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dc.contributor.authorLee, Jung-Yuen_US
dc.contributor.authorLin, Si-Yuen_US
dc.contributor.authorChuang, Yi-Hsuanen_US
dc.contributor.authorHuang, Sing-Hanen_US
dc.contributor.authorTseng, Yu-Yaoen_US
dc.contributor.authorYang, Jinn-Moonen_US
dc.contributor.authorLin, Chun-Yuen_US
dc.contributor.authorWang, Hung-Jungen_US
dc.date.accessioned2019-04-02T06:04:24Z-
dc.date.available2019-04-02T06:04:24Z-
dc.date.issued2018-01-01en_US
dc.identifier.issn2471-7819en_US
dc.identifier.urihttp://dx.doi.org/10.1109/BIBE.2018.00037en_US
dc.identifier.urihttp://hdl.handle.net/11536/150964-
dc.description.abstractProstate cancer (PCa) is the second-leading cause of cancer death among men in the worldwide. Most PCa is slowly growing and usually early symptomless. About 70% of PCa patients were diagnosed at later stage and metastasis has been observed. Additionally, the cure rate of PCa closely relies on the early diagnosis with biomarkers. Prostatic Specific Antigen (PSA) is currently the only clinical biomarker for PCa diagnosis. However, the PSA test has inherent limitations and has about 75% of false-positive results. The identification of a set of genes (as biomarkers) for diagnosis and prognosis is an urgent clinical issue for PCa. Here, we integrated genome-wide analysis and protein-protein interaction network to identify potential genes for early diagnostic biomarkers of PCa. First, we collected gene expression datasets of 145 PCa samples, consisting of both tumor and corresponding normal tissues, from two different sources in Gene Expression Omnibus (GEO). We found 158 and 268 significantly highly and lowly expressed genes, respectively, in tumor samples. Moreover, we proposed cluster score (CS) and predicting score (PS) to select 28 prostate cancer-related genes (called PCa28). The results indicate that PCa28 can discriminate between the normal/tumor tissues and are specific for prostate cancer. Finally, we examined 8 genes in PCa28 on four PCa cell lines by real time quantitative polymerase chain reaction (RT-qPCR). Experimental results show that up-regulated genes have higher expression level in tumor cells in comparison to normal cells, and down-regulated genes have lower expression level in tumor cells. We believe that our method is useful and PCa28 are potential biomarkers that provide the clues to develop targeting therapy for PCa.en_US
dc.language.isoen_USen_US
dc.subjectprostate canceren_US
dc.subjectgene expression profilingen_US
dc.subjectprotein-protein interaction networken_US
dc.subjectdiagnosisen_US
dc.titleIdentification of the PCa28 gene signature as a predictor in prostate canceren_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1109/BIBE.2018.00037en_US
dc.identifier.journalPROCEEDINGS 2018 IEEE 18TH INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOENGINEERING (BIBE)en_US
dc.citation.spage155en_US
dc.citation.epage158en_US
dc.contributor.department生物資訊及系統生物研究所zh_TW
dc.contributor.departmentInstitude of Bioinformatics and Systems Biologyen_US
dc.identifier.wosnumberWOS:000455225600029en_US
dc.citation.woscount0en_US
Appears in Collections:Conferences Paper