联合长链非编码RNA Lnc-cCSC1构建结直肠癌临床预后个体化模型

Establishment of individualized model for clinical prognosis of colorectal cancer with long non-coding RNA Lnc-cCSC1

目的分析结直肠癌(colorectal cancer,CRC)组织中CRC细胞干性相关长链非编码RNA1(CRC stem cell related lncRNA 1,Lnc-cCSC1)的表达及预后价值,并联合Lnc-cCSC1构建可个体化评估CRC预后风险的列线图。方法选取行根治性手术切除的274例CRC患者,其中于川北医学院附属医院接受根治性手术治疗的195例CRC患者作为实验组,川北医学院肝胆胰肠疾病研究所生物标本库的79例CRC患者标本作为验证组。定量聚合酶链反应(quantitative polymerase chain reaction,qPCR)用于检测CRC组织和癌旁组织中Lnc-cCSC1的表达,收集分析患者临床资料。受试者工作特征(receiver operating characteristic,ROC)曲线获得计量资料的最佳截断值。Kaplan-Meier法和Log-rank检验绘制生存曲线,分析Lnc-cCSC1表达对患者总体生存的影响。应用多因素Cox回归模型确定CRC预后的独立危险因素并以此建立列线图,计算一致性指数(C-index)评估模型准确性,并与TNM分期系统比较预测效能。根据构建的nomogram模型将验证组79例患者分为高风险组和低风险组,Kaplan-Meier法和Log-rank检验绘制生存曲线,分析构建的nomogram模型评估CRC患者行根治术后临床预后效果。结果CRC组织中Lnc-cCSC1表达水平高于癌旁组织[(14.7±1.8)vs(6.5±1.6),(P<0.01)]。Lnc-cCSC1判断预后的曲线下面积(area under curve,AUC)为0.710(P<0.01),最佳截断值为14.65,敏感度和特异度分别为69.1%和64.4%。Lnc-cCSC1高表达的患者预后较低表达患者更差(P<0.01)。Cox多因素回归分析显示,Lnc-cCSC1、肿瘤原发部位、癌胚抗原(carcinoembryonic antigen,CEA)水平、糖类抗原(carbohydrate antigen 199,CA199)水平和TNM分期是CRC术后总体生存的独立危险因素(均P<0.05)。联合Lnc-cCSC1及临床病理因素构建列线图能进一步提高患者术后生存的个体化评估准确性,其C-index为0.792。验证组生存曲线分析结果表明,构建的nomogram模型能够很好评估CRC患者行根治术后的临床预后。结论Lnc-cCSC1在CRC组织中高表达且是预后不良的独立危险因素,构建的列线图能够更准确预测CRC患者的总体生存状况。

Objective To analyze the expression and prognostic value of colorectal cancer(CRC)stem cell related long non-coding RNA 1(Lnc-cCSC1)in CRC tissues,and to construct a nomogram that can individually assess the prognostic risk of CRC in combination with Lnc-cCSC1.Methods Among the 274 CRC patients who underwent radical surgical resection,195 CRC patients from the Affiliat-ed Hospital of North Sichuan Medical College were selected as the experimental group,and 79 CRC samples preserved in the biological specimen database of the Institute of Hepato-Biliary-Pancreatic-Intestinal Disease of North Sichuan Medical College were selected as the validation group.Quantitative polymerase chain reaction(qPCR)was carried out to measure the expression level of Lnc-cCSC1 in cancer tissues and paracancerous tissues,and the clinical data of patients were collected for statistical analysis.The receiver operating character-istic(ROC)curve was used to obtain the optimal cutoff value for the continuous data.Kaplan-Meier and Log-rank test were used to draw survival curves and analyze the effect of Lnc-cCSC1 expression on overall survival of patients.A multivariate Cox regression model was used to determine the independent risk factors for the prognosis of CRC,and a nomogram was established and the C index was calculated to evaluate the accuracy of the model,and the prediction efficiency was compared with the TNM staging system.According to the constructed nomogram model,79 patients in the validation group were divided into the high risk group and low risk group.Kaplan-Meier and Log-rank test were used to draw survival curves,and the nomogram model was analyzed to evaluate the clinical prognosis of colorectal cancer patients after radical resection.Results The expression level of Lnc-cCSC1 in cancer tissues was significantly higher than that in adjacent tissues[(14.7±1.8)vs(6.5±1.6),P<0.01].The area under curve(AUC)value of Lnc-cCSC1 to judge the prognosis was 0.710(P<0.01),the op-timal cutoff value was 14.65,and the sensitivity and specificity were 69.1%and 64.4%,respectively.Kaplan-Meier survival curve analysis showed that patients with high expression of Lnc-cCSC1 had significantly worse prognosis than patients with low expression of Lnc-cCSC1(P<0.01).Cox multivariate regression analysis showed that Lnc-cCSC1,primary tumor site,carcinoembryonic antigen(CEA),carbohydrate antigen 199(CA199),and TNM stages were independent risk factors for the prognosis of CRC(all P<0.05).Combining Lnc-cCSC1 and pathological factors to construct a nomogram could further improve the accuracy of individualized assessment of postoperative survival of patients,and its C-index was 0.792.The results of survival curve analysis in the validation group showed that the constructed nomogram model could well evaluate the clinical prognosis of patients with CRC after radical resection.Conclusions Lnc-cCSC1 is highly expressed in CRC tissues and is an independent risk factor for poor prognosis.The constructed nomogram can predict the prognosis of CRC patients more accurately.