ArticleScientific reports2014
Identification of phenotype deterministic genes using systemic analysis of transcriptional response.
Article in Scientific reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- Classification of IDH wild-type glioblastoma tumorspheres into low- and high-invasion groups based on their transcriptional program.British journal of cancer · 2023Article
- Single-cell RNA sequencing reveals a pro-metastatic subpopulation and the driver transcription factor NFE2L1 in ovarian cancer cells.Genes & genomics · 2023Article
- Mesenchymal Stem-Like Cells Derived from the Ventricle More Effectively Enhance Invasiveness of Glioblastoma Than Those Derived from the Tumor.Yonsei medical journal · 2023Article
- Evaluation of drug-targetable genes by defining modes of abnormality in gene expression.Scientific reports · 2015Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Systemic identification of deterministic genes for different phenotypes is a primary application of high-throughput expression profiles. However, gene expression differences cannot be used when the differences between groups are not significant. Therefore, novel methods incorporating features other than expression differences are required. We developed a promising method using transcriptional response as an operational feature, which is quantified as the correlation between expression levels of pathway genes and target genes of the pathway. We applied this method to identify causative genes associated with chemo-sensitivity to tamoxifen and epirubicin. Genes whose transcriptional response was dysregulated only in the drug-resistant patient group were chosen for in vitro validation in human breast cancer cells. Finally, we discovered two genes responsible for tamoxifen sensitivity and three genes associated with epirubicin sensitivity. The method we propose here can be widely applied to identify deterministic genes for different phenotypes with only minor differences in gene expression levels.
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