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Proteomics analysis in lung cancer: Challenges and opportunities
Author(s) -
KIKUCHI Takefumi,
CARBONE David P.
Publication year - 2007
Publication title -
respirology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.857
H-Index - 85
eISSN - 1440-1843
pISSN - 1323-7799
DOI - 10.1111/j.1440-1843.2006.00957.x
Subject(s) - proteomics , profiling (computer programming) , biomarker discovery , lung cancer , computational biology , medicine , biomarker , protein expression , bioinformatics , data science , pathology , computer science , biology , gene , operating system , biochemistry
Recent technological developments in proteomic analysis are bringing us new insights into the molecular classification of tumours. Although proteomic analysis in cancer profiling is still under development both in terms of the instruments used and the data analytical tools, this method has great potential advantages for the analysis of biospecimens of many types. Direct measurement of abnormally expressed or modified proteins in the tumour tissue and/or patient blood may be an effective approach for discovering new biomarkers. Proteomics has the significant advantage of being able to discern not only changes in expression levels but also in post‐translational modifications. Thus, the proteomics approach to protein profiling and biomarker discovery uncovers biomarkers from a different viewpoint than microarray analysis. This review summarizes the range of proteomics technologies employed for cancer profiling, and how they have been used to derive new classification models for human lung cancer.