Portal de Periódicos da CAPES

Identification of Novel Response and Predictive Biomarkers to Hsp90 Inhibitors Through Proteomic Profiling of Patient-derived Prostate Tumor Explants

2018; Elsevier BV; Volume: 17; Issue: 8 Linguagem: Inglês

10.1074/mcp.ra118.000633

1535-9484

Elizabeth V. Nguyen, Margaret M. Centenera, Max Moldovan, Rajdeep Das, Swati Irani, Andrew Vincent, Howard Chan, Lisa G. Horvath, David J. Lynn, Roger J. Daly, Lisa M. Butler,

Hepatitis B Virus Studies

Inhibition of the heat shock protein 90 (Hsp90) chaperone is a promising therapeutic strategy to target expression of the androgen receptor (AR) and other oncogenic drivers in prostate cancer cells. However, identification of clinically-relevant responses and predictive biomarkers is essential to maximize efficacy and treatment personalization. Here, we combined mass spectrometry (MS)-based proteomic analyses with a unique patient-derived explant (PDE) model that retains the complex microenvironment of primary prostate tumors. Independent discovery and validation cohorts of PDEs (n = 16 and 30, respectively) were cultured in the absence or presence of Hsp90 inhibitors AUY922 or 17-AAG. PDEs were analyzed by LC-MS/MS with a hyper-reaction monitoring data independent acquisition (HRM-DIA) workflow, and differentially expressed proteins identified using repeated measure analysis of variance (ANOVA; raw p value <0.01). Using gene set enrichment, we found striking conservation of the most significantly AUY922-altered gene pathways between the discovery and validation cohorts, indicating that our experimental and analysis workflows were robust. Eight proteins were selectively altered across both cohorts by the most potent inhibitor, AUY922, including TIMP1, SERPINA3 and CYP51A (adjusted p < 0.01). The AUY922-mediated decrease in secretory TIMP1 was validated by ELISA of the PDE culture medium. We next exploited the heterogeneous response of PDEs to 17-AAG in order to detect predictive biomarkers of response and identified PCBP3 as a marker with increased expression in PDEs that had no response or increased in proliferation. Also, 17-AAG treatment led to increased expression of DNAJA1 in PDEs that exhibited a cytostatic response, revealing potential drug resistance mechanisms. This selective regulation of DNAJA1 was validated by Western blot analysis. Our study establishes "proof-of-principle" that proteomic profiling of drug-treated PDEs represents an effective and clinically-relevant strategy for identification of biomarkers that associate with certain tumor-specific responses. Inhibition of the heat shock protein 90 (Hsp90) chaperone is a promising therapeutic strategy to target expression of the androgen receptor (AR) and other oncogenic drivers in prostate cancer cells. However, identification of clinically-relevant responses and predictive biomarkers is essential to maximize efficacy and treatment personalization. Here, we combined mass spectrometry (MS)-based proteomic analyses with a unique patient-derived explant (PDE) model that retains the complex microenvironment of primary prostate tumors. Independent discovery and validation cohorts of PDEs (n = 16 and 30, respectively) were cultured in the absence or presence of Hsp90 inhibitors AUY922 or 17-AAG. PDEs were analyzed by LC-MS/MS with a hyper-reaction monitoring data independent acquisition (HRM-DIA) workflow, and differentially expressed proteins identified using repeated measure analysis of variance (ANOVA; raw p value <0.01). Using gene set enrichment, we found striking conservation of the most significantly AUY922-altered gene pathways between the discovery and validation cohorts, indicating that our experimental and analysis workflows were robust. Eight proteins were selectively altered across both