Browsing by Author "Lin, Si-Yu"
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Item type:Item, Identification of the PCa28 gene signature as a predictor in prostate cancer(2018-01-01) ;Lee, Jung-Yu ;Lin, Si-Yu ;Chuang, Yi-Hsuan ;Huang, Sing-HanTseng, Yu-YaoProstate 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.Item type:Item, Identification of the PCA29 gene signature as a predictor in prostate cancer(2019-06-01) ;Lee, Jung-Yu ;Lin, Si-Yu ;Lin, Chun-Yu ;Chuang, Yi-HuanHuang, Sing-HanProstate cancer (PCa) is the second leading cause of cancer death among men worldwide. 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. The identification of biomarkers for diagnosis and prognosis is an urgent clinical issue for PCa. Here, we developed a novel scoring strategy, including cluster score (CS) and predicting score (PS), to identify 29 PCa genes (called PCa29) for early diagnostic biomarkers from two datasets in Gene Expression Omnibus. The result indicates that PCa29 can discriminate between normal and tumor tissues and are specific for prostate cancer. To validate PCa29, we found that 97% of PCa29 were consistently significant with these gene expressions in The Cancer Genome Atlas; furthermore, similar to 70% of PCa29 are consensus to the protein expression in The Human Protein Atlas. Finally, we examined 10 genes in PCa29 on three PCa cell lines by real-time quantitative polymerase chain reaction. The experimental results show that the trend of the differential PCa29 expression is consistent with the analyzed results from our novel scoring method. We believe that our method is useful and PCa29 are potential biomarkers that provide the clues to develop targeting therapy for PCa.