Long Noncoding RNAs CAT2064 and CAT2042 may Function as Diagnostic Biomarkers for Prostate Cancer by Affecting Target MicrorRNAs.

Q2 Chemistry Journal of Biomolecular Screening Pub Date : 2024-07-01 Epub Date: 2021-08-24 DOI:10.1007/s12291-021-00999-6

Farzane Amirmahani, Nasim Ebrahimi, Rafee Habib Askandar, Marzieh Rasouli Eshkaftaki, Katayoun Fazeli, Michael R Hamblin

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Abstract

Prostate cancer (PCa) is the second most common cancer in men throughout the world, and the main cause of cancer death. Long noncoding RNAs (lncRNAs) act as crucial regulators in many human cancers. In this research, we measured the expression level of novel lncRNAs and their associated micro-RNAs (miRNAs) in PCa. In the present research, three lncRNAs were selected using the Mitranscriptome projec (CAT2064, CAT2042, and CAT2164.2). Samples of prostate tissue (20 PCa, and 20 BPH) and blood (14 PCa, and 14 BPH) were collected and the Real-time Quantitative Polymerase Chain Reaction (RT-qPCR) was used to measure the expression levels of the lncRNAs and their associated miRNAs. Based on our results, CAT2064 was significantly increased and CAT2042 was significantly decreased in human PCa tissue in comparison with BPH tissue. To discriminate PCa from BPH, CAT2064 (P < 0.05; 0.8750 AUC-ROC) showed a better potential as a diagnostic molecular biomarker compared to CAT2042 (P < 0.05; 0.8454 AUC-ROC). Furthermore, RT-qPCR results measured in blood samples from PCa patients showed a higher expression level of CAT2064 (P < 0.0001; AUC-ROC value of 0.8914) in comparison to CAT2042. CAT2064 and CAT2042 showed a positive correlation with the expression of miR-5095 and miR-1273a (r = 0.02885, 0.3202; P = 0.9413, 0.2266, respectively). CAT2064 and CAT2042 also had a negative correlation with miR-1304-3p and miR-1285-5p (r = - 0.3877, - 0.09330; P = 0.15, 0.7311, respectively). Collectively, CAT2064 and CAT2042 and their miRNA targets may constitute a regulatory network in PCa, and could serve as novel biomarkers.

Supplementary information: The online version contains supplementary material available at 10.1007/s12291-021-00999-6.

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长非编码 RNA CAT2064 和 CAT2042 可通过影响目标微小 RNA 发挥前列腺癌诊断生物标志物的作用。

前列腺癌（PCa）是全球第二大男性常见癌症，也是导致癌症死亡的主要原因。长非编码 RNA（lncRNA）是许多人类癌症的关键调控因子。在这项研究中，我们测量了新型lncRNA及其相关微RNA（miRNA）在PCa中的表达水平。本研究利用 Mitranscriptome projec 选定了三个 lncRNA（CAT2064、CAT2042 和 CAT2164.2）。研究人员采集了前列腺组织样本（20 个 PCa 和 20 个 BPH）和血液样本（14 个 PCa 和 14 个 BPH），并使用实时定量聚合酶链式反应（RT-qPCR）测定了这些 lncRNAs 及其相关 miRNAs 的表达水平。结果显示，与良性前列腺增生组织相比，CAT2064在人PCa组织中明显升高，而CAT2042则明显降低。为了区分 PCa 和良性前列腺增生，CAT2064（P P P P = 0.9413，0.2266，分别）和 CAT2042（P P P = 0.9413，0.2266，分别）都明显增加。CAT2064 和 CAT2042 还与 miR-1304-3p 和 miR-1285-5p 呈负相关（r = - 0.3877，- 0.09330；P = 0.15，0.7311）。总之，CAT2064和CAT2042及其miRNA靶标可能构成了PCa的调控网络，并可作为新型生物标志物：在线版本包含补充材料，见 10.1007/s12291-021-00999-6。

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来源期刊

Journal of Biomolecular Screening 生物-分析化学

CiteScore

2.41

自引率

0.00%

发文量

审稿时长

4-8 weeks

期刊介绍： Advancing the Science of Drug Discovery: SLAS Discovery reports how scientists develop and utilize novel technologies and/or approaches to provide and characterize chemical and biological tools to understand and treat human disease. SLAS Discovery is a peer-reviewed journal that publishes scientific reports that enable and improve target validation, evaluate current drug discovery technologies, provide novel research tools, and incorporate research approaches that enhance depth of knowledge and drug discovery success. SLAS Discovery emphasizes scientific and technical advances in target identification/validation (including chemical probes, RNA silencing, gene editing technologies); biomarker discovery; assay development; virtual, medium- or high-throughput screening (biochemical and biological, biophysical, phenotypic, toxicological, ADME); lead generation/optimization; chemical biology; and informatics (data analysis, image analysis, statistics, bio- and chemo-informatics). Review articles on target biology, new paradigms in drug discovery and advances in drug discovery technologies. SLAS Discovery is of particular interest to those involved in analytical chemistry, applied microbiology, automation, biochemistry, bioengineering, biomedical optics, biotechnology, bioinformatics, cell biology, DNA science and technology, genetics, information technology, medicinal chemistry, molecular biology, natural products chemistry, organic chemistry, pharmacology, spectroscopy, and toxicology.