cohorts by the most potent inhibitor, AUY922, including TIMP1, SERPINA3 and CYP51A (adjusted p < 0.01). The AUY922-mediated decrease in secretory TIMP1 was validated by ELISA of the PDE culture medium. We next exploited the heterogeneous response of PDEs to 17-AAG in order to detect predictive biomarkers of response and identified PCBP3 as a marker with increased expression in PDEs that had no response or increased in proliferation. Also, 17-AAG treatment led to increased expression of DNAJA1 in PDEs that exhibited a cytostatic response, revealing potential drug resistance mechanisms. This selective regulation of DNAJA1 was validated by Western blot analysis. Our study establishes "proof-of-principle" that proteomic profiling of drug-treated PDEs represents an effective and clinically-relevant strategy for identification of biomarkers that associate with certain tumor-specific responses. Prostate cancer is the most commonly diagnosed cancer, and the second leading cause of cancer-related death, in men in the developed world (1Jemal A. Siegel R. Xu J. Ward E. Cancer statistics, 2010.Cancer J. Clin. 2010; 60 (doi: caac.20073 [pii] 10 3322/caac.20073): 277-300Crossref PubMed Scopus (12357) Google Scholar). Despite intense research efforts, no curative therapies currently exist for men with advanced, metastatic prostate cancer. Consequently, there is an urgent need to develop new therapeutic approaches that will achieve more durable responses and thereby improve patient outcomes. A challenge that has constrained the clinical development of novel agents for prostate and other solid tumors is the difficulty in predicting and monitoring their clinical efficacy. Despite promising in vitro findings, preclinical efficacy of new therapeutics does not necessarily translate into clinical activity (2Johnson J.I. Decker S. Zaharevitz D. Rubinstein L.V. Venditti J.M. Schepartz S. Kalyandrug S. Christian M. Arbuck S. Hollingshead M. Sausville E.A. Relationships between drug activity in NCI preclinical in vitro and in vivo models and early clinical trials.Br. J. Cancer. 2001; 84: 1424-1431Crossref PubMed Scopus (623) Google Scholar, 3Voskoglou-Nomikos T. Pater J.L. Seymour L. Clinical predictive value of the in vitro cell line, human xenograft, and mouse allograft preclinical cancer models.Clin. Cancer Res. 2003; 9: 4227-4239PubMed Google Scholar), with only 5% of all potential anticancer compounds ever gaining regulatory approval (4Kamb A. Wee S. Lengauer C. Why is cancer drug discovery so difficult?.Nat. Rev. Drug Discovery. 2007; 6: 115-120Crossref PubMed Scopus (278) Google Scholar). The reasons for this inefficiency of research translation are complex, but two clear problems have been identified: a lack of preclinical models that accurately predict activity of new agents, and a lack of robust biomarkers indicating an individual patient's response to an agent (5Scher H.I. Halabi S. Tannock I. Morris M. Sternberg C.N. Carducci M.A. Eisenberger M.A. Higano C. Bubley G.J. Dreicer R. Petrylak D. Kantoff P. Basch E. Kelly W.K. Figg W.D. Small E.J. Beer T.M. Wilding G. Martin A. Hussain M. Design and end points of clinical trials for patients with progressive prostate cancer and castrate levels of testosterone: recommendations of the Prostate Cancer Clinical Trials Working Group.J. Clin. Oncol. 