Proteome informatics for cancer research: From molecules to clinic

Proteomics offers the most direct approach to understand disease and its molecular biomarkers. Biomarkers denote the biological states of tissues, cells, or body fluids that are useful for disease detection and classification. Clinical proteomics is used for early disease detection, molecular diagnosis of disease, identification and formulation of therapies, and disease monitoring and prognostics. Bioinformatics tools are essential for converting raw proteomics data into knowledge and subsequently into useful applications. These tools are used for the collection, processing, analysis, and interpretation of the vast amounts of proteomics data. Management, analysis, and interpretation of large quantities of raw and processed data require a combination of various informatics technologies such as databases, sequence comparison, predictive models, and statistical tools. We have demonstrated the utility of bioinformatics in clinical proteomics through the analysis of the cancer antigen survivin and its suitability as a target for cancer immunotherapy.

[1]  Ralph S Freedman,et al.  Peritoneal inflammation – A microenvironment for Epithelial Ovarian Cancer (EOC) , 2004, Journal of Translational Medicine.

[2]  L. Karabon,et al.  IL-6 production in ovarian carcinoma is associated with histiotype and biological characteristics of the tumour and influences local immunity , 2000, British Journal of Cancer.

[3]  Bo Franzén,et al.  Frozen tissue biobanks. Tissue handling, cryopreservation, extraction, and use for proteomic analysis , 2006, Acta oncologica.

[4]  Robert Longtin,et al.  For tissue organization theory of cancer, a difficult road to acceptance. , 2005, Journal of the National Cancer Institute.

[5]  Ingo Fricke,et al.  Dendritic Cells and Tumor Microenvironment: A Dangerous Liaison , 2006, Immunological investigations.

[6]  P. Carmeliet,et al.  Angiogenesis in cancer and other diseases , 2000, Nature.

[7]  John Quackenbush,et al.  Synchronous global assessment of gene and protein expression in colorectal cancer progression. , 2005, Genomics.

[8]  H. Rammensee,et al.  SYFPEITHI: database for MHC ligands and peptide motifs , 1999, Immunogenetics.

[9]  Amos Bairoch,et al.  Swiss-Prot: Juggling between evolution and stability , 2004, Briefings Bioinform..

[10]  B. Zetter,et al.  Cancer biomarkers: knowing the present and predicting the future. , 2005, Future oncology.

[11]  Ellis L. Reinherz,et al.  Enhancement to the RANKPEP resource for the prediction of peptide binding to MHC molecules using profiles , 2004, Immunogenetics.

[12]  Mads Hald Andersen,et al.  Identification of Novel Survivin-Derived CTL Epitopes with Different HLA-A-Restriction Profiles , 2004, Cancer biology & therapy.

[13]  Philip E. Bourne,et al.  The RCSB PDB information portal for structural genomics , 2005, Nucleic Acids Res..

[14]  François Chevenet,et al.  The pitfalls of proteomics experiments without the correct use of bioinformatics tools , 2006, Proteomics.

[15]  Ole Mogensen,et al.  Carcinoma in situ cervicis uteri and inheritance--a Danish twin study. , 2006, Gynecologic oncology.

[16]  Tsviya Olender,et al.  Human Gene-Centric Databases at the Weizmann Institute of Science: GeneCards, UDB, CroW 21 and HORDE , 2003, Nucleic Acids Res..

[17]  Toshihisa Takagi,et al.  PRIME: automatically extracted PRotein Interactions and Molecular Information databas , 2004, Silico Biol..

[18]  Gregory D. Schuler,et al.  Database resources of the National Center for Biotechnology Information: update , 2004, Nucleic acids research.

[19]  Hongyu Zhao,et al.  Serum protein markers for early detection of ovarian cancer. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[20]  Daniel Birnbaum,et al.  Protein expression profiling identifies subclasses of breast cancer and predicts prognosis. , 2005, Cancer research.

[21]  J. Downing,et al.  Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling. , 2002, Cancer cell.

[22]  Michael Karin,et al.  Intracellular pattern recognition receptors in the host response , 2006, Nature.

