Quantitative Proteomic Profiling of Prostate Cancer Reveals a Role for miR-128 in Prostate Cancer
2009; Elsevier BV; Volume: 9; Issue: 2 Linguagem: Inglês
10.1074/mcp.m900159-mcp200
ISSN1535-9484
AutoresAmjad Khan, Laila Poisson, Vadiraja B. Bhat, Damian Fermin, Rong Zhao, Shanker Kalyana‐Sundaram, George Michailidis, Alexey I. Nesvizhskii, Gilbert S. Omenn, Arul M. Chinnaiyan, Arun Sreekumar,
Tópico(s)RNA Research and Splicing
ResumoMultiple, complex molecular events characterize cancer development and progression. Deciphering the molecular networks that distinguish organ-confined disease from metastatic disease may lead to the identification of biomarkers of cancer invasion and disease aggressiveness. Although alterations in gene expression have been extensively quantified during neoplastic progression, complementary analyses of proteomic changes have been limited. Here we interrogate the proteomic alterations in a cohort of 15 prostate-derived tissues that included five each from adjacent benign prostate, clinically localized prostate cancer, and metastatic disease from distant sites. The experimental strategy couples isobaric tags for relative and absolute quantitation with multidimensional liquid phase peptide fractionation followed by tandem mass spectrometry. Over 1000 proteins were quantified across the specimens and delineated into clinically localized and metastatic prostate cancer-specific signatures. Included in these class-specific profiles were both proteins that were known to be dysregulated during prostate cancer progression and new ones defined by this study. Enrichment analysis of the prostate cancer-specific proteomic signature, to gain insight into the functional consequences of these alterations, revealed involvement of miR-128-a/b regulation during prostate cancer progression. This finding was validated using real time PCR analysis for microRNA transcript levels in an independent set of 15 clinical specimens. miR-128 levels were elevated in benign prostate epithelial cell lines compared with invasive prostate cancer cells. Knockdown of miR-128 induced invasion in benign prostate epithelial cells, whereas its overexpression attenuated invasion in prostate cancer cells. Taken together, our profiles of the proteomic alterations of prostate cancer progression revealed miR-128 as a potentially important negative regulator of prostate cancer cell invasion. Multiple, complex molecular events characterize cancer development and progression. Deciphering the molecular networks that distinguish organ-confined disease from metastatic disease may lead to the identification of biomarkers of cancer invasion and disease aggressiveness. Although alterations in gene expression have been extensively quantified during neoplastic progression, complementary analyses of proteomic changes have been limited. Here we interrogate the proteomic alterations in a cohort of 15 prostate-derived tissues that included five each from adjacent benign prostate, clinically localized prostate cancer, and metastatic disease from distant sites. The experimental strategy couples isobaric tags for relative and absolute quantitation with multidimensional liquid phase peptide fractionation followed by tandem mass spectrometry. Over 1000 proteins were quantified across the specimens and delineated into clinically localized and metastatic prostate cancer-specific signatures. Included in these class-specific profiles were both proteins that were known to be dysregulated during prostate cancer progression and new ones defined by this study. Enrichment analysis of the prostate cancer-specific proteomic signature, to gain insight into the functional consequences of these alterations, revealed involvement of miR-128-a/b regulation during prostate cancer progression. This finding was validated using real time PCR analysis for microRNA transcript levels in an independent set of 15 clinical specimens. miR-128 levels were elevated in benign prostate epithelial cell lines compared with invasive prostate cancer cells. Knockdown of miR-128 induced invasion in benign prostate epithelial cells, whereas its overexpression attenuated invasion in prostate cancer cells. Taken together, our profiles of the proteomic alterations of prostate cancer progression revealed miR-128 as a potentially important negative regulator of prostate cancer cell invasion. Prostate cancer is the second most common cause of cancer-related death in America and afflicts one of nine men over the age of 65. The American Cancer Society estimates that 186,320 American men will be diagnosed with prostate cancer and 28,660 will die this year (1American Cancer Society How Many Men Get Prostate Cancer? American Cancer Society, Atlanta, GA2008Google Scholar). The advent of prostate-specific antigen (PSA) 1The abbreviations used are:PSAprostate-specific antigenBPHbenign prostatic hyperplasiaPCAprostate cancerOCMOncomine Concepts MapBenignbenign adjacent prostateMetsmetastatic prostate tumoriTRAQisobaric tags for relative and absolute quantitationQ-PCRquantitative RT-PCRPHBProhibitinSCXstrong cation exchangeIPIInternational Protein IndexFDRfalse discovery rateIDidentificationPrECprostate epithelial cellsGOLM1Golgi membrane protein 1TMSB10Thymosin β10VIMVimentinAPRILA Proliferation Inducing LigandVCPValosin Containing ProteinLPPLipoma Preferred PartnerTROVETelomerase RO and VaultCTthreshold cycle. 