Identification of key miRNAs in prostate cancer progression based on miRNA-mRNA network construction.
Identification of key miRNAs in prostate cancer progression based on miRNA-mRNA network construction.
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DOI：
10.1016/j.csbj.2022.02.002
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发表时间：
2022
影响因子：
6
通讯作者：
Cava C
中科院分区：
文献类型：
--
作者：
Santo GD;Frasca M;Bertoli G;Castiglioni I;Cava C
前列腺癌(PC)是男性的主要癌症之一。PC的鉴别诊断对于个体化治疗是必不可少的，即描述肿瘤分级的Gleason评分(GS)可以用来选择合适的治疗方法。然而，目前的PC诊断和预后技术并不总是有效的。为了找出可用于PC鉴别诊断的潜在标记物，我们分析了miRNA-mRNA的相互作用，并建立了PC发生和进展的特异性网络。通过计算网络拓扑度量的三个参数：单个调控mRNA数(NSR)、靶基因数(NTG)和NSR/NTG，筛选出每个GS的关键差异表达miRNAs。获得这三个参数的高统计显着值的miRNAs被选为潜在的生物标记物，用于计算验证和路径分析。20个miRNAs被确定为PC的关键候选基因。在20个miRNAs中，有8个miRNAs(miR-25-3p、miR-93-3p、miR-122-5p、miR-183-5p、miR-615-3p、miR-7-5p、miR-375和miR-92a-3p)在所有GS中均有差异表达，可作为PC发病的生物标志物。此外，已鉴定的miRNAs的差异表达靶基因显著丰富了“细胞外-受体相互作用”、“焦点黏附”和“肿瘤中的microRNAs”。在PC组织中，MIR-10a-5p在GS 6、7和8中有差异表达。3个miRNAs被鉴定为PC GS特异性差异表达的miRNAs：在含有GS 6的PC样品中检测到miR-155-5p，在具有GS 9的PC样品中检测到miR-142-3p和miR-296-3p。结果表明，我们的20个miRNAs的性能(AUC：0.73)好于自动特征提取方法Boruta算法选择的miRNAs(AUC：0.55)。在研究miRNA-mRNA的相关性时，关键的miRNAs被用一种计算方法确定为PC的发生和进展。未来的翻译开发还需要进一步的实验验证。
Prostate cancer (PC) is one of the major male cancers. Differential diagnosis of PC is indispensable for the individual therapy, i.e., Gleason score (GS) that describes the grade of cancer can be used to choose the appropriate therapy. However, the current techniques for PC diagnosis and prognosis are not always effective. To identify potential markers that could be used for differential diagnosis of PC, we analyzed miRNA-mRNA interactions and we build specific networks for PC onset and progression. Key differentially expressed miRNAs for each GS were selected by calculating three parameters of network topology measures: the number of their single regulated mRNAs (NSR), the number of target genes (NTG) and NSR/NTG. miRNAs that obtained a high statistically significant value of these three parameters were chosen as potential biomarkers for computational validation and pathway analysis. 20 miRNAs were identified as key candidates for PC. 8 out of 20 miRNAs (miR-25-3p, miR-93-3p, miR-122-5p, miR-183-5p, miR-615-3p, miR-7-5p, miR-375, and miR-92a-3p) were differentially expressed in all GS and proposed as biomarkers for PC onset. In addition, “Extracellular-receptor interaction”, “Focal adhesion”, and “microRNAs in cancer” were significantly enriched by the differentially expressed target genes of the identified miRNAs. miR-10a-5p was found to be differentially expressed in GS 6, 7, and 8 in PC samples. 3 miRNAs were identified as PC GS-specific differentially expressed miRNAs: miR-155-5p was identified in PC samples with GS 6, and miR-142-3p and miR-296-3p in PC samples with GS 9. The efficacy of 20 miRNAs as potential biomarkers was revealed with a Random Forest classification using an independent dataset. The results demonstrated our 20 miRNAs achieved a better performance (AUC: 0.73) than miRNAs selected with Boruta algorithm (AUC: 0.55), a method for the automated feature extraction. Studying miRNA-mRNA associations, key miRNAs were identified with a computational approach for PC onset and progression. Further experimental validations are needed for future translational development.
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影响因子：
5.6
作者：
Cava C;Bertoli G;Colaprico A;Bontempi G;Mauri G;Castiglioni I
通讯作者：
Castiglioni I
DOI：
10.1016/j.omtn.2018.09.008
发表时间：
2018-12-07
期刊：
Molecular therapy. Nucleic acids
影响因子：
--
作者：
Cava C;Manna I;Gambardella A;Bertoli G;Castiglioni I
通讯作者：
Castiglioni I
影响因子：
14.9
作者：
Colaprico A;Silva TC;Olsen C;Garofano L;Cava C;Garolini D;Sabedot TS;Malta TM;Pagnotta SM;Castiglioni I;Ceccarelli M;Bontempi G;Noushmehr H
通讯作者：
Noushmehr H
影响因子：
3.7
作者：
Lin Y;Miao Z;Zhang X;Wei X;Hou J;Huang Y;Shen B
通讯作者：
Shen B
影响因子：
6
作者：
Laursen, Emma B.;Fredsoe, Jacob;Sorensen, Karina D.
通讯作者：
Sorensen, Karina D.