Article

Wang Y, Klijn JGM, Zhang Y, Sieuwerts AM, Look MP, Yang F et al.. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 365: 671

Veridex LLC, a Johnson & Johnson Company, San Diego, CA, USA.
The Lancet (Impact Factor: 45.22). 01/2006; 365(9460):671-9. DOI: 10.1016/S0140-6736(05)17947-1
Source: PubMed

ABSTRACT Genome-wide measures of gene expression can identify patterns of gene activity that subclassify tumours and might provide a better means than is currently available for individual risk assessment in patients with lymph-node-negative breast cancer.
We analysed, with Affymetrix Human U133a GeneChips, the expression of 22000 transcripts from total RNA of frozen tumour samples from 286 lymph-node-negative patients who had not received adjuvant systemic treatment.
In a training set of 115 tumours, we identified a 76-gene signature consisting of 60 genes for patients positive for oestrogen receptors (ER) and 16 genes for ER-negative patients. This signature showed 93% sensitivity and 48% specificity in a subsequent independent testing set of 171 lymph-node-negative patients. The gene profile was highly informative in identifying patients who developed distant metastases within 5 years (hazard ratio 5.67 [95% CI 2.59-12.4]), even when corrected for traditional prognostic factors in multivariate analysis (5.55 [2.46-12.5]). The 76-gene profile also represented a strong prognostic factor for the development of metastasis in the subgroups of 84 premenopausal patients (9.60 [2.28-40.5]), 87 postmenopausal patients (4.04 [1.57-10.4]), and 79 patients with tumours of 10-20 mm (14.1 [3.34-59.2]), a group of patients for whom prediction of prognosis is especially difficult.
The identified signature provides a powerful tool for identification of patients at high risk of distant recurrence. The ability to identify patients who have a favourable prognosis could, after independent confirmation, allow clinicians to avoid adjuvant systemic therapy or to choose less aggressive therapeutic options.

Download full-text

Full-text

Available from: Els M J J Berns, Aug 27, 2015
1 Follower
 · 
595 Views
  • Source
    • "Simon and Dr A . Peng Lam on a series of human breast tumours ( n ¼ 344 ) described in detail elsewhere ( Wang et al , 2005 ) . We used a filter to refine the metastasis - related gene set . "
    [Show abstract] [Hide abstract]
    ABSTRACT: Vascular endothelial growth factor (VEGF) is a multifunctional cytokine that has important roles in angiogenesis. Our knowledge of the significance of VEGF isoforms in human cancer remains incomplete. Bioluminescence imaging and transcriptomic analysis were used to study the colonisation capacity of the human breast cancer cells MDA-MB-231 controlling or overexpressing the VEGF165 or VEGF189 isoform (named cV-B, V165-B and V189-B, respectively) in nude mice. When injected into the bloodstream, V189-B cells induced less metastasis in the lungs and bone than V165-B and cV-B control cells, consistent with longer survival of these mice and delay in tumour uptake in the mice injected with a V189-B clone. Histological analysis confirmed that there were less αSMA-positive cells in the lungs of the mice injected with V189-B. In vitro V189-B cells decreased both cell invasion and survival. Using transcriptomic analysis, we identified a subset of 18 genes expressed differentially between V189 and V165 cell lines and in 120 human breast tumours. V165 was associated with poor prognosis, whereas V189 was not, suggesting a complex regulation by VEGF isoforms. Our results showed a negative correlation between the expression pattern of VEGF189 and the levels of expression of seven genes that influence metastasis. Our findings provide the first evidence that VEGF isoforms have different effects on breast cancer cell line colonisation in vivo.British Journal of Cancer advance online publication, 21 July 2015; doi:10.1038/bjc.2015.267 www.bjcancer.com.
    British Journal of Cancer 07/2015; DOI:10.1038/bjc.2015.267 · 4.82 Impact Factor
  • Source
    • "Other two datasets refer to breast cancer samples: in the rst we have primary tumour specimens that developed metastasis or not (97 and 28 samples respectively, referred to as Met", GEO accession number GSE2990 [16] [17]), while in the second there are primary tumour biopsies that relapsed or not (107 and 179 samples respectively, referred to as Rel", GEO accession number GSE2034 [18]). "
    Molecular BioSystems 04/2015; DOI:10.1039/C5MB00143A · 3.18 Impact Factor
  • Source
    • "TABLE 1 Summary of the Utilized Microarray Datasets Dataset # Samples a # High-risk # Low-risk Source GSE2034 286 95 169 [2] "
    IEEE/ACM Transactions on Computational Biology and Bioinformatics 01/2015; DOI:10.1109/TCBB.2015.2407407 · 1.54 Impact Factor
Show more