2008; 26: 1148-1159Crossref PubMed Scopus (1787) Google Scholar, 6Tan D.S. Thomas G.V. Garrett M.D. Banerji U. de Bono J.S. Kaye S.B. Workman P. Biomarker-driven early clinical trials in oncology: a paradigm shift in drug development.Cancer J. 2009; 15: 406-420Crossref PubMed Scopus (138) Google Scholar, 7Adams D.J. The Valley of Death in anticancer drug development: a reassessment.Trends Pharmacol. Sci. 2012; 33: 173-180Abstract Full Text Full Text PDF PubMed Scopus (62) Google Scholar). A class of agents that exemplifies these challenges is the heat shock protein 90 (Hsp90) 1The abbreviations used are:Hsp90Heat shock protein 9017-AAG17-N-allylamino-17-demethoxygeldanamycinADTAndrogen deprivation therapyAGCAutomatic gain controlANOVAAnalysis of varianceCRPCCastrate-resistant prostate cancerDIAData Independent AcquisitionFAFormic acidFBSFetal bovine serumHCLHydrochloric acidHIF-1Hypoxia-inducible factors −1HRMHyper reaction monitoringiRTRetention-time-normalizedITIon trapMS/MSTandem mass spectrometryNH4OHAmmonium hydroxidePCAPrincipal component analysisPDEPatient-derived prostate cancer explantRPMIRoswell Park Memorial Institute. 1The abbreviations used are:Hsp90Heat shock protein 9017-AAG17-N-allylamino-17-demethoxygeldanamycinADTAndrogen deprivation therapyAGCAutomatic gain controlANOVAAnalysis of varianceCRPCCastrate-resistant prostate cancerDIAData Independent AcquisitionFAFormic acidFBSFetal bovine serumHCLHydrochloric acidHIF-1Hypoxia-inducible factors −1HRMHyper reaction monitoringiRTRetention-time-normalizedITIon trapMS/MSTandem mass spectrometryNH4OHAmmonium hydroxidePCAPrincipal component analysisPDEPatient-derived prostate cancer explantRPMIRoswell Park Memorial Institute. inhibitors. Targeting Hsp90 was considered a particularly attractive therapeutic strategy for prostate cancer as Hsp90 is commonly overexpressed in prostate cancer cells compared with normal prostate epithelium (8Cardillo M.R. Ippoliti F. IL-6, IL-10 and HSP-90 expression in tissue microarrays from human prostate cancer assessed by computer-assisted image analysis.Anticancer Res. 2006; 26: 3409-3416PubMed Google Scholar); therefore, prostate cancer cells are often selectively sensitive to targeting of Hsp90. Moreover, Hsp90 inhibition affords the opportunity to simultaneously degrade the androgen receptor (AR), the driver of prostate tumorigenesis, along with other oncogenic proteins that are Hsp90 clients (e.g. Her2, Akt, and Raf-1). However, despite robust preclinical data demonstrating anti-tumor activity of first-generation ansamycin-derived Hsp90 inhibitors (e.g. 17-AAG) in prostate cancer (9Solit D.B. Zheng F.F. Drobnjak M. Munster P.N. Higgins B. Verbel D. Heller G. Tong W. Cordon-Cardo C. Agus D.B. Scher H.I. Rosen N. 17-Allylamino-17-demethoxygeldanamycin induces the degradation of androgen receptor and HER-2/neu and inhibits the growth of prostate cancer xenografts.Clin. Cancer Res. 2002; 8: 986-993PubMed Google Scholar), poor clinical responses in prostate cancer trials initially cast doubt over this class of agent (10Heath E.I. Hillman D.W. Vaishampayan U. Sheng S. Sarkar F. Harper F. Gaskins M. Pitot H.C. Tan W. Ivy S.P. Pili R. Carducci M.A. Erlichman C. Liu G. A phase II trial of 17-allylamino-17-demethoxygeldanamycin in patients with hormone-refractory metastatic prostate cancer.Clin. Cancer Res. 2008; 14: 7940-7946Crossref PubMed Scopus (152) Google Scholar). This lack of efficacy has been attributed to poor solubility and pharmacokinetics, hepatotoxicity and multidrug resistance mechanisms that prevented adequate therapeutic doses from being achieved (11Trepel J. Mollapour M. Giaccone G. Neckers L. Targeting the dynamic HSP90 complex in cancer.Nat. Rev. Cancer. 