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Application of Proteomics in Cancer Research

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					 Application of Proteomics
    in Cancer Research
Andreas Humeny

Lehrstuhl für Biochemie und Molekulare Medizin
Institut für Biochemie
Emil-Fischer-Zentrum
Friedrich-Alexander Universität Erlangen-Nürnberg


Contact:      andreas.humeny@biochem.uni-erlangen.de
Homepage:     http://www.humeny.net  downloads
Application of Proteomics in Cancer Research



        Overview
      • Proteomics

      • Cancer

      • Aims

      • Tools

      • Results

      • Challenges

      • Summary
Application of Proteomics in Cancer Research




      •   Proteomics
      • Cancer

      • Aims

      • Tools

      • Results

      • Challenges

      • Summary
                  Application of Proteomics in Cancer Research


         What is the proteome ?
classical information flow: DNA  RNA  Protein
                                        Protein

• Genome:           30.000 – 40.000 genes, static

• Transcriptome: > 100.000 RNAs, dynamic

• Proteome:         Set of expressed proteins in an organism,
                    organ, tissue, cell or body fluid under
                    defined conditions.
                    > 400.000 proteins, dynamic

  variability:     genomic variations,
                    gene expression, alternative splicing,
                    protein cleavage, modifications
                 Application of Proteomics in Cancer Research



            What is proteomics ?
“Omics” revolution: fundamental shift in strategy from
         - piece-by-piece to global analysis
         - hypothesis-driven to discovery-based research

Expression proteomics:
 • analysis of differential protein expression

Functional proteomics:
 • posttranslational modifications
 • protein-protein, protein-ligand interactions
 • sequence-structure-function relationships
                Application of Proteomics in Cancer Research



       Why perform proteomics ?
      Genomics  Transcriptomics  Proteomics
      Genomics   Transcriptomics   Proteomics

• Protein alterations cannot be fully deduced from DNA.

• RNA expression does not always reflect protein levels:
  translational control, degradation, turnover

• Body fluids are not suitable for RNA expression analysis.
• Proteins are the physiological/pathological active key players.

               DNA tells what possibly,
              RNA what probably and
              Proteins what actually happens.
Application of Proteomics in Cancer Research




      • Proteomics

      •   Cancer
      • Aims

      • Tools

      • Results

      • Challenges

      • Summary
            Application of Proteomics in Cancer Research



           What is Cancer ?

Tumors:     loss of cell cycle control
             de-differentiation and proliferation


 benign:    encapsulated by connective tissue
            rarely life-threatening


 malignant: invasive growth
            cell shedding  metastasis                     cancer
            life-threatening
                Application of Proteomics in Cancer Research



        Molecular basis of cancer
Causes of cancer: - carcinogens, radiation, viruses, random
                    - hereditary vs. spontaneous tumors
                    - multi step process


Genes and gene products involved in cancer:
• activation of proto-oncogenes to oncogenes (gain-of-function)

• inactivation of tumor suppressor genes (loss-of-function)

• altered activity of modulator genes
                 Application of Proteomics in Cancer Research



    Characteristics of cancer cells
• general changes:             - loss of division limits (immortality)
                               - uncontrolled proliferation


• genetic changes:             - point mutations …
                               - chromosomal changes


• structural changes:          - less organized cytoskeleton
                               - increased membrane fluidity


• biochemical changes: - altered protein expression
                       - altered protein modification
                 Application of Proteomics in Cancer Research



       Cancer facts and treatment
• > 100 different types of human cancer

•  20 % of the mortalities in industrialized nations


detection  classification and localization  therapy


                    imaging                                     surgery
                    histology                                   radiation
                    biomarkers                                  chemotherapy
Application of Proteomics in Cancer Research




      • Proteomics

      • Cancer

      •   Aims
      • Tools

      • Results

      • Challenges

      • Summary
                  Application of Proteomics in Cancer Research



Proteomic aims in cancer research
General goal:
• better understanding of genesis and progression of cancer


Clinical goals:
• early cancer detection using biomarkers

• identification of potential therapeutic target structures

• efficient monitoring of therapy control
                  Application of Proteomics in Cancer Research



                  Tumor markers
• diagnostic markers:         detection of malignant disease

         sensitivity =        detected positives / real positives
         specificity =        detected negatives / real negatives


• prognostic markers:         malignant potential, disease recurrence


• predictive markers:         response to different therapies


• positioning markers:        positional information (e.g. for surgery)
Application of Proteomics in Cancer Research




      • Cancer

      • Proteomics

      • Aims

      •   Tools
      • Results

      • Challenges

      • Summary
               Application of Proteomics in Cancer Research



              Proteomic workflow
                                      protein
                                   quantification             bioinformatics



 sample                  protein                        protein
collection              separation                   identification

cells             chromatography                 Edman sequencing
body fluids       electrophoresis                mass spectrometry
tissues           ...
                  Application of Proteomics in Cancer Research



                Sample collection
• biomarker discovery, identification, characterization, validation

• study design (retrospective, prospective ...)

