Gene expression profiling predicts a three-gene expression signature of endometrial adenocarcinoma in a rat model

Identification of long non-coding RNAs biomarkers associated with progression of endometrial carcinoma and patient outcomes

Endometrial carcinoma is a complex disease characterized by both genetic, epigenetic and environmental factors. Increasing evidence has suggested that long non-coding RNAs (lncRNAs) play important roles in the development and progression of cancers. In this study, we performed a comparison analysis for lncRNA expression between patients with early-stage (stage I/II) and those with advanced-stage (stage III/IV) derived from The Cancer Genome Atlas (TCGA) project and identified 17 differentially expressed lncRNAs using student t-test. Five of the 17 differentially expressed lncRNAs were selected as optimal biomarkers that are significantly associated with progression of UCEC using random forest feature selection procedure. A risk classifier of five lncRNAs was developed to as a molecular signature that identifies patients at high risk for progression using support vector machine. Results of five-lncRNA risk classifier achieved high discriminatory performance in distinguishing advanced stage from early stage with 78% prediction accuracy, 96.6% sensitivity and 76.6% specificity. Functional analysis suggested that these five lncRNA biomarkers may play critical roles in the progression of UCEC by participating in important cancer-related biological processes. Our study will help to improve our understanding of underlying mechanisms in the progression of UCEC and provide novel lncRNAs as candidate predictive biomarkers for the identification of patients with high risk for progression.

C-kit Mutations in Endometrial Cancer: Correlation with Tumor Histologic Type

OBJECTIVE

Endometrial cancer is the fourth most common cancer among women in developed countries. Affected patients may benefit from systemic chemotherapy, alone or in combination with targeted therapies if the disease is clinically diagnosed prior to expansion and metastasis to other organs.The aim of this study was to evaluate the prognostic role of c-kit mutations and comparision with tumor type and grade in human uterine endometrial carcinomas.

MATERIALS AND METHODS

Seventy five patients with endometrial carcinoma and seventy five normal controls were studied for possible mutations in exon 17 of the c-kit gene using single strand conformational polymorphisms and sequencing.

RESULTS

c-kit mutation in exon 17 appeared to be significantly different between endometrial carcinoma and normal endometrium. The pattern and frequency of the mutations was also shown to be different between tumors from different stages.

Differential expression and anti-oxidant function of glutathione peroxidase 3 in mouse uterus during decidualization

Glutathione peroxidase 3 (GPX3) is an important member of antioxidant enzymes for reducing reactive oxygen species and maintaining the oxygen balance. Gpx3 mRNA is strongly expressed in decidual cells from days 5 to 8 of pregnancy. After pregnant mice are treated with GPX inhibitor for 3 days, pregnancy rate is significantly reduced. Progesterone stimulates Gpx3 expression through PR/HIF1α in mouse endometrial stromal cells. In the decidua, the high level of GPX3 expression is closely associated with the reduction of hydrogen peroxide (H2O2). Based on our data, GPX3 may play a major role in reducing H2O2 during decidualization.

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.

Expression patterns of Phf5a/PHF5A and Gja1/GJA1 in rat and human endometrial cancer

Endometrial adenocarcinoma is the most frequently diagnosed cancer of the female genital tract in the western world. Studies of complex diseases can be difficult to perform on human tumor samples due to the high genetic heterogeneity in human. The use of rat models is preferable since rat has similarities in pathogenesis and histopathological properties to that of human.

A genomic region including the highly conserved Phf5a gene associated to development of EAC has previously been identified in an association study. PHF5A has been suggested to acts as a transcription factor or cofactor in the up regulation of expression of Gja1 gene in the presence of estrogen. It has earlier been shown that the Phf5a gene is down regulated in rat EAC derived cell lines by means of expression microarrays.

We analyzed the expression of Phf5a and Gja1 by qPCR, and potential relations between the two genes in EAC tumors and non-malignant cell lines derived from the BDII rat model. In addition, the expression pattern of these genes was compared in rat and human EAC tumor samples.

