A Computational Framework to Infer Prostate Cancer-Associated Long Noncoding RNAs and Analyses for Identifying a Competing Endogenous RNA Network.

Background: Prostate cancer (PC) is the second leading cause of cancer death after lung cancer in men. Current biomarkers are ineffective for the treatment and management of the disease. Long noncoding RNAs (lncRNAs) are a heterogeneous group of transcripts that are involved in complex gene expression regulatory networks. Although lncRNAs have been suggested to be promising as future biomarkers, the connection between the majority of lncRNAs and human disease remains to be elucidated. One approach to elucidate the roles of lncRNAs in disease is through the development of computational models. For example, a novel computational model termed HyperGeometric distribution for LncRNA-Disease Association (HGLDA) has been developed. Such models need to be developed on a tumor-specific basis to better suit the particular problem. Methods: In this study, we constructed a potential pipeline through two models, HGLDA and pathway-based using data from several databases. To validate the obtained data, the expression levels of selected lncRNAs were investigated quantitatively in the DU-145, LNCaP, and PC3 PC cell lines using quantitative real-time PCR. Results: We obtained a number of lncRNAs from both models, many of which were filtered through several databases that ultimately resulted in identification of six high-value lncRNA targets. Their expression was correlated with one important component of the PI3K pathway, known to be related to PC. Conclusion: Through the assembly of a lncRNA-miRNAs-mRNA competing endogenous RNA network, we successfully predicted lncRNAs interfering with miRNAs and coding genes related to PC.

JPX and LINC00641 ncRNAs expression in prostate tissue: a case-control study.

BACKGROUND AND PURPOSE: Prostate cancer (PC) is the second most prevalent cancer in men. Prostate-specific antigen (PSA) is the main biomarker for screening PC. An increase in PSA could lead to false-positive results. Thus, more appropriate markers should be investigated. In the present study, JPX and LINC00641 expression levels were measured in tumoral prostate tissue compared with the non-tumor tissue. EXPERIMENTAL APPROACH: 43 pairs of prostate tumoral and non-tumor tissue were prepared. The expression levels of JPX and LINC00641 were investigated by RT-qPCR. FINDINGS/RESULTS: Significant upregulation of LINC00641 (2.47 ± 0.5 vs 1.41 ± 0.2) and downregulation of JPX (1.42 ± 0.6 vs 2.83 ± 1.0) were observed in PC tissues compared with the normal tissues (their adjacent non-tumoral tissues). CONCLUSION AND IMPLICATIONS: Dysregulation of JPX and LINC00641 in PC patients could be used in the future as a prognostic biomarker in PC.

Upregulation of MTOR, RPS6KB1, and EIF4EBP1 in the whole blood samples of Iranian patients with multiple sclerosis compared to healthy controls.

Various genetic and epigenetic mechanisms have been suggested to play roles as the underlying pathophysiology of Multiple Sclerosis (MS). Changes in different parts of the mTOR signaling pathway are among the potential suggested mechanisms based on the specific roles of this pathway in CNS. MTOR, RPS6KB1, and EIFEBP1 genes are among important genes in the mTOR pathway, responsible for the proper function of acting proteins in this signaling pathway. This study aimed to investigate the relative expression levels of these genes in the blood samples of relapsing-remitting MS (RRMS) patients compared to healthy controls. In this case-control study blood samples were collected from 30 newly diagnosed RRMS patients and 30 age and sex-matched healthy controls. mRNA level of MTOR, RPS6KB1, and EIFEBP1 genes were assessed using Real-Time PCR. The expression of MTOR, RPS6KB1, and EIF4EBP1 genes was up regulated in MS patients compared to healthy controls (p < 0.001 for all mentioned genes). Considering gender differences, expression of the mentioned genes was increased among female patients (all P < 0.001). However, no statistically significant changes were observed among male patients. Based on the receiver operating characteristic, MTOR gene had the highest diagnostic value followed by EIF4EBP1 and RPS6KB1 genes in differentiating RRMS patients from controls. In conclusion, we found the simultaneous upregulation of MTOR, RPS6KB1, and EIF4EBP1 genes among RRMS patients. MTOR showed to have the highest diagnostic value compared to other 2 genes in differentiating RRMS patients. Further studies evaluating the importance of these findings from pharmacological and prognostic perspectives are necessary.

Epigenetics and Common Non Communicable Disease.

Common Non communicable diseases (NCDs), such as cardiovascular disease, cancer, schizophrenia, and diabetes, have become the major cause of death in the world. They result from an interaction between genetics, lifestyle and environmental factors. The prevalence of NCDs are increasing, and researchers hopes to find efficient strategies to predict, prevent and treat them. Given the role of epigenome in the etiology of NCDs, insight into epigenetic mechanisms may offer opportunities to predict, detect, and prevent disease long before its clinical onset.Epigenetic alterations are exerted through several mechanisms including: chromatin modification, DNA methylation and controlling gene expression by non-coding RNAs (ncRNAs). In this chapter, we will discuss about NCDs, with focus on cancer, diabetes and schizophrenia. Different epigenetic mechanisms, categorized into two main groups DNA methylation and chromatin modifications and non-coding RNAs, will be separately discussed for these NCDs.