TY - JOUR
T1 - Integrative bioinformatic analyses of an oncogenomic profile reveal the biology of endometrial cancer and guide drug discovery
AU - Wong, Henry Sung Ching
AU - Juan, Yung-Shun
AU - Wu, Mei-Shin
AU - Zhang, Yan-Feng
AU - Hsu, Yu-Wen
AU - Chen, Huang-Hui
AU - Liu, Wei-Min
AU - Chang, Wei-Chiao
N1 - Export Date: 6 April 2016
通訊地址: Chang, W.-C.; Taipei Medical University, School of PharmacyTaiwan; 電子郵件: [email protected]
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PY - 2016
Y1 - 2016
N2 - 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 genomewide 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.
AB - 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 genomewide 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.
KW - Cancer drivers
KW - Cancer drug repurposing
KW - Cancer genomics
KW - Endometrial cancers
KW - Expression-associated somatic mutations
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M3 - Article
SN - 1949-2553
VL - 7
SP - 5909
EP - 5923
JO - Oncotarget
JF - Oncotarget
IS - 5
ER -