ArticleBreast cancer research : BCR2010
Microarray data analysis in neoadjuvant biomarker studies in estrogen receptor-positive breast cancer.
Article in Breast cancer research : BCR, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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5 citing papers in PubMed.
- Identification of Seven Cell Cycle-Related Genes with Unfavorable Prognosis and Construction of their TF-miRNA-mRNA regulatory network in Breast Cancer.Journal of Cancer · 2021Article
- Recent advances of therapeutic targets based on the molecular signature in breast cancer: genetic mutations and implications for current treatment paradigms.Journal of hematology & oncology · 2019Review
- Integrated bioinformatics analysis reveals key candidate genes and pathways in breast cancer.Molecular medicine reports · 2018Article
- Differential gene expression in tamoxifen-resistant breast cancer cells revealed by a new analytical model of RNA-Seq data.PloS one · 2012Article
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Abstract
Microarray data have been widely utilized to discover biomarkers predictive of response to endocrine therapy in estrogen receptor-positive breast cancer. Typically, these data have focused on analyses conducted on the diagnostic specimen. However, dynamic temporal changes in gene expression associated with treatment may deliver significant improvements to the current generation of predictive models. We present and discuss some statistical issues relevant to the paper by Taylor and colleagues, who conducted studies to model the prognostic potential of gene expression changes that occur after endocrine treatment.
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