing the probability of cancerous mutations) and decrease the rate of cancer growth (by imposing a large death toll on dividing cells). Two of the many selective pressures acting upon a tumour, the need for variability and the need to minimize deleterious mutations, affect the tumour's ‘choice’ of a stable or unstable ‘strategy’. As cancer progresses, the balance of the two pressures will change. In this paper, we examine how the optimal strategy of cancerous cells is shaped by the changing selective pressures. We consider the two most common patterns in multistage carcinogenesis: the activation of an oncogene (a one-step process) and an inactivation of a tumour-suppressor gene (a two-step process). For these, we formulate an optimal control problem for the mutation rate in cancer cells. We then develop a method to find optimal time-dependent strategies. It turns out that for a wide range of parameters, the most successful strategy is to start with a high rate of mutations and then switch to stability. This agrees with the growing biological evidence that genetic instability, prevalent in early cancers, turns into stability later on in the progression. We also identify parameter regimes where it is advantageous to keep stable (or unstable) constantly throughout the growth