• number of samples (statistical power, significance)

• patients and control group: - age, sex
                              - medication
                              - healthy, benign and malignant
                                  tumors, other diseases

• clinical classification of tumors (stages: early, late …)

• informed consent of patients and controls (bioethics)
                  Application of Proteomics in Cancer Research



                Sample collection
• sample type: cells, body fluids, tissues

• time of sample collection (daily and monthly variations)

• prevention of contaminants (necrotic tissue, blood ...)

• biological variability (patient-to-patient, tumor-to-tumor)


• identical collection, treatment and storage

                 “The devil is in the details !”
                                                            http://www.holzwurm-meine.de/images/teufel.gif
                        Application of Proteomics in Cancer Research



Sample collection: Tissue and LCM
• Laser capture microdissection (LCM):
 Laser-cutting of stained tissue slides under microscopic control
  defined procurement of cells

• intra-patient control: tumor vs. non-tumor tissue

• Example: LCM in pancreatic cancer:
   before laser pulse               after laser pulse                              cap view




                                                  (adapted from http://www.dmmc.ie/Edu_Download/TSMM2003_12.pdf)


• pitfalls: staining, cell-selection …
                 Application of Proteomics in Cancer Research



              Protein separation
• Protein-specific biochemical-biophysical parameters:
        isoelectric point (IP), molecular weight (MW), affinity...


• chromatographic methods:               HPLC
                                         2D-HPLC
                                         ProteinChips


• electrophoretic methods:               SDS-PAGE
                                         2-dimensional (2DE)
                    Application of Proteomics in Cancer Research



   2-Dimensional gel electrophoresis
• 1. dimension: isoelectric focussing (IEF)  separation by IP
 2. dimension: SDS-PAGE                                      separation by MW

• staining  > 1000 proteins /gel

• Example: breast cancer cell lines:
                   Fontana et al. Proteomics 2004, 4, 849




• molecular analysis by mass spectrometry, HPLC, Westernblot ...

• pitfalls:   very basic / acidic; large / small; hydrophobic;
              low-abundance proteins …
                 Application of Proteomics in Cancer Research



            Protein identification
• Identification and characterization (modifications) by
 combined bioanalytics and bioinformatics

• Edman sequencing: N-terminal sequence tags


• mass spectrometry: peptide finger prints (digests)
                             C-terminal sequence tags (ladder seq.)
                             fragmentation analysis
                             (tandem MS, MS/MS, MSn)

• data bases and bioinformatic algorithms (scoring)
                                    Application of Proteomics in Cancer Research



                                 Mass spectrometry
• Measurement of mass/charge (m/z) ratios                                                (z= 1  m [Da])

    ionization                                   m/z analysis                                    detection
 matrix-assisted laser                          time-of-flight (TOF)                       secondary electron
 desorption/ionization                          quadrupol (Q)                              multiplier
 (MALDI)
                                                ion trap (IT)                              micro channel plates
 electrospray ionization                        fourier transform
 (ESI)                                          ion cyclotron (FTICR)


• different combinations: accuracy, sensitivity, mass range …

• in-tissue MALDI-TOF-MS of brain tumors:                                                                  MALDI-TOF-MS
                                           frozen tissue biopsy                                            analysis


                                                                     matrix deposition
                                                                                         laser      ions
                                                    mounted
                                                    tissue section
  adapted from Schwartz et al.
  Clin. Cancer Res. 2004, 20, 981
                  Application of Proteomics in Cancer Research



            Protein quantification
• high-abundance proteins: 109 molecules /cell
  low-abundance proteins: 102 molecules /cell


• parameters: sensitivity, linear range, reproducibility

• quantification on separation level:            protein staining (2DE)
                                                 UV-detection (HPLC)

• quantification by internal controls:
     covalent labelling:                         DIGE (2DE), ICAT (MS)
     spectra analysis:                           ICAT (MS), SELDI (MS)
                      Application of Proteomics in Cancer Research



                ProteinChips and SELDI
• ProteinChips with functionalized chromatographic surfaces:

  hydrophobic     anionic        cationic           IMAC             normal phase




• surface-enhanced laser desorption/ionization (SELDI)-TOF-MS:
  detection of Chip-bound proteins

• bioinformatic quantification of specific proteins or clusters

• pitfalls: mass resolution, reproducibility …

• Examples: various tumor markers
                                                      Wiesner, Curr Pharm Biotech. 2004, 5, 45
Application of Proteomics in Cancer Research




      • Proteomics

      • Cancer

      • Aims

      • Tools

      •   Results
      • Challenges

      • Summary
              Application of Proteomics in Cancer Research



                   Biomarkers
• samples:         cells, body fluids, tissues


• methods:         combinations of LCM, 2DE, MS, ...


