Dataset Information

Phosphoproteome profiles of prostate cancer cell lines

ABSTRACT: Prostate cancer (PCa) is a major public health issue in industrialized countries, mainly because of patients’ relapse by castration-refractory disease after androgen ablation. PCa progresses through a series of clinical states characterized by the extent of the disease, the hormonal status (castration-sensitive or castration-resistant) and the presence or absence of metastases. Progression to castration-resistant prostate cancer (CRPCa) involves several mechanisms such as ligand-independent androgen receptor activation and adaptive up-regulation of anti-apoptotic genes. CRPCa is highly aggressive and incurable, jeopardizing the patient’s quality of life and lifespan. Identifying the molecular events responsible for the progression to CRPCa is essential to avoid its development and design specific therapies. Despite the existing treatment guidelines for PCa and novel clinical trials for CRPCa, major challenges still remain for identifying specific CRPCa biomarkers and therapeutic targets for effective tailored therapy design for these patients. In this context, molecular profiling of human PCa may importantly contribute to the identification of new disease-specific biomarkers in order to improve PCa early diagnosis, prognosis and disease course and to predict strategies that help develop novel therapies. System-wide approaches such as transcriptomics and proteomics are nowadays applied to monitor molecular variations at the cellular level. Proteomics approaches offer a great potential for the discovery of novel biomarkers and the identification of new therapeutic agents by accurate quantification of proteins. Several studies have been published in the past where different proteomics approaches were used to identify PCa proteome. In the present study we analyzed the PCa proteome from several PCa cell lines representing different hormonal status of the disease to identify potential biomarkers differentially expressed in CRPCa.

INSTRUMENT(S): LTQ Orbitrap Velos, Q Exactive

ORGANISM(S): Homo Sapiens (human)

DISEASE(S): Prostate Adenocarcinoma

SUBMITTER: Luc Camoin

LAB HEAD: Luc Camoin

PROVIDER: PXD004992 | Pride | 2020-01-14

REPOSITORIES: pride

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Dataset's files

Source:

			Action	DRS
	150814_LNCaP_NT10_TiO2_Elut1.raw	Raw
	150814_LNCaP_NT10_TiO2_Elut1_StepNCE23-29.raw	Raw
	150814_LNCaP_NT10_TiO2_Elut2.raw	Raw
	150814_LNCaP_NT10_TiO2_Elut2_StepNCE23-29.raw	Raw
	150814_LNCaP_NT10_TiO2_Elut3.raw	Raw

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Publications

Integrative proteomic and phosphoproteomic profiling of prostate cell lines.

Katsogiannou Maria M Boyer Jean-Baptiste JB Valdeolivas Alberto A Remy Elisabeth E Calzone Laurence L Audebert Stéphane S Rocchi Palma P Camoin Luc L Baudot Anaïs A

PloS one 20191101 11

<h4>Background</h4>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.<h4>Methods</h4>We conducted here a large SILAC-based Mass Spectrometry experiment to map the proteomes and ...[more]

PMID: 31675377

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Project description:Background: Aldo-keto reductase (AKR) 1C family member 3 (AKR1C3), one of four identified human AKR enzymes, catalyzes steroid, prostaglandin, and xenobiotic metabolism. In the prostate, AKR1C3 is up-regulated in localized and advanced prostate adenocarcinoma, and is associated with prostate cancer (PCa) aggressiveness. Here we provide initial evidence for potential roles of AKR1C3 in PCa progression. Methods: Spatial distribution of AKR1C3 was analyzed using immunohistochemical staining in prostate adenocarcinoma tissue array. Human PCa PC-3 cells were stably transfected with AKR1C3 cDNA to establish PC3-AKR1C3 transfectants. Microarray and bioinformatics analyses were performed to identify pathways that are activated by elevated AKR1C3 expression in PCa cells. Functional confirmation of microarray and bioinformatics results was performed by immunoblot analysis and an in vitro Matrigel angiogenesis assay. Results: Elevated AKR1C3 expression was specifically limited to human prostate adenocarcinoma. Microarray and bioinformatics analysis suggested that elevated AKR1C3 expression in PC-3 cells modulates estradiol and androgen metabolism and activates insulin growth factor (IGF)-1 and Akt signaling pathways. Immunoblots confirmed that phosphorylated levels of IGF-1 receptor (IGF-1R) and Akt are significantly up-regulated in PC3-AKR1C3 as compared to mock transfectants. PC3-AKR1C3 transfectants promoted endothelial cell tube formation in Matrigel as compared to parental PC-3 cells and mock transfectants. Conclusion: Microarray and bioinformatics data followed by biological analyses suggest that elevated AKR1C3 expression in PC-3 cells promotes PCa angiogenesis and aggressiveness. These results suggest AKR1C3 can promote the aggressiveness of PCa through modulating estrogen and androgen metabolism with subsequent activation of growth factor IGF-1 and cytoplasmic Akt signaling pathways. Total RNA from mock- and ACR1C3 transfected PC-3 cells was isolated, with 2 or 3 biological replicates each. Gene expression data from AKR1C3 transfected PC-3 cells were compared with mock-transfected data.