Gene signatures associated with drug resistance to irinotecan and oxaliplatin predict a poor prognosis in patients with colorectal cancer

被引:13
作者
Sun, Xinrong [1 ]
Wang, Xiang [1 ]
Feng, Wenming [1 ]
Guo, Huihui [1 ]
Tang, Chengwu [1 ]
Lu, Yongliang [2 ]
Xiang, Xiaobin [3 ]
Bao, Ying [1 ]
机构
[1] First Peoples Hosp Huzhou, Huzhou Teachers Coll, Affiliated Hosp 1, Dept Surg Gastroenterol, 158 Guangchanghou Rd, Huzhou 313000, Zhejiang, Peoples R China
[2] Huzhou Teachers Coll, Dept Med, Huzhou 313000, Zhejiang, Peoples R China
[3] Guangdong Orthoped Hosp, Dept Sports Med, Guangzhou 510045, Guangdong, Peoples R China
关键词
colorectal cancer; prognosis; gene signature; microarray; chemotherapy resistance; EXPRESSION LEVELS; RECURRENCE; TUMORS; ID4;
D O I
10.3892/ol.2017.5691
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
The identification of novel survival predictors may help to improve the appropriate management of colorectal cancer (CRC). In the present study, two gene sets associated with irinotecan or oxaliplatin resistance in CRC cell lines were first identified and subsequently applied to the clinical CRC microarray dataset GSE14333. Subsequently, a 60-gene irinotecan resistance-associated signature and a 13-gene oxaliplatin resistance-associated signature were established, which were able to classify CRC patients into high-and low-risk subgroups with varied clinical outcomes [irinotecan-resistance gene signature: hazard ratio (HR)=0.4607, 95% confidence interval (CI)=0.3369-0.6300, P < 0.0001; oxaliplatin-resistance gene signature: HR=0.6119, 95% CI=0.4547-0.8233, P=0.0008]. The performance of these two gene expression signatures in predicting outcome risk were also validated in two other independent CRC gene expression microarray datasets, GSE17536 (irinotecan-resistance gene signature: HR=0.5318, 95% CI=0.3359-0.8419, P=0.0079; oxaliplatin-resistance gene signature: HR=0.5383, 95% CI=0.3400-0.8521, P=0.0114) and GSE17537 (irinotecan-resistance gene signature: HR=0.2827, 95% CI=0.1173-0.6813, P=0.0088; oxaliplatin-resistance gene signature: HR=0.2378, 95% CI=0.09773-0.5784, P=0.0023). Furthermore, the combination of these two gene classifiers demonstrated a superior performance in CRC prognosis prediction than either used individually. Therefore, this study proposed novel gene classifier models for CRC prognosis prediction, which may be potentially useful to inform treatment decisions for patients with CRC in clinical settings.
引用
收藏
页码:2089 / 2096
页数:8
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