2010; 10: 537-549Crossref PubMed Scopus (1148) Google Scholar). Consequently, there has been considerable interest in developing new generation Hsp90 inhibitors such as AUY922, a synthetic resorcinylic isoxazole amide (12Eccles S.A. Massey A. Raynaud F.I. Sharp S.Y. Box G. Valenti M. Patterson L. de Haven Brandon A. Gowan S. Boxall F. Aherne W. Rowlands M. Hayes A. Martins V. Urban F. Boxall K. Prodromou C. Pearl L. James K. Matthews T.P. Cheung K.M. Kalusa A. Jones K. McDonald E. Barril X. Brough P.A. Cansfield J.E. Dymock B. Drysdale M.J. Finch H. Howes R. Hubbard R.E. Surgenor A. Webb P. Wood M. Wright L. Workman P. NVP-AUY922: a novel heat shock protein 90 inhibitor active against xenograft tumor growth, angiogenesis, and metastasis.Cancer Res. 2008; 68: 2850-2860Crossref PubMed Scopus (400) Google Scholar), that have improved clinical bioavailability and toxicity profiles. We previously reported on the efficacy of AUY922 in prostate cancer, showing that AUY922 is markedly more effective at killing prostate cancer cells in vitro and ex vivo than 17-AAG (13Centenera M.M. Gillis J.L. Hanson A.R. Jindal S. Taylor R.A. Risbridger G.P. Sutherland P.D. Scher H.I. Raj G.V. Knudsen K.E. Yeadon T. Australian Prostate Cancer B. Tilley W.D. Butler L.M. Evidence for efficacy of new Hsp90 inhibitors revealed by ex vivo culture of human prostate tumors.Clin. Cancer Res. 2012; 18: 3562-3570Crossref PubMed Scopus (88) Google Scholar). Moreover, AUY922 maintained its efficacy even in prostate cancer cells containing constitutively active AR variants that are thought to drive advanced, castration-resistant prostate cancer. Heat shock protein 90 17-N-allylamino-17-demethoxygeldanamycin Androgen deprivation therapy Automatic gain control Analysis of variance Castrate-resistant prostate cancer Data Independent Acquisition Formic acid Fetal bovine serum Hydrochloric acid Hypoxia-inducible factors −1 Hyper reaction monitoring Retention-time-normalized Ion trap Tandem mass spectrometry Ammonium hydroxide Principal component analysis Patient-derived prostate cancer explant Roswell Park Memorial Institute. Heat shock protein 90 17-N-allylamino-17-demethoxygeldanamycin Androgen deprivation therapy Automatic gain control Analysis of variance Castrate-resistant prostate cancer Data Independent Acquisition Formic acid Fetal bovine serum Hydrochloric acid Hypoxia-inducible factors −1 Hyper reaction monitoring Retention-time-normalized Ion trap Tandem mass spectrometry Ammonium hydroxide Principal component analysis Patient-derived prostate cancer explant Roswell Park Memorial Institute. Further complicating the clinical development of these agents is the lack of response markers to ensure the maximum benefit from a drug is obtained for an individual patient. Monitoring response markers will allow for optimal selection of agents, regimens, and patients for clinical trials. Protein markers of the AUY922 response have been investigated in a wide range of cancer cell line models using a priori approaches such as Western blot analysis (14Stingl L. Stuhmer T. Chatterjee M. Jensen M.R. Flentje M. Djuzenova C.S. Novel HSP90 inhibitors, NVP-AUY922 and NVP-BEP800, radiosensitise tumour cells through cell-cycle impairment, increased DNA damage and repair protraction.Br. J. Cancer. 2010; 102: 1578-1591Crossref PubMed Scopus (77) Google Scholar, 15Garon E.B. Finn R.S. Hamidi H. Dering J. Pitts S. Kamranpour N. Desai A.J. Hosmer W. Ide S. Avsar E. Jensen M.R. Quadt C. Liu M. Dubinett S.M. Slamon D.J. The HSP90 inhibitor NVP-AUY922 potently inhibits non-small cell lung cancer growth.Mol. Cancer Ther. 2013; 12: 890-900Crossref PubMed Scopus (56) Google Scholar, 16Mayor-Lopez L. Tristante E. Carballo-Santana M. Carrasco-Garcia E. Grasso S. Garcia-Morales P. Saceda M. Lujan J. Garcia-Solano J. Carballo F. de Torre C. Martinez-Lacaci I. Comparative study of 17-AAG and NVP-AUY922 in pancreatic and colorectal cancer cells: are there common determinants of sensitivity?.Transl. Oncol. 