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

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, an...

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Detalles Bibliográficos
Autores principales: Liu, Yingchao, Wu, Jinsong, Yan, Guoquan, Hou, Ruiping, Zhuang, Dongxiao, Chen, Luping, Pang, Qi, Zhu, Jianhong
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2825229/
https://www.ncbi.nlm.nih.gov/pubmed/20205839
http://dx.doi.org/10.1186/1477-5956-8-2
Descripción
Sumario: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.