ArticleBMC cancer2014
Systematic assessment of prognostic gene signatures for breast cancer shows distinct influence of time and ER status.
Article in BMC cancer, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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20 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.
- Integration of single-cell and bulk RNA-sequencing data reveals the prognostic potential of epithelial gene markers for prostate cancer.Molecular oncology · 2025Pooled it
- Deep contrastive learning for predicting cancer prognosis using gene expression values.Briefings in bioinformatics · 2024Article
- Evaluation and comparison of different breast cancer prognosis scores based on gene expression data.Breast cancer research : BCR · 2023Article
- RNA-seq RNAaccess identified as the preferred method for gene expression analysis of low quality FFPE samples.PloS one · 2023Article
- Decision Theory versus Conventional Statistics for Personalized Therapy of Breast Cancer.Journal of personalized medicine · 2022Article
- KRT13 promotes stemness and drives metastasis in breast cancer through a plakoglobin/c-Myc signaling pathway.Breast cancer research : BCR · 2022Article
- Immunophenotype-associated gene signature in ductal breast tumors varies by receptor subtype, but the expression of individual signature genes remains consistent.Cancer medicine · 2021Article
- Decision theory for precision therapy of breast cancer.Scientific reports · 2021Article
- Molecular Biological Features of Nottingham Histological Grade 3 Breast Cancers.Annals of surgical oncology · 2020Article
- Decision of Adjuvant Systemic Treatment in HR+ HER2- Early Invasive Breast Cancer: Which Biomarkers Could Help?Cancer management and research · 2019Review
- Novel 18-gene signature for predicting relapse in ER-positive, HER2-negative breast cancer.Breast cancer research : BCR · 2018Article
- Development of a Novel Proteomic Risk-Classifier for Prognostication of Patients With Early-Stage Hormone Receptor-Positive Breast Cancer.Biomarker insights · 2018Article
- Gene expression information improves reliability of receptor status in breast cancer patients.Oncotarget · 2017Article
- Transposon insertional mutagenesis in mice identifies human breast cancer susceptibility genes and signatures for stratification.Proceedings of the National Academy of Sciences of the United States of America · 2017Article
- MammaPrint versus EndoPredict: Poor correlation in disease recurrence risk classification of hormone receptor positive breast cancer.PloS one · 2017Article
- Gene expression analysis supports tumor threshold over 2.0 cm for T-category breast cancer.EURASIP journal on bioinformatics & systems biology · 2016Article
- Determining breast cancer histological grade from RNA-sequencing data.Breast cancer research : BCR · 2016Article
- Article
- Gene expression profiling leads to discovery of correlation of matrix metalloproteinase 11 and heparanase 2 in breast cancer progression.BMC cancer · 2015Article
- Gene expression profile analysis of t1 and t2 breast cancer reveals different activation pathways.ISRN oncology · 2013Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
methodsA 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. The recently published METABRIC cohort was used as an additional validation set.
resultsSurvival predictions were fairly concordant across most signatures. Prognostic power declined with follow-up time. During the first 5 years of followup, all signatures except for Hypoxia were predictive for DMFS in ER-positive disease, and 76-gene, Hypoxia and Wound-Response were prognostic in ER-negative disease. After 5 years, the signatures had little prognostic power. Gene signatures provide significant prognostic information beyond tumor size, node status and histological grade.
conclusionsGenerally, these signatures performed better for ER-positive disease, indicating that risk within each ER stratum is driven by distinct underlying biology. Most of the signatures were strong risk predictors for DMFS during the first 5 years of follow-up. Combining gene signatures with histological grade or tumor size, could improve the prognostic power, perhaps also of long-term survival.
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