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- W2955345908 abstract "ABSTRACT Background Prostate cancer is a major public health issue, mainly because patients relapse after androgen deprivation therapy. Proteomic strategies, aiming to reflect the functional activity of cells, are nowadays among the leading approaches to tackle the challenges not only of better diagnosis, but also of unraveling mechanistic details related to disease etiology and progression. Methods We conducted here a large SILAC-based Mass Spectrometry experiment to map the proteomes and phosphoproteomes of four widely used prostate cell lines, namely PNT1A, LNCaP, DU145 and PC3, representative of different cancerous and hormonal status. Results We identified more than 3000 proteins and phosphosites, from which we quantified more than 1000 proteins and 500 phosphosites after stringent filtering. Extensive exploration of this proteomics and phosphoproteomics dataset allowed characterizing housekeeping as well as cell-line specific proteins, phosphosites and functional features of each cell line. In addition, by comparing the sensitive and resistant cell lines, we identified protein and phosphosites differentially expressed in the resistance context. Further data integration in a molecular network highlighted the differentially expressed pathways, in particular migration and invasion, RNA splicing, DNA damage repair response and transcription regulation. Conclusions Overall, this study proposes a valuable resource toward the characterization of proteome and phosphoproteome of four widely used prostate cell lines and reveals candidates to be involved in prostate cancer progression for further experimental validation." @default.
- W2955345908 created "2019-07-12" @default.
- W2955345908 creator A5002637615 @default.
- W2955345908 creator A5005126161 @default.
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- W2955345908 creator A5080878366 @default.
- W2955345908 creator A5082003101 @default.
- W2955345908 date "2019-07-09" @default.
- W2955345908 modified "2023-10-18" @default.
- W2955345908 title "Integrative proteomic and phosphoproteomic profiling of prostate cell lines" @default.
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