Identification of Novel Prognosis and Prediction Markers in Advanced Prostate Cancer Tissues Based on Quantitative Proteomics
Identification of Novel Prognosis and Prediction Markers in Advanced Prostate Cancer Tissues Based on Quantitative Proteomics
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DOI：
10.21873/cgp.20180
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发表时间：
2020-03-01
影响因子：
2.5
通讯作者：
Lee, Sangkyu
中科院分区：
文献类型：
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作者：
Kwon, Oh Kwang;Ha, Yun-Sok;Lee, Sangkyu
背景/目的：前列腺癌(Pca)是世界范围内最常见的男性癌症，其死亡率呈逐年上升趋势。然而，目前尚无进展期或侵袭性PCa的分子标志物，临床迫切需要可用于PCa预后和预测的生物标志物。材料和方法：采用基于质谱学的蛋白质组学方法，从诊断为T2、T3或区域淋巴结转移的前列腺癌患者的组织中鉴定新的生物标志物。结果：在1,904个蛋白质中，共鉴定出344个差异表达蛋白质，其中124个表达上调，216个表达下调。随后，基于偏最小二乘判别分析、基因本体论和京都百科全书的基因和基因组浓缩分析结果，我们提出精胺合成酶(SRM)、核仁和盘状体磷蛋白1(NOLC1)和前列环素合成酶(PTGIS)是诊断晚期PCa的新的蛋白质生物标志物。转移性前列腺癌细胞系的免疫印迹试验和前列腺标本的间接酶联免疫吸附试验证实了这些蛋白质组学结果。结论：SRM随肿瘤分期的不同而显著增加，证实了SRM作为预测晚期PCa预后的生物标志物的可能性。
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.