Genome-wide Discovery and Identification of a Novel miRNA Signature for Recurrence Prediction in Stage II and III Colorectal Cancer.
Genome-wide Discovery and Identification of a Novel miRNA Signature for Recurrence Prediction in Stage II and III Colorectal Cancer.
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DOI：
10.1158/1078-0432.ccr-17-3236
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发表时间：
2018-08-15
期刊：
影响因子：
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通讯作者：
Goel A
中科院分区：
文献类型：
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作者：
Kandimalla R;Gao F;Matsuyama T;Ishikawa T;Uetake H;Takahashi N;Yamada Y;Becerra C;Kopetz S;Wang X;Goel A
目前的TNM（肿瘤淋巴结转移）分期系统不足以识别高危结直肠癌（CRC）患者。使用系统和全面的生物标志物发现和验证方法，我们旨在确定一种mirna复发分类器（MRC），该分类器可以改进当前的tnm分期，并且优于目前提供的分子分析。三个独立的全基因组miRNA表达谱数据集用于生物标志物发现（N=158）和计算机验证（N=109和N=40），以确定预测结直肠癌患者肿瘤复发的miRNA特征。随后，该特征在回顾性收集的独立新鲜冷冻（N=127，队列1）和FFPE （N=165，队列2和N=139，队列3）标本患者队列中进行分析训练和验证。我们在发现（p=0.002）和两个独立的公开数据集（p=0.00006和p=0.002）中发现了一个8-miRNA特征，可以显著预测无复发间隔（RFI）。基于独立临床队列的RT-PCR验证显示，mrc衍生的高危患者在II期和III期CRC患者中RFI明显较差[队列1:HR: 3.44 (1.56-7.45)， P=0.001，队列2:HR: 6.15 (3.33-11.35)， P=0.001，队列3:HR: 4.23 (2.26-7.92)， P=0.0003]。在多变量分析中，MRC成为肿瘤复发的独立预测因子，并且比目前可用的分子分析具有更高的预测准确性。基于RT-PCR的MRC风险评分=(−0.1218×miR−744)+(−3.7142×miR-429) +(−2.2051×miR-362) + (3.0564×miR-200b) + (2.4997×miR-191) +(−0.0065×miR-30c2) + (2.2224×miR-30b) +（−1.1162×miR-33a）。这种新的mirna -复发分类器优于目前使用的临床病理特征和NCCN标准，并且独立于辅助化疗状态识别高危II期和III期CRC患者。这可以很容易地在临床实践中使用FFPE标本进行决策，等待进一步的模型测试和验证。
The current TNM (Tumor Node Metastasis) staging system is inadequate at identifying high-risk colorectal cancer (CRC) patients. Using a systematic and comprehensive-biomarker discovery and validation approach, we aimed to identify a miRNA-recurrence classifier (MRC) that can improve upon the current TNM-staging as well as superior to currently offered molecular assays. Three independent genome-wide miRNA-expression profiling datasets were used for biomarker discovery (N=158) and in-silico validation (N=109 and N=40) to identify a miRNA signature for predicting tumor recurrence in CRC patients. Subsequently, this signature was analytically trained and validated in retrospectively collected independent patient cohorts of fresh frozen (N=127, cohort 1) and FFPE (N=165, cohort 2 and N=139, cohort 3) specimens. We identified an 8-miRNA signature that significantly predicted recurrence free interval (RFI) in the discovery (p=0.002) and two independent publicly available datasets (p=0.00006 and p=0.002). The RT-PCR based validation in independent clinical cohorts revealed that MRC-derived high-risk patients succumb to significantly poor RFI in stage II and III CRC patients [cohort 1: HR: 3.44 (1.56–7.45), P=0.001, cohort 2: HR: 6.15 (3.33–11.35), P=0.001 and cohort 3: HR: 4.23 (2.26–7.92), P=0.0003]. In multivariate analyses, MRC emerged as an independent predictor of tumor recurrence, and achieved superior predictive accuracy than the currently available molecular assays. The RT-PCR based MRC risk score = (−0.1218×miR−744) + (−3.7142×miR-429) + (−2.2051×miR-362) + (3.0564×miR-200b) + (2.4997×miR-191) + (−0.0065×miR-30c2) + (2.2224×miR-30b) + (−1.1162×miR-33a). This novel miRNA-recurrence classifier works superior to currently used clinicopathological features, as well as NCCN criteria, and works independent of adjuvant chemotherapy status in identifying high-risk stage II and III CRC patients. This can be readily deployed in clinical practice with FFPE specimens for decision making pending further model testing and validation.