Biomedical subjects

Ruty Mehrian Shai

Publications and source records attributed to Ruty Mehrian Shai.

3 recordsLinked to original sources

PubMed2006

Microarray tools for deciphering complex diseases.

Individual genetic findings associated with complex diseases are unlikely to fully explain their substantial impact or provide new comprehensive insights into disease pathogenesis. These also lack the comprehensive data much needed for development of new effective drugs in majority of the disease cases in a population. In fact multilevel etiologic factors underlie almost all human diseases, including: environmental causes, epigenetic factors, DNA mutations, amplifications, and deletions, RNA expression levels, protein (translation, post translation modification, localization) and combinations thereof. Each individual might consist of different combinations of these multiple etiologic factors. Integrative evaluation of all these modifications will shed light on the whole identity of the disease and the underlying molecular mechanisms. Until now it was inconceivable to have a full grasp of such a complex etiology. Microarrays enable us to interrogate the individualized various factors (DNA, RNA and protein content) involved in disease state on genome-wide scale simultaneously and expeditiously in single cell or the tissue of interest (Figure 1). The new disciplines of microarray studies in combination hold the promise of effective, current, and comprehensive understanding of complex diseases and may be a good approach for reducing the costs and time lines associated with discovery and efficacy improvement of therapeutic drugs. In the future, through utilizing the colossal amount of microarray data findings, defining the structure, function, and dynamics of entire biological pathways and cellular networks under various physiological states, and the development of robust and efficient methods for analyzing and interpreting high dimensional data, it will be possible to connect combination of experimental results with individualized disease state. This will facilitate precise diagnosis prognosis and therapy.

Alternative Splicing↗

PubMed2006

Comparisons of PCR-based genome amplification systems using CpG island microarrays.

The characterization of complex DNA libraries by high-throughput sequencing technologies provides a powerful approach toward finding mutations and genetic variation in the human genome. However, the value of these analyses is highly dependent upon the quality of the DNA libraries themselves. For example, the sequence composition of libraries made using PCR-based procedures can be skewed due to biases in the amplification efficiency of individual library members. Here, we used CpG island microarrays to evaluate the biases incurred in PCR-based genome amplification using three different DNA polymerase mixtures designed to efficiently amplify problematic sequence tracts. Based on hybridization properties of dye-labeled DNA libraries to these microarrays, we quantified the overall and specific trends in the PCR efficiency of more than 1,400 sequences with high GC-content, which generally amplify with low efficiency using conventional PCR protocols. Overall, all three DNA polymerase mixtures produced libraries that show substantial increases in the representation of CpG island segments that poorly amplify with Taq DNA polymerase. However, the effects of these DNA polymerases were quite specific since they did not alter the relative representation of segments that efficiently amplify with Taq DNA polymerase. Furthermore, we demonstrate that DNA microarrays provide a robust platform for rapidly evaluating the ability of different PCR systems to amplify difficult genomic regions targeted for mutational, resequencing, and genotyping analyses.

Base Composition↗

PubMed2005

Robustness of gene expression profiling in glioma specimen samplings and derived cell lines.

One of the most promising applications of microarrays is class distinction through gene expression profiling as a diagnostic tool. However, as there is apparent spatial heterogeneity in the morphology of cancer cells within a tumor, it is unclear if tumor sampling can be applied and yield consistent signals. In this report, we examined six brain tumors, four glioblastoma, and two oligodendroglioma biopsies. The six brain tumor tissues from two distinct different classes were dissected in four distinct areas and gene expression was profiled using microarrays. We used hierarchical clustering to compare the variability of gene expression profiles between spatially distinct biopsies of the same tumor as compared to the variability between tumors of the same histologic group. We conclude that, in general, repeat spatially distinct samples are not needed for microarray experiments and the gene expression signatures are robust across the tumor. Predominantly, variation was much greater between samples from different patients than from the multiple samplings of given tumor. Further, we compared biopsy expression profiles to the cell lines derived from those tissues. In general, the tumor cell lines vary greatly from the parental tissues and cluster more strongly with each other than the parental tissue. We select and examine the set of genes altered in expression to allow adaptation to cell culture.

Brain Neoplasms↗