Proteomics of breast carcinoma

Richard I. Somiari*, Stella Somiari, Stephen Russell, Craig D. Shriver

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

90 Scopus citations


Beast cancer is the most diagnosed cancer in women, accounting for approximately 40,000 deaths annually in the USA. Significant advances have been made in the areas of detection and treatment, but a significant number of breast cancers are detected late. The advent of proteomics provides the hope of discovering novel biological markers that can be used for early detection, disease diagnosis, prognostication and prediction of response to therapy. Several proteomics technologies including 2D-PAGE, 2D-DIGE, ICAT, SELDI-TOF, MudPIT and protein arrays have been used to uncover molecular mechanisms associated with breast carcinoma at the global level, and a number of these technologies, particularly the SELDI-TOF hold promise as a proteomic approach that can be applied at the bedside for discovering protein patterns that distinguish disease and disease-free states with high sensitivity and specificity. Laser microdissection, a method for selection of homogenous cell populations, coupled to 2D-DIGE or MudPIT constitute a new proteomics-based paradigm for detecting disease in pathology specimens and monitoring disease response to therapy. This review describes proteomics technologies, and their application in the proteomic analysis of breast carcinoma.

Original languageEnglish
Pages (from-to)215-225
Number of pages11
JournalJournal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences
Issue number1-2
StatePublished - 5 Feb 2005
Externally publishedYes


  • Proteomics
  • Reviews


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