2014; 7: 590-604Crossref PubMed Scopus (24) Google Scholar, 17Jensen M.R. Schoepfer J. Radimerski T. Massey A. Guy C.T. Brueggen J. Quadt C. Buckler A. Cozens R. Drysdale M.J. Garcia-Echeverria C. Chene P. NVP-AUY922: a small molecule HSP90 inhibitor with potent antitumor activity in preclinical breast cancer models.Breast Cancer Res. 2008; 10: R33Crossref PubMed Scopus (185) Google Scholar). Global proteomic analysis was performed in Jurkat cells that highlighted 64 proteins (e.g. CDK1, CDK6, DNAJB1, SERPINH1, FKBP52, and mitochondrial chaperonin 10) to be markers of HSP90 inhibition by AUY922 (18Voruganti S. Lacroix J.C. Rogers C.N. Rogers J. Matts R.L. Hartson S.D. The anticancer drug AUY922 generates a proteomics fingerprint that is highly conserved among structurally diverse Hsp90 inhibitors.J. Proteome Res. 2013; 12: 3697-3706Crossref PubMed Scopus (19) Google Scholar). Nevertheless, there is substantial variation and a lack of conservation of results from these cell line studies emphasizing the need for a more clinically-relevant model system. To circumvent the limitations of current cell line-based models of prostate cancer, we have developed a model of culturing human prostate cancer tissue ex vivo that retains the structure and stromal-epithelial interactions of the tumor microenvironment, has proliferative capacity, and most importantly takes into account the heterogeneous nature of the disease. Using this patient-derived explant model, we have showed that AUY922 but not 17-AAG, markedly inhibits cell proliferation and induces apoptosis in human prostate tumors, warranting further clinical investigation of this class of agents (13Centenera M.M. Gillis J.L. Hanson A.R. Jindal S. Taylor R.A. Risbridger G.P. Sutherland P.D. Scher H.I. Raj G.V. Knudsen K.E. Yeadon T. Australian Prostate Cancer B. Tilley W.D. Butler L.M. Evidence for efficacy of new Hsp90 inhibitors revealed by ex vivo culture of human prostate tumors.Clin. Cancer Res. 2012; 18: 3562-3570Crossref PubMed Scopus (88) Google Scholar). When we assessed our patient-derived prostate explants (PDEs) for induction of the clinical pharmacodynamic biomarker of Hsp90 inhibition, Hsp70 (19Dakappagari N. Neely L. Tangri S. Lundgren K. Hipolito L. Estrellado A. Burrows F. Zhang H. An investigation into the potential use of serum Hsp70 as a novel tumour biomarker for Hsp90 inhibitors.Biomarkers. 2010; 15: 31-38Crossref PubMed Scopus (49) Google Scholar), we saw equivalent induction of the biomarker with both 17-AAG and AUY922. This confirms that Hsp70 expression indicates target modulation but not anti-tumor activity of these inhibitors. These results are consistent with clinical studies wherein Hsp70 levels were not correlated with clinical response (20Kummar S. Gutierrez M.E. Gardner E.R. Chen X. Figg W.D. Zajac-Kaye M. Chen M. Steinberg S.M. Muir C.A. Yancey M.A. Horneffer Y.R. Juwara L. Melillo G. Ivy S.P. Merino M. Neckers L. Steeg P.S. Conley B.A. Giaccone G. Doroshow J.H. Murgo A.J. Phase I trial of 17-dimethylaminoethylamino-17-demethoxygeldanamycin (17-DMAG), a heat shock protein inhibitor, administered twice weekly in patients with advanced malignancies.Eur. J. Cancer. 2010; 46: 340-347Abstract Full Text Full Text PDF PubMed Scopus (99) Google Scholar, 21Ramanathan R.K. Egorin M.J. Erlichman C. Remick S.C. Ramalingam S.S. Naret C. Holleran J.L. TenEyck C.J. Ivy S.P. Belani C.P. Phase I pharmacokinetic and pharmacodynamic study of 17-dimethylaminoethylamino-17-demethoxygeldanamycin, an inhibitor of heat-shock protein 90, in patients with advanced solid tumors.J. Clin. Oncol. 