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[摘要]目的大数据挖掘影响肺腺癌总生存的分子机制。方法分析癌症基因组图谱(TCGA)数据库中肺腺癌RNA测序数据,将肺腺癌样本中上调的mRNA分别在10套GEO基因芯片数据中进行生存分析。应用生物信息分析方法探索微小染色体维持蛋白4(MCM4)基因上游相关的微小RNA(miRNA)以及长链非编码RNA(lncRNA)。结果MCM4 mRNA高表达,在10套独立数据中均可致肺腺癌总生存下降(χ2=4.16~10.70,P<0.05)。与MCM4呈显著线性负相关的miRNA为miR-338-3p(r=-0.379,P<0.01),与MCM4呈显著线性正相关的lncRNA为ENSG00000228801.5(r=0.438,P<0.001)、ENSG00000234129.3(r=0.461,P<0.001)、ENSG00000259758.1(r=0.431,P<0.001),并且利用miRanda及DIANA tool数据库证明了调控的可信性。结论ENSG00000228801.5→miR-338-3p→MCM4、ENSG00000234129.3→miR-338-3p→MCM4、ENSG00000259758.1→miR-338-3p→MCM4通路与肺腺癌病人的总生存相关。
[关键词]肺肿瘤;腺癌;生存时间;数据挖掘;微小染色体维持蛋白类
[中图分类号]R734.2[文献标志码]A[文章编号]2096-5532(2018)06-0639-04
MOLECULAR MECHANISM INFLUENCING THE OVERALL SURVIVAL OF LUNG ADENOCARCINOMA: A STUDY BASED ON BIG DATA MINING ZHANG Jianbo, LIU Huamin, WANG Guie, XIA Yujun(Department of Human Anatomy and His-toembryology, School of Basic Medicine, Qingdao University, Qingdao 266071, China)
[ABSTRACT]ObjectiveTo investigate the molecular mechanism influencing the overall survival of lung adenocarcinoma based on big data mining. MethodsBased on TCGA lung adenocarcinoma RNA sequencing data, we first collected up-regulated mRNAs in lung adenocarcinoma samples, and then conducted survival analysis using the up-regulated mRNAs in 10 independent GEO datasets. Bioinformatics methods were used to find the potential upstream long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) of minichromosome maintenance complex component 4 (MCM4). ResultsUp-regulated MCM4 mRNA was asso-ciated with significantly reduced overall survival of lung adenocarcinoma in all 10 datasets (χ2 =4.16-10.70,P<0.05). miR-338-3p was negatively correlated with MCM4 (r=-0.379,P<0.01), and three lncRNAs, ENSG00000228801.5 (r=0.438,P<0.001), ENSG00000234129.3 (r=0.461,P<0.001), and ENSG00000259758.1 (r=0.431,P<0.001), were positively correlated with MCM4. Furthermore, we used miRanda and DIANA tool to attest the validity of these regulations. ConclusionThree lncRNA-miRNA-mRNA regulations, ENSG00000228801.5→miR-338-3p→MCM4, ENSG00000234129.3→miR-338-3p→MCM4, and ENSG00000259758.1→miR-338-3p→MCM4, are related to the overall survival of lung adenocarcinoma patients.
[KEY WORDS]lung neoplasms; adenocarcinoma; survival time; data mining; minichromosome maintenance proteins
