Analysis of prostate cancer by proteomics using tissue specimens
Analysis of prostate cancer by proteomics using tissue specimens
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DOI：
10.1097/01.ju.0000146543.33543.a3
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发表时间：
2005-01-01
影响因子：
6.6
通讯作者：
Diamond, DL
中科院分区：
文献类型：
--
作者：
Liu, AY;Zhang, H;Diamond, DL
目的：前列腺癌细胞与正常前列腺癌细胞在基因表达上存在差异。因此，癌症和正常组织/细胞将在其蛋白质组中显示差异。从诊断的角度来看，分泌蛋白种类组成的差异尤其相关。我们使用ProteinChip Array（Ciphergen Biosystems，Fremont，加州）表面增强激光解吸/电离（SELDI）飞行时间质谱分析前列腺组织样品以产生表型指纹。我们使用定量蛋白质组学的基础上糖肽捕获，然后通过串联质谱法，以确定差异表达的protein.Materials和方法：患者匹配的癌症和非癌标本消化胶原酶的单细胞。消化后，将细胞沉淀并将无细胞上清液用于分析。使用反相疏水蛋白芯片阵列从43个原发性前列腺肿瘤中产生SELDI模式，其中包括26个匹配的非癌标本。结果：SELDI图谱显示TNM分期相似的肿瘤更可能具有相似的图谱。在定量蛋白质组学上，组织金属蛋白酶抑制剂-1被鉴定为在癌症中下调。组织金属蛋白酶抑制剂-1的表达定位于分泌细胞。结论：SELDI蛋白质谱相对容易进行，通过模式识别在前列腺癌诊断中具有巨大潜力。定量蛋白质组学可以潜在地确定许多前列腺癌特异性生物标志物的身份。
Purpose: Prostate cancer cells differ from their normal counterpart in gene expression. Therefore, cancer and normal tissue/cells would show differences in their proteomes. From a diagnostic standpoint differences in the composition of secreted protein species are especially relevant. We used ProteinChip Array (Ciphergen Biosystems, Fremont, California) surface enhanced laser desorption/ionization (SELDI) time of flight mass spectrometry to profile prostate tissue samples to generate phenomic fingerprints. We used quantitative proteomics based on glycopeptide capture followed by tandem mass spectrometry to identify differentially expressed proteins.Materials and Methods: Patient matched cancer and noncancer specimens were digested by collagenase to single cells. After digestion the cells were pelleted and the cell-free supernatant was used for analysis. A reversed phase hydrophobic ProteinChip Array was used to generate SELDI patterns from 43 primary prostate tumors, including 26 with matched noncancer specimens. Quantitative proteomics was applied to 1 specimen and the expression pattern was verified by Western blotting and immunohistochemistry.Results: SELDI profiles showed that cancers of similar TNM stages were more likely to have similar profiles. On quantitative proteomics tissue metalloproteinase inhibitor-1 was identified to be down-regulated in cancer. Tissue metalloproteinase inhibitor-1 expression was localized to secretory cells.Conclusions: Protein profiling by SELDI is relatively easy to perform and it has great potential in prostate cancer diagnosis through pattern recognition. Quantitative proteomics can potentially determine the identity of many biomarkers specific for prostate cancer.