基于癌症基因组图谱构建乳腺癌中WAC反义RNA1的加权基因共表达网络和临床预测模型

Construction of WGCNA network and clinical prediction model of lncRNA WAC-AS1 in breast cancer based on TCGA database

目的:基于癌症基因组图谱(TCGA)和基因组织表达(GTE)数据库探索长链非编码RNA(lncRNA)WAC反义RNA1(WAC-AS1)在乳腺癌中的生物学功能以及对乳腺癌预后的影响。方法:基于TCGA和GTE数据库的WAC-AS1表达数据,比较WAC-AS1在乳腺癌组织和正常乳腺组织中的表达差异;以WAC-AS1表达中位值为标准,将乳腺癌患者分为WAC-AS1高表达和低表达2组,比较2组患者的OS、无进展生存期(PFS)、疾病特异性生存期(DSS)和DFS以及癌组织中浸润的免疫细胞差异;使用肿瘤体细胞突变检测工具VarScan分析WAC-AS1相关的基因突变;采用基因集差异分析(GSVA)以及基因集富集分析(GSEA)寻找WAC-AS1在乳腺癌中可能参与的信号通路;采用加权基因共表达网络分析(WGCNA)构建乳腺癌预后的临床预测模型,并用受试者操作特征(ROC)曲线以及3年、5年OS的校准曲线分别评价模型的预测效能以及准确性。采用实时荧光定量PCR实验检测MCF-10A、MCF-7和MDA-MB-231细胞中WAC-AS1的表达。结果:(1)WAC-AS1在乳腺癌中相对正常组织呈明显高表达[4.17(3.91,4.41)比3.70(3.37,4.09),Z=3.880,P<0.001]。(2)WAC-AS1高表达与低表达组的中位OS分别为10年和17.2年,组间比较差异有统计学意义(HR=1.680,95%CI:1.208~2.338,P=0.002)。2组患者的PFS、DSS和DFS比较差异无统计学意义(HR=1.105,95%CI:0.798~1.529,P=0.548;HR=1.303,95%CI:0.846~2.008,P=0.230;HR=1.092,95%CI:0.711~1.678,P=0.687)。高表达WAC-AS1的乳腺癌组织中有4种免疫细胞数量增加,包括幼稚B细胞、CD8+T细胞、滤泡辅助性T细胞和激活树突状细胞,而静息CD4+记忆T细胞和静息肥大细胞数量减少(P均<0.050)。(3)WAC-AS1相关突变频率最高的基因为TP53、PIKCA和TTN。(4)GSVA与GSEV结果显示WAC-AS1与DNA修复、MYC靶点V2、MYC靶点V1、E2F靶点、mTORC1信号通路正相关。(5)WGCNA分析发现WAC-AS1与黄绿色模块中91个与小分子生物合成相关的基因相关性最高(r=0.270,P<0.001)。(6)单因素分析结果显示,年龄(HR=1.034,95%CI:1.021~1.047,P<0.001)、性别(HR=1.388,95%CI:0.188~9.929,P=0.870)、临床分期(Ⅱ、Ⅲ、Ⅳ期分别与Ⅰ期比较,HR=1.457,95%CI:1.043~2.022,P=0.017;HR=4.022,95%CI:2.804~5.739,P<0.001;HR=16.130,95%CI:9.413~27.630,P<0.001)以及WAC-AS1表达量(HR=1.032,95%CI:1.005~1.061,P=0.020)是患者OS的影响因素。多因素分析结果表明:WAC-AS1的表达量与乳腺癌患者OS相关(HR=1.377,95%CI:1.021~1.872,P=0.039)。(7)所构建的临床预测模型的C-指数为0.759,ROC曲线下面积(AUC)为0.626(95%CI:58.0%~67.3%,P<0.001),敏感度为76.9%,特异度为46.8%。预测曲线接近于理想曲线,拟合度较高。(8)PCR检测WAC-AS1在3种细胞株MCF-10A、MCF-7和MDA-MB-231的CT值分别为32.39±0.10、30.55±0.25和30.82±0.07,组间比较差异有统计学意义(F=30.310,P<0.001)。进一步两两比较分析显示,乳腺癌细胞株MCF-7和MDA-MB-231的WAC-AS1表达均高于正常乳腺上皮细胞株MCF-10A(t=7.916、7.431,P均<0.001)。结论:本研究表明lncRNA WAC-AS1与乳腺癌的肿瘤微环境以及免疫浸润相关,高表达WAC-AS1影响乳腺癌患者的预后。WAC-AS1可能成为今后乳腺癌治疗中的一个潜在靶点及预后标志。