肺癌是發病率和死亡率增长最快的恶性肿瘤,中国国家癌症中心2015年发布的数据显示,我国2006—2011年的5年肺癌患病率在男性恶性肿瘤中居第2位,在女性恶性肿瘤中居第4位[1]。肺癌由于早期诊断困难及缺乏有效的治疗手段,其5年生存率仅为15%左右[2-4]。肺腺癌作为肺癌最常见的病理类型,恶性程度高,容易复发和发生远处转移,导致病人生存率低,预后差[5-8]。肺腺癌发生的分子机制复杂,涉及染色体不稳定、抑癌基因失活、癌基因激活、信号传导通路异常及DNA错配修复缺失等多分子事件。研究影响肺腺癌病人总生存的相关分子事件,或可为提高肺腺癌的疗效提供转化医学的证据。本文拟利用癌症基因组图谱(TCGA)数据库及GEO数据库样本进行数据挖掘,初步探索影响肺腺癌总生存的分子机制。 1材料与方法
1.1实验样本信息收集
于TCGA数据库(https://cancergenome.nih.gov/)中收集肺腺癌相关的RNA测序数据(Level 3),筛选所有同时具备肺腺癌组织与癌旁正常组织的测序数据的样本,共58对。
640青岛大学学报(医学版)54卷
收集TCGA数据库中肺腺癌RNA测序数据(Level 3),筛选同时具备微小RNA(miRNA)、长链非编码RNA(lncRNA)及mRNA测序信息的样本,共420例。
1.2独立验证样本信息收集
于GEO数据库(https://www.ncbi.nlm.nih.gov/gds/)中收集具备生存时间信息的肺腺癌相关mRNA基因芯片数据,共10套,分别为GSE43767、68465、3141、41271、11969、30219、42172、50081、13213、8894。
1.3统计学处理
所有数据均采用R语言(版本号2.15.3)进行分析。差异表达mRNA热图绘制应用“pheatmap”包,生存曲线绘制及生存分析计算应用“survival”包,线性相关分析绘图应用“ggplot2”包。总生存率的比较采用χ2检验,以P<0.05为差异有显著性;相关性检验采用线性相关分析,以P<0.001为差异有显著性。
2结果
2.1癌与癌旁配对样本差异表达的mRNA
将58对肺腺癌标本癌及癌旁正常组织的RNA测序数据进行差异基因分析,取经FDR校正后的P<1×10-6、差异倍数(fold change)>4,得到肺腺癌中表达上调的574个mRNA以及表达下调的900个mRNA,热图见图1。
2.2微小染色体维持蛋白4 (MCM4)mRNA与总生存的相关性
将上述肺腺癌样本中上调的574个mRNA,依据RNA表达量的中位值分为高、低表达两组,分别在10套带有生存信息的GEO基因芯片数据(共计1 367例样本)中进行Kaplan-Meier生存分析。结果显示,只有MCM4 mRNA在10套GEO数据中均能显著区分生存,并且均是在MCM4 mRNA高表达时,肺腺癌的总生存率下降(χ2=4.16~10.70,P<0.05)。见图2。
2.3与MCM4相关的miRNA和lncRNA筛选
为深入研究MCM4影响肺腺癌总生存的分子机制,进一步在TCGA数据库中筛选与MCM4相关的miRNA和lncRNA,探索可能的lncRNA-miRNA-MCM4调控通路。将所有表达的miRNA与MCM4进行线性相关分析,入选条件:①R<-0.3,P<0.001;②符合miRanda miRNA-mRNA关系对预测算法。结果满足条件的miRNA仅有1个,为miR-338-3p,与MCM4呈显著线性负相关(r=-0.379,P<0.001)。将所有表达的lncRNA与MCM4进行线性相关分析,入选条件:①r>0.3,P<0.001;②符合DIANA tools lncRNA-miRNA关系对预测算法。结果共筛选到3个lncRNA,分别为ENSG00000228801.5、ENSG00000234129.3以及ENSG00000259758.1,三者均与MCM4呈显著的线性正相关(r=0.431~0.461,P<0.001)。据此,可以得到3条可能影响肺腺癌总生存的lncRNA-miRNA-MCM4通路:ENSG00000228801.5→miR-338-3p→MCM4、ENSG00000234129.3→miR-338-3p→MCM4、ENSG00000259758.1→miR-338-3p→MCM4。miRNA和lncRNA与MCM4 mRNA的相关性分析见图3。
3讨论
近10余年来,随着分子靶向药物的不断涌现,肺腺癌的治疗已经从以铂类为基础的化疗发展到个体化分子精准治疗。越来越多的驱动基因被发现并被应用于临床治疗。本研究应用生物信息分析技术从大数据挖掘影响肺腺癌总生存的mRNA角度着手,对1 367例mRNA基因芯片样本进行分析,结果显示,MCM4 mRNA高表达可显著缩短肺腺癌病人的总生存时间。查阅文献未见MCM4 mRNA与肺腺癌侵袭、转移及总生存时间之间关系的报道。MCM4是微小染色体维持蛋白家族成员[9-11],与DNA复制的启动相关[9,12-15]。MCM4在妇科肿瘤中的研究较多,结果显示MCM4在宫颈癌、卵巢浆液性肿瘤、子宫内膜腺癌中高表达,并与其不良预后相关[16-17]。亦有研究显示,MCM4在食管癌中高表達,并与食管癌的早期发生相关[18]。MCM4在肺癌
6期张建波,等. 大数据挖掘影响肺腺癌总生存的分子机制641中的研究较少,KIKUCHI等[19]研究显示,MCM4高表达可促进肺癌细胞增殖,并且MCM4高表达与男性、吸烟、组织低分化相关,可促进Ki-67及细胞周期蛋白E的表达。然而,MCM4促进肿瘤细胞增殖及导致不良预后的机制研究仍较少,在卵巢癌中的研究发现,转录因子E2F2可诱导MCM4的高表达,并缩短病人的总生存时间[20]。
