Research Papers:

Association of a cytarabine chemosensitivity related gene expression signature with survival in cytogenetically normal acute myeloid leukemia

Han Yan _, Lu Wen, Dan Tan, Pan Xie, Feng-mei Pang, Hong-hao Zhou, Wei Zhang, Zhao-qian Liu, Jie Tang, Xi Li and Xiao-ping Chen

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Oncotarget. 2017; 8:1529-1540. https://doi.org/10.18632/oncotarget.13650

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Han Yan1,2,4, Lu Wen3, Dan Tan1,2,4, Pan Xie1,2,4, Feng-mei Pang1,2,4, Hong-hao Zhou1,2,4, Wei Zhang1,2,4, Zhao-qian Liu1,2,4, Jie Tang1,2,4, Xi Li1,2,4, Xiao-ping Chen1,2,4

1Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410008, P. R. China

2Institute of Clinical Pharmacology, Central South University, Hunan Key Laboratory of Pharmacogenetics, Changsha 410078, P. R. China

3Department of Diagnostic Radiology, Hunan Cancer Hospital, Changsha 410013, Hunan, P. R. China

4Hunan Province Cooperation Innovation Center for Molecular Target New Drug Study, Hengyang 421001, P. R. China

Correspondence to:

Xiao-Ping Chen, email: [email protected]

Xi Li, email: [email protected]

Keywords: cytarabine, chemosensitivity, acute myeloid leukemia, prognosis, signature

Received: August 08, 2016     Accepted: November 15, 2016     Published: November 26, 2016


The prognosis of cytogenetically normal acute myeloid leukemia (CN-AML) varies greatly among patients. Achievement of complete remission (CR) after chemotherapy is indispensable for a better prognosis. To develop a gene signature predicting overall survival (OS) in CN-AML, we performed data mining procedure based on whole genome expression data of both blood cancer cell lines and AML patients from open access database. A gene expression signature including 42 probes was derived. These probes were significantly associated with both cytarabine half maximal inhibitory concentration values in blood cancer cell lines and OS in CN-AML patients. By using cox regression analysis and linear regression analysis, a chemo-sensitive score calculated algorithm based on mRNA expression levels of the 42 probes was established. The scores were associated with OS in both the training sample (p=5.13 × 10-4, HR=2.040, 95% CI: 1.364-3.051) and the validation sample (p=0.002, HR=2.528, 95% CI: 1.393-4.591) of the GSE12417 dataset from Gene Expression Omnibus. In The Cancer Genome Atlas (TCGA) CN-AML patients, higher scores were found to be associated with both worse OS (p=0.013, HR=2.442, 95% CI: 1.205-4.950) and DFS (p=0.015, HR=2.376, 95% CI: 1.181-4.779). Results of gene ontology (GO) analysis showed that all the significant GO Terms were correlated with cellular component of mitochondrion. In summary, a novel gene set that could predict prognosis of CN-AML was identified presently, which provided a new way to identify genes impacting AML chemo-sensitivity and prognosis.

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