SKY analysis revealed recurrent numerical and structural chromosome changes in BDII rat endometrial carcinomas

<p>Abstract</p> <p>Background</p> <p>Genomic alterations are common features of cancer cells, and some of these changes are proven to be neoplastic-specific. Such alterations may serve as valuable tools for diagnosis and classification of tumors, prediction of clinical outcome, disease monitoring, and choice of therapy as well as for providing clues to the location of crucial cancer-related genes.</p> <p>Endometrial carcinoma (EC) is the most frequently diagnosed malignancy of the female genital tract, ranking fourth among all invasive tumors affecting women. Cytogenetic studies of human ECs have not produced very conclusive data, since many of these studies are based on karyotyping of limited number of cases and no really specific karyotypic changes have yet been identified. As the majority of the genes are conserved among mammals, the use of inbred animal model systems may serve as a tool for identification of underlying genes and pathways involved in tumorigenesis in humans. In the present work we used spectral karyotyping (SKY) to identify cancer-related aberrations in a well-characterized experimental model for spontaneous endometrial carcinoma in the BDII rat tumor model.</p> <p>Results</p> <p>Analysis of 21 experimental ECs revealed specific nonrandom numerical and structural chromosomal changes. The most recurrent numerical alterations were gains in rat chromosome 4 (RNO4) and losses in RNO15. The most commonly structural changes were mainly in form of chromosomal translocations and were detected in RNO3, RNO6, RNO10, RNO11, RNO12, and RNO20. Unbalanced chromosomal translocations involving RNO3p was the most commonly observed structural changes in this material followed by RNO11p and RNO10 translocations.</p> <p>Conclusion</p> <p>The non-random nature of these events, as documented by their high frequencies of incidence, is suggesting for dynamic selection of these changes during experimental EC tumorigenesis and therefore for their potential contribution into development of this malignancy. Comparative molecular analysis of the identified genetic changes in this tumor model with those reported in the human ECs may provide new insights into underlying genetic changes involved in EC development and tumorigenesis.</p

Loss of glutathione peroxidase 3 expression is correlated with epigenetic mechanisms in endometrial adenocarcinoma

Glutathione peroxidase 3 (GPX3) is one of the key enzymes in the cellular defense against oxidative stress and the hepatocyte growth factor receptor, (MET) has been suggested to be influenced by the GPX3 gene expression. In a previous microarray study performed by our group, Gpx3 was identified as a potential biomarker for rat endometrial adenocarcinoma (EAC), since the expression was highly downregulated in rat EAC tumors. Herein, we have investigated the mRNA expression and Gpx3 and Met in rat EAC by real time quantitative PCR (qPCR), and the methylation status of Gpx3. In addition we have examined the expression of GPX3 and MET in 30 human EACs of different FIGO grades and 20 benign endometrial tissues. We found that the expression of GPX3 was uniformly down regulated in both rat and human EAC, regardless of tumor grade or histopathological subtype, implying that the down-regulation is an early event in EAC. The rate of Gpx3 promoter methylation reaches 91%, where biallelic methylation was present in 90% of the methylated tumors. The expression of the Met oncogene was slightly upregulated in EACs that showed loss of expression of Gpx3, but no tumor suppressor activity of Gpx3/GPX3 was detected. Preliminary results also suggest that the production of H2O2 is higher in rat endometrial tumors with down-regulated Gpx3 expression. A likely consequence of loss of GPX3 protein function would be a higher amount of ROS in the cancer cell environment. Thus, the results suggest important clinical implications of the GPX3 expression in EAC, both as a molecular biomarker for EAC and as a potential target for therapeutic interventions

Gene Map of the Rat

info:eu-repo/semantics/publishe

Rat gene map and comparative mapping with the mouse and other species.

Comparative StudyJournal Articleinfo:eu-repo/semantics/publishe

Validation of suitable endogenous control genes for quantitative PCR analysis of microRNA gene expression in a rat model of endometrial cancer

Abstract Background: MicroRNAs are small RNA molecules that negatively regulate gene expression by translational inhibition or mRNA cleavage. The discovery that abnormal expression of particular miRNAs contributes to human disease, including cancer, has spurred growing interest in analysing expression profiles of these molecules. Quantitative polymerase chain reaction is frequently used for quantification of miRNA expression due to its sensitivity and specificity. To minimize experimental error in this system an appropriate endogenous control gene must be chosen. An ideal endogenous control gene should be expressed at a constant level across all samples and its expression stability should be unaffected by the experimental procedure

Validation of Suitable Endogenous Control Genes for Quantitative PCR Analysis of microRNA gene expression in a rat model of endometrial cancer

Background MicroRNAs are small RNA molecules that negatively regulate gene expression by translational inhibition or mRNA cleavage. The discovery that abnormal expression of particular miRNAs contributes to human disease, including cancer, has spurred growing interest in analysing expression profiles of these molecules. Quantitative polymerase chain reaction is frequently used for quantification of miRNA expression due to its sensitivity and specificity. To minimize experimental error in this system an appropriate endogenous control gene must be chosen. An ideal endogenous control gene should be expressed at a constant level across all samples and its expression stability should be unaffected by the experimental procedure. Results The expression and validation of candidate control genes (4.5S RNA(H) A, Y1, 4.5S RNA(H) B, snoRNA, U87 and U6) was examined in 21 rat cell lines to establish the most suitable endogenous control for miRNA analysis in a rat model of cancer. The stability of these genes was analysed using geNorm and NormFinder algorithms. U87 and snoRNA were identified as the most stable control genes, while Y1 was least stable. Conclusion This study identified the control gene that is most suitable for normalizing the miRNA expression data in rat. That reference gene will be useful when miRNAs expression are analyzed in order to find new miRNA markers for endometrial cancer in rat.CC BY 2.0</p

Genome-wide discovery of miRNAs using ensembles of machine learning algorithms and logistic regression

In silico prediction of novel miRNAs from genomic sequences remains a challenging problem. This study presents a genome-wide miRNA discovery software package called GenoScan and evaluates two hairpin classification methods. These methods, one ensemble-based and one using logistic regression were benchmarked along with 15 published methods. In addition, the sequence-folding step is addressed by investigating the impact of secondary structure prediction methods and the choice of input sequence length on prediction performance. Both the accuracy of secondary structure predictions and the miRNA prediction are evaluated. In the benchmark of hairpin classification methods, the regression model achieved highest classification accuracy. Of the structure prediction methods evaluated, ContextFold achieved the highest agreement between predicted and experimentally determined structures. However, both the choice of secondary structure prediction method and input sequence length had limited impact on hairpin classification performance