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大數據挖掘影響肺腺癌總生存的分子機制

2018-04-29 00:00:00張建波劉華敏王桂娥夏玉軍
青島大學學報(醫學版) 2018年6期

[摘要]目的大數據挖掘影響肺腺癌總生存的分子機制。方法分析癌癥基因組圖譜(TCGA)數據庫中肺腺癌RNA測序數據,將肺腺癌樣本中上調的mRNA分別在10套GEO基因芯片數據中進行生存分析。應用生物信息分析方法探索微小染色體維持蛋白4(MCM4)基因上游相關的微小RNA(miRNA)以及長鏈非編碼RNA(lncRNA)。結果MCM4 mRNA高表達,在10套獨立數據中均可致肺腺癌總生存下降(χ2=4.16~10.70,P<0.05)。與MCM4呈顯著線性負相關的miRNA為miR-338-3p(r=-0.379,P<0.01),與MCM4呈顯著線性正相關的lncRNA為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數據庫證明了調控的可信性。結論ENSG00000228801.5→miR-338-3p→MCM4、ENSG00000234129.3→miR-338-3p→MCM4、ENSG00000259758.1→miR-338-3p→MCM4通路與肺腺癌病人的總生存相關。

[關鍵詞]肺腫瘤;腺癌;生存時間;數據挖掘;微小染色體維持蛋白類

[中圖分類號]R734.2[文獻標志碼]A[文章編號]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,Plt;0.05). miR-338-3p was negatively correlated with MCM4 (r=-0.379,Plt;0.01), and three lncRNAs, ENSG00000228801.5 (r=0.438,Plt;0.001), ENSG00000234129.3 (r=0.461,Plt;0.001), and ENSG00000259758.1 (r=0.431,Plt;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長最快的惡性腫瘤,中國國家癌癥中心2015年發布的數據顯示,我國2006—2011年的5年肺癌患病率在男性惡性腫瘤中居第2位,在女性惡性腫瘤中居第4位[1]。肺癌由于早期診斷困難及缺乏有效的治療手段,其5年生存率僅為15%左右[2-4]。肺腺癌作為肺癌最常見的病理類型,惡性程度高,容易復發和發生遠處轉移,導致病人生存率低,預后差[5-8]。肺腺癌發生的分子機制復雜,涉及染色體不穩定、抑癌基因失活、癌基因激活、信號傳導通路異常及DNA錯配修復缺失等多分子事件。研究影響肺腺癌病人總生存的相關分子事件,或可為提高肺腺癌的療效提供轉化醫學的證據。本文擬利用癌癥基因組圖譜(TCGA)數據庫及GEO數據庫樣本進行數據挖掘,初步探索影響肺腺癌總生存的分子機制。

1材料與方法

1.1實驗樣本信息收集

于TCGA數據庫(https://cancergenome.nih.gov/)中收集肺腺癌相關的RNA測序數據(Level 3),篩選所有同時具備肺腺癌組織與癌旁正常組織的測序數據的樣本,共58對。

640青島大學學報(醫學版)54卷

收集TCGA數據庫中肺腺癌RNA測序數據(Level 3),篩選同時具備微小RNA(miRNA)、長鏈非編碼RNA(lncRNA)及mRNA測序信息的樣本,共420例。

1.2獨立驗證樣本信息收集

于GEO數據庫(https://www.ncbi.nlm.nih.gov/gds/)中收集具備生存時間信息的肺腺癌相關mRNA基因芯片數據,共10套,分別為GSE43767、68465、3141、41271、11969、30219、42172、50081、13213、8894。

1.3統計學處理

所有數據均采用R語言(版本號2.15.3)進行分析。差異表達mRNA熱圖繪制應用“pheatmap”包,生存曲線繪制及生存分析計算應用“survival”包,線性相關分析繪圖應用“ggplot2”包。總生存率的比較采用χ2檢驗,以P<0.05為差異有顯著性;相關性檢驗采用線性相關分析,以P<0.001為差異有顯著性。

