Integrative bioinformatic analyses of an oncogenomic profile reveal the biology of endometrial cancer and guide drug discovery
| Autor: | Yu-Wen Hsu, Wei Chiao Chang, Yung-Shun Juan, Yanfeng Zhang, Mei Shin Wu, Henry Sung Ching Wong, Huang-Hui Chen, Wei-Min Liu |
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| Rok vydání: | 2015 |
| Předmět: |
0301 basic medicine
Databases Factual Genomics Computational biology medicine.disease_cause endometrial cancers 03 medical and health sciences Drug Discovery Biomarkers Tumor medicine Carcinoma Humans Precision Medicine cancer genomics Mutation Traditional medicine Drug discovery business.industry cancer drivers Endometrial cancer Drug Repositioning Computational Biology cancer drug repurposing medicine.disease Precision medicine Endometrial Neoplasms Drug repositioning 030104 developmental biology Oncology Genomic Profile Female business expression-associated somatic mutations Research Paper |
| Zdroj: | Oncotarget |
| ISSN: | 1949-2553 |
| Popis: | A major challenge in personalized cancer medicine is to establish a systematic approach to translate huge oncogenomic datasets to clinical situations and facilitate drug discovery for cancers such as endometrial carcinoma. We performed a genome-wide somatic mutation-expression association study in a total of 219 endometrial cancer patients from TCGA database, by evaluating the correlation between ∼5,800 somatic mutations to ∼13,500 gene expression levels (in total, ∼78, 500, 000 pairs). A bioinformatics pipeline was devised to identify expression-associated single nucleotide variations (eSNVs) which are crucial for endometrial cancer progression and patient prognoses. We further prioritized 394 biologically risky mutational candidates which mapped to 275 gene loci and demonstrated that these genes collaborated with expression features were significantly enriched in targets of drugs approved for solid tumors, suggesting the plausibility of drug repurposing. Taken together, we integrated a fundamental endometrial cancer genomic profile into clinical circumstances, further shedding light for clinical implementation of genomic-based therapies and guidance for drug discovery. |
| Databáze: | OpenAIRE |
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