[23]  L. Staudt,et al.  The use of molecular profiling to predict survival after chemotherapy for diffuse large-B-cell lymphoma. , 2002, The New England journal of medicine.

[24]  J. Weinstein,et al.  Workshop on cancer biometrics: identifying biomarkers and surrogates of cancer in patients: a meeting held at the Masur Auditorium, National Institutes of Health. , 2005, Journal of immunotherapy.

[25]  Federica Cavallo,et al.  Vaccines for tumour prevention , 2006, Nature Reviews Cancer.

[26]  Michel C. Nussenzweig,et al.  Dendritic Cells Induce Peripheral T Cell Unresponsiveness under Steady State Conditions in Vivo , 2001, The Journal of experimental medicine.

[27]  Pierre P Massion,et al.  Novel strategies for the early detection and prevention of lung cancer. , 2005, Seminars in oncology.

[28]  Yixin Wang,et al.  Novel Genes Associated with Malignant Melanoma but not Benign Melanocytic Lesions , 2005, Clinical Cancer Research.

[29]  E Springer,et al.  Survivin-deltaEx3 and survivin-2B: two novel splice variants of the apoptosis inhibitor survivin with different antiapoptotic properties. , 1999, Cancer research.

[30]  R. Sturm Skin colour and skin cancer - MC1R, the genetic link. , 2002, Melanoma research.

[31]  Thomas A Luger,et al.  Immune response modifiers – mode of action , 2006, Experimental dermatology.

[32]  Lars Fugger,et al.  MHC class II proteins and disease: a structural perspective , 2006, Nature Reviews Immunology.

[33]  H. Fischer Towards quantitative biology: integration of biological information to elucidate disease pathways and to guide drug discovery. , 2005, Biotechnology annual review.

[34]  Ivan Martin,et al.  Three‐dimensional culture of melanoma cells profoundly affects gene expression profile: A high density oligonucleotide array study , 2005, Journal of cellular physiology.

[35]  Marie-Christine W. Gast,et al.  Clinical proteomics: searching for better tumour markers with SELDI-TOF mass spectrometry. , 2006, Trends in pharmacological sciences.

[36]  M. Katoh,et al.  Bioinformatics for Cancer Management in the Post-Genome Era , 2006, Technology in cancer research & treatment.

[37]  Wei Zhou,et al.  Allelic variations in gene expression , 2004, Current opinion in oncology.

[38]  Vladimir Brusic,et al.  MULTIPRED: a computational system for prediction of promiscuous HLA binding peptides , 2005, Nucleic Acids Res..

[39]  Ziding Feng,et al.  Optimized Normalization for Antibody Microarrays and Application to Serum-Protein Profiling*S , 2005, Molecular & Cellular Proteomics.

[40]  L. Coussens,et al.  The inflammatory tumor microenvironment and its impact on cancer development. , 2006, Contributions to microbiology.

[41]  Dennis P Curran,et al.  Systems cell biology knowledge created from high content screening. , 2005, Assay and drug development technologies.

[42]  M. Fields,et al.  Ovarian cancer screening: a look at the evidence. , 2006, Clinical journal of oncology nursing.

[43]  Henrik Alm,et al.  Normalization and expression changes in predefined sets of proteins using 2D gel electrophoresis: A proteomic study of L-DOPA induced dyskinesia in an animal model of Parkinson's disease using DIGE , 2006, BMC Bioinformatics.

[44]  H. Rammensee,et al.  Generation of survivin-specific CD8+ T effector cells by dendritic cells pulsed with protein or selected peptides. , 2000, Cancer research.

[45]  Sam Hanash,et al.  HUPO Initiatives Relevant to Clinical Proteomics* , 2004, Molecular & Cellular Proteomics.

[46]  Edison T Liu,et al.  Systems Biology, Integrative Biology, Predictive Biology , 2005, Cell.

[47]  Chee Keong Kwoh,et al.  PREDTAP: a system for prediction of peptide binding to the human transporter associated with antigen processing , 2006, Immunome research.

[48]  Balwir Matharoo-Ball,et al.  The identification of human tumour antigens: current status and future developments , 2006, Cancer Immunology, Immunotherapy.

