Ozlen Konu

Nicotine, Body Weight and Potential Implications in the Treatment of Obesity

Obesity is an epidemic problem in the U. S. and many other industrialized nations. Historically, the drugs used for the treatment of obesity generally targeted small molecule neurotransmitters. As research grows to decipher the underlying molecular mechanisms behind energy homeostasis, it is becoming evident that the modulating effects of neuropeptides also are critical in the regulation of appetite and metabolism. The search for drugs to modify these monoaminergic and peptidergic pathways may eventually prove successful in the treatment of obesity. While tobacco smoking has long been used as one strategy to maintain a lower body weight, especially in female smokers, its adverse associations with addiction and disease overshadow its potential use as an antiobesity agent. Potential pharmacological effects of nicotine could be better understood as the intricacies of the nicotinic acetylcholine receptor are revealed. The objective of this review is threefold: first is to provide an overview of the physiological effects of nicotine on body weight while focusing on the drugs that are available as antiobesity and smoking cessation agents. Second is to provide the present status of the nicotinic acetylcholine receptor as it relates to energy homeostasis and its potential as an effective treatment modality for obesity. Third is to present the current knowledge with respect to nicotines effects on energy homeostatic and reward related pathways at the molecular level. A better understanding of the regulatory mechanisms underlying the pharmacological effects of nicotine on body weight will provide insights in identification of potential targets for the development of appropriate medicines in the treatment of obesity.

Identification of endogenous reference genes for qRT-PCR analysis in normal matched breast tumor tissues.

Quantitative gene expression measurements from tumor tissue are frequently compared with matched normal and/or adjacent tumor tissue expression for diagnostic marker gene selection as well as assessment of the degree of transcriptional deregulation in cancer. Selection of an appropriate reference gene (RG) or an RG panel, which varies depending on cancer type, molecular subtypes, and the normal tissues used for interindividual calibration, is crucial for the accurate quantification of gene expression. Several RG panels have been suggested in breast cancer for making comparisons among tumor subtypes, cell lines, and benign/malignant tumors. In this study, expression patterns of 15 widely used endogenous RGs (ACTB, TBP, GAPDH, SDHA, HPRT, HMBS, B2M, PPIA, GUSB, YWHAZ2, PGK1, RPLP0, PUM1, MRPL19, and RPL41), and three candidate genes that were selected through analysis of two independent microarray datasets (IL22RA1, TC22, ZNF224) were determined in 23 primary breast tumors and their matched normal tissues using qRT-PCR. Additionally, 18S rRNA, ACTB, and SDHA were tested using randomly primed cDNAs from 13 breast tumor pairs to assess the rRNA/mRNA ratio. The tumors exhibited significantly lower rRNA/mRNA ratio when compared to their normals, on average. The expression of the studied RGs in breast tumors did not exhibit differences in terms of grade, ER, or PR status. The stability of RGs was examined based on two different statistical models, namely GeNorm and NormFinder. Among the 18 tested endogenous reference genes, ACTB and SDHA were identified as the most suitable reference genes for the normalization of qRT-PCR data in the analysis of normal matched tumor breast tissue pairs by both programs. In addition, the expression of the gelsolin (GSN) gene, a well-known downregulated target in breast tumors, was analyzed using the two most suitable genes and different RG combinations to validate their effectiveness as a normalization factor (NF). The GSN expression of the tumors used in this study was significantly lower than that of normals showing the effectivity of using ACTB and SDHA as suitable RGs in this set of tumor-normal tissue panel. The combinational use of the best performing two RGs (ACTB and SDHA) as a normalization factor can be recommended to minimize sample variability and to increase the accuracy and resolution of gene expression normalization in tumor-normal paired breast cancer qRT-PCR studies.

