Chromosome-breakage genomic instability and chromothripsis in breast cancer

Background

Chromosomal breakage followed by faulty DNA repair leads to gene amplifications and deletions in cancers. However, the mere assessment of the extent of genomic changes, amplifications and deletions may reduce the complexity of genomic data observed by array comparative genomic hybridization (array CGH). We present here a novel approach to array CGH data analysis, which focuses on putative breakpoints responsible for rearrangements within the genome.

Results

We performed array comparative genomic hybridization in 29 primary tumors from high risk patients with breast cancer. The specimens were flow sorted according to ploidy to increase tumor cell purity prior to array CGH. We describe the number of chromosomal breaks as well as the patterns of breaks on individual chromosomes in each tumor. There were differences in chromosomal breakage patterns between the 3 clinical subtypes of breast cancers, although the highest density of breaks occurred at chromosome 17 in all subtypes, suggesting a particular proclivity of this chromosome for breaks. We also observed chromothripsis affecting various chromosomes in 41% of high risk breast cancers.

Conclusions

Our results provide a new insight into the genomic complexity of breast cancer. Genomic instability dependent on chromosomal breakage events is not stochastic, targeting some chromosomes clearly more than others. We report a much higher percentage of chromothripsis than described previously in other cancers and this suggests that massive genomic rearrangements occurring in a single catastrophic event may shape many breast cancer genomes.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-579) contains supplementary material, which is available to authorized users.     

Using the ratio of means as the effect size measure in combining results of microarray experiments

Background  

Development of efficient analytic methodologies for combining microarray results is a major challenge in gene expression analysis. The widely used effect size models are thought to provide an efficient modeling framework for this purpose, where the measures of association for each study and each gene are combined, weighted by the standard errors. A significant disadvantage of this strategy is that the quality of different data sets may be highly variable, but this information is usually neglected during the integration. Moreover, it is widely known that the estimated standard deviations are probably unstable in the commonly used effect size measures (such as standardized mean difference) when sample sizes in each group are small.     

Development and characterization of highly polymorphic long TC repeat microsatellite markers for genetic analysis of peanut

Background

The immune system has paradoxical roles during cancer development and the prognostic significance of immune modulating factors is controversial. The aim of this study was to determine the expression of cyclooxygenase 2 (COX-2), transforming growth factor-beta (TGF- beta), interleukin-10 (IL-10) and their prognostic significance in breast cancers. Ki67 was included as a measure of growth fraction of tumor cells.

Methods

On immunohistochemical stained slides from 38 breast cancer patients, we performed digital video analysis of tumor cell areas and adjacent tumor stromal areas from the primary tumors and their corresponding lymph node metastases. COX-2 was recorded as graded staining intensity.

Results

The expression of TGF-beta, IL-10 and Ki67 were recorded in tumor cell areas and adjacent tumor stromal areas. In both primary tumors and metastases, the expression of COX-2 was higher in the tumor stromal areas than in the tumor cell areas (both P < 0.001). High stromal staining intensity in the primary tumors was associated with a 3.9 (95% CI 1.1-14.2) times higher risk of death compared to the low staining group (P = 0.036). The expression of TGF-beta was highest in the tumor cell areas of both primary tumors and metastases (both P < 0.001). High stromal expression of TGF-beta was associated with increased mortality. For IL-10, the stromal expression was highest in the primary tumors (P < 0.001), whereas in the metastases the expression was highest in tumor cell areas (P < 0.001). High IL-10 expression in tumor- and stromal cell areas of primary tumors predicted mortality. Ki67 was higher expressed in tumor stromal areas of the metastases, and in tumor cell areas of the primary tumors (P < 0.001). Ki67 expression in tumor cell areas and stromal areas of the metastases was independently associated with breast cancer mortality.

Conclusions

Stromal expression of COX-2, TGF-beta and Ki67 may facilitate tumor progression in breast cancer.     

