Mehmet Baysan

Histone Demethylase Jumonji D3 (JMJD3) as a Tumor Suppressor by Regulating p53 Protein Nuclear Stabilization

Histone methylation regulates normal stem cell fate decisions through a coordinated interplay between histone methyltransferases and demethylases at lineage specific genes. Malignant transformation is associated with aberrant accumulation of repressive histone modifications, such as polycomb mediated histone 3 lysine 27 (H3K27me3) resulting in a histone methylation mediated block to differentiation. The relevance, however, of histone demethylases in cancer remains less clear. We report that JMJD3, a H3K27me3 demethylase, is induced during differentiation of glioblastoma stem cells (GSCs), where it promotes a differentiation-like phenotype via chromatin dependent (INK4A/ARF locus activation) and chromatin independent (nuclear p53 protein stabilization) mechanisms. Our findings indicate that deregulation of JMJD3 may contribute to gliomagenesis via inhibition of the p53 pathway resulting in a block to terminal differentiation.

Age-specific signatures of glioblastoma at the genomic, genetic, and epigenetic levels.

Age is a powerful predictor of survival in glioblastoma multiforme (GBM) yet the biological basis for the difference in clinical outcome is mostly unknown. Discovering genes and pathways that would explain age-specific survival difference could generate opportunities for novel therapeutics for GBM. Here we have integrated gene expression, exon expression, microRNA expression, copy number alteration, SNP, whole exome sequence, and DNA methylation data sets of a cohort of GBM patients in The Cancer Genome Atlas (TCGA) project to discover age-specific signatures at the transcriptional, genetic, and epigenetic levels and validated our findings on the REMBRANDT data set. We found major age-specific signatures at all levels including age-specific hypermethylation in polycomb group protein target genes and the upregulation of angiogenesis-related genes in older GBMs. These age-specific differences in GBM, which are independent of molecular subtypes, may in part explain the preferential effects of anti-angiogenic agents in older GBM and pave the way to a better understanding of the unique biology and clinical behavior of older versus younger GBMs.

G-CIMP Status Prediction of Glioblastoma Samples Using mRNA Expression Data

Glioblastoma Multiforme (GBM) is a tumor with high mortality and no known cure. The dramatic molecular and clinical heterogeneity seen in this tumor has led to attempts to define genetically similar subgroups of GBM with the hope of developing tumor specific therapies targeted to the unique biology within each of these subgroups. Recently, a subset of relatively favorable prognosis GBMs has been identified. These glioma CpG island methylator phenotype, or G-CIMP tumors, have distinct genomic copy number aberrations, DNA methylation patterns, and (mRNA) expression profiles compared to other GBMs. While the standard method for identifying G-CIMP tumors is based on genome-wide DNA methylation data, such data is often not available compared to the more widely available gene expression data. In this study, we have developed and evaluated a method to predict the G-CIMP status of GBM samples based solely on gene expression data.

Micro-Environment Causes Reversible Changes in DNA Methylation and mRNA Expression Profiles in Patient-Derived Glioma Stem Cells

In vitro and in vivo models are widely used in cancer research. Characterizing the similarities and differences between a patients tumor and corresponding in vitro and in vivo models is important for understanding the potential clinical relevance of experimental data generated with these models. Towards this aim, we analyzed the genomic aberrations, DNA methylation and transcriptome profiles of five parental tumors and their matched in vitro isolated glioma stem cell (GSC) lines and xenografts generated from these same GSCs using high-resolution platforms. We observed that the methylation and transcriptome profiles of in vitro GSCs were significantly different from their corresponding xenografts, which were actually more similar to their original parental tumors. This points to the potentially critical role of the brain microenvironment in influencing methylation and transcriptional patterns of GSCs. Consistent with this possibility, ex vivo cultured GSCs isolated from xenografts showed a tendency to return to their initial in vitro states even after a short time in culture, supporting a rapid dynamic adaptation to the in vitro microenvironment. These results show that methylation and transcriptome profiles are highly dependent on the microenvironment and growth in orthotopic sites partially reverse the changes caused by in vitro culturing.

Gene expression profiles of autophagy-related genes in multiple sclerosis

Multiple sclerosis (MS) is an imflammatory disease of central nervous system caused by genetic and environmental factors that remain largely unknown. Autophagy is the process of degradation and recycling of damaged cytoplasmic organelles, macromolecular aggregates, and long-lived proteins. Malfunction of autophagy contributes to the pathogenesis of neurological diseases, and autophagy genes may modulate the T cell survival. We aimed to examine the expression levels of autophagy-related genes. The blood samples of 95 unrelated patients (aged 17-65years, 37 male, 58 female) diagnosed as MS and 95 healthy controls were used to extract the RNA samples. After conversion to single stranded cDNA using polyT priming: the targeted genes were pre-amplified, and 96×78 (samples×primers) qRT-PCR reactions were performed for each primer pair on each sample on a 96.96 array of Fluidigm BioMark™. Compared to age- and sex-matched controls, gene expression levels of ATG16L2, ATG9A, BCL2, FAS, GAA, HGS, PIK3R1, RAB24, RGS19, ULK1, FOXO1, HTT were significantly altered (false discovery rate<0.05). Thus, altered expression levels of several autophagy related genes may affect protein levels, which in turn would influence the activity of autophagy, or most probably, those genes might be acting independent of autophagy and contributing to MS pathogenesis as risk factors. The indeterminate genetic causes leading to alterations in gene expressions require further analysis.

Semi-online two-level supply chain scheduling problems

We consider two-level supply chain scheduling problems where customers release jobs to a manufacturer that has to process the jobs and deliver them to the customers. Processed jobs are grouped into batches, which are delivered to the customers as single shipments. The objective is to minimize the total cost which is the sum of the total flow time and the total delivery cost. Such problems have been considered in the off-line environment where future jobs are known, and in the online environment where at any time there is no information about future jobs. It is known that the best possible competitive ratio for an online algorithm is 2. We consider the problem in the semi-online environment, assuming that a lower bound P for all processing times is available a priori, and present a semi-online algorithm with competitive ratio

Variable power broadcast using local information in ad hoc networks

\frac{2D}{D+P}

A Polynomial Time Solution to Minimum Forwarding Set Problem in Wireless Networks under Unit Disk Coverage Model

where D is the cost of a delivery. Also, for the special case where all processing times are equal, we prove that the algorithm is

Approximation algorithm for the on-line multi-customer two-level supply chain scheduling problem

1.045\sqrt{\frac{2-u}{u}}

Master regulators, regulatory networks, and pathways of glioblastoma subtypes.

-competitive, where u is the density of the instance.