|
Takayuki Iwamoto
Department Kawasaki Medical School Kawasaki Medical School, Department of Breast and Thyroid Surgery, Position Assistant Professor |
|
| Article types | 原著 |
| Language | English |
| Peer review | Peer reviewed |
| Title | Relative Prognostic and Predictive Value of Gene Signature and Histologic Grade in Estrogen Receptor-Positive, HER2-Negative Breast Cancer. |
| Journal | Formal name：Clinical breast cancer Abbreviation：Clin Breast Cancer ISSN code：19380666/15268209 |
| Domestic / Foregin | Foregin |
| Volume, Issue, Page | 16(2),pp.95-100.e1 |
| Author and coauthor | Takayuki Iwamoto, Catherine Kelly, Taeko Mizoo, Tomohiro Nogami, Takayuki Motoki, Tadahiko Shien, Naruto Taira, Naoki Hayashi, Naoki Niikura, Toshiyoshi Fujiwara, Hiroyoshi Doihara, Junji Matsuoka |
| Authorship | Lead author,Corresponding author |
| Publication date | 2016/04 |
| Summary | BACKGROUND:In estrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancer, first-generation genomic signatures serve predominately as prognostic biomarkers and secondarily as predictors of response to chemotherapy. We compared both the prognostic and predictive value of histologic grades and genomic markers.METHODS:We retrieved publicly available cDNA microarray data from 1373 primary ER(+)/HER2(-) breast cancers and developed a genomic signature simulated from Recurrence Online (http://www.recurrenceonline.com/) to calculate the recurrence score and risk using predefined sets of genes in the cDNA microarray. We then compared the prognostic and predictive information provided by histologic grade and genomic signature.RESULTS:Based on genomic signatures, 55%, 28%, and 17% of breast cancers were classified as low, intermediate, and high risk, respectively, whereas the histologic grades were I, II, and III in 22%, 59%, and 19% of breast cancers, respectively. Univariate analysis in the untreated cohort revealed that both histologic grade (overall P = .007) and genomic signature (P < .001) could predict prognosis. Results were similar using the genomic signature, with pathologic complete response rates of 4.6%, 5.7%, and 16.5% for low-, intermediate-, and high-risk cancers, respectively. Neither biomarker was statistically significant in multivariate analysis for predictive response to neoadjuvant chemotherapy (NAC).CONCLUSION:Genomic signature was better at identifying low-risk cases compared to histologic grade alone, but both markers had similar predictive values for NAC response. Better predictive biomarkers for NAC response are still needed. |
| DOI | 10.1016/j.clbc.2015.10.004 |
| PMID | 26631838 |