Quantification of SLIT-ROBO transcripts in hepatocellular carcinoma reveals two groups of genes with coordinate expression

BackgroundSLIT-ROBO families of proteins mediate axon pathfinding and their expression is not solely confined to nervous system. Aberrant expression of SLIT-ROBO genes was repeatedly shown in a wide variety of cancers, yet data about their collective behavior in hepatocellular carcinoma (HCC) is missing. Hence, we quantified SLIT-ROBO transcripts in HCC cell lines, and in normal and tumor tissues from liver.MethodsExpression of SLIT-ROBO family members was quantified by real-time qRT-PCR in 14 HCC cell lines, 8 normal and 35 tumor tissues from the liver. ANOVA and Pearsons correlation analyses were performed in R environment, and different clinicopathological subgroups were pairwise compared in Minitab. Gene expression matrices of cell lines and tissues were analyzed by Mantels association test.ResultsGenewise hierarchical clustering revealed two subgroups with coordinate expression pattern in both the HCC cell lines and tissues: ROBO1, ROBO2, SLIT1 in one cluster, and ROBO4, SLIT2, SLIT3 in the other, respectively. Moreover, SLIT-ROBO expression predicted AFP-dependent subgrouping of HCC cell lines, but not that of liver tissues. ROBO1 and ROBO2 were significantly up-regulated, whereas SLIT3 was significantly down-regulated in cell lines with high-AFP background. When compared to normal liver tissue, ROBO1 was found to be significantly overexpressed, while ROBO4 was down-regulated in HCC. We also observed that ROBO1 and SLIT2 differentiated histopathological subgroups of liver tissues depending on both tumor staging and differentiation status. However, ROBO4 could discriminate poorly differentiated HCC from other subgroups.ConclusionThe present study is the first in comprehensive and quantitative evaluation of SLIT-ROBO family gene expression in HCC, and suggests that the expression of SLIT-ROBO genes is regulated in hepatocarcinogenesis. Our results implicate that SLIT-ROBO transcription profile is bi-modular in nature, and that each module shows intrinsic variability. We also provide quantitative evidence for potential use of ROBO1, ROBO4 and SLIT2 for prediction of tumor stage and differentiation status.

Genome-Wide Transcriptional Reorganization Associated with Senescence-to-Immortality Switch during Human Hepatocellular Carcinogenesis

Senescence is a permanent proliferation arrest in response to cell stress such as DNA damage. It contributes strongly to tissue aging and serves as a major barrier against tumor development. Most tumor cells are believed to bypass the senescence barrier (become “immortal”) by inactivating growth control genes such as TP53 and CDKN2A. They also reactivate telomerase reverse transcriptase. Senescence-to-immortality transition is accompanied by major phenotypic and biochemical changes mediated by genome-wide transcriptional modifications. This appears to happen during hepatocellular carcinoma (HCC) development in patients with liver cirrhosis, however, the accompanying transcriptional changes are virtually unknown. We investigated genome-wide transcriptional changes related to the senescence-to-immortality switch during hepatocellular carcinogenesis. Initially, we performed transcriptome analysis of senescent and immortal clones of Huh7 HCC cell line, and identified genes with significant differential expression to establish a senescence-related gene list. Through the analysis of senescence-related gene expression in different liver tissues we showed that cirrhosis and HCC display expression patterns compatible with senescent and immortal phenotypes, respectively; dysplasia being a transitional state. Gene set enrichment analysis revealed that cirrhosis/senescence-associated genes were preferentially expressed in non-tumor tissues, less malignant tumors, and differentiated or senescent cells. In contrast, HCC/immortality genes were up-regulated in tumor tissues, or more malignant tumors and progenitor cells. In HCC tumors and immortal cells genes involved in DNA repair, cell cycle, telomere extension and branched chain amino acid metabolism were up-regulated, whereas genes involved in cell signaling, as well as in drug, lipid, retinoid and glycolytic metabolism were down-regulated. Based on these distinctive gene expression features we developed a 15-gene hepatocellular immortality signature test that discriminated HCC from cirrhosis with high accuracy. Our findings demonstrate that senescence bypass plays a central role in hepatocellular carcinogenesis engendering systematic changes in the transcription of genes regulating DNA repair, proliferation, differentiation and metabolism.

Enhancer cooperativity as a novel mechanism underlying the transcriptional regulation of E-cadherin during mesenchymal to epithelial transition.

Epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) highlight crucial steps during embryogenesis and tumorigenesis. Induction of dramatic changes in gene expression and cell features is reflected by modulation of Cdh1 (E-cadherin) expression. We show that Cdh1 activity during MET is governed by two enhancers at +7.8 kb and at +11.5 kb within intron 2 that are activated by binding of Grhl3 and Hnf4α, respectively. Recruitment of Grhl3 and Hnf4α to the enhancers is crucial for activating Cdh1 and accomplishing MET in non-tumorigenic mouse mammary gland cells (NMuMG). Moreover, the two enhancers cooperate via Grhl3 and Hnf4α binding, induction of DNA-looping and clustering at the promoter to orchestrate E-cadherin re-expression. Our results provide novel insights into the cellular mechanisms whereby cells respond to MET signals and re-establish an epithelial phenotype by enhancer cooperativity. A general importance of our findings including MET-mediated colonization of metastasizing tumor cells is suggested.

A resampling-based meta-analysis for detection of differential gene expression in breast cancer

BackgroundAccuracy in the diagnosis of breast cancer and classification of cancer subtypes has improved over the years with the development of well-established immunohistopathological criteria. More recently, diagnostic gene-sets at the mRNA expression level have been tested as better predictors of disease state. However, breast cancer is heterogeneous in nature; thus extraction of differentially expressed gene-sets that stably distinguish normal tissue from various pathologies poses challenges. Meta-analysis of high-throughput expression data using a collection of statistical methodologies leads to the identification of robust tumor gene expression signatures.MethodsA resampling-based meta-analysis strategy, which involves the use of resampling and application of distribution statistics in combination to assess the degree of significance in differential expression between sample classes, was developed. Two independent microarray datasets that contain normal breast, invasive ductal carcinoma (IDC), and invasive lobular carcinoma (ILC) samples were used for the meta-analysis. Expression of the genes, selected from the gene list for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes were tested on 10 independent primary IDC samples and matched non-tumor controls by real-time qRT-PCR. Other existing breast cancer microarray datasets were used in support of the resampling-based meta-analysis.ResultsThe two independent microarray studies were found to be comparable, although differing in their experimental methodologies (Pearson correlation coefficient, R = 0.9389 and R = 0.8465 for ductal and lobular samples, respectively). The resampling-based meta-analysis has led to the identification of a highly stable set of genes for classification of normal breast samples and breast tumors encompassing both the ILC and IDC subtypes. The expression results of the selected genes obtained through real-time qRT-PCR supported the meta-analysis results.ConclusionThe proposed meta-analysis approach has the ability to detect a set of differentially expressed genes with the least amount of within-group variability, thus providing highly stable gene lists for class prediction. Increased statistical power and stringent filtering criteria used in the present study also make identification of novel candidate genes possible and may provide further insight to improve our understanding of breast cancer development.

miR-564 acts as a dual inhibitor of PI3K and MAPK signaling networks and inhibits proliferation and invasion in breast cancer.

Dysregulation of PI3K and MAPK pathways promotes uncontrolled cell proliferation, apoptotic inhibition and metastasis. Individual targeting of these pathways using kinase inhibitors has largely been insufficient due to the existence of cross-talks between these parallel cascades. MicroRNAs are small non-coding RNAs targeting several genes simultaneously and controlling cancer-related processes. To identify miRNAs repressing both PI3K and MAPK pathways in breast cancer, we re-analyzed our previous miRNA mimic screen data with reverse phase protein array (RPPA) output, and identified miR-564 inhibiting both PI3K and MAPK pathways causing markedly decreased cell proliferation through G1 arrest. Moreover, ectopic expression of miR-564 blocks epithelial-mesenchymal transition (EMT) and reduces migration and invasion of aggressive breast cancer cells. Mechanistically, miR-564 directly targets a network of genes comprising AKT2, GNA12, GYS1 and SRF, thereby facilitating simultaneous repression of PI3K and MAPK pathways. Notably, combinatorial knockdown of these target genes using a cocktail of siRNAs mimics the phenotypes exerted upon miR-564 expression. Importantly, high miR-564 expression or low expression of target genes in combination is significantly correlated with better distant relapse-free survival of patients. Overall, miR-564 is a potential dual inhibitor of PI3K and MAPK pathways, and may be an attractive target and prognostic marker for breast cancer.

