ArticleScientific reports2016
Exploring the intrinsic differences among breast tumor subtypes defined using immunohistochemistry markers based on the decision tree.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed.
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- Isoform switching leads to downregulation of cytokine producing genes in estrogen receptor positive breast cancer.Frontiers in genetics · 2023Article
- Integrated bioinformatic analysis of potential biomarkers of poor prognosis in triple-negative breast cancer.Translational cancer research · 2022Article
- Newly identified breast luminal progenitor and gestational stem cell populations likely give rise to HER2-overexpressing and basal-like breast cancers.Discover oncology · 2022Article
- Artificial intelligence in cancer target identification and drug discovery.Signal transduction and targeted therapy · 2022Review
- Gene-environment interaction identification via penalized robust divergence.Biometrical journal. Biometrische Zeitschrift · 2022Article
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- ClearF: a supervised feature scoring method to find biomarkers using class-wise embedding and reconstruction.BMC medical genomics · 2019Article
- Extracting predictors for lung adenocarcinoma based on Granger causality test and stepwise character selection.BMC bioinformatics · 2019Article
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- Recurrent mutations at estrogen receptor binding sites alter chromatin topology and distal gene expression in breast cancer.Genome biology · 2018Article
- A novel information diffusion method based on network consistency for identifying disease related microRNAs.RSC advances · 2018Article
- Global Similarity Method Based on a Two-tier Random Walk for the Prediction of microRNA-Disease Association.Scientific reports · 2018Article
- Combining DNA methylation and RNA sequencing data of cancer for supervised knowledge extraction.BioData mining · 2018Article
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Exploring the intrinsic differences among breast cancer subtypes is of crucial importance for precise diagnosis and therapeutic decision-making in diseases of high heterogeneity. The subtypes defined with several layers of information are related but not consistent, especially using immunohistochemistry markers and gene expression profiling. Here, we explored the intrinsic differences among the subtypes defined by the estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 based on the decision tree. We identified 30 mRNAs and 7 miRNAs differentially expressed along the tree's branches. The final signature panel contained 30 mRNAs, whose performance was validated using two public datasets based on 3 well-known classifiers. The network and pathway analysis were explored for feature genes, from which key molecules including FOXQ1 and SFRP1 were revealed to be densely connected with other molecules and participate in the validated metabolic pathways. Our study uncovered the differences among the four IHC-defined breast tumor subtypes at the mRNA and miRNA levels, presented a novel signature for breast tumor subtyping, and identified several key molecules potentially driving the heterogeneity of such tumors. The results help us further understand breast tumor heterogeneity, which could be availed in clinics.
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