Dataset for: Recurrence-associated gene signature optimizes recurrence free survival prediction of colorectal cancer

High throughput gene expression profiling has showed great promise in providing insight into molecular mechanisms. Metastasis-related mRNAs may potentially enrich genes with the ability to predict cancer recurrence，therefore we attempted to build a recurrence-associated gene signature to improve prognostic prediction of colorectal cancer (CRC). We identified 2848 differentially expressed mRNAs by analyzing CRC tissues with or without metastasis. For the selection of prognostic genes, a LASSO Cox regression model was employed. Using this method, a 13-mRNA signature was identified and then validated in two independent Gene Expression Omnibus (GEO) cohorts. This classifier could successfully discriminate the high-risk patients in discovery cohort (HR = 5.27, 95%CI= 2.30-12.08, P < 0.0001). Analysis in two independent cohorts yielded consistent results (GSE14333: HR=4.55, 95%CI=2.18 – 9.508, P<0.0001) (GSE33113: HR=3.26, 95%CI=2.16 – 9.16, P=0.0176). Further analysis revealed that the prognostic value of this signature was independent of tumor stage, postoperative chemotherapy and somatic mutation. Receiver operating characteristic (ROC) analysis showed that the area under receiver operating characteristic curve (AUC) of this signature was 0.8861 and 0.8157 in the discovery and validation cohort, respectively. A nomogram was constructed for clinicians, which did well in the calibration plots. Furthermore, this 13-mRNA signature outperformed other known gene signatures, including oncotypeDX colon cancer assay. Single-sample gene-set enrichment analysis (ssGSEA) revealed that a group of pathways related to drug resistance, cancer metastasis and stemness were significantly enriched in the high-risk patients. In conclusion, this 13-mRNA signature may be a useful tool for prognostic evaluation and will facilitate personalized management of CRC patients.

高通量基因表达谱（High throughput gene expression profiling）在解析分子机制方面展现出巨大应用潜力。转移相关mRNA可富集具备预测癌症复发潜能的基因，因此本研究尝试构建复发相关基因特征，以优化结直肠癌（colorectal cancer, CRC）的预后预测效能。本研究通过分析伴转移与不伴转移的结直肠癌组织，鉴定出2848个差异表达mRNA。为筛选预后相关基因，本研究采用LASSO Cox回归模型。通过该方法，本研究鉴定得到一条由13个mRNA组成的基因特征，并在两个独立的基因表达综合数据库（Gene Expression Omnibus, GEO）队列中完成验证。该分类器可在发现队列中有效区分高风险患者（风险比HR=5.27，95%置信区间CI=2.30~12.08，P<0.0001）。在两个独立验证队列中均得到一致结果：GSE14333队列（HR=4.55，95%CI=2.18~9.508，P<0.0001）、GSE33113队列（HR=3.26，95%CI=2.16~9.16，P=0.0176）。进一步分析表明，该基因特征的预后价值不受肿瘤分期、术后化疗及体细胞突变状态的影响。受试者工作特征（Receiver operating characteristic, ROC）分析显示，该特征在发现队列与验证队列中的曲线下面积（area under receiver operating characteristic curve, AUC）分别为0.8861与0.8157。本研究为临床医师构建了列线图（nomogram），其校准曲线表现优异。此外，该13-mRNA基因特征的预后效能优于包括oncotypeDX结肠癌检测试剂盒（oncotypeDX colon cancer assay）在内的其他已知基因特征。单样本基因集富集分析（Single-sample gene-set enrichment analysis, ssGSEA）结果显示，与药物耐药、癌症转移及干细胞干性相关的多条通路在高风险患者中显著富集。综上，该13-mRNA基因特征可作为结直肠癌患者预后评估的有效工具，有助于推动结直肠癌患者的个体化诊疗管理。