2010; 28: 1520-1526Crossref PubMed Scopus (80) Google Scholar), and highlight the urgent need for biomarkers that reflect biological activity rather than target modulation only. The goal of the current study was to identify protein biomarkers associated with response or resistance to specific Hsp90 inhibitors in PDEs from clinical prostate tumors. Using HRM-DIA mass spectrometry, we report the identification of markers correlating with antiproliferative responses to the new-generation agent AUY922, and identify candidate predictive markers of 17-AAG responsiveness. The Hsp90 inhibitors 17-N-allylamino-17-demethoxygeldanamycin (17-AAG; National Cancer Institute, MD) and AUY922 (Novartis, now Vernalis, Winnersh, UK) were dissolved and diluted in dimethyl sulfoxide (DMSO). The effective dose of 500 nm for Hsp90 inhibitors, determined previously to induce Hsp70 and decrease levels of the androgen receptor and Akt in 8 independent tumors, was used in this study (13Centenera M.M. Gillis J.L. Hanson A.R. Jindal S. Taylor R.A. Risbridger G.P. Sutherland P.D. Scher H.I. Raj G.V. Knudsen K.E. Yeadon T. Australian Prostate Cancer B. Tilley W.D. Butler L.M. Evidence for efficacy of new Hsp90 inhibitors revealed by ex vivo culture of human prostate tumors.Clin. Cancer Res. 2012; 18: 3562-3570Crossref PubMed Scopus (88) Google Scholar). Human ethical approval for this project was obtained from the Adelaide University Human Research Ethics Committee and the research ethics committees of the Royal Adelaide Hospital and St Andrew's Hospital. Fresh prostate cancer specimens were obtained with written informed consent through the Australian Prostate Cancer BioResource from men undergoing robotic radical prostatectomy at the Royal Adelaide Hospital and St Andrew's Hospital (Adelaide, South Australia). Tumors from two cohorts of patients were used for this study: a discovery cohort (n = 16) and a validation cohort (n = 30). Clinicopathological features of tumors used in each cohort are detailed in supplemental Table S1. A single 6 mm core of tissue was obtained per patient. A longitudinal section of the entire core was taken for hematoxylin and eosin (H&E) analysis of tumor content. The remaining tissue was dissected into 1 mm3 pieces and cultured in triplicate on a presoaked gelatin sponge (Johnson and Johnson, New Brunswick, NJ) in 24-well plates containing 500 μl RPMI 1640 with 10% FBS, 1× antibiotic/antimycotic solution (Sigma, St Louis, MO), 0.01 mg/ml hydrocortisone, 0.01 mg/ml insulin (Sigma) and cultured for 48 h with 17-AAG, AUY922 (500 nm each) or DMSO vehicle alone as previously described (13Centenera M.M. Gillis J.L. Hanson A.R. Jindal S. Taylor R.A. Risbridger G.P. Sutherland P.D. Scher H.I. Raj G.V. Knudsen K.E. Yeadon T. Australian Prostate Cancer B. Tilley W.D. Butler L.M. Evidence for efficacy of new Hsp90 inhibitors revealed by ex vivo culture of human prostate tumors.Clin. Cancer Res. 2012; 18: 3562-3570Crossref PubMed Scopus (88) Google Scholar). Tissues were cultured at 37 °C for 48 h, then were either formalin-fixed and paraffin-embedded or snap frozen in liquid nitrogen and stored at −80 °C until further analysis. Tissues containing ≥70% tumor content and ≥5% baseline Ki67 positivity, determined as outlined below, were included for proteomic analysis. Paraffin-embedded tissues were sectioned (2 mm) on Ultraplus slides prior to hematoxylin and eosin (H&E) staining and immunohistochemical (IHC) detection of the proliferative marker, Ki67 (Agilent, M7240 antibody; 1:200 dilution, Santa Clara, CA). IHC staining was performed and tissues assessed for tumor content and Ki67 positivity in a blinded fashion as described previously (22Armstrong H.K. Koay Y.C. Irani S. Das R. Nassar Z.D. Australian Prostate Cancer B. Selth L.A. Centenera M.M. McAlpine S.R. Butler L.M. A novel class of Hsp90 C-terminal modulators have pre-clinical efficacy in prostate tumor cells without induction of a heat shock response.Prostate. 