ArticleScientific reports2015
Evaluation of drug-targetable genes by defining modes of abnormality in gene expression.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 14 citations in OpenAlex.
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- Single-cell RNA sequencing reveals a pro-metastatic subpopulation and the driver transcription factor NFE2L1 in ovarian cancer cells.Genes & genomics · 2023Article
- MAPKAPK2-centric transcriptome profiling reveals its major role in governing molecular crosstalk of IGFBP2, MUC4, and PRKAR2B during HNSCC pathogenesis.Computational and structural biotechnology journal · 2023Article
- Machine learning multi-omics analysis reveals cancer driver dysregulation in pan-cancer cell lines compared to primary tumors.Communications biology · 2022Article
- Prognostic Value of mRNA Expression of MAP4K Family in Acute Myeloid Leukemia.Technology in cancer research & treatment · 2019Article
- Astragalus polysaccharide combined with 10-hydroxycamptothecin inhibits metastasis in non-small cell lung carcinoma cell lines via the MAP4K3/mTOR signaling pathway.International journal of molecular medicine · 2018Article
- Article
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- Potential prognostic biomarkers identified by DNA methylation profiling analysis for patients with lung adenocarcinoma.Oncology letters · 2018Article
- Germinal-center kinase-like kinase co-crystal structure reveals a swapped activation loop and C-terminal extension.Protein science : a publication of the Protein Society · 2017Article
Corrections and comments
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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
In the post-genomic era, many researchers have taken a systematic approach to identifying abnormal genes associated with various diseases. However, the gold standard has not been established, and most of these abnormalities are difficult to be rehabilitated in real clinical settings. In addition to identifying abnormal genes, for a practical purpose, it is necessary to investigate abnormality diversity. In this context, this study is aimed to demonstrate simply restorable genes as useful drug targets. We devised the concept of "drug targetability" to evaluate several different modes of abnormal genes by predicting events after drug treatment. As a representative example, we applied our method to breast cancer. Computationally, PTPRF, PRKAR2B, MAP4K3, and RICTOR were calculated as highly drug-targetable genes for breast cancer. After knockdown of these top-ranked genes (i.e., high drug targetability) using siRNA, our predictions were validated by cell death and migration assays. Moreover, inhibition of RICTOR or PTPRF was expected to prolong lifespan of breast cancer patients according to patient information annotated in microarray data. We anticipate that our method can be widely applied to elaborate selection of novel drug targets, and, ultimately, to improve the efficacy of disease treatment.
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