Chromosomal instability suppresses the growth of K-Ras-induced lung adenomas.

Chromosomal instability (CIN) is defined as a high rate of whole chromosome loss or gain and is a hallmark of many aneuploid solid tumors. CIN positively correlates with poor patient prognosis and chemotherapeutic resistance. Despite this clinical importance, the role of CIN in tumor initiation, growth and/or progression remains poorly understood. To date, the only strategies developed to determine how CIN contributes to tumorigenesis have relied on transgenic mouse models that deliberately increase the rate of chromosomal mis-segregation. Here we develop a strain of transgenic mice that is designed to strategically decrease the rate of chromosome mis-segregation and suppress CIN. These animals modestly overexpress the kinesin-13 microtubule depolymerase Kif2b, a strategy proven successful in restoring faithful chromosome segregation to human cancer cells in culture. Using the LA2 K-Ras G12D-induced model for lung cancer, we show that Kif2b expression reduces the number of chromosome segregation defects but does not change the incidence of lung tumor lesions. However, pulmonary tumors were significantly larger in animals expressing Kif2b and those tumors exhibited elevated rates of Ki-67 positive cells relative to controls. Thus, in lung cancers driven by mutations in K-Ras, CIN has little impact on tumor initiation but suppresses tumor growth. These data support a model in which CIN imposes a burden on tumor cells, and that enhancement of mitotic fidelity results in accelerated tumor growth.

Numerical chromosomal instability mediates susceptibility to radiation treatment.

The exquisite sensitivity of mitotic cancer cells to ionizing radiation (IR) underlies an important rationale for the widely used fractionated radiation therapy. However, the mechanism for this cell cycle-dependent vulnerability is unknown. Here we show that treatment with IR leads to mitotic chromosome segregation errors in vivo and long-lasting aneuploidy in tumour-derived cell lines. These mitotic errors generate an abundance of micronuclei that predispose chromosomes to subsequent catastrophic pulverization thereby independently amplifying radiation-induced genome damage. Experimentally suppressing whole-chromosome missegregation reduces downstream chromosomal defects and significantly increases the viability of irradiated mitotic cells. Further, orthotopically transplanted human glioblastoma tumours in which chromosome missegregation rates have been reduced are rendered markedly more resistant to IR, exhibiting diminished markers of cell death in response to treatment. This work identifies a novel mitotic pathway for radiation-induced genome damage, which occurs outside of the primary nucleus and augments chromosomal breaks. This relationship between radiation treatment and whole-chromosome missegregation can be exploited to modulate therapeutic response in a clinically relevant manner.

JCoDA: a tool for detecting evolutionary selection.

BACKGROUND: The incorporation of annotated sequence information from multiple related species in commonly used databases (Ensembl, Flybase, Saccharomyces Genome Database, Wormbase, etc.) has increased dramatically over the last few years. This influx of information has provided a considerable amount of raw material for evaluation of evolutionary relationships. To aid in the process, we have developed JCoDA (Java Codon Delimited Alignment) as a simple-to-use visualization tool for the detection of site specific and regional positive/negative evolutionary selection amongst homologous coding sequences. RESULTS: JCoDA accepts user-inputted unaligned or pre-aligned coding sequences, performs a codon-delimited alignment using ClustalW, and determines the dN/dS calculations using PAML (Phylogenetic Analysis Using Maximum Likelihood, yn00 and codeml) in order to identify regions and sites under evolutionary selection. The JCoDA package includes a graphical interface for Phylip (Phylogeny Inference Package) to generate phylogenetic trees, manages formatting of all required file types, and streamlines passage of information between underlying programs. The raw data are output to user configurable graphs with sliding window options for straightforward visualization of pairwise or gene family comparisons. Additionally, codon-delimited alignments are output in a variety of common formats and all dN/dS calculations can be output in comma-separated value (CSV) format for downstream analysis. To illustrate the types of analyses that are facilitated by JCoDA, we have taken advantage of the well studied sex determination pathway in nematodes as well as the extensive sequence information available to identify genes under positive selection, examples of regional positive selection, and differences in selection based on the role of genes in the sex determination pathway. CONCLUSIONS: JCoDA is a configurable, open source, user-friendly visualization tool for performing evolutionary analysis on homologous coding sequences. JCoDA can be used to rapidly screen for genes and regions of genes under selection using PAML. It can be freely downloaded at http://www.tcnj.edu/~nayaklab/jcoda.