2016; 76: 1546-1559Crossref PubMed Scopus (21) Google Scholar). Snap frozen PDEs were homogenized in 0.5 ml tubes containing 1.4 mm ceramic beads (Precellys® CK14 Lysing Kit, Bertin Instruments, Montigny-le-Bretonneux, France) and 100 μl 8 m Urea buffer (8 m Urea, 20 mm HEPES, 2.5 mm sodium pyrophosphate, 1 mm beta-glycerol phosphate, 1 mm sodium orthovanadate, 1 mm ethylenediaminetetraacetic acid, pH7.5) using the Precellys®24 tissue homogenizer (Bertin Instruments). Lysates from triplicate PDEs were combined and transferred to Eppendorf tubes, centrifuged at 10,000 rpm for 10 min, and supernatants stored at −80 °C. Total protein measurements were determined using the Bicinchoninic acid protein assay (Bio-Rad, Hercules, CA). 100 μg of protein extracts were denatured with 6 m urea in 25 mm Ammonium Bicarbonate, before reduction with 5 mm TCEP at 37 °C for 1h and alkylation with 32 mm iodoacetamide in the dark for 1 h. Alkylation was stopped by addition of 27 mm DTT. The samples were then diluted 1:10 with ammonium bicarbonate and digested with a 1:50 modified trypsin (Promega, Madison, WI) to protein weight at 37 °C for 18 h. Tryptic digests were slightly acidified with 10% TFA to pH 2–3, desalted with a C18 spin column (Thermo Fisher Scientific, Waltham, MA), and eluted with 0.1% TFA/40% ACN. Peptides were dried with a speed vacuum and resuspended in 2% ACN/0.1% FA before mass spectrometry analysis. Samples were analyzed on an UltiMate 3000 RSLC nano LC system (Thermo Scientific) coupled to an LTQ-Orbitrap mass spectrometer (LTQ-Orbitrap, Thermo Scientific). Peptides for analysis were loaded via an Acclaim PepMap 100 trap column (100 μm × 2 cm, nanoViper, C18, 5 μm, 100Å, Thermo Scientific) and subsequent peptide separation was on an Acclaim PepMap RSLC analytical column (75 μm x 50 cm, nanoViper, C18, 2 μm, 100 Å, Thermo Scientific). For each liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis, an estimated amount of 1 μg of peptides was loaded on the precolumn with microliter pickup. Peptides were eluted using a 2 h linear gradient of 80% acetonitrile/0.1% FA gradient flowing at 250 nL/min using mobile phase gradient of 2.5–42.5% acetonitrile. The eluting peptides were interrogated with an Orbitrap mass spectrometer. The HRM DIA method consisted of a survey scan (MS1) at 35,000 resolution (automatic gain control target 5e6 and maximum injection time of 120ms) from 400 to 1220 m/z followed by tandem MS/MS scans (MS2) through 19 overlapping DIA windows increasing from 30 to 222 Da. MS/MS scans were acquired at 35,000 resolution (automatic gain control target 3e6 and auto for injection time). Stepped collision energy was 22.5%, 25%, 27.5% and a 30 m/z isolation window. The spectra were recorded in profile type. The DIA data were analyzed with Spectronaut 8, a mass spectrometer vendor-independent software from Biognosys (Schlieren, Switzerland). The default settings were used for the Spectronaut search. Retention time prediction type was set to dynamic iRT. Decoy generation was set to scrambled with no decoy limit. Interference correction on MS2 level was enabled. The false discovery rate (FDR) was set to 1% at peptide level. For generation of the spectral libraries, DDA measurements of each sample were performed. The DDA spectra were analyzed with the MaxQuant Version 1.5.2.8 analysis software using default settings. Enzyme specificity was set to Trypsin/P, minimal peptide length of 6, and up to 3 missed cleavages were allowed. Search criteria included carbamidomethylation of cysteine as a fixed modification, oxidation of methionine and acetyl (protein N terminus) as variable modifications. The mass tolerance for the precursor was 4.5 ppm and for the fragment ions was 20 ppm. The DDA files were searched against the human UniProt fasta database (v2015–08, 20,210 entries) and the Biognosys HRM calibration peptides. The identifications were filtered to satisfy FDR of 1% on peptide and protein level. The spectral library was generated in Spectronaut and normalized to iRT peptides (23Bruderer R. Bernhardt O.M. Gandhi T. Miladinovic S.M. Cheng L.Y. Messner S. Ehrenberger T. Zanotelli V. Butscheid Y. Escher C. Vitek O. Rinner O. Reiter L. Extending the limits of quantitative proteome profiling with data-independent acquisition and application to acetaminophen-treated three-dimensional liver microtissues.Mol. Cell. Proteomics. 2015; 14: 1400-1410Abstract Full Text Full Text PDF PubMed Scopus (521) Google Scholar). A peptide identification required at least 3 transitions in quantification. Quantification was based on the top 3 proteotypic peptide for each protein (24Collins B.C. Hunter C.L. Liu Y. Schilling B. Rosenberger G. Bader S.L. Chan D.W. Gibson B.W. Gingras A.C. Held J.M. Hirayama-Kurogi M. Hou G. Krisp C. Larsen B. Lin L. Liu S. Molloy M.P. Moritz R.L. Ohtsuki S. Schlapbach R. Selevsek N. Thomas S.N. Tzeng S.C. Zhang H. Aebersold R. Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectrometry.Nat. Commun. 2017; 8: 291Crossref PubMed Scopus (269) Google Scholar) and exported as an excel file with Spectronaut 8 software (23Bruderer R. Bernhardt O.M. Gandhi T. Miladinovic S.M. Cheng L.Y. Messner S. Ehrenberger T. Zanotelli V. Butscheid Y. Escher C. Vitek O. Rinner O. Reiter L. Extending the limits of quantitative proteome profiling with data-independent acquisition and application to acetaminophen-treated three-dimensional liver microtissues.Mol. Cell. Proteomics. 2015; 14: 1400-1410Abstract Full Text Full Text PDF PubMed Scopus (521) Google Scholar). Differentially expressed proteins between treatment groups were identified using repeated measure analysis of variance (ANOVA) with the Multi-Experiment Viewer analysis software (25Saeed A.I. Sharov V. White J. Li J. Liang W. Bhagabati N. Braisted J. Klapa M. Currier T. Thiagarajan M. Sturn A. Snuffin M. Rezantsev A. Popov D. Ryltsov A. Kostukovich E. Borisovsky I. Liu Z. Vinsavich A. Trush V. Quackenbush J. TM4: a free, open-source system for microarray data management and analysis.BioTechniques. 2003; 34: 374-378Crossref PubMed Scopus (3996) Google Scholar). A raw p value <.01 and an F ratio >5 were used to define differential expression, and plots of local FDR estimates generated by LocalFDR from Anapuce R package. Based on analysis of the protein abundance data obtained from the initial cohort, an additional validation cohort of n = 30 patients was designed to have at least 95% power to detect an effect size of 1SD in a t test (2-sided alpha = 0.05) of within-sample difference between vehicle and AUY treatments. Unpaired t test of PDE samples that responded compared with samples that had no response or showed poor response based on Ki67 proliferation was performed to determine differential proteins prior to 17-AAG treatment (raw p value <.05). A paired t test (raw p value <.01) prior and after treatment with 17-AAG was implemented with the Multi-Experiment Viewer software to determine differential proteins. All comparative tests were normalized with the Spectronaut software and exported for analysis (supplemental Fig. S1). Functional annotation of the proteome was conducted using database for annotation, visualization, and integrated discovery (DAVID) software (26Dennis Jr, G. Sherman B.T. Hosack D.A. Yang J. Gao W. Lane H.C. Lempicki R.A. DAVID: Database for Annotation, Visualization, and Integrated Discovery.Genome Biol. 2003; 4: P3Crossref PubMed Google Scholar). Overrepresented functional categories among proteins enriched in each sample population were relative to a background of all identified proteins in study. Criteria for reported functional enrichment required a fold enrichment >1.5, FDR <5, and p value <.05. Experimentally verified and published protein-protein interactions from several resources including REACTOME (27Fabregat A. Sidiropoulos K. Garapati P. Gillespie M. Hausmann K. Haw R. Jassal B. Jupe S. Korninger F. McKay S. Matthews L.