本研究对TCGA数据库中RNA测序数据进行分析,结果显示,MCM4在肺腺癌样本中高表达,并且其高表达在10套独立GEO数据中均可显著缩短病人的总生存时间。进一步行生物信息分析得到了其上游的3条通路:ENSG00000228801.5→miR-338-3p→MCM4、ENSG00000234129.3→miR-338-3p→MCM4、ENSG00000259758.1→miR-338-3p→MCM4。这为后续研究MCM4影响肺腺癌总生存的分子机制提供了思路,或可通过深入探索为肺腺癌的精准治疗提供分子依据。
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[关键词]肺肿瘤;腺癌;生存时间;数据挖掘;微小染色体维持蛋白类
[中图分类号]R734.2[文献标志码]A[文章编号]2096-5532(2018)06-0639-04
MOLECULAR MECHANISM INFLUENCING THE OVERALL SURVIVAL OF LUNG ADENOCARCINOMA: A STUDY BASED ON BIG DATA MINING ZHANG Jianbo, LIU Huamin, WANG Guie, XIA Yujun(Department of Human Anatomy and His-toembryology, School of Basic Medicine, Qingdao University, Qingdao 266071, China)
[ABSTRACT]ObjectiveTo investigate the molecular mechanism influencing the overall survival of lung adenocarcinoma based on big data mining. MethodsBased on TCGA lung adenocarcinoma RNA sequencing data, we first collected up-regulated mRNAs in lung adenocarcinoma samples, and then conducted survival analysis using the up-regulated mRNAs in 10 independent GEO datasets. Bioinformatics methods were used to find the potential upstream long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) of minichromosome maintenance complex component 4 (MCM4). ResultsUp-regulated MCM4 mRNA was asso-ciated with significantly reduced overall survival of lung adenocarcinoma in all 10 datasets (χ2 =4.16-10.70,P<0.05). miR-338-3p was negatively correlated with MCM4 (r=-0.379,P<0.01), and three lncRNAs, ENSG00000228801.5 (r=0.438,P<0.001), ENSG00000234129.3 (r=0.461,P<0.001), and ENSG00000259758.1 (r=0.431,P<0.001), were positively correlated with MCM4. Furthermore, we used miRanda and DIANA tool to attest the validity of these regulations. ConclusionThree lncRNA-miRNA-mRNA regulations, ENSG00000228801.5→miR-338-3p→MCM4, ENSG00000234129.3→miR-338-3p→MCM4, and ENSG00000259758.1→miR-338-3p→MCM4, are related to the overall survival of lung adenocarcinoma patients.
[KEY WORDS]lung neoplasms; adenocarcinoma; survival time; data mining; minichromosome maintenance proteins
肺癌是發病率和死亡率增长最快的恶性肿瘤,中国国家癌症中心2015年发布的数据显示,我国2006—2011年的5年肺癌患病率在男性恶性肿瘤中居第2位,在女性恶性肿瘤中居第4位[1]。肺癌由于早期诊断困难及缺乏有效的治疗手段,其5年生存率仅为15%左右[2-4]。肺腺癌作为肺癌最常见的病理类型,恶性程度高,容易复发和发生远处转移,导致病人生存率低,预后差[5-8]。肺腺癌发生的分子机制复杂,涉及染色体不稳定、抑癌基因失活、癌基因激活、信号传导通路异常及DNA错配修复缺失等多分子事件。研究影响肺腺癌病人总生存的相关分子事件,或可为提高肺腺癌的疗效提供转化医学的证据。本文拟利用癌症基因组图谱(TCGA)数据库及GEO数据库样本进行数据挖掘,初步探索影响肺腺癌总生存的分子机制。 1材料与方法