2結果

2.1癌與癌旁配對樣本差異表達的mRNA

將58對肺腺癌標本癌及癌旁正常組織的RNA測序數據進行差異基因分析,取經FDR校正后的P<1×10-6、差異倍數(fold change)>4,得到肺腺癌中表達上調的574個mRNA以及表達下調的900個mRNA,熱圖見圖1。

2.2微小染色體維持蛋白4 (MCM4)mRNA與總生存的相關性

將上述肺腺癌樣本中上調的574個mRNA,依據RNA表達量的中位值分為高、低表達兩組,分別在10套帶有生存信息的GEO基因芯片數據(共計1 367例樣本)中進行Kaplan-Meier生存分析。結果顯示,只有MCM4 mRNA在10套GEO數據中均能顯著區分生存,并且均是在MCM4 mRNA高表達時,肺腺癌的總生存率下降(χ2=4.16~10.70,P<0.05)。見圖2。

2.3與MCM4相關的miRNA和lncRNA篩選

為深入研究MCM4影響肺腺癌總生存的分子機制,進一步在TCGA數據庫中篩選與MCM4相關的miRNA和lncRNA,探索可能的lncRNA-miRNA-MCM4調控通路。將所有表達的miRNA與MCM4進行線性相關分析,入選條件:①R<-0.3,P<0.001;②符合miRanda miRNA-mRNA關系對預測算法。結果滿足條件的miRNA僅有1個,為miR-338-3p,與MCM4呈顯著線性負相關(r=-0.379,P<0.001)。將所有表達的lncRNA與MCM4進行線性相關分析,入選條件:①r>0.3,P<0.001;②符合DIANA tools lncRNA-miRNA關系對預測算法。結果共篩選到3個lncRNA,分別為ENSG00000228801.5、ENSG00000234129.3以及ENSG00000259758.1,三者均與MCM4呈顯著的線性正相關(r=0.431~0.461,P<0.001)。據此,可以得到3條可能影響肺腺癌總生存的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與MCM4 mRNA的相關性分析見圖3。

3討論

近10余年來,隨著分子靶向藥物的不斷涌現,肺腺癌的治療已經從以鉑類為基礎的化療發展到個體化分子精準治療。越來越多的驅動基因被發現并被應用于臨床治療。本研究應用生物信息分析技術從大數據挖掘影響肺腺癌總生存的mRNA角度著手,對1 367例mRNA基因芯片樣本進行分析,結果顯示,MCM4 mRNA高表達可顯著縮短肺腺癌病人的總生存時間。查閱文獻未見MCM4 mRNA與肺腺癌侵襲、轉移及總生存時間之間關系的報道。MCM4是微小染色體維持蛋白家族成員[9-11],與DNA復制的啟動相關[9,12-15]。MCM4在婦科腫瘤中的研究較多,結果顯示MCM4在宮頸癌、卵巢漿液性腫瘤、子宮內膜腺癌中高表達,并與其不良預后相關[16-17]。亦有研究顯示,MCM4在食管癌中高表達,并與食管癌的早期發生相關[18]。MCM4在肺癌

6期張建波,等. 大數據挖掘影響肺腺癌總生存的分子機制641中的研究較少,KIKUCHI等[19]研究顯示,MCM4高表達可促進肺癌細胞增殖,并且MCM4高表達與男性、吸煙、組織低分化相關,可促進Ki-67及細胞周期蛋白E的表達。然而,MCM4促進腫瘤細胞增殖及導致不良預后的機制研究仍較少,在卵巢癌中的研究發現,轉錄因子E2F2可誘導MCM4的高表達,并縮短病人的總生存時間[20]。

本研究對TCGA數據庫中RNA測序數據進行分析,結果顯示,MCM4在肺腺癌樣本中高表達,并且其高表達在10套獨立GEO數據中均可顯著縮短病人的總生存時間。進一步行生物信息分析得到了其上游的3條通路:ENSG00000228801.5→miR-338-3p→MCM4、ENSG00000234129.3→miR-338-3p→MCM4、ENSG00000259758.1→miR-338-3p→MCM4。這為后續研究MCM4影響肺腺癌總生存的分子機制提供了思路,或可通過深入探索為肺腺癌的精準治療提供分子依據。

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