Chang Yu-Tang, Yeh Yung-Sung, Ma Cheng-Jen, Huang Ching-Wen, Tsai Hsiang-Lin, Huang Ming-Yii, Cheng Tian-Lu, Wang Jaw-Yuan
Division of Pediatric Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan; Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan; Department of Surgery, Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.
Division of Trauma and Critical Care, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan; Department of Emergency Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan; Division of Colorectal Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan; Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.
J Surg Res. 2017 Dec;220:427-437. doi: 10.1016/j.jss.2017.06.030. Epub 2017 Jul 12.
With the recent development of molecular markers, strategies for identifying patients with colorectal cancer (CRC) having a high risk of postoperative early relapse (within 1 y) and relapse have been improved. We previously constructed a multigene biochip with 19 candidate genes. The objective of the present study was to optimize a multigene biochip for detecting the risk of postoperative early relapse and relapse in patients with CRC.
We included 357 patients with stage I-III CRC who underwent curative resection at a single institution between June 2010 and May 2015. During each follow-up, a postoperative surveillance strategy including the National Comprehensive Cancer Network recommendations and a multigene biochip was used. A statistical algorithm was developed to select candidate biomarkers for an optimal combination.
After a 30.9-mo median follow-up, 67 patients (18.8%) had postoperative relapse, of whom 25 (7.0%) relapsed within 1 y after operation and accounted for 37.3% of all relapsed patients. Of the 19 circulating biomarkers, ELAVL4, PTTG1, BIRC5, PDE6D, CHRNB1, MMP13, and PSG2, which presented significant predictive validity, were selected for combination. The expression of the seven-biomarker biochip resulted in area under the receiver operating characteristic curve values of 0.854 (95% confidence interval: 0.756-0.952) for early relapse and 0.884 (95% confidence interval: 0.830-0.939) for relapse. Moreover, the sensitivity, specificity, and predictive accuracy levels were 84.0%, 83.1%, and 83.2% for early relapse and 76.1%, 91.0%, and 88.2% for relapse (P = 0.415, 0.006, and 0.054, respectively). The median lead times before the detection of postoperative early relapse and relapse were 3.8 and 10.4 mo, respectively.
From 19 circulating biomarkers, we optimized seven contemporary circulating biomarkers. The prediction model used for the early and accurate identification of Taiwanese patients with CRC having a high risk of postoperative early relapse and relapse seems to be feasible and comparable.
随着分子标志物的最新发展，用于识别术后早期复发（1年内）和复发风险较高的结直肠癌（CRC）患者的策略已得到改进。我们之前构建了一个包含19个候选基因的多基因生物芯片。本研究的目的是优化一种多基因生物芯片，用于检测CRC患者术后早期复发和复发的风险。
我们纳入了2010年6月至2015年5月期间在单一机构接受根治性切除的357例I-III期CRC患者。在每次随访期间，采用包括美国国立综合癌症网络建议和多基因生物芯片的术后监测策略。开发了一种统计算法来选择候选生物标志物以进行最佳组合。
经过30.9个月的中位随访，67例患者（18.8%）出现术后复发，其中25例（7.0%）在术后1年内复发，占所有复发患者的37.3%。在19种循环生物标志物中，选择了具有显著预测有效性的ELAVL4、PTTG1、BIRC5、PDE6D、CHRNB1、MMP13和PSG2进行组合。七生物标志物生物芯片的表达导致早期复发的受试者工作特征曲线下面积值为0.854（95%置信区间：0.756-0.952），复发的为0.884（95%置信区间：0.830-0.939）。此外，早期复发的敏感性、特异性和预测准确性水平分别为84.0%、83.1%和83.2%，复发的为76.1%、91.0%和88.2%（P分别为0.415、0.006和0.054）。检测术后早期复发和复发前的中位提前期分别为3.8个月和10.4个月。
从19种循环生物标志物中，我们优化了7种当代循环生物标志物。用于早期准确识别台湾CRC患者术后早期复发和复发高风险的预测模型似乎是可行的且具有可比性。