Mdm2 Snp309 G allele displays high frequency and inverse correlation with somatic P53 mutations in hepatocellular carcinoma

Loss of function of the p53 protein, which may occur through a range of molecular events, is critical in hepatocellular carcinoma (HCC) evolution. MDM2, an oncogene, acts as a major regulator of the p53 protein. A polymorphism in the MDM2 promoter, SNP309 (T/G), has been shown to alter protein expression and may thus play a role in carcinogenesis. MDM2 SNP309 is also associated with HCC. However, the role of SNP309 in hepatocarcinogenesis with respect to TP53 mutations is unknown. In this study, we investigated the distribution of the MDM2 SNP309 genotype and somatic TP53 (the p53 tumor suppressor gene) mutations in 99 human HCC samples from Africa, Europe, China and Japan. Samples exhibited striking geographical differences in their distribution of SNP309 genotypes. The frequency and spectrum of p53 mutations also varied geographically; TP53 mutations were frequent in Africa, where the SNP309 T/T genotype predominated but were rare in Europe and Japan, where the SNP309 G allele was present more frequently. TP53 mutations were detected in 18% (4/22) of SNP309 T/G and G/G and 82% (18/22) of SNP309 T/T genotype holders; this difference was statistically highly significant (P-value=0.0006). Our results indicated that the presence of the SNP309 G allele is inversely associated with the presence of somatic TP53 mutations because they only coincided in 4% of HCC cases. This finding suggests that the SNP309 G allele may functionally replace p53 mutations, and in addition to known etiological factors, may be partly responsible for differential HCC prevalence.

Alternatively spliced Robo2 isoforms in zebrafish and rat

Robo2, a member of the robo gene family, functions as a repulsive axon guidance receptor as well as a regulator of cell migration and tissue morphogenesis in different taxa. In this study, a novel isoform of the zebrafish robo2 (robo2_tv2), which included an otherwise alternatively spliced exon (CAE), has been characterized. Robo2_tv2 is expressed differentially in most non-neuronal tissues of adult zebrafish whereas robo2_tv1 expression to a great extent is restricted to the brain and eye. In zebrafish, robo2_tv2 exhibits a very-low-level basal expression starting from 1 day post fertilization until the mid-larval stages, at which time its expression increases dramatically and could be detected throughout adulthood. Our findings demonstrate that the amino acid sequence coded by CAE of the robo2 gene is highly conserved between zebrafish and mammals, and also contains conserved motifs shared with robo1 and robo4 but not with robo3. Furthermore, we provide an account of differential transcription of the CAE homolog in various tissues of the adult rat. These results suggest that the alternatively spliced robo2 isoforms may exhibit tissue specificity.

Relative expression of rRNA transcripts and 45S rDNA promoter methylation status are dysregulated in tumors in comparison with matched-normal tissues in breast cancer

Ribosomal RNA (rRNA) expression, one of the most important factors regulating ribosome production, is primarily controlled by a CG-rich 45 S rDNA promoter. However, the DNA methylation state of the 45 S rDNA promoter, as well as its effect on rRNA gene expression in types of human cancers is controversial. In the present study we analyzed the methylation status of the rDNA promoter (-380 to +53 bp) as well as associated rRNA expression levels in breast cancer cell lines and breast tumor-normal tissue pairs. We found that the aforementioned regulatory region was extensively methylated (74-96%) in all cell lines and in 68% (13/19 tumor-normal pairs) of the tumors. Expression levels of rRNA transcripts 18 S, 28 S, 5.8 S and 45 S external transcribed spacer (45 S ETS) greatly varied in the breast cancer cell lines regardless of their methylation status. Analyses of rRNA transcript expression levels in the breast tumor and normal matched tissues showed no significant difference when normalized with TBP. On the other hand, using the geometric mean of the rRNA expression values (GM-rRNA) as reference enabled us to identify significant changes in the relative expression of rRNAs in the tissue samples. We propose GM-rRNA normalization as a novel strategy to analyze expression differences between rRNA transcripts. Accordingly, the 18S rRNA/GM-rRNA ratio was significantly higher whereas the 5.8S rRNA/GM-rRNA ratio was significantly lower in breast tumor samples than this ratio in the matched normal samples. Moreover, the 18S rRNA/GM-rRNA ratio was negatively correlated with the 45 S rDNA promoter methylation level in the normal breast tissue samples, yet not in the breast tumors. Significant correlations observed between the expression levels of rRNA transcripts in the normal samples were lost in the tumor samples. We showed that the expression of rRNA transcripts may not be based solely on promoter methylation. Carcinogenesis may cause dysregulation of the correlation between spliced rRNA expression levels, possibly due to changes in rRNA processing, which requires further investigation.