1The abbreviations used are:PSAprostate-specific antigenBPHbenign prostatic hyperplasiaPCAprostate cancerOCMOncomine Concepts MapBenignbenign adjacent prostateMetsmetastatic prostate tumoriTRAQisobaric tags for relative and absolute quantitationQ-PCRquantitative RT-PCRPHBProhibitinSCXstrong cation exchangeIPIInternational Protein IndexFDRfalse discovery rateIDidentificationPrECprostate epithelial cellsGOLM1Golgi membrane protein 1TMSB10Thymosin β10VIMVimentinAPRILA Proliferation Inducing LigandVCPValosin Containing ProteinLPPLipoma Preferred PartnerTROVETelomerase RO and VaultCTthreshold cycle. screening has led to earlier detection of prostate cancer (2Catalona W.J. 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Proteomics. 2008; 7: 1162-1173Abstract Full Text Full Text PDF PubMed Scopus (185) Google Scholar) have used iTRAQ-based quantification to assess global alterations in the proteome using tissues from prostate cancer and head and neck cancer patients, respectively. We used a similar approach to quantify global changes associated with the prostate cancer proteome in the stages of progression from organ-confined to metastatic disease. Additionally, we extended our analysis beyond delineation of tumor-specific proteomic signatures to nominate and confirm the miR-128 pathway as a critical intermediary in tumor invasion.EXPERIMENTAL PROCEDURESPatient Population and Sample SelectionThe Institutional Review Board of the University of Michigan Medical School approved this study on discovery of proteomic alterations of prostate cancer progression. Tissue samples obtained postsurgery from clinically localized prostate cancer patients (PCA; n = 5), advanced prostate cancer patients (Mets; n = 5), and benign adjacent controls (Benign; n = 5) were procured in a frozen state from the University of Michigan Specialized Research Program in Prostate Cancer (Specialized Program of Research Excellence) tissue bank. Two men provided both tumor and benign tissue samples. All other tissue samples were from unique patients. Deidentified numeric specimen codes were used to protect the identity of the men. Detailed clinical and pathology data for this study are available in supplemental Table 1. The histological diagnosis of each sample was confirmed by microscopic examination of hematoxylin- and eosin-stained frozen sections by a board-certified pathologist.Chemicals and ReagentsAll chemicals were purchased from Sigma unless otherwise mentioned.AntibodiesMouse monoclonal antibodies directed to Vimentin (VIM), Ezrin, RAN, and fatty-acid synthase and polyclonal antibodies to SLC25A3, Thymosin β10 (TMSB10), and Prohibitin (PHB) were purchased from BD Biosciences and Novus Biologicals (Littleton, CO), respectively. Goat polyclonal antibodies against ARF1, APRIL (ANP32B), and glyceraldehyde-3-phosphate dehydrogenase were procured from Abcam Inc. (Cambridge, MA), and VCP antibodies were purchased from Santa Cruz Biotechnology (Santa Cruz, CA). Antibodies to RAP1B and TROVE domain family member 2 (TROVE2) were purchased from Cell Signaling Technologies (Danvers, MA) and Genway (San Diego, CA), respectively. Rabbit polyclonal antibodies to Golgi membrane protein 1 (GOLM1) were a kind gift from Dr. Claus J. Fimmel (Edward Hines Veterans Affairs Medical Center, Hines, IL).Protein ExtractionFor protein extraction, the tissue samples were resuspended in lysis buffer consisting of 7 m urea, 2 m thiourea, 100 mm DTT, 0.5% Bio-Lyte pH 3–10 (Bio-Rad), 2% octyl glucoside, and 1 mm PMSF. Samples were lysed at room temperature for 30 min followed by centrifugation at 35,000 rpm at 4 °C for 1 h. The protein solution was exchanged into 50 mm triethylammonium bicarbonate, pH 9 using a PD-10 column according to the manufacturer's instruction (GE Healthcare). Total protein content was measured using the Bradford assay (Bio-Rad), and the lysates were stored at −80 °C for future use.Protein Digestion and iTRAQ Labeling200 µg of total protein from each tissue sample were used to generate iTRAQ-labeled peptides according to the manufacturer's protocol. Specifically, the proteins were first subjected to reduction and alkylation using DTT and iodoacetamide provided in the iTRAQ labeling kit (iTRAQ® Reagents Multiplex kit, Applied Biosystems, Foster City, CA). They were then digested to peptides using porcine trypsin (1:50; Promega, Madison, WI) in 50 mm triethylammonium bicarbonate, pH 9. The digestion was performed for 24 h at 37 °C. At the end of 24 h, the trypsin activity was stopped using 3% formic acid. The digested peptides were subjected to iTRAQ labeling according to the protocol described previously (36Keshamouni V.G. Michailidis G. Grasso C.S. Anthwal S. Strahler J.R. Walker A. Arenberg D.A. Reddy R.C. Akulapalli S. Thannickal V.J. Standiford T.J. Andrews P.C. Omenn G.S. Differential protein expression profiling by iTRAQ-2DLC-MS/MS of lung cancer cells undergoing epithelial-mesenchymal transition reveals a migratory/invasive phenotype.J. Proteome Res. 2006; 5: 1143-1154Crossref PubMed Scopus (251) Google Scholar). The iTRAQ experiments were performed in five sets, each containing four samples. Specifically, for labeling, 100 µg of protein each from Benign, PCA, and Mets were labeled with isobaric tags 114, 115, and 116, respectively (Fig. 1). A reference pool containing 67 µg of protein from each of the tissue samples (n = 5 each of Benign, PCA, and Mets) used in the study was created (total protein amount in the pool, 1 mg) and labeled with isobaric tag 117 (see Fig. 1). 