1.1实验样本信息收集
于TCGA数据库(https://cancergenome.nih.gov/)中收集肺腺癌相关的RNA测序数据(Level 3),筛选所有同时具备肺腺癌组织与癌旁正常组织的测序数据的样本,共58对。
640青岛大学学报(医学版)54卷
收集TCGA数据库中肺腺癌RNA测序数据(Level 3),筛选同时具备微小RNA(miRNA)、长链非编码RNA(lncRNA)及mRNA测序信息的样本,共420例。
1.2独立验证样本信息收集
于GEO数据库(https://www.ncbi.nlm.nih.gov/gds/)中收集具备生存时间信息的肺腺癌相关mRNA基因芯片数据,共10套,分别为GSE43767、68465、3141、41271、11969、30219、42172、50081、13213、8894。
1.3统计学处理
所有数据均采用R语言(版本号2.15.3)进行分析。差异表达mRNA热图绘制应用“pheatmap”包,生存曲线绘制及生存分析计算应用“survival”包,线性相关分析绘图应用“ggplot2”包。总生存率的比较采用χ2检验,以P<0.05为差异有显著性;相关性检验采用线性相关分析,以P<0.001为差异有显著性。
2结果
2.1癌与癌旁配对样本差异表达的mRNA
将58对肺腺癌标本癌及癌旁正常组织的RNA测序数据进行差异基因分析,取经FDR校正后的P<1×10-6、差异倍数(fold change)>4,得到肺腺癌中表达上调的574个mRNA以及表达下调的900个mRNA,热图见图1。
2.2微小染色体维持蛋白4 (MCM4)mRNA与总生存的相关性
将上述肺腺癌样本中上调的574个mRNA,依据RNA表达量的中位值分为高、低表达两组,分别在10套带有生存信息的GEO基因芯片数据(共计1 367例样本)中进行Kaplan-Meier生存分析。结果显示,只有MCM4 mRNA在10套GEO数据中均能显著区分生存,并且均是在MCM4 mRNA高表达时,肺腺癌的总生存率下降(χ2=4.16~10.70,P<0.05)。见图2。
2.3与MCM4相关的miRNA和lncRNA筛选
为深入研究MCM4影响肺腺癌总生存的分子机制,进一步在TCGA数据库中筛选与MCM4相关的miRNA和lncRNA,探索可能的lncRNA-miRNA-MCM4调控通路。将所有表达的miRNA与MCM4进行线性相关分析,入选条件:①R<-0.3,P<0.001;②符合miRanda miRNA-mRNA关系对预测算法。结果满足条件的miRNA仅有1个,为miR-338-3p,与MCM4呈显著线性负相关(r=-0.379,P<0.001)。将所有表达的lncRNA与MCM4进行线性相关分析,入选条件:①r>0.3,P<0.001;②符合DIANA tools lncRNA-miRNA关系对预测算法。结果共筛选到3个lncRNA,分别为ENSG00000228801.5、ENSG00000234129.3以及ENSG00000259758.1,三者均与MCM4呈显著的线性正相关(r=0.431~0.461,P<0.001)。据此,可以得到3条可能影响肺腺癌总生存的lncRNA-miRNA-MCM4通路:ENSG00000228801.5→miR-338-3p→MCM4、ENSG00000234129.3→miR-338-3p→MCM4、ENSG00000259758.1→miR-338-3p→MCM4。miRNA和lncRNA与MCM4 mRNA的相关性分析见图3。
3讨论
近10余年来,随着分子靶向药物的不断涌现,肺腺癌的治疗已经从以铂类为基础的化疗发展到个体化分子精准治疗。越来越多的驱动基因被发现并被应用于临床治疗。本研究应用生物信息分析技术从大数据挖掘影响肺腺癌总生存的mRNA角度着手,对1 367例mRNA基因芯片样本进行分析,结果显示,MCM4 mRNA高表达可显著缩短肺腺癌病人的总生存时间。查阅文献未见MCM4 mRNA与肺腺癌侵袭、转移及总生存时间之间关系的报道。MCM4是微小染色体维持蛋白家族成员[9-11],与DNA复制的启动相关[9,12-15]。MCM4在妇科肿瘤中的研究较多,结果显示MCM4在宫颈癌、卵巢浆液性肿瘤、子宫内膜腺癌中高表达,并与其不良预后相关[16-17]。亦有研究显示,MCM4在食管癌中高表達,并与食管癌的早期发生相关[18]。MCM4在肺癌
6期张建波,等. 大数据挖掘影响肺腺癌总生存的分子机制641中的研究较少,KIKUCHI等[19]研究显示,MCM4高表达可促进肺癌细胞增殖,并且MCM4高表达与男性、吸烟、组织低分化相关,可促进Ki-67及细胞周期蛋白E的表达。然而,MCM4促进肿瘤细胞增殖及导致不良预后的机制研究仍较少,在卵巢癌中的研究发现,转录因子E2F2可诱导MCM4的高表达,并缩短病人的总生存时间[20]。
本研究对TCGA数据库中RNA测序数据进行分析,结果显示,MCM4在肺腺癌样本中高表达,并且其高表达在10套独立GEO数据中均可显著缩短病人的总生存时间。进一步行生物信息分析得到了其上游的3条通路:ENSG00000228801.5→miR-338-3p→MCM4、ENSG00000234129.3→miR-338-3p→MCM4、ENSG00000259758.1→miR-338-3p→MCM4。这为后续研究MCM4影响肺腺癌总生存的分子机制提供了思路,或可通过深入探索为肺腺癌的精准治疗提供分子依据。
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