Amin Moqadami; Mohammad Khalaj-Kondori
Abstract
Long non-coding RNAs (lncRNAs) have recently emerged as effective regulatory agents in biological processes as well as in the formation of tumors. LncRNAs are important regulators of cell transformation and cancer progression. LncRNA NEAT1 is one of the most important lncRNAs, and its deregulation has ...
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Long non-coding RNAs (lncRNAs) have recently emerged as effective regulatory agents in biological processes as well as in the formation of tumors. LncRNAs are important regulators of cell transformation and cancer progression. LncRNA NEAT1 is one of the most important lncRNAs, and its deregulation has been reported in a variety of human cancers. Ovarian cancer has an inverse relationship with the number of reported pregnancies and deliveries, while it has a direct relationship with infertility. This study aimed to investigate NEAT1 expression in ovarian cancer. A total of 140 tissue samples, including 70 ovarian tumors and 70 marginal samples, were included in the study. Total RNA was extracted using the RNXplus solution. The quality and quantity of the extracted RNAs were determined using gel electrophoresis and a NanoDrop device. The complementary DNA was synthesized by the reverse transcriptase enzyme, and quantitative reverse transcriptase PCR was used to quantify the expression of NEAT1. A comparison between the mean expression of NEAT1 in ovarian tumors and marginal samples showed an increase in NEAT1 expression in tumor tissue that was not statistically significant (P-value = 0.2). ROC curve analysis also showed that NEAT1 expression level might not be an informative biomarker for ovarian cancer.
Seyedeh Nahid Fotuhi; Mohammad Khalaj-Kondori; Hadis Karimi
Abstract
Patients with ovarian cancer are mostly diagnosed at advanced stages which leads to poor prognosis and high mortality rate. Deregulation of lncRNA HOXD-AS1 expression associates with cancer development and metastasis. However, the expression level of this lncRNA in ovarian cancer ...
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Patients with ovarian cancer are mostly diagnosed at advanced stages which leads to poor prognosis and high mortality rate. Deregulation of lncRNA HOXD-AS1 expression associates with cancer development and metastasis. However, the expression level of this lncRNA in ovarian cancer is not determined.50paired ovarian tumors and their adjusted normal tissues were included in the study. Total RNA was extracted by TRIzol® Reagent and reverse-transcribed to cDNA using PrimeScript II cDNA synthesis kit. The expression levels of HOXD-AS1 were quantified by qRT-PCR and compared. The Roc curve analysis was used to evaluate the capacity of HOXD-AS1 as a biomarker for ovarian cancer. We observed that lncRNA HOXD-AS1 was significantly upregulated in ovarian tumors compared to their adjusted normal tissues (p <0.003). Moreover, the ROC curve analysis revealed that the lncRNA HOXD-AS1 expression level could discriminate tumoral and non-tumoral tissues with 85% sensitivity and 88% specificity. The lncRNA HOXD-AS1 expression level might be considered as a potential biomarker for ovarian cancer development.
Mina Jahandideh; Ebrahim Barzegari
Abstract
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 ...
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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.