• biomarkers:      diagnostic, prognostic, predictive


• parameters:      sensitivity, specificity


• problems:        complexity, variability, reproducibility
                   Application of Proteomics in Cancer Research



                        Biomarkers
• Example: biomarker for bladder cancer
           2DE of tissues
           silver staining
                                 bladder cancer tissue                 healthy urothelium


           MALDI-TOF-MS and sequencing Calreticulin

           Westernblot:
           anti-calreticulin
           antibody              bladder cancer tissue                 healthy urothelium


           Westernblot analysis of urine                          sensitivity: 73 %
                                                                  specificity: 86 %
                                             (Kageyama et al. Clin. Chem. 2004, online Feb 19, in press)
                   Application of Proteomics in Cancer Research



                        Biomarkers
• biomarker: discovery, identification, characterization, validation
        combined bioanalytics and bioinformatics

• advantage of body fluids over tissues:
        easily accessible in larger quantities

• advantage of combined markers over single markers:
           analysis of protein patterns (cluster analysis)
        increased sensitivity and specificity
                       Application of Proteomics in Cancer Research



                            Biomarkers
• diagnostic biomarkers: cancer detection in body fluids (SELDI)
  cancer       sample          biomarkers              sensitivity                 specificity
  bladder      urine                 5                    87 %                         66 %
  prostate     serum                 7                    83 %                          97 %
  breast       serum                 3                    93 %                          91 %
  ovarian      serum                 8                  100 %                           95 %
                                                                adapted from Fels et al. Dig. Dis. 2003, 21, 292


• data analysis in protein profiling is important!
           initial results by Petricoin et al. 2002    vs.
      e.g. critical data re-analysis by Baggerly et al. 2004
       reproducibility, artifacts ?
                             “The devil is … !”
                                                                 http://www.holzwurm-meine.de/images/teufel.gif
                     Application of Proteomics in Cancer Research



                          Biomarkers
• tumor antigens and tumor specific antibodies:
    lung cancer        PGP 9.5             neurospecific protein
    breast cancer      RS/DJ-1             RNA-protein interaction regulator



• prognostic biomarkers: low vs. high malignant tumors
    ovarian cancer     FK506BP             regulatory function (TGFb-R-pathway)



• predictive biomarkers: response to different therapies
    ovarian cancer     glyoxylase I        detoxification (chemotherapy)
                  Application of Proteomics in Cancer Research



            Therapeutic targets
      1.) identification of potential therapeutic targets

      2.) development of specific inhibitors

      3.) tests: in-vitro  in-vivo  clinical trials

• Example Her2:        human epidermal growth factor receptor
                       overexpression in breast cancer cells
                       inhibition by monoclonal antibodies
                        decreased cellular proliferation
                       Herceptin (truncated blocking-antibody)
                 Application of Proteomics in Cancer Research



                 Therapy control

1.) monitoring of positive therapeutic effects
      • based on identified tumor markers  limited number
      • initial attempts with proteomic patterns


2.) monitoring of negative therapeutic effects
       • proteomic monitoring of radiation or chemically induced
         protein modification
       • serum and tissue proteins (preliminary experiments)
Application of Proteomics in Cancer Research




      • Proteomics

      • Cancer

      • Aims

      • Tools

      • Results

      •   Challenges
      • Summary
               Application of Proteomics in Cancer Research



                     Challenges
                     General
                     • complexity
                     • variability
                     • reproducibility

Bioanalytics                               Bioinformatics
• limited throughput                       • data management
• absolute quantification                  • integrated data bases
• low-abundance proteins                   • sensitive algorithms
            Application of Proteomics in Cancer Research



        Integrated approach
        bioanalytics                  bioinformatics




genomics            transcriptomics                        proteomics




          complementary information
        physiology and pathophysiology


basic science                                     patient„s benefit
Application of Proteomics in Cancer Research




      • Proteomics

      • Cancer

      • Aims

      • Tools

      • Examples

      • Challenges

      •   Summary
                     Application of Proteomics in Cancer Research



                             Summary
• bioanalytics and bioinformatics are important in proteomics

• cancer is a challenging field: scientists, physicians and patients

• biomarker identification and therapeutic aspects

• workflow: collection, separation, identification, quantification

• limitations (e.g. reproducibility, throughput, data management)

• integration of genomics, transcriptomics and proteomics
 Contact:    andreas.humeny@biochem.uni-erlangen.de
 Homepage:   http://www.humeny.net  downloads

				
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