PURPOSE: In the low-risk group of breast cancer patients, a subgroup experiences metastatic recurrence of the disease. The aim of this study was to examine the performance of gene sets, developed mainly from high-risk tumors, in a group of low-malignant tumors. EXPERIMENTAL DESIGN: Twenty-six tumors from low-risk patients and 34 low-malignant T2 tumors from patients with slightly higher risk have been examined by genome-wide gene expression analysis. Nine prognostic gene sets were tested in this data set. RESULTS: A 32-gene profile (HUMAC32) that accurately predicts metastasis has previously been developed from this data set. In the present study, six of the eight other gene sets have prognostic power in the low-malignant patient group, whereas two have no prognostic value. Despite a relatively small overlap between gene sets, there is high concordance of classification of samples. This, together with analysis of functional gene groups, indicates that the same pathways may be represented by several of the gene sets. However, the results suggest that low-risk patients may be classified more accurately with gene signatures developed especially for this patient group. CONCLUSION: Several gene sets, mainly developed in high-risk cancers, predict metastasis from low-malignant cancer.
PURPOSE: In the low-risk group of breast cancerpatients, a subgroup experiences metastatic recurrence of the disease. The aim of this study was to examine the performance of gene sets, developed mainly from high-risk tumors, in a group of low-malignant tumors. EXPERIMENTAL DESIGN: Twenty-six tumors from low-risk patients and 34 low-malignant T2 tumors from patients with slightly higher risk have been examined by genome-wide gene expression analysis. Nine prognostic gene sets were tested in this data set. RESULTS: A 32-gene profile (HUMAC32) that accurately predicts metastasis has previously been developed from this data set. In the present study, six of the eight other gene sets have prognostic power in the low-malignant patient group, whereas two have no prognostic value. Despite a relatively small overlap between gene sets, there is high concordance of classification of samples. This, together with analysis of functional gene groups, indicates that the same pathways may be represented by several of the gene sets. However, the results suggest that low-risk patients may be classified more accurately with gene signatures developed especially for this patient group. CONCLUSION: Several gene sets, mainly developed in high-risk cancers, predict metastasis from low-malignant cancer.
Authors: Ten-Yang Yen; Spencer Bowen; Roger Yen; Alexandra Piryatinska; Bruce A Macher; Leslie C Timpe Journal: J Proteome Res Date: 2017-03-21 Impact factor: 4.466
Authors: Jadwiga R Bienkowska; Gul S Dalgin; Franak Batliwalla; Normand Allaire; Ronenn Roubenoff; Peter K Gregersen; John P Carulli Journal: Genomics Date: 2009-08-20 Impact factor: 5.736
Authors: Roman Rouzier; Paolo Pronzato; Elisabeth Chéreau; Josh Carlson; Barnaby Hunt; William J Valentine Journal: Breast Cancer Res Treat Date: 2013-05-31 Impact factor: 4.872
Authors: Maria B Lyng; Anne-Vibeke Lænkholm; Qihua Tan; Werner Vach; Karina H Gravgaard; Ann Knoop; Henrik J Ditzel Journal: PLoS One Date: 2013-01-16 Impact factor: 3.240