Effect of local spatial plant distribution and conspecific density on bumble bee foraging behaviour

1. Size variations in pollinator populations may modify competitive interactions among foragers. Competition among pollinators has been shown to lead to one of two contrasting behaviours: either specialisation to the most profitable plant species or generalisation to several species. When foraging, pollinators are also confronted with heterogeneity in the spatial distribution of plant resources. Because variations in both the forager density and plant spatial distribution can affect pollinator behaviour, focus was on the interactive effect of these two factors. 2. Bumble bee (Bombus terrestris L.) individuals were trained on a focal species (Lotus corniculatus L.) and experimentally tested whether variations in the forager density (two or six bumble bees foraging together), plant community spatial distribution (two plant species: L. corniculatus and Medicago sativa, which were either patchily or randomly distributed), and their interaction modified bumble bee foraging behaviour. 3. It was shown that when confronted with a high forager density, bumble bees focused their visits towards the most familiar species, especially when foraging under a random plant distribution. These modifications affected the fruiting of the focal plant species, with a significantly lower reproductive success under low density/patchy conditions. 4. This study demonstrates that the foraging decisions of bumble bees are influenced by variations in both the conspecific density and plant spatial distribution. Given the increasing impact of human activities on plant‐pollinator communities, this raises the question of the potential implications of these results for plant communities in natural conditions when confronted with variations in the pollinator density and spatial distribution of plants.     

Spatial Organization and Mineralization of the Basal Plate of Elasmoid Scales in Osteichthyans

In Sarcopterygii (Latimeria, Neoceratodus, Protopterus, Leptdosiren)and Amiidae (Amia) collagen fibrils of the basal plate are packedin bundles whereas they remain isolated in Teleostei. The basalplate looks like plywood, a system of superimposed layers ofparallel fibers or fibrils the directions of which rotate witha regular angle in two successive layers. The double twistedplywood is constituted of two imbricate systems, the odd andthe even, where the rotation of the fibrillar directions isright-handed in Sarcopterygii and lefthanded in Amiidae andnumerous primitive Teleostei. The orthogonal plywood, with itstwo main orthogonal fibrillar directions, characterizes theevolved Teleostei and some more primitive ones. In most teleosteanspecies, as in Amia and Protopterus, mineralization of the basalplate in elasmoid scales involves Mandl's corpuscles that mineralizewithout contact with a pre-existing calcified tissue; they growand coalesce with the neighbouring ones and fuse to the mineralizingfront. Their shape is directly influenced by the local arrangementof the collagenous fibrils. In two teleostean families (Osteoglossidaeand Mormyridae) Mandl's corpuscles are completely lacking butspreading of mineralization in the basal plate has a peculiaraspect. Whatever that may be, the various characteristic organizationsof the skeletal tissues or isopedine that constitute the basalplate of osteichthyan elasmoid scales, all are varieties ofbone tissue that have undergone more or less important specializationlinked to the general regression of dermal ossifications andto functional adaptations.     

Integrative analysis of multiple gene expression profiles with quality-adjusted effect size models

Background  

With the explosion of microarray studies, an enormous amount of data is being produced. Systematic integration of gene expression data from different sources increases statistical power of detecting differentially expressed genes and allows assessment of heterogeneity. The challenge, however, is in designing and implementing efficient analytic methodologies for combination of data generated by different research groups.     

Curvilinear Three-Dimensional Modeling of Spinal Curves with Dual Kriging

In spinal deformation studies, three-dimensional reconstruction of the spine is frequently represented as a curve in space fitted to the vertebral centroids. Conventional interpolation techniques such as splines. Bezier and the least squares method are limited since they cannot describe precisely the great variety of spinal morphologies. This article presents a more general technique called dual kriging, which includes two mathematical constituents (drift and covariance) to adjust the interpolated functions to spinal deformity better. The cross-validation technique was used to compare the parametric representations of spinal curves with different combinations of drift and covariance functions. Model validation was performed from a series of analytic curves reflecting typical scoliotic spines. Calculation of geometric torsion, a sensitive parameter, was done to evaluate the accuracy of the kriging models. The best model showed an absolute mean difference of 1.2 x 10～5 (±7·1 × l()～ ⁵) mm^?1 between the analytical and estimated geometric torsions compared to 5·25 × 10～ (±3.7 × ³10～²) mm* ¹ for the commonly used least-squares Fourier series method, a significant improvement in spinal torsion evaluation.