Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model
Abstract Background Prostate cancer (PCa) is a fatal malignant tumor among males in the world and the metastasis is a leading cause for PCa death. Biomarkers are therefore urgently needed to detect PCa metastatic signature at the early time. MicroRNAs are small non-coding RNAs with the potential to...
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doaj-9fba84936d27461ca8a0118d248dd0d32020-11-24T22:06:51ZengBMCJournal of Translational Medicine1479-58762018-05-0116111610.1186/s12967-018-1506-7Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis modelYuxin Lin0Feifei Chen1Li Shen2Xiaoyu Tang3Cui Du4Zhandong Sun5Huijie Ding6Jiajia Chen7Bairong Shen8Center for Systems Biology, Soochow UniversityCenter for Systems Biology, Soochow UniversityCenter for Systems Biology, Soochow UniversityCenter for Systems Biology, Soochow UniversityCenter for Systems Biology, Soochow UniversityCenter for Systems Biology, Soochow UniversityCenter for Systems Biology, Soochow UniversitySchool of Chemistry, Biology and Material Engineering, Suzhou University of Science and TechnologyCenter for Systems Biology, Soochow UniversityAbstract Background Prostate cancer (PCa) is a fatal malignant tumor among males in the world and the metastasis is a leading cause for PCa death. Biomarkers are therefore urgently needed to detect PCa metastatic signature at the early time. MicroRNAs are small non-coding RNAs with the potential to be biomarkers for disease prediction. In addition, computer-aided biomarker discovery is now becoming an attractive paradigm for precision diagnosis and prognosis of complex diseases. Methods In this study, we identified key microRNAs as biomarkers for predicting PCa metastasis based on network vulnerability analysis. We first extracted microRNAs and mRNAs that were differentially expressed between primary PCa and metastatic PCa (MPCa) samples. Then we constructed the MPCa-specific microRNA-mRNA network and screened microRNA biomarkers by a novel bioinformatics model. The model emphasized the characterization of systems stability changes and the network vulnerability with three measurements, i.e. the structurally single-line regulation, the functional importance of microRNA targets and the percentage of transcription factor genes in microRNA unique targets. Results With this model, we identified five microRNAs as putative biomarkers for PCa metastasis. Among them, miR-101-3p and miR-145-5p have been previously reported as biomarkers for PCa metastasis and the remaining three, i.e. miR-204-5p, miR-198 and miR-152, were screened as novel biomarkers for PCa metastasis. The results were further confirmed by the assessment of their predictive power and biological function analysis. Conclusions Five microRNAs were identified as candidate biomarkers for predicting PCa metastasis based on our network vulnerability analysis model. The prediction performance, literature exploration and functional enrichment analysis convinced our findings. This novel bioinformatics model could be applied to biomarker discovery for other complex diseases.http://link.springer.com/article/10.1186/s12967-018-1506-7Bioinformatics modelNetwork vulnerability analysisMicroRNA biomarkersProstate cancer metastasis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yuxin Lin Feifei Chen Li Shen Xiaoyu Tang Cui Du Zhandong Sun Huijie Ding Jiajia Chen Bairong Shen |
spellingShingle |
Yuxin Lin Feifei Chen Li Shen Xiaoyu Tang Cui Du Zhandong Sun Huijie Ding Jiajia Chen Bairong Shen Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model Journal of Translational Medicine Bioinformatics model Network vulnerability analysis MicroRNA biomarkers Prostate cancer metastasis |
author_facet |
Yuxin Lin Feifei Chen Li Shen Xiaoyu Tang Cui Du Zhandong Sun Huijie Ding Jiajia Chen Bairong Shen |
author_sort |
Yuxin Lin |
title |
Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model |
title_short |
Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model |
title_full |
Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model |
title_fullStr |
Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model |
title_full_unstemmed |
Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model |
title_sort |
biomarker micrornas for prostate cancer metastasis: screened with a network vulnerability analysis model |
publisher |
BMC |
series |
Journal of Translational Medicine |
issn |
1479-5876 |
publishDate |
2018-05-01 |
description |
Abstract Background Prostate cancer (PCa) is a fatal malignant tumor among males in the world and the metastasis is a leading cause for PCa death. Biomarkers are therefore urgently needed to detect PCa metastatic signature at the early time. MicroRNAs are small non-coding RNAs with the potential to be biomarkers for disease prediction. In addition, computer-aided biomarker discovery is now becoming an attractive paradigm for precision diagnosis and prognosis of complex diseases. Methods In this study, we identified key microRNAs as biomarkers for predicting PCa metastasis based on network vulnerability analysis. We first extracted microRNAs and mRNAs that were differentially expressed between primary PCa and metastatic PCa (MPCa) samples. Then we constructed the MPCa-specific microRNA-mRNA network and screened microRNA biomarkers by a novel bioinformatics model. The model emphasized the characterization of systems stability changes and the network vulnerability with three measurements, i.e. the structurally single-line regulation, the functional importance of microRNA targets and the percentage of transcription factor genes in microRNA unique targets. Results With this model, we identified five microRNAs as putative biomarkers for PCa metastasis. Among them, miR-101-3p and miR-145-5p have been previously reported as biomarkers for PCa metastasis and the remaining three, i.e. miR-204-5p, miR-198 and miR-152, were screened as novel biomarkers for PCa metastasis. The results were further confirmed by the assessment of their predictive power and biological function analysis. Conclusions Five microRNAs were identified as candidate biomarkers for predicting PCa metastasis based on our network vulnerability analysis model. The prediction performance, literature exploration and functional enrichment analysis convinced our findings. This novel bioinformatics model could be applied to biomarker discovery for other complex diseases. |
topic |
Bioinformatics model Network vulnerability analysis MicroRNA biomarkers Prostate cancer metastasis |
url |
http://link.springer.com/article/10.1186/s12967-018-1506-7 |
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