|
Takayuki Iwamoto
Department Kawasaki Medical School Kawasaki Medical School, Department of Breast and Thyroid Surgery, Position Assistant Professor |
|
| Article types | 総説 |
| Language | English |
| Peer review | Peer reviewed |
| Title | Predicting prognosis of breast cancer with gene signatures: are we lost in a sea of data? |
| Journal | Formal name：Genome medicine Abbreviation：Genome Med ISSN code：1756994X/1756994X |
| Domestic / Foregin | Foregin |
| Volume, Issue, Page | 2(11),pp.81 |
| Author and coauthor | Takayuki Iwamoto, Lajos Pusztai |
| Authorship | Lead author |
| Publication date | 2010/11 |
| Summary | A large number of prognostic and predictive signatures have been proposed for breast cancer and a few of these are now available in the clinic as new molecular diagnostic tests. However, several other signatures have not fared well in validation studies. Some investigators continue to be puzzled by the diversity of signatures that are being developed for the same purpose but that share few or no common genes. The history of empirical development of prognostic gene signatures and the unique association between molecular subsets and clinical phenotypes of breast cancer explain many of these apparent contradictions in the literature. Three features of breast cancer gene expression contribute to this: the large number of individually prognostic genes (differentially expressed between good and bad prognosis cases); the unstable rankings of differentially expressed genes between datasets; and the highly correlated expression of informative genes. |
| DOI | 10.1186/gm202 |
| PMID | 21092148 |