Journal of Cell and Molecular Research
Volume:12 Issue: 1, Summer and Autumn 2020

Epithelial ovarian cancer (EOC), as a challenging disease among women with poor prognosis and unclear molecular pathogenesis, each year is responsible for 140000 deaths globally. Recent progress in the field revealed the importance of proteins as key players of different biological events. Considering the complicated protein interactions, taking a deeper look at protein-protein interactions (PPIs) could be considered as a superior strategy to unravel complex mechanisms encountered with regulatory cell signaling pathways of ovarian cancer. Hence, PPI network analysis was performed on differentially expressed genes (DEGs) of ovarian cancer to discover hub genes which have the potential to be introduced as biomarkers with clinical utility. A PPI network with 600 DEGs was constructed. Network topology analysis determined UBC, FN1, SPP1, ACTB, GAPDH, JUN, and RPL13A, with the highest Degree (K) and betweenness centrality (BC), as shortcuts of the network. KEGG pathway analysis showed that these genes are commonly enriched in ribosome and ECM-receptor interaction pathways. These pivotal hub genes, mainly UBC, FN1, RPL13A, SPP1, and JUN have been reported previously as potential prognostic biomarkers of different types of cancer. However, further experimental molecular studies and computational processes are required to confirm the function and association of the identified hub genes with epithelial ovarian cancer prognosis.

MicroRNAs are interesting as cancer diagnostic and prognostic biomarkers because of their unique tissue expression profiles, higher stability in the blood in comparison to mRNAs, and the possibility for reliable quantification. In the case of prostate cancer (PCa), it is currently emphasized to explore new biomarkers, particularly from microRNAs which are freely available in the bloodstream. In this study, the gene expression omnibus database (GEO), a repository of microarray data for PCa circulating extracellular vesicle-free microRNAs profiling, was analyzed for differentially expressed miRNAs (DE-miRs). Top 20 most differentially expressed miRs with significant (adjusted p-value < 0.01) high expression (fold change) levels were extracted by the simultaneous application of different filtering criteria. Then, microRNA-gene networks were constructed for the two sets of positively (n=20) or negatively (n=20) regulated miRNAs. Gene ontology annotations of the target gene sets were also extracted and analyzed. Results indicated that human miR-1587, miR-223-3p, miR-3125, and miR-642b-3p are highly significant DE-miRs in PCa. In addition, human miR-4459, miR-1273g, miR 642a-3p, and miR-642b-3p were identified as top-ranked hubs in the relevant miRNA-gene networks. FOXK1, PML, CD24, ATN1, BAZ2A, CDKN1A, NUFIP2, and HARNPU were identified as microRNA target genes with significant dysregulation. miR-4459, miR-1273g-3p, miR-3135b, miR-5001-5p, and miR-1587 were proposed as novel microRNAs with the potential to be utilized as diagnostic biomarkers of prostate cancer among circulating vesicle-free miRNAs.

Previous studies have found several distinct alleles at both levels of transcriptional activity and protein-DNA binding manners in breast cancer patients vs. healthy individuals through multi-step experimental approaches. This study presents a computational-based model to investigate the regulatory potential and functional properties of disease-related non-coding single nucleotide polymorphisms (SNPs) variants through several online in silico tools in the Iranian population. The association between the risk of breast cancer and its putative single nucleotide polymorphisms in the Iranian population was investigated through SNPedia database and genome-wide association studies (GWAS). Furthermore, a meta-analysis was performed by Comprehensive Meta-Analysis (CMA) software. Functional analyses were carried out through LDlink, HaploReg, and RegulomeDB. The impact of each single nucleotide polymorphism on gene expression profiles and transcription factor binding sites were predicted by the RegulomeDB. "5", "6", and "1d" scores were assigned to rs3746444, rs1062577, and rs1049174 by this scoring system, respectively. RegulomeDB scores of rs3746444-MYH7B/MIR499A and rs1062577-ESR1 suggested that they are not putative functional single nucleotide polymorphisms; and may not associate with significant eQTL signals. The “1d” score for rs1049174-RP11-277P12.20 confirmed an association with the expression of the target gene. Proxy variants rs6088678 and rs2617160 have been identified using LDlink in non-coding segments. They were in strong linkage disequilibrium (LD) with single nucleotide polymorphisms rs3746444 and rs1049174, respectively. Also, non-coding variants rs6088678-TRPC4AP and rs2617160- RP11-277P12.20 with high-ranked scores showed the strongest related-expression. This work provides a rapid and direct in silico-based approach for the identification of functional genetic variants in the breast cancer. These analyses were conducted to evaluate the association of intended SNPs with the regulatory elements of histones, DNases, motif changes, and selected eQTL signals. It can be extended to some other complex single nucleotide polymorphism-related diseases.

The Caspian Sea is the largest inland body of water in the world and so has both common characteristics of seas and lakes with over 153 fish species which inhabit the sea and its basin. However, little is known about the trace element (TE) contaminations (TECs) in its tissues. In the present study, 122 specimens of three fish species including Rutilus caspius (Roach, n=71), Leuciscus aspius (Asp, n=20), and Tinca tinca (Tench, n=31) were collected from three different fisheries regions (i.e. Astara, Anzali and Kiashahr) of the southern part of the Caspian Sea from September 2017 to June 2018. Inductively coupled plasma optical emission spectrometry (ICP-OES) was employed to measure TE levels in different fish tissues. An attempt was made to assess possible influences of habitat on element accumulation in the liver and kidney of three fish species in the southwest of the Caspian Sea basin. Some elements including Ca, K, Mg, P, S, Sc, and Sr showed different concentrations in the liver and kidney. Also their levels were significantly different between freshwater resident (Tench) and marine (Roach) species (p < 0.05). The differences among TECs in the liver and kidney of Roach, Asp and Tench were reduced to three components using principal component analysis (PCA). Results indicated that 83.60% of the total variability is related to TEs such as Cu, Fe, Sr, Ca, S, Na, Mg, K, and Al. The impact of habitat variability on the element accumulation was confirmed through linear chart obtained for liver and kidney (as body filtering organs) of Roach and Asp as marine residents as well as Tench as a freshwater resident. This could illustrate the borderline created by these habitats.

Recent genome-wide association studies have introduced several genetic variants which contribute to the late-onset Alzheimer's disease (LOAD). Polymorphisms of CHAT, TOMM40, and SORL1 genes have been reported to be associated with the LOAD phenotype. This study was endeavored to evaluate the association of the CHAT rs3810950, TOMM40 rs1160985 and SORL1 rs11218304 polymorphisms with the LOAD in the Turkish-speaking Azeri population of northwest Iran. In a case-control study, we included 174 cases: 88 cases with LOAD diagnosis and 86 healthy individuals. Peripheral blood samples were collected and the genomic DNA of all participants were extracted. Genotyping was carried out by the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. We did not observe any significant association between the CHAT rs3810950 and SORL1 rs11218304 alleles with the LOAD. However, both the TOMM40 rs1160985 minor allele T and TT genotype showed significant negative associations with the LOAD. Hence, the TOMM40 rs1160985 polymorphism could be considered as a protective genetic factor against the LOAD in the Turkish-speaking Azeri population of northwest Iran.