Changes in expression for Phf5a/PHF5A were found in tumors from both rat and human even though the observed pattern was not completely consistent between the two species. By separating rat EAC cell lines according to the genetic background, a significant lower expression of Phf5a in one of the two cross backgrounds was revealed, but not for the other. In contrast to other studies, Phf5a/PHF5A regulation of Gja1/GJA1 was not revealed in this study.

p53-induced gene 3 mediates cell death induced by glutathione peroxidase 3

Expression of glutathione peroxidase 3 (GPx3) is down-regulated in a variety of human malignancies. Both methylation and deletion of GPx3 gene underlie the alterations of GPx3 expression in prostate cancer. A strong correlation between the down-regulation of GPx3 expression and progression of prostate cancer and the suppression of prostate cancer xenografts in SCID mice by forced expression of GPx3 suggests a tumor suppression role of GPx3 in prostate cancer. However, the mechanism of GPx3-mediated tumor suppression remains unclear. In this report, GPx3 was found to interact directly with p53-induced gene 3 (PIG3). Forced overexpression of GPx3 in prostate cancer cell lines DU145 and PC3 as well as immortalized prostate epithelial cells RWPE-1 increased apoptotic cell death. Expression of GPx3(x73c), a peroxidase-negative OPAL codon mutant, in DU145 and PC3 cells also increased cell death. The induced expression of GPx3 in DU145 and PC3 cells resulted in an increase in reactive oxygen species and caspase-3 activity. These activities were abrogated by either knocking down PIG3 or mutating the PIG3 binding motif in GPx3 or binding interference from a peptide corresponding to PIG3 binding motif in GPx3. In addition, UV-treated RWPE-1 cells underwent apoptotic death, which was partially prevented by knocking down GPx3 or PIG3, suggesting that GPx3-PIG3 signaling is critical for UV-induced apoptosis. Taken together, these results reveal a novel signaling pathway of GPx3-PIG3 in the regulation of cell death in prostate cancer.

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.

Metabolomics-based discovery of diagnostic biomarkers for onchocerciasis

Background

Development of robust, sensitive, and reproducible diagnostic tests for understanding the epidemiology of neglected tropical diseases is an integral aspect of the success of worldwide control and elimination programs. In the treatment of onchocerciasis, clinical diagnostics that can function in an elimination scenario are non-existent and desperately needed. Due to its sensitivity and quantitative reproducibility, liquid chromatography-mass spectrometry (LC-MS) based metabolomics is a powerful approach to this problem.

Methodology/Principal Findings

Analysis of an African sample set comprised of 73 serum and plasma samples revealed a set of 14 biomarkers that showed excellent discrimination between Onchocerca volvulus–positive and negative individuals by multivariate statistical analysis. Application of this biomarker set to an additional sample set from onchocerciasis endemic areas where long-term ivermectin treatment has been successful revealed that the biomarker set may also distinguish individuals with worms of compromised viability from those with active infection. Machine learning extended the utility of the biomarker set from a complex multivariate analysis to a binary format applicable for adaptation to a field-based diagnostic, validating the use of complex data mining tools applied to infectious disease biomarker discovery and diagnostic development.

Conclusions/Significance

An LC-MS metabolomics-based diagnostic has the potential to monitor the progression of onchocerciasis in both endemic and non-endemic geographic areas, as well as provide an essential tool to multinational programs in the ongoing fight against this neglected tropical disease. Ultimately this technology can be expanded for the diagnosis of other filarial and/or neglected tropical diseases.

Onchocerciasis, caused by the filarial parasite Onchocerca volvulus, afflicts millions of people, causing such debilitating symptoms as blindness and acute dermatitis. There are no accurate, sensitive means of diagnosing O. volvulus infection. Clinical diagnostics are desperately needed in order to achieve the goals of controlling and eliminating onchocerciasis and neglected tropical diseases in general. In this study, a metabolomics approach is introduced for the discovery of small molecule biomarkers that can be used to diagnose O. volvulus infection. Blood samples from O. volvulus infected and uninfected individuals from different geographic regions were compared using liquid chromatography separation and mass spectrometry identification. Thousands of chromatographic mass features were statistically compared to discover 14 mass features that were significantly different between infected and uninfected individuals. Multivariate statistical analysis and machine learning algorithms demonstrated how these biomarkers could be used to differentiate between infected and uninfected individuals and indicate that the diagnostic may even be sensitive enough to assess the viability of worms. This study suggests a future potential of these biomarkers for use in a field-based onchocerciasis diagnostic and how such an approach could be expanded for the development of diagnostics for other neglected tropical diseases.