50 µg of peptides labeled with each of the four isobaric labels were combined and subjected to two-dimensional fractionation coupled to tandem mass spectrometry (Fig. 1).SCX Fractionation200 µg of iTRAQ-labeled peptide samples described above were completely dried in a SpeedVac, resuspended in 40 µl of 0.1% formic acid in 5% acetonitrile (mobile phase A), and directly loaded onto a 1 × 150-mm polysulfoethyl aspartamide strong cation exchange column (Michrom Bioresources, Auburn, CA) using an Agilent 1200 auto sampler. Buffer containing 1 m ammonium formate, 10% formic acid in 5% acetonitrile (mobile phase B) was used to create a linear chromatographic gradient at a flow rate of 50 µl/min. A total of 10 fractions were collected over a 40-min gradient encompassing a salt concentration of 0–100 mm ammonium formate. An additional five fractions were generated over the next 10 min at a higher salt concentration range of 100–1000 mm. Fractionated peptides were completely dried and reconstituted in 10 µl of 0.1% TFA prior to LC-MS/MS analysis.HPLC-Chip/Mass Spectrometry AnalysisRefer to Fig. 1 for an outline. A total of 3 µl of reconstituted peptide mixture (∼30% of SCX fraction) was injected onto an LC-MS system consisting of a 1200 Series liquid chromatograph, HPLC-Chip Cube MS interface, and 6510 Q-TOF mass spectrometer (all Agilent Technologies, Santa Clara, CA). The system was equipped with an HPLC-Chip (Agilent Technologies) that incorporated either a 40-nl enrichment column and a 43 mm × 5 µm reverse phase column (low capacity chip) or a 160-nl enrichment column and a 150 mm × 75 µm reverse phase column (high capacity chip). In both cases, the reverse phase column was packed with Zorbax 300SB-C18 5-µm particles. Three analytical replicates of each of the five iTRAQ sets were analyzed by mass spectrometry. This included duplicate analysis on the high capacity chip (henceforth termed high capacity 1 and high capacity 2) and a single run on a low capacity chip (henceforth termed low capacity). Overall the experimental design resulted in a total of 15 independent mass spectrometry data points or experiments (n = 3 for each iTRAQ set) for the entire study.For each mass spectrometry experiment, peptides were loaded onto the enrichment column with 97% solvent A (water with 0.1% formic acid). A two-step gradient generated at a flow rate 0.3 µl/min was used for peptide elution. This included a linear gradient from 3% B (acetonitrile with 0.1% formic acid) to 45% B over 25 min followed by a sharp increase to 90% B within 5 min. The total run time, including column reconditioning, was 40 min. The column effluent in all cases was directly analyzed by the 6510 Q-TOF mass spectrometer that was interfaced in tandem through an HPLC-Chip Cube nanospray source. The latter was operated at a capillary voltage of 1900 V with a capillary current of 1.1 µA in 1 GHz. The MS data were acquired in the positive ionization mode using Agilent MassHunter Workstation Q-TOF B.01.03. During the course of data acquisition, the fragmentor voltage, skimmer voltage, and octopole RF were set to 175, 65, and 750 V, respectively. Auto-MS/MS was performed with a total cycle time of 1.97 s. In each cycle, MS spectra were acquired at 3 Hz (three spectra/s) (m/z 450–1500), and the four most abundant ions (with charge states 2+, 3+, and >3+) exceeding 2000 counts were selected for MS/MS at 3 Hz (three spectra/s) (m/z 50–2000). A medium isolation (4 m/z) window was used for precursor isolation. A collision energy with slope of 3.9 V/100 Da and offset of 2.9 V was used for fragmentation. Reference mass correction was activated using a reference mass of 1221.99. Precursors were set in an exclusion list for 0.5 min after two MS/MS spectra.Mass Spectral Data AnalysisMS/MS spectra generated above were extracted from the raw data in mzXML file format using a converter from the Institute for Systems Biology (trapper). The mzXML files were searched using SEQUEST against the human International Protein Index (IPI) database version 3.26 (containing 67,655 entries) appended with an equal number of decoy sequences (reversed sequences from the original database). The following search parameters were selected: 0.5-Da precursor mass tolerance, monoisotopic mass, semitryptic search with two or fewer missed cleavages, oxidized methionine specified as a variable modif
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