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免疫激光捕获显微切割联合在线二维纳升级液相色谱/质谱分析催乳素瘤细胞的蛋白质组学研究。

Proteomic analysis of prolactinoma cells by immuno-laser capture microdissection combined with online two-dimensional nano-scale liquid chromatography/mass spectrometry.

机构信息

Department of Neurosurgery, Shandong Provincial hospital affiliated to Shandong University, Jinan, 250021, China.

Shanghai Neurosurgical Center, Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China.

出版信息

Proteome Sci. 2010 Jan 29;8:2. doi: 10.1186/1477-5956-8-2.

Abstract

BACKGROUND

Pituitary adenomas, the third most common intracranial tumor, comprise nearly 16.7% of intracranial neoplasm and 25%-44% of pituitary adenomas are prolactinomas. Prolactinoma represents a complex heterogeneous mixture of cells including prolactin (PRL), endothelial cells, fibroblasts, and other stromal cells, making it difficult to dissect the molecular and cellular mechanisms of prolactin cells in pituitary tumorigenesis through high-throughout-omics analysis. Our newly developed immuno-laser capture microdissection (LCM) method would permit rapid and reliable procurement of prolactin cells from this heterogeneous tissue. Thus, prolactin cell specific molecular events involved in pituitary tumorigenesis and cell signaling can be approached by proteomic analysis.

RESULTS

Proteins from immuno-LCM captured prolactin cells were digested; resulting peptides were separated by two dimensional-nanoscale liquid chromatography (2D-nanoLC/MS) and characterized by tandem mass spectrometry. All MS/MS spectrums were analyzed by SEQUEST against the human International Protein Index database and a specific prolactinoma proteome consisting of 2243 proteins was identified. This collection of identified proteins by far represents the largest and the most comprehensive database of proteome for prolactinoma. Category analysis of the proteome revealed a widely unbiased access to various proteins with diverse functional characteristics.

CONCLUSIONS

This manuscript described a more comprehensive proteomic profile of prolactinomas compared to other previous published reports. Thanks to the application of immuno-LCM combined with online two-dimensional nano-scale liquid chromatography here permitted identification of more proteins and, to our best knowledge, generated the largest prolactinoma proteome. This enlarged proteome would contribute significantly to further understanding of prolactinoma tumorigenesis which is crucial to the management of prolactinomas.

摘要

背景

垂体腺瘤是第三大常见颅内肿瘤,占颅内肿瘤的近 16.7%,其中 25%-44%为催乳素瘤。催乳素瘤是一种由催乳素(PRL)、内皮细胞、成纤维细胞和其他基质细胞组成的复杂异质混合物,这使得通过高通量组学分析来剖析催乳素细胞在垂体肿瘤发生中的分子和细胞机制变得非常困难。我们新开发的免疫激光捕获显微切割(LCM)方法将允许从这种异质组织中快速可靠地获取催乳素细胞。因此,通过蛋白质组学分析可以研究涉及垂体肿瘤发生和细胞信号传导的催乳素细胞特异性分子事件。

结果

免疫 LCM 捕获的催乳素细胞中的蛋白质被消化;所得肽段通过二维纳升液相色谱(2D-nanoLC/MS)分离,并通过串联质谱进行鉴定。所有 MS/MS 光谱均通过 SEQUEST 与人类国际蛋白质索引数据库以及由 2243 种蛋白质组成的特定催乳素瘤蛋白质组进行比对分析。到目前为止,这个由鉴定蛋白组成的集合代表了最大和最全面的催乳素瘤蛋白质组数据库。蛋白质组的类别分析揭示了对具有不同功能特征的各种蛋白质的广泛无偏见的访问。

结论

与其他先前发表的报告相比,本文描述了催乳素瘤更全面的蛋白质组学特征。免疫 LCM 与在线二维纳升液相色谱的联合应用在这里允许鉴定更多的蛋白质,据我们所知,产生了最大的催乳素瘤蛋白质组。这个扩大的蛋白质组将对进一步了解催乳素瘤的肿瘤发生做出重大贡献,这对于催乳素瘤的管理至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ec4/2825229/97de187fd36c/1477-5956-8-2-1.jpg

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