TY - JOUR T1 - Identification of Novel Prognosis and Prediction Markers in Advanced Prostate Cancer Tissues Based on Quantitative Proteomics JF - Cancer Genomics - Proteomics JO - Cancer Genomics Proteomics SP - 195 LP - 208 DO - 10.21873/cgp.20180 VL - 17 IS - 2 AU - OH KWANG KWON AU - YUN-SOK HA AU - ANN-YAE NA AU - SO YOUNG CHUN AU - TAE GYUN KWON AU - JUN NYUNG LEE AU - SANGKYU LEE Y1 - 2020/03/01 UR - http://cgp.iiarjournals.org/content/17/2/195.abstract N2 - Background/Aim: Prostate cancer (PCa) is the most frequent cancer found in males worldwide, and its mortality rate is increasing every year. However, there are no known molecular markers for advanced or aggressive PCa, and there is an urgent clinical need for biomarkers that can be used for prognosis and prediction of PCa. Materials and Methods: Mass spectrometry-based proteomics was used to identify new biomarkers in tissues obtained from patients with PCa who were diagnosed with T2, T3, or metastatic PCa in regional lymph nodes. Results: Among 1,904 proteins identified in the prostate tissues, 344 differentially expressed proteins were defined, of which 124 were up-regulated and 216 were down-regulated. Subsequently, based on the results of partial least squares discriminant analysis and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses, we proposed that spermidine synthase (SRM), nucleolar and coiled-body phosphoprotein 1 (NOLC1), and prostacyclin synthase (PTGIS) represent new protein biomarkers for diagnosis of advanced PCa. These proteomics results were verified by immunoblot assays in metastatic PCa cell lines and by indirect enzyme-linked immunosorbent assay in prostate specimens. Conclusion: SRM was significantly increased depending on the cancer stage, confirming the possibility of using SRM as a biomarker for prognosis and prediction of advanced PCa. ER -