Proteome informatics for cancer research: from molecules to clinic

Proteomics. 2007 Mar;7(6):976-91. doi: 10.1002/pmic.200600965.


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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Amino Acid Sequence
  • Biomarkers, Tumor / genetics
  • Biomarkers, Tumor / metabolism
  • Computational Biology*
  • Humans
  • Immune System / physiology
  • Molecular Sequence Data
  • Neoplasm Proteins / classification
  • Neoplasm Proteins / genetics
  • Neoplasm Proteins / metabolism
  • Neoplasms* / classification
  • Neoplasms* / diagnosis
  • Neoplasms* / physiopathology
  • Neoplasms* / therapy
  • Prognosis
  • Proteome*
  • Proteomics
  • Software*


  • Biomarkers, Tumor
  • Neoplasm Proteins
  • Proteome