ArticleBMC cancer2010
Comparative survival analysis of breast cancer microarray studies identifies important prognostic genetic pathways.
Article in BMC cancer, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Comparative study of joint analysis of microarray gene expression data in survival prediction and risk assessment of breast cancer patients.Briefings in bioinformatics · 2016Pooled it
- Identification of Key lncRNA-mRNA Pairs and Functional lncRNAs in Breast Cancer by Integrative Analysis of TCGA Data.Frontiers in genetics · 2021Article
- Prognostic genes of breast cancer revealed by gene co-expression network analysis.Oncology letters · 2017Article
- Novel image markers for non-small cell lung cancer classification and survival prediction.BMC bioinformatics · 2014Article
- Functional characterization of breast cancer using pathway profiles.BMC medical genomics · 2014Article
- Bisphenol-A-induced inactivation of the p53 axis underlying deregulation of proliferation kinetics, and cell death in non-malignant human breast epithelial cells.Carcinogenesis · 2013Article
- canEvolve: a web portal for integrative oncogenomics.PloS one · 2013Article
- Validating the impact of a molecular subtype in ovarian cancer on outcomes: a study of the OVCAD Consortium.Cancer science · 2012Article
- Article
- Patient-specific data fusion defines prognostic cancer subtypes.PLoS computational biology · 2011Article
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5 authors.
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Abstract
backgroundAn estimated 12% of females in the United States will develop breast cancer in their lifetime. Although, there are advances in treatment options including surgery and chemotherapy, breast cancer is still the second most lethal cancer in women. Thus, there is a clear need for better methods to predict prognosis for each breast cancer patient. With the advent of large genetic databases and the reduction in cost for the experiments, researchers are faced with choosing from a large pool of potential prognostic markers from numerous breast cancer gene expression profile studies.
methodsFive microarray datasets related to breast cancer were examined using gene set analysis and the cancers were categorized into different subtypes using a scoring system based on genetic pathway activity.
resultsWe have observed that significant genes in the individual studies show little reproducibility across the datasets. From our comparative analysis, using gene pathways with clinical variables is more reliable across studies and shows promise in assessing a patient's prognosis.
conclusionsThis study concludes that, in light of clinical variables, there are significant gene pathways in common across the datasets. Specifically, several pathways can further significantly stratify patients for survival. These candidate pathways should help to develop a panel of significant biomarkers for the prognosis of breast cancer patients in a clinical setting.
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