Purpose: To assess the benefit from adjuvant systemic tamoxifen therapy in breast cancer risk groups identified by the previously established prognostic 76-gene signature.
Methods: In 300 lymph node-negative (LNN), estrogen receptor-positive (ER+) breast cancer patients (136 treated with adjuvant tamoxifen, 164 having received no systemic adjuvant therapy), distant metastasis-free survival (DMFS) as a function of the 76-gene signature was determined in a multicenter fashion.
Results: In 136 tamoxifen-treated patients, the 76-gene signature identified a group of patients with a poor prognosis [hazard ratio (HR), 4.62; P = 0.0248]. These patients showed a 12.3% absolute benefit of tamoxifen in 10-year DMFS (HR, 0.52; P = 0.0318) compared with untreated high-risk patients. This represented a 71% increase in relative benefit compared with the 7.2% absolute benefit observed for all 300 patients without using the gene signature. In the low-risk group there was no significant 10-year DMFS benefit of tamoxifen.
Conclusions: The 76-gene signature defines high-risk patients who benefit from adjuvant tamoxifen therapy. Although we did not study the value of chemotherapy in this study, low-risk patients identified by the 76-gene signature have a prognosis good enough that chemotherapy would be difficult to justify. The prognosis of these patients is sufficiently good, in fact, that a disease-free benefit for tamoxifen therapy is difficult to prove, though benefits in terms of loco-regional relapse and a reduction in risk for contralateral breast cancer might justify hormonal therapy in these patients.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s10549-008-0183-2 | DOI Listing |
Cancer Manag Res
May 2019
Key Laboratory of Anticancer Drugs and Biotherapy, the First Hospital of China Medical University, Shenyang, Liaoning, 110001, People's Republic of China.
The chr1p/19q co-deletion is a favorable prognostic factor in patients with lower grade glioma. The aim of this study was to reveal key genes for prognosis and establish prognostic gene signatures based on genes encoded by chr1p/19q. The data was downloaded from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA) and Gene Expression Omnibus (GEO).
View Article and Find Full Text PDFProc Natl Acad Sci U S A
March 2017
Terry Fox Laboratory, BC Cancer Agency, Vancouver, BC, Canada V5Z1L3;
Gene-gene or gene-drug interactions are typically quantified using fitness as a readout because the data are continuous and easily measured in high throughput. However, to what extent fitness captures the range of other phenotypes that show synergistic effects is usually unknown. Using and focusing on a matrix of DNA repair mutants and genotoxic drugs, we quantify 76 gene-drug interactions based on both mutation rate and fitness and find that these parameters are not connected.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
March 2015
Departments of Pathology and
BMC Cancer
March 2014
Department of Genetics, Institute for Cancer Research, Oslo University Hospital, The Norwegian Radium Hospital, Montebello 0310 Oslo, Norway.
Background: The aim was to assess and compare prognostic power of nine breast cancer gene signatures (Intrinsic, PAM50, 70-gene, 76-gene, Genomic-Grade-Index, 21-gene-Recurrence-Score, EndoPredict, Wound-Response and Hypoxia) in relation to ER status and follow-up time.
Methods: A gene expression dataset from 947 breast tumors was used to evaluate the signatures for prediction of Distant Metastasis Free Survival (DMFS). A total of 912 patients had available DMFS status.
Cancer Treat Rev
April 2014
Brustzentrum, Klinikum der Universität München, Maistraße 11, 80337 Munich, Germany; Université Paul Sabatier Toulouse III, Faculté des Sciences Pharmaceutiques, 31062 Toulouse Cedex 09, France. Electronic address:
In early breast cancer (eBC), established clinicopathological factors are not sufficient for clinical decision making particularly regarding adjuvant chemotherapy since substantial over- or undertreatment may occur. Thus, novel protein- and molecular markers have been put forward as decision aids. Since these potential prognosis and/or predictive tests differ substantially regarding their methodology, analytical and clinical validation, this review attempts to summarize the essential facts for clinicians.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!