[49]  M. Hilario,et al.  Processing and classification of protein mass spectra. , 2006, Mass spectrometry reviews.

[50]  Kiyoko F. Aoki-Kinoshita,et al.  From genomics to chemical genomics: new developments in KEGG , 2005, Nucleic Acids Res..

[51]  Thomas L. Madden,et al.  Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. , 1997, Nucleic acids research.

[52]  A. Melnick,et al.  Specific peptides for the therapeutic targeting of oncogenes. , 2006, Current opinion in genetics & development.

[53]  Frédérique Lisacek,et al.  Proteome informatics II: Bioinformatics for comparative proteomics , 2006, Proteomics.

[54]  B. Bodey,et al.  Mechanisms and markers of carcinogenesis and neoplastic progression , 2005, Expert opinion on biological therapy.

[55]  Philip E. Bourne,et al.  Curation of complex, context-dependent immunological data , 2006, BMC Bioinformatics.

[56]  Paolo Bechi,et al.  Differential expression proteomics of human colon cancer. , 2006, American journal of physiology. Gastrointestinal and liver physiology.

[57]  L. Suva,et al.  Genomics and Proteomics of Bone Cancer , 2006, Clinical Cancer Research.

[58]  S Brunak,et al.  Sensitive quantitative predictions of peptide-MHC binding by a 'Query by Committee' artificial neural network approach. , 2003, Tissue antigens.

[59]  Federico Garrido,et al.  MHC class I antigens, immune surveillance, and tumor immune escape , 2003, Journal of cellular physiology.

[60]  A. Joe,et al.  Mechanisms of Disease: oncogene addiction—a rationale for molecular targeting in cancer therapy , 2006, Nature Clinical Practice Oncology.

[61]  Lajos Pusztai,et al.  Molecular classification of breast cancer: limitations and potential. , 2006, The oncologist.

[62]  Arie Admon,et al.  Proteomics in cancer vaccine development , 2005, Expert review of proteomics.

[63]  Concha Bielza,et al.  Machine Learning in Bioinformatics , 2008, Encyclopedia of Database Systems.

[64]  Eugene Kolker,et al.  A predictive model for identifying proteins by a single peptide match , 2007, Bioinform..

[65]  Nina Bhardwaj,et al.  Antigen-Specific Inhibition of Effector T Cell Function in Humans after Injection of Immature Dendritic Cells , 2001, The Journal of experimental medicine.

[66]  Balazs Györffy,et al.  A Web-based data warehouse on gene expression in human malignant melanoma. , 2007, The Journal of investigative dermatology.

[67]  P. Swain,et al.  Stochastic Gene Expression in a Single Cell , 2002, Science.

[68]  G. Omenn Strategies for plasma proteomic profiling of cancers , 2006, Proteomics.

[69]  Thomas Rades,et al.  Immunostimulatory colloidal delivery systems for cancer vaccines , 2006, Expert opinion on drug delivery.

[70]  R. Appel,et al.  Guidelines for the next 10 years of proteomics , 2009, Proteomics.

[71]  K. Kinzler,et al.  Cancer genes and the pathways they control , 2004, Nature Medicine.

[72]  J. Foekens,et al.  Do the survivin (BIRC5) splice variants modulate or add to the prognostic value of total survivin in breast cancer? , 2006, Clinical chemistry.

[73]  A. Semjonow,et al.  Pilot study of capillary electrophoresis coupled to mass spectrometry as a tool to define potential prostate cancer biomarkers in urine , 2005, Electrophoresis.

[74]  Donna Niedzwiecki,et al.  Telomerase mRNA-Transfected Dendritic Cells Stimulate Antigen-Specific CD8+ and CD4+ T Cell Responses in Patients with Metastatic Prostate Cancer 1 , 2005, The Journal of Immunology.

[75]  G. Omenn,et al.  Exploring the Human Plasma Proteome , 2005, Proteomics.

[76]  S. Wadler,et al.  Advances in the treatment of metastatic colorectal cancer. , 2001, Clinical colorectal cancer.

[77]  Alistair J. P. Brown,et al.  PEDRo: A database for storing, searching and disseminating experimental proteomics data , 2004, BMC Genomics.

[78]  K. Parker,et al.  Scheme for ranking potential HLA-A2 binding peptides based on independent binding of individual peptide side-chains. , 1994, Journal of immunology.

[79]  A. Eggermont,et al.  Gene expression profiling of primary cutaneous melanoma and clinical outcome. , 2006, Journal of the National Cancer Institute.

[80]  Markus Weininger,et al.  Complete remission of liver metastasis of pancreatic cancer under vaccination with a HLA-A2 restricted peptide derived from the universal tumor antigen survivin , 2006, Cancer Immunology, Immunotherapy.

[81]  Chris F. Taylor,et al.  Minimum Reporting Requirements for Proteomics: A MIAPE Primer , 2006, Proteomics.

[82]  Rolf Apweiler,et al.  Bioinformatics Resources for In Silico Proteome Analysis , 2003, Journal of biomedicine & biotechnology.

[83]  K. Hoek,et al.  Whole-genome expression profiling of the melanoma progression pathway reveals marked molecular differences between nevi/melanoma in situ and advanced-stage melanomas , 2005, Cancer biology & therapy.

[84]  Michael Heberer,et al.  Culture of Melanoma Cells in 3-Dimensional Architectures Results in Impaired Immunorecognition by Cytotoxic T Lymphocytes Specific for Melan-A/MART-1 Tumor-Associated Antigen , 2005 .

[85]  Scott McMillan,et al.  A compilation of molecular biology web servers: 2006 update on the Bioinformatics Links Directory , 2006, Nucleic Acids Res..

[86]  G. Linette,et al.  Molecular diagnostics in melanoma. , 2005, Journal of the American Academy of Dermatology.

[87]  L. Tussey,et al.  Mapping and binding analysis of peptides derived from the tumor-associated antigen survivin for eight HLA alleles. , 2005, Cancer immunity.

[88]  Catherine Brooksbank,et al.  The European Bioinformatics Institute's data resources: towards systems biology , 2004, Nucleic Acids Res..

[89]  N. Hamasaki,et al.  Expression of lysosome-associated membrane proteins in human colorectal neoplasms and inflammatory diseases. , 2001, The American journal of pathology.

[90]  Kun Yu,et al.  Methods for Prediction of Peptide Binding to MHC Molecules: A Comparative Study , 2002, Molecular medicine.

[91]  D. Hanahan,et al.  The Hallmarks of Cancer , 2000, Cell.

[92]  Vladimir Brusic,et al.  Information technologies for vaccine research , 2005, Expert review of vaccines.

[93]  J. Venables Unbalanced alternative splicing and its significance in cancer , 2006, BioEssays : news and reviews in molecular, cellular and developmental biology.

[94]  D. Altieri,et al.  A novel anti-apoptosis gene, survivin, expressed in cancer and lymphoma , 1997, Nature Medicine.

[95]  Augusto C. Ochoa,et al.  Mechanisms of Tumor Escape from the Immune Response , 2002 .

[96]  R. Guleria,et al.  Biomarkers in cancer screening, research and detection: present and future: a review , 2006, Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals.

[97]  Michael Y. Galperin The Molecular Biology Database Collection: 2007 update , 2006, Nucleic Acids Res..

[98]  Ron D Appel,et al.  Proteome informatics I: Bioinformatics tools for processing experimental data , 2006, Proteomics.

[99]  Thomas M. Mack,et al.  Heritable breast cancer in twins , 2002, British Journal of Cancer.

[100]  Lieve Moons,et al.  CXCL12 and vascular endothelial growth factor synergistically induce neoangiogenesis in human ovarian cancers. , 2005, Cancer research.

[101]  Hans Morreau,et al.  High-resolution analysis of HLA class I alterations in colorectal cancer , 2006, BMC Cancer.

[102]  Anne S. De Groot,et al.  Immunomics: discovering new targets for vaccines and therapeutics , 2006 .

[103]  Eugene Kolker,et al.  Randomized sequence databases for tandem mass spectrometry peptide and protein identification. , 2005, Omics : a journal of integrative biology.

[104]  M. Blagosklonny,et al.  Molecular theory of cancer , 2005, Cancer biology & therapy.