DJ-1与cofilin-1蛋白在小细胞肺癌耐药作用中的研究
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摘要
研究背景
据全球癌症发病的最新统计资料显示肺癌的发病率居恶性肿瘤的首位,在我国情况也是如此。每年因为肺癌死亡的人数超过100万,是严重威胁人类健康的疾病。更另人担忧的是肺癌的发病率呈明显上升趋势,这与人口的老龄化、城市的工业化、农村的城市化、环境污染以及不良生活习惯如吸烟相关。根据肿瘤组织形态学的不同,肺癌主要分为小细胞肺癌(small cell lung cancer, SCLC)和非小细胞肺癌(non-small cell lung cancer, NSCLC),后者包括腺癌、鳞癌和大细胞癌。SCLC发病率约占原发性肺癌的15%,分化程度低,易较早发生血行转移,预后极差。虽然SCLC对初始化疗比较敏感,但极易发生多药耐药(multi-drug resistance, MDR)现象,从而导致化疗失败,肿瘤进展较快,患者早期出现了复发与转移,最终因多器官功能衰竭而死亡,5年存活率不足5%。因此,SCLC的多药耐药性是目前SCLC基础应用研究和临床治疗亟待解决的问题之一。
恶性肿瘤化疗治疗失败的主要原因是多药耐药,是指对已经接触过抗肿瘤药物无论在功能上或结构上都不相关的多种药物具有获得性耐药。肿瘤多药耐药机制主要有包括下面几种因素：(1)药理性耐药(pharmacological resistance):指由机体本身对药物的影响所导致的耐药,如药物进入机体后代谢活动增强或药物活化障碍,肿瘤组织血供不足,药物与组织亲透力差等；(2)微环境耐药(microenvironment resistance):指肿瘤细胞的存活和生长有赖于器官微环境,而器官微环境可以通过不同的耐药基因表达来影响肿瘤细胞对化疗药物的敏感性从而产生；(3)凋亡耐药(apoptosis resistance):参与控制的细胞凋亡基因如P53、BCL-2、C-myc等受到了抑制；(4)生化耐药(biochemical resistance):指肿瘤细胞的遗传性及生化特性发生变化,使细胞通过不同途径对药物产生耐药,其中研究最为广泛的是ABCC膜转运蛋白超家族成员即药物输出泵,如P-糖蛋白(P-gp)、多药耐药相关蛋白(MP)、肺耐药相关蛋白(LRP)、谷胱甘肽转移酶等。这些蛋白既然参与肿瘤细胞的多药耐药,但是如何发现这些蛋白质,进行鉴定,并研究其作用机制以及想办法改变其功能是蛋白质组学研究的重要内容。
细胞凋亡异常：凋亡逃逸是肿瘤细胞的共同特性,也是SCLC产生化疗抗性的重要原因。在细胞黏附介导的耐药中,胞外基质蛋白可对抗细胞毒性药物诱导的凋亡信号。细胞外基质(extracellular matrix, ECM)在β1整合素(β lintegrin)介导下,通过激活P13K信号通路,从而使下游靶区PKB、GSK3β表达增高,阻断细胞凋亡。CD9是四次跨膜蛋白Tetraspanin家族成员之一,在转移性SCLC组织以及顺铂或依托泊苷耐药的SCLC细胞系中具有高表达。CD9阳性的耐药SCLC细胞在β1整合素(β1integrin)的介导下,与纤连蛋白(fibronectin)的连接更为紧密,通过激活PI3K/AKT/mTOR信号通路,引起肿瘤对化疗诱导的凋亡不敏感。使用靶向CD9的特异性单克隆抗体ALB6或小干扰RNA(small interfering RNA, siRNA)可成功触发上述耐药细胞发生凋亡。抑癌基因p53蛋白可应答DNA损伤信号,激活生长阻滞通路(抑制DNA修复)和凋亡通路。p53基因缺失或突变的肺癌患者预后不良,常伴有对放、化疗的抗性。在超过80%的SCLC中均发现野生型p53蛋白活性的缺失,通过抑制细胞周期依赖性激酶抑制剂p21wafl表达,引起细胞周期检查点异常,最终导致细胞增殖失控、凋亡受阻,与疾病进展、预后不良及化疗耐药相关。Bcl-2基因定位于染色体的18q21,编码相对分子质量为26000的蛋白,Bcl-2属凋亡调节基因家族成员。在SCLC中常有Bcl-2表达上调,体外诱导的耐药SCLC细胞系中亦可见Bcl-2表达增加。
郭用microRNA芯片技术发现,小细胞肺癌耐药细胞株H69AR细胞与药物敏感细胞株H69细胞相比,有61种microRNA存在差别,其中24种表达增高,37种表达下调。48种microRNA首次报道与肿瘤的耐药相关,包括miR-134, miR-379与miR-495。用miR-134miR-379与miR-495的类似物转染到H69AR细胞中,其对DDP、ADM及VP-16的药物敏感性增加。进一步研究发现,miR-134调节的靶蛋白是MRPA/ABCC1,转染miR-134类似物MRPA/ABCC1蛋白表达下降,并且H69AR细胞对DDP、ADM及VP-16的药物敏感性。同源异型盒(homeobox)基因(HOXA1)是细胞分化、增殖和凋亡等生物学过程的关键调节基因,参与胚胎发育和个体生长的调节。有研究表明同源异形盒基因可以调节肿瘤的凋亡或耐药性。肖以SCLC多药耐药细胞株H69AR和敏感细胞株H69作为研究对象,采用cDNA基因芯片分析两株细胞中具有差异表达的基因,结果显示HOXA1在SCLC细胞株H69中的表达是多药耐药细胞株H69AR中的表达的4.16倍,实时荧光定量PCR结果和Western Blot检测结果验证了基因芯片的结果。上调HOXA1的表达明显增加H69AR细胞的药物敏感性,下调HOXA1的表达显著增加H69细胞的耐药性。免疫组化染色结果显示,HOXA1在存活患者中的阳性表达率为91.7%(11/12),在死亡患者中的阳性表达率为35.3%(18/51),两者的HOXA1阳性表达率具有统计学差异(x2=12.427, P<0.001), HOXA1阳性表达者生存时间显著高于HOXA1阴性表达患者。HOXA1是miR-100的靶基因,可受到miR-100调控,转染miR-100的抑制物,可使HOXA1表达增加,并增加H69细胞的耐药性。上皮和内皮细胞酪氨酸激酶(Epethelial and endothelial tyrosine kinase, Ekt)是BTK家庭中的重要成员之一,研究发现它在上皮增值、分化、凋亡和肿瘤发生过程中有着重要的调控作用。周应用荧光定量PCR和Western blot技术证实H69AR细胞中Ekt表达水平明显高于H69细胞,基因沉默降低H69AR中Ekt水平后,H69AR对阿霉素的敏感性显著增加,进一步证实Ekt有抵抗药物诱导细胞凋亡的作用,并且在小细胞耐药性产生过程可能有重要作用。
细胞膜蛋白药泵表达异常：MDR的形成与膜蛋白如ABC家族成员P-gp、 MDR相关蛋白(MDR1、MRP1、MRP2)等的过度表达有关。在耐药的SCLC组织和体外培养SCLC细胞系中都发现P-gp和MRP-1表达水平的增高。MDR的形成也与LRP高度表达相关,它能介导以DNA为靶点的化疗药物,如阻止顺铂、卡铂等烷化剂进入细胞核,起到中间关卡的作用,组织药物进入细胞核内或者将已进入核内的药物通过转运载体重新运出细胞核或将细胞浆中的药物转运至运输囊泡,从而使药物呈房室性分布,并通过胞吐机制将药物排出细胞,降低细胞内的药物浓度,最终产生耐药。有学者从基因芯片证实FZD1、GLI1和FRZB在SCLC的耐药细胞株及呈现耐药现象的患者中显著高表达。FZD1是参与编码跨膜Wnt受体卷曲蛋白的基因。参与编码Wnt受体卷曲蛋白的基因共10种(FZD1～FZD10),其在恶性肿瘤的发生发展中起着非常重要的作用。该研究基因芯片证实FZD1无论在离体H69AR细胞还是活体内,都呈现出较高的表达水平。FZD1作为Wnt受体卷曲蛋白的重要编码基因可作为逆转SCLC多耐药的理想靶标。GLI是Sonic hedgehog(Shh)信号通路重要的转录因子。Shh信号通路在胰腺癌、基底细胞癌、SCLC等肿瘤中异常激活。Shh信号通路对靶细胞的作用是通过细胞膜上的Patched(PTC)(?)(?)2个转录原件所介导,最终激活一种转录因子GLI。化疗药物反复刺激Shh信号通路的上游基因,引发下游转录因子出现生物功能的改变。GLI1作为Shh信号通路的终点,充分说明GLI1不仅参与肿瘤的发生发展而且参与了肿瘤细胞对化疗药物的耐药。FRZB是Wnt信号通路的负性调节因子,该研究发现FRZB在SCLC的耐药细胞株及呈现耐药现象的患者中显著高表达,在细胞学研究中,耐药细胞株的表达显著高于亲本细胞株,说明该基因参与了肿瘤的耐药性。但这些基因的变化是如何参与肿瘤细胞的耐药以及如何避免这些耐药基因作用的发挥仍需要深层次的研究。
细胞内酶系统异常：DNA拓扑异构酶(topoisomerase, Top)是细胞DNA复制和转录的主要核酶。Top抑制剂是SCLC最常用的化疗药物之一,Top表达水平下调以及表达类型的改变是SCLC对Top抑制剂耐药的重要原因。最近一项研究发现,脂质体介导的人工合成siRNA瞬时转染可有效抑制人小细胞肺癌细胞株H446的TopⅠ表达并显著提高对VP16的敏感性,提示转染后的细胞株TopⅠ水平下降的同时有Top Ⅱ的表达水平升高。体内、外实验均已经证实TopⅠ抑制剂和Top Ⅱ抑制剂联合应用时具有明显的协同作用。Lawson等通过cDNA芯片分析筛选SCLC耐药相关基因,并人为改变候选靶基因表达水平以观察其对SCLC药物敏感性的影响,结果发现,DNA聚合酶β (DNA polymerase β)和神经内分泌转录因子NKX的高表达可能与SCLC对依托泊苷的耐药有关,这一结论在SCLC组织芯片结果中亦得到证实。
细胞修复系统增强：近年来研究表明,DNA错配修复(mismatch repair, MMR)在SCLC的获得性耐药中起着非常重要的作用。有学者发现MMR基因MLH1和MSH2的表达下调可能与SCLC的发生及其MDR有关。至于MMR基因表达下调的具体机制目前尚不清楚,可能与组蛋白去乙酰化、磷酸化或启动子超甲基化造成的MMR基因沉默有关。
蛋白质学是肿瘤临床和基础研究中的热点,对于了解肿瘤尤其是发病机制,诊断和治疗等多方面都有重要作用。“蛋白质组学”则是应用大规模蛋白质分离和鉴定技术,从蛋白质水平探索生命的本质及其规律的一门学科,是高通量的蛋白质筛选技术。包括结构蛋白质组学和功能蛋白质组学。蛋白质组学研究技术主要包括蛋白质分离技术、鉴定技术和生物信息学技术。蛋白质组学研究的样品可用细胞、组织、血液、体液等。近年来,激光捕获显微切割技术(LCM)的应用,既保证了肿瘤组织取材可获得足够量的单一细胞成分,也能保持细胞原有形态。蛋白质分离的关键技术是二维聚丙烯酰胺凝胶电泳(2D-PAGE),其原理是根据蛋白质等电点与分子量的不同,通过电泳的方式把蛋白质分离。
蛋白质鉴定技术主要是质谱分析法(massspectrometry, MS),最常用的是基质辅助激光解析电离飞行时间质谱(matrix-assisted laserdesorption/ionization-time of flight-mass spectrometry, MALDI—TOF—MS)。质谱分析的原理是利用电离源将蛋白质转化为离子,然后借助于质谱仪的电场与磁场将具有特定质量与电荷比例(M/Z)的蛋白质分子分离开来,经过离子检测器收集分离的离子,确定离子的M/Z值,分析鉴定未知的蛋白质。具有高分辨、高敏感、高通量及直接检测复杂的生物学样本等优点,已成为蛋白质组学研究的特色技术。
生物信息学也是蛋白质组学研究的重要部分,其在蛋白质组学的研究中对构建和分析2-DE图谱,数据库的搜索与构建等方面有重要作用。蛋白质组数据库是蛋白质组研究水平的标志和基础。蛋白组学必须结合生物信息学才能在复杂的数据里提取有价值的信息,为研究工作提供有效指引。
目的
通过比较SCLC多药耐药细胞株(H69AR)和敏感细胞株(H69)中蛋白表达差异,从多种表达差异的蛋白中选取表达差异显著的蛋白DJ-1和confilin-1(CFL-1)进行进一步研究。利用RNA干扰技术下调此蛋白的表达水平,并观察耐药株对阿霉素(Doxorubicin，ADM)、顺铂(Csiplatin,DDP)、足叶乙甙(Etoposid,VP-16)等的药物敏感性变化；分析DJ-1和CFL-1在SCLC组织中表达以及与临床病理资料关系,探讨其作为SCLC治疗靶点和预后判断的生物学指标可能性,进一步丰富SCLC多药耐药性的分子机制,为临床治疗提供理论和实验依据。
内容与方法
一、分析SCLC多药耐药细胞株H69AR和敏感细胞株H69中蛋白组表达差异性
以SCLC多药耐药细胞株H69AR和敏感细胞株H69作为研究对象,应用双相电泳(2D-PAGE)和质谱分析技术,分析两株细胞中具有差异表达的蛋白。从多种表达差异的蛋白质中选取表达差异显著的DJ-1与CFL-1进一步研究,采用Western Blot技术验证两种蛋白在两株细胞中的表达差异。
二、利用RNA干扰技术下调DJ-1与CFL-1在H69AR细胞株的表达
首先合成DJ-1与CFL-1的siRNA以及control siRNA,然后通过脂质体法转染H69AR细胞与H69细胞,培养24h后提取总蛋白。利用western blotting技术检测转染DJ-1-siRNA、CFL-1-siRNA和control siRNA组中DJ-1、CFL-1的蛋白表达差异。
三、分析下调DJ-1与CFL-1表达后对H69AR细胞株耐药性的影响
利用CCK-8法分析H69AR-DJ1-siRNA394细胞与H69AR-CFL1-siRNA523细胞对不同浓度的小细胞肺癌常用化疗药物阿霉素(ADM)、顺铂(DDP)、足叶乙苷(VP16)药物敏感性变化。
四、DJ-1与CFL-1在SCLC组织中的表达及临床意义
收集116例SCLC的石蜡包埋组织,患者平均年龄60岁(58.92±10.09),随访时间0-128月。其中男性101例,女性15例；年龄<60岁有58例,年龄≥60岁也是58例；临床分期局限期72例,广泛期46例；接受化疗或放疗95例,未进行化疗或放疗的21例。免疫组织化学染色S-P法检测SCLC组织中DJ-1与CFL-1的表达情况,并分析DJ-1与CFL-1的表达水平与临床病理特征及患者预后的关系。
五、统计分析
数据以均数±标准差(Mean±SD)表示,所有结果均经SPSS13.0统计软件处理。CCK8采用两因素析因设计的方差分析,多重比较用SNK法。同一组内不同浓度间比较和同一浓度不同组间比较用one-way ANOVA。参数比较前均先进行方差齐性检验,若方差不齐用基于方差不齐的近似F检验Welch法。免疫组化染色强度的比较采用Mann-Whitney U检验;小细胞肺癌组织中DJ-1与CFL-1表达水平与生存率的关系采用Kaplain-Meier分析。应用Chi-square test分析DJ-1与CFL-1表达水平与临床病理特征的关系。应用Cox回归模型分析分析DJ-1与CFL-1临床病理特征参数与SCLC患者预后的关系。以P<0.05为差异有统计学意义。
结果
一、SCLC沛癌多药耐药细胞株H69AR与敏感细胞株H69中差异表达蛋白的筛选双相电泳分析发现有35蛋白质斑点在两组凝胶中有显著性差异表达,表达量相差两倍以上,其中在H69AR细胞中表达量升高的蛋白质斑点有25个,表达量下降的蛋白质斑点有10个。取25个表达量显著增高的斑点进行MALDI-TOF-MS分析,结果显示质谱鉴定最终得到16个H69AR/H69差异表达蛋白质,主要包括分子伴侣蛋白(HSPB1)、葡萄糖代谢酶(IMPDH2, Alpha-enolase)、细胞骨架蛋白(Cytoskeletal9, Cytoskeletal1, Cofilin-1)、钙结合蛋白(Annexin-A2、Sorcin、 S100A6)、细胞周期和凋亡相关蛋白(14-3-3epsilon, PCNA, Stathmin)及其它(Protein DJ-1, GIPC1,PPIA, vinculin)等。
进一步采用Western blot验证多药耐药细胞株H69AR与敏感细胞株H69中DJ-1与CFL-1蛋白表达水平,结果发现H69AR细胞株中DJ-1与CFL-1蛋白水平显著高于H69细胞株。
二、DJ-1与CFL-1siRNA干扰效率的鉴定针对DJ-1与CFL-1基因各设计3条siRNA (DJ-1-homo-394、DJ-1-homo-483、 DJ-1-homo-612; CFL-1-homo-326、CFL-1-homo-523、CFL-1-homo-579),在小细胞肺癌耐药细胞株H69AR中转染上述的siRNA以及control siRNA,结果显示转染DJ1-siRNA394与CFL1-siRNA523组DJ-1和CFL-1的表达水平下调最为显著,选取作为后续研究的siRNA。
三、下调DJ-1与CFL-1表达后对SCLC多药耐药性的影响
通过干扰技术下调DJ-1与CFL-1表达后,在H69AR细胞和H69细胞中DJ-1与CFL-1的表达水平明显下降。利用CCK-8法分析显示H69AR-DJ-1-siRNA394细胞对不同浓度的ADM (F=8981.090, P<0.001)、DDP (F=2670.697, P<0.001)、 VP16(F=2693.832, P<0.001)的生存率较mock组细胞的生存率明显降低。同样,H69AR-CFL1-siRNA523细胞对不同浓度的ADM、DDP、VP16的生存率较]mock组细胞的生存率也明显降低。
四、DJ-1与CFL-1表达水平与SCLCI临床病理特征的关系
(1)免疫组化染色显示DJ-1主要定位于肿瘤细胞质,在116例SCLC组织中,DJ-1蛋白阳性的60例,阳性率为51.7%(60/116),其中男性患者DJ-1中阳性表达率52.5%(53/101),女性患者中的阳性表达率为46.7%(7/15),两者阳性表达率的差异无显著性(X2=0.176,P=0.674)。60岁以下患者中DJ-1阳性表达率为53.4%(31/58),60岁以上患者中阳性表达率为50.0%(29/58),两者阳性表达率差异无统计学(X2=0.138,P=0.710)。局限期患者中DJ-1阳性表达率为52.8%(38/72),广泛期患者中阳性表达率为50.0%(22/44),两者的DJ-1阳性表达率差异无显著性(X2=0.084,P=0.771)。95例接受化疗患者中,DJ-1阳性表达率为50.5%(48/95),21例未接受化疗患者中阳性表达率为51.7%(12/21)，两者的DJ-1阳性表达率差异无显著性(χ2=0.302, P=0.583)。DJ-1在存活患者中的阳性表达率为15.4%(2/13),在死亡患者中的阳性表达率为57.1%(52/93),两者的DJ-1阳性表达率有显著性(X2=7.946,P=0.005)。
(2)免疫组化染色显示CFL-1主要定位于肿瘤细胞质,116例SCLC组织中CFL-1阳性表达61例,阳性表达率为52.6%(61/116),其中在男性患者中CFL-1阳性表达率55.4%(56/101),在女性患者中的阳性表达率为33.3%(5/15),两者的阳性表达率差异无显著性(X2=2.561,P=0.110)。在60岁以下患者中CFL-1阳性表达率为51.7%(30/58),60岁以上患者中阳性表达率为53.4%(31/58),两者的CFL-1阳性表达率差异无显著性(X2=0.035,P=0.852)。局限期患者中CFL-1的阳性表达率为50.0%(36/72),广泛期患者中的阳性表达率为58.8%(25/44),两者的CFL-1阳性表达率差异无显著性(#=0.509,P=0.475)。在95例接受化疗的患者中CFL-1阳性表达率为51.6%(49/95),21例未接受化疗的患者中阳性表达率为51.7%(12/21),两者的CFL-1阳性表达率差异无显著性(X2=0.214,P=0.664)。在存活患者中CFL-1的阳性表达率为23.1%(3/13),在死亡患者中的阳性表达率为57.1%(52/93),两者的CFL1阳性表达率差异有显著性(X2=5.298,P<0.05)。
五、SCLC患者预后因素分析
Kaplan-Meier生存分析结果显示,DJ-1(10g-rank test,χ2:19.084,P<0.001)和CFL-1(log rank test,χ2=11.035,P=0.001)高表达预示SCLC预后不良。
对116例SCLC病例进行单因素Cox回归分析,结果表明,DJ-1高表达(HR=2.509,P<0.001,95%CI:1.622-3.880)和CFL-1高表达(HR=2.000,P=0.001,95%CI:1.304-3.068)分别是SCLC预后不良的指标之一,此外接受化疗(HR=0.488,P:0.012,95%CI:0.278-0.856)也是SCLC的预后指标。
Cox多重回归分析(Enter)表明,DJ-1高表达(HR:2.960,P=0.001,95%CI:1.519-5.767)是SCLC预后不良的独立指标之一,接受化疗是SCLC患者的保护性因素(HR=0.488,P=0.012,95%CI:0.278-0.856)。
Cox回归全变量模型分析患者的性别、年龄、疾病分期、手术、化疗、转移、DJ-1及Confilin表达与患者预后的关系,发现DJ-1、手术治疗及疾病的转移与患者的预后相关。DJ-1高表达患者的预后较差,可作为独立的预后因子,差异具有统计学意义(W=13.594,P<0.001),高表达DJ-1患者的相对风险度为3.861,95%相对风险度的可信区间为1.883-7.919；无转移患者的相对风险度较转移患者降低,RR=0.414,95%相对风险度的可信区间为0.175-0.977,差异具有统计学意义(W=4.053,P=0.044),进行手术治疗患者的相对危险度为2.195，95%相对危险度的可信区间为1.275-3.776，差异具有统计学意义(W=8.057,P=0.005)。Cox回归逐步回归模型与全变量回归模型的结果一致
结论
1、应用蛋白质组学的双相电泳技术与质谱分析技术可筛查出SCLC多药耐药相关蛋白。
2、DJ-1和CFL-1在SCLC多药耐药细胞株H69AR中高表达,而在药物敏感细胞株H69中低表达,下调DJ-1和CFL-1的表达可引起多药耐药细胞株H69AR对药物敏感性的变化,说明了DJ-1与CFL-1参与了SCLC的耐药。
3、DJ-1和CFL-1在SCLC组织中表达与患者的生存时间相关,而与患者的性别、年龄、临床分期等无统计学意义,这两种蛋白有望成为SCLC患者的预后指标及药物治疗的靶点。
Background
According to the latest global cancer statistics, the incidence of lung cancer ranks first in all malignant. So does the situation in China. More than one million people die from lung cancer. It is a serous threat to human health. More worrisome is clear upward trend in the incidence of lung cancer. This is related to the aging of population, the city's industrialization, urbanization in rural areas, environmental pollution and unhealthy habits such as smoking. According to the morphology under microscope, lung cancer can be divided into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). The latter include adenocarcinoma, squamous cell carcinoma and large cell lung cancer. SCLC accouts for about15%of primary lung cancers. It is poorly differentiated and easy to hematogenous metastasis at early stage, which leads to poor prognosis. Although sensitive to chemotherapy initially, SCLC develop multi-drug resistance (MDR) soon, which resulted in failure of chemotherapy and rapid progression. Recurrence and metastasis will be found in patients with early stage. Eventually died of multiple organ failure.5-year survival rate of SCLC is less than5%. Therefore, MDR is one of the problems to be conquered in the basic research and clinical treatment of SCLC.
Multi-drug resistance is the main reason for the failure of chemotherapy treatment of malignant tumors. The tumors have acquired resistance to contact anticancer drugs regardless of function or structure not related to a variety of drugs. Multi-drug resistance mechanisms include the following factors. The first factor is pharmacological resistance. The resistance caused by the body itself and the influence of drugs. Such as enhanced metabolic activity of the drug into the body or drug activation barrier, insufficient blood supply of the tumor tissue, poor affinity and penetration between the drug and the organization. The second factor is microenvironment resistance. The survival and growth of tumor cells depends on the organ microenvironment, Organ microenvironment can influence gene expression by different drug sensitivity of tumor cells to chemotherapeutic agents resulting in. The third is apoptosis resistance which involved in the control of apoptosis genes was inhibited, such as P53, BCL-2, C-myc. In addition, biochemical resistance factor is also important.
Changes in the genetic and biochemical characteristics of the tumor cells allows the cells to the emergence of drug resistance through different channels. ABCC membrane transporter protein super-family members, that is drug export pump, get the most extensively studied. The family include P-glycoprotein (P-gp), Multidrug resistance-associated protein (MRP), Lung resistance-related protein (LRP), and Glutathione S-transferase. These proteins are involved in multidrug resistance of tumor cells, but how to find and identify these proteins is important content. Subsequent study of its mechanism of action, changing its function by molecular biology techniques proteomics research is also important.
Abnormal apoptosis:Apoptosis escape is the common characteristics of the tumor cells, that also play important role in SCLC chemotherapy resistant. In cell adhesion mediated drug, extracellular matrix proteins against cytotoxic drug-induced apoptosis signal. The extracellular matrix (ECM) mediated by β1integrin and activate the PI3K signaling pathway, upregulateing the target PKB of GSK3β expression and blocking apoptosis. CD9is the protein of the four transmembrane family members. CD9expressed higher in metastatic SCLC tissues, and the SCLC cell lines with cisplatin-resistant or etoposide-resistant was higher expression. The SCLC cell with CD9-positive resistant mediated β1integrin (β1integrin), and fibronectin protein (fibronectin) connection closer, by activating PI3K/AKT/mTOR signaling pathway, caused to chemotherapy-induced withered death not sensitive. The specificity using targeting CD9the monoclonal antibody ALB6small interference RNA (siRNA) can successfully trigger apoptosis in the resistant cells. The tumor suppressor gene p53protein response to DNA damage signal activation of growth arrest pathway and apoptosis pathway. Deletion or mutation of the p53gene in lung cancer patients with poor prognosis, often accompanied by radiotherapy and chemotherapy resistance. More than80%of the SCLC patients absented of wild-type p53protein, activity through the inhibition of cyclin-dependent kinase inhibitor p21wafl expression caused abnormal cell cycle checkpoint, eventually leading to uncontrolled cell proliferation, apoptosis blocked and caused disease progression. poor prognosis and resistance to chemotherapy related. Bcl-2gene is located on chromosome18q21, encoding the relative molecular mass of26,000protein, Bcl-2gene family members is a regulation of apoptosis. In SCLC often Bcl-2expression, which can also be found in the increased expression of Bcl-2in vitro induced resistant SCLC cell lines.
Guo used microRNA microarray to analysis the differences microRNA in SCLC multidrug resistant cell line H69AR and sensitive cell lines H69. The results showed that61miRNAs are presented significanty including up-regulation of24miRNAs and down-regulation of37miRNA. Among these miRNAs,48of61differentially expressed miRNAs were firstly reported to be closely associated with drug resistance, including miR-134, miR-379and miR-495. Following transfection of H69AR cells with the mimics of miR-134, miR-379and miR-495, respectively, the sensitivity to Cisplatin, Etoposides and Doxorubicin was significantly increased. MRPA/ABCC1was the target of miR-134. After transfecting of H69AR cells with the mimics of miR-134, that the MRPA/ABCC1protein was considerably decreased, and the sensitivity to Cisplatin, Etoposides and Doxorubicin was also increased. Homeobox genes are critical genes that modulate biological processes, such as cell differentiation, proliferation and apoptosis. They involved in embryonic development and ontogeny. Studies have shown that homeobox genes can regulate apoptosis and multi-drug resistance of cancers. Xiao analyzed the differences of gene expression between H69 and H69AR by using cDNA microarray. The studies showed that HOXA1expression in SCLC cell lines H69was4.16-fold of that in multi-drug resistant cell line H69AR. The result was verified by using quantitive real-time PCR and Western Blot. Forced HOXA1expression increased chemo-sensitivity of H69AR cells, reduction of HOXA1expression in H69cell increased its chemo-resistance. HOXA1is the target genes of miR-100. After transfection of miR-100inhibitor into H69AR cell, miR-100expression reduced, but HOXA1protein levels increased. Up-regulation of miR-100in H69cell resulted in increase of resistance to ADM, DDP and VP-16. Epithelial and endothelial tyrosine kinase (Ekt) is one of the important members of the Btk family. Studies found that plays an important role in epithelial proliferation, differentiation, apoptosis and tumorigenesis. Zhow Confirmed that the Etk expression levels in H69AR cell was significantly higher than in H69cells by real-time PCR and western blotting. After the gene silencing to reduce Etk level in H69AR cells, the sensitivity to doxorubicin increased significantly. That further confirmed the Etk resistance to chemotