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Quantitative Proteomics Research: Breast and Prostate Cancer Biology Spiros D. Garbis, PhD Investigator, Faculty Member Center for Basic Research II Division of Biotechnology. O utline. Background and Overview Clinical Tissue Procurement Mass Spectrometry Essentials

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  1. Quantitative Proteomics Research: Breast and Prostate Cancer BiologySpiros D. Garbis, PhDInvestigator, Faculty MemberCenter for Basic Research IIDivision of Biotechnology

  2. Outline • Background and Overview • Clinical Tissue Procurement • Mass Spectrometry Essentials • Summary of Current Findings

  3. Poor cancer diagnosis and prognosis Higher prevalence in elderly populations Complex process Synergic behavior of pathways Combinatorial Signaling aspects Related to the metabolic syndrome (epidemiology) Breast and Prostate Cancer Albiniet al. 2007

  4. The accurate study of Carcinogenesismust account for: Multi-parameter nature of cancer initiation, promotion, progression Crucial role of tumor microenvironment Biological variance of tissue specimens Fully accounted for in our LC-MS based proteomics infrastructure Considerations for Experimental Design To provide a window in gaining a better insight to cancer biology

  5. Perspective and Considerations • The current state-of-the-art in the molecular characterization require prior knowledge of the proteins involved • Promising pre-clinical data is essential (for confirmation and justification for the pharmacoproteomic study) • What is frequently missed is all the systemic effects • The global (discovery or hypothesis generating science) • targeted (hypothesis driven science) • Long term implications (i.e xenografted or mutated mouse models, pilot scale human clinical trials, etc) • NOT about generating lists of proteins. It’s about de-coding quantitative profiles into canonical and novel pathways

  6. “Garbage in…Garbage out” Poorly characterized specimens are usually poor of information Well characterized specimens can minimize variability and facilitate analytical methodology Iterative process process involving a perpetual feedback loop between tissue procurement/preparation & analytical method development in order to generate a reproducible and accurate quantitative protein profile Selection of Clinical Material

  7. Protein MAPPING: The ID of a maximum number of proteins constituting a sample Protein EXPRESSION: The ID of altered proteins as a response to a stimulus • PROTEOMICS of • TISSUE, • CELL CULTURE, • SERUM Protein MODIFICATION: Determine how and where a protein is post-translationally modified Ligand-enzyme INTERACTION: Determine how proteins interact with medicinal agents

  8. Tissue Procurement and Patient Characteristics • Well defined inclusion/exclusion criteria were used for both clinical groups (staging, Gleason Score  6, no androgen intervention, etc.)Adherance to GCP/ICH guidelines • 10 Patients BPH [mean age ± S.D of 70 ± 9 years, mean serum PSA ± S.D of 4.1 ± 1.9 ng/mL] • 10 PCa Cases [mean age ± S.D of 66 ± 4 years, mean serum PSA ± S.D of 9.3 ± 4.6 ng/mL] • Cancer specimens histochemically confirmed(>70%) 5 mm • -80 OC within 5 min • Proteomics Lab and analysis after histochemical evaluation of the mirror part PCa

  9. Proteomics • Proteomics as an INTERDISCIPLINARY science should reliably provide greater insight: • Proteins mediate molecular and biochemical functions • (signalling, cell division, metabolism, cell migration) • Alteration of proteins denote disease states • Proteins serve as viable biomarkers of disease • Proteins can serve as drug/therapeutic targets

  10. BIOLOGICAL SAMPLE (CELLS, TISSUE, FLUID) SUBFRACTIONATION STABLE ISOTOPE LABELING 2DGE OR 2D DIGE MULTI-DIMENSIONAL CHROMATOGRAPHY EXCISE SPOTS, IN-GEL DIGEST ON-LINE LC-MS-MS ANALYSIS MALDI-TOF MS ANALYSIS DATA ANALYSIS PROTEIN ID & PROTEIN EXPRESSION ANALYSIS Garbis SD, et al.J. of Chromatogr. A, 2005, 1077, 1-18.

  11. «Bottom-Up Proteomics» Workflow

  12. Comparative Proteomics Beecher, 1999

  13. Chromatography Directed Protein Isolation and Enrichment • PRINCIPLE: • Isolate proteins in concordance to chromatographic chemistry to be used, • Separate and enrich these tryptic peptides with HPLC (high selectivity, reproducibility and capacity)

  14. Multidimensional Liquid Chromatography SCX Peptide mixture RP-nanoHPLC MS/MS 1st Dimension 2nd Dimension Separation according to hydrophobicity index ORTHOGONAL CHEMISTRIES Separation according to i.e. charge state – polarityindex

  15. P P E P P E P PEPTIDE PE PEPTIDE CID P E P T m/z seperation PEPTIDE PEPT PEPTIDE P E PT I PEPTI PEPTIDE P E P T I D PEPTID PEP P E P T I D E Tandem Mass Spectrometry (MS/MS) RevealsSEQUENCEand PTM informationabout the peptides MS spectrum MS-ΜS spectrum Collision induced dissociation, CID MS MS fragmentation Mixture of Peptide ions (LC-ESI) Precursor ion Product ions

  16. Peptide abundance • Peptide ionization • Peptide volatility • Instrument status • Preparation process Protein confidence Quality of MS/MS spectra Peptide confidence • Peptide length • Number of peptides • Uniquely occurring peptides Protein Identification TITEVIHGR …is based on peptide sequence determination EGETITEVIHGEPIIK

  17. 115 116 116 117 115 115 116 114 114 114 114 115 115 iTRAQ 114 31 115 30 116 29 117 28 Isobaric Tags for Relative and Absolute Quantification (iTRAQTM) 145 114-117 31-28 MS/MS spectrum Peptide with differential abundance Protein with differential abundance The same mass in MS Different reporter ions The same peptide fragments + A B A mix C + B D 2D-LC 114 115 116 117 m/z C + D +

  18. iTRAQ 115 iTRAQ 117 iTRAQ 114 iTRAQ 116 Methodology Tissue1 PCa Tissue2 PCa Tissue3 BPH Tissue4 BPH Trypsin digestion of protein extracts Differential peptide labeling with isotopic reagents (iTRAQ) Mix Peptides 2-Dimentional Liquid Chromatography (2D-LC) Tandem Mass Spectrometry (MS/MS) Algorithmic Data processing & Evaluation

  19. Summary of BrCa & PCa Proteomics • QSTAR XL MS-MS Resolution ~ 12,000 @ 500 – 1500 Da • MS Accuracy  3-ppm; MS-MS Accuracy  15-ppm • Reproducible identification of ~ 1000 proteins ( ≥ 95% confidence) spanning the high mol – low amol on-column amounts • Wide range of physico-chemical properties • 100s of PTM variants identified of which > 60% are novel • Differentially expressed proteins are traceable to canonical and novel mechanistic pathways of carcinogenesis • Independent biological confirmation • Extensive commonality of proteins with respective human cell lines and sera specimens (secreted proteins) Garbis SD, et al. J Proteome Res.2008;7(8):3146-3158. Bouchal P, Roumeliotis T, et al. J Proteome Res. 2008, In Press.

  20. PCA Bouchal P, Roumeliotis T, et al. J Proteome Res. 2008, In Press.

  21. Putative NFB Activating Protein Effective multidimensional chromatography is essential to the quality of the product-ion spectra Garbis SD, et al. J Proteome Res.2008;7(8):3146-3158. Bouchal P, Roumeliotis T, et al. J Proteome Res. 2008, In Press.

  22. Proteomic Feature Maps: A new visualization approach in proteomic analysis Giannopoulou EG, et al.J Biomed Inf2008, In Press.

  23. Garbis SD, et al. J Proteome Res.2008;7(8):3146-3158.

  24. Garbis SD, et al. J Proteome Res.2008;7(8):3146-3158.

  25. Garbis SD, et al. J Proteome Res.2008;7(8):3146-3158.

  26. Novel & Quantitative Phosphoproteome Supplementary Information: Garbis SD, et al. J Proteome Res.2008;7(8):3146-3158. Bouchal P, Roumeliotis T, et al. J Proteome Res. 2008, In Press.

  27. Prostate Specific Antigen (PSA) Garbis SD, et al. J Proteome Res.2008;7(8):3146-3158.

  28. SDK[IT4]LPEEMGLLQGSSGDK[IT4]R Prec. Mass: 2478.3386, z: +4 BPH BPH PCa PCa y4 y2 y5 y1 b2 y3 y6 619.364 447.316 706.396 175.119 b1 347.168 562.343 INTENSITY 793.428 60 y12++ 232.141 b4++ b7++ y7 696.361 b3++ 366.230 544.269 850.450 b9++ 309.683 y15++ 637.800 30 873.938 m/z 200 300 400 500 600 700 900 800 BPH PCa Cell surface glycoprotein (CD146 Antigen) Garbis SD, et al. J Proteome Res.2008;7(8):3146-3158.

  29. p22HBP GST -1 Bouchal P, Roumeliotis T, et al. J Proteome Res. 2008, In Press.

  30. CTL 6h 12h 36h Voltage-dependent N-type calcium channel subunit α-1B: A Quantitative and Temporal Proteomics Appoach • Novel Phosphopeptide • Time-dependent phosphorylation • Novel apoptosis mechanism • Physiologic Target

  31. Activity-Based Proteomic Profiling Bach, et al 2005

  32. Glycogen Debranching Enzyme Woo, et al. 2008

  33. Roscovitine-Affinity Site

  34. CANONICAL PATHWAY : Apoptosis (p < 0.001)

  35. Overall Conclusions Differentially expressed proteins are relative to: • Cellular structure and growth • Tumor microenvironment and stroma-epithelium interactions (inflammation factors, angiogenesis factors) • Detoxification • Breast & Prostate physiology • Targets for pharmaceutical or chemopreventive intervention • The majority of differentially expressed proteins is relative to established carcinogenesis pathways • The methodology used made possible the simultaneous detectionof multiple molecular alterations • Novel findings amenable to further investigation as novel pathways of BrCa & PrCa • Detection of proteins which have also been detected in human plasma proteome • MOLECULAR EVIDENCE FOR NUTRITIONAL AND IMMUNOLOGIC FACTORS IN THE MANIFESTATION OF BREAST AND PROSTATE CANCER

  36. From Proteomics to Proteonomics:The New Biology

  37. X = S e , H O O H O O H O O O H O H ALTERNATIVE QSAR INTERPRETATION:Pharmaco-PROTEOMIC & Toxico-PROTEOMICS BENZOFURAN TOCOTRIENOL-X CONJUGATES O O O X O H O DEOXYBENZOIN SOY ISOFLAVONE DERIVATIVES

  38. University of Cyprus Prof. Andreas Constantinou Prof. Anastasios Keramidas Dr. Andreani Odysseos University of Athens Prof. Leandros Skaltsounis Prof. Evi Lianidou Prof. Elias Manolakos University of Toronto Prof. Eleftherios Diamandis CNRS Cell-Cycle Biology Lab Prof. Laurent Meijer Hellenic National Research Institute Dr. Mixalis Alexis Dr. Xanthipi Alexi Demokritos Dr. Evangelos Gogolides Dr. Aggeliki Tserepi Masaryk Memorial Cancer Institute, Brno, The Check Republic Dr. Pavel Bouchal Dr. Roman Hrstka Dr. Rudolf Nenutil Dr. Borivoj Vojtesek University of Adelaide, Australia Prof. Andreas Evdokiou Biomedical Research Foundation-Academy of Athens Dr. Antonia Vlahou Dr. Sophia Kossida Dr. Constantin Tamvakopoulos Laiko University Hospital Prof. Konstantinos Constantinides Prof. Kitty Pavlaki Dr. Stavros Tyritzis Biosolutions-Applied Biosystems Konstantina Tasiouka George Magkaniotis Collaborators

  39. Garbis SD, et al.J. of Chromatogr. A, 2005, 1077, 1-18. Garbis SD, et al. J Proteome Res.2008;7(8):3146-3158. Bouchal P, Roumeliotis T, et alJ Proteome Res. 2008, In Press. Giannopoulou EG, et al.J Biomed Inf.2008, In Press. Delehouz C, et al., J. Biol. Chem.2008,In Press. Manadas B, et al. Mol. & Cell. Proteomics 2008, In Press 7 more manuscripts in preparation! BRFAA Relevant References

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