Objective:To explore the biological function of long non-coding RNA(lncRNA)WAC antisense RNA1(WAC-AS1)in breast cancer and its impact on the prognosis of breast cancer based on the Cancer Genome Atlas(TCGA)and Gene Tissue Expression(GTE)databases.Methods:Based on the data of lncRNA WAC-AS1 expression in the TCGA and GTE databases,the expression of WAC-AS1 in breast cancer tissue was analyzed and compared with normal breast tissues.The breast cancer patients were divided into high expression group and low expression group according to the median value of WAC-AS1 expression.The OS,progression-free survival(PFS),disease-specific survival(DSS),DFS,and proportion of immune cells infiltrated in cancer tissues were compared between the two groups.WAC-AS1 related gene mutations were analyzed using the tumor somatic mutation detection tool VarScan.Gene set variation analysis(GSVA)and gene set enrichment analysis(GSEA)were also performed to explore WAC-AS1-involved signaling pathways in breast cancer.Finally,weighted gene correlation network analysis(WGCNA)was performed and a clinical prognostic model was constructed in breast cancer.The receiver operating characteristic(ROC)curve and the calibration curve of 3-year and 5-year OS were used to evaluate the prediction efficiency and accuracy of the model.The expression of WAC-AS1 was detected by fluorescence-based quantitative real-time PCR in MCF-10A,MCF-7 and MDA-MB-231 cells.Results:(1)WAC-AS1 expression in breast cancer tissue was significantly higher compared with normal breast tissues[4.17(3.91,4.41)vs 3.70(3.37,4.09),Z=3.880,P<0.001].(2)The median OS in WAC-AS1 high expression group and low expression group was 10.0 years and 17.2 years,respectively,indicating a significant difference(HR=1.680,95%CI:1.208-2.338,P=0.002).There was no significant difference in PFS,DSS and DFS between those two groups(HR=1.105,95%CI:0.798-1.529,P=0.548;HR=1.303,95%CI:0.846-2.008,P=0.230;HR=1.092,95%CI:0.711-1.678,P=0.687).In breast cancer tissues with high expression of WAC-AS1,4 kinds of immune cells(naive B cells,CD8+T cells,follicular helper T cells and activated dendritic cells)were increased,while resting CD4+memory T cells and resting mast cells were decreased(all P<0.050).(3)The genes with the highest frequency of WAC-AS1 related mutations were TP53,PIKCA and TTN.(4)The results of GSVA and GSEV showed a positive correlation between WAC-AS1 and DNA repair,MYC target V2,MYC target V1,E2F target,and mTORC1 signaling pathway.(5)WGCNA analysis found that WAC-AS1 had the highest correlation with 91 genes related to small molecule biosynthesis in the yellow green module(r=0.270,P<0.001).(6)The results of univariate analysis showed that age(HR=1.034,95%CI:1.021-1.047,P<0.001),gender(female vs male,HR=1.388,95%CI:0.188-9.929,P=0.870),clinical stage(PhaseⅡvs PhaseⅠ,HR=1.457,95%CI:1.043-2.022,P=0.017;PhaseⅢvs PhaseⅠ,HR=4.022,95%CI:2.804-5.739,P<0.001;and PhaseⅣvs Phase I,HR=16.130,95%CI:9.413-27.630,P<0.001)and WAC-AS1 expression(HR=1.032,95%CI:1.005-1.061,P=0.020)were influencing factors for OS.Multivariate analysis showed that the expression of WAC-AS1 was correlated with OS in breast cancer patients(HR=1.377,95%CI:1.021-1.872,P=0.039).(7)The C-index of the constructed clinical prediction model was 0.759,the area under the ROC curve(AUC)was 0.626(95%CI:0.58.0-0.673,P<0.001),the sensitivity was 76.9%,and the specificity was 46.8%.The predicted curve fit well with the ideal curve.(8)The CT values of WAC-AS1 detected by PCR in three cell lines MCF-10A,MCF-7,and MDA-MB-231 were 32.39±0.10,30.55±0.25,and 30.82±0.07,respectively,indicating a significant difference(F=30.310,P<0.001).Pairwise comparison showed that WAC-AS1 expression in MCF-7 and MDA-MB-231 cells was significantly higher than that in MCF-10A cells(t=7.916,7.431,both P<0.001).Conclusions:The lncRNA WAC-AS1 is related to the tumor microenvironment and immune infiltration in breast cancer.The high expression of WAC-AS1 affects the prognosis of breast cancer pateints.WAC-AS1 may be a potential target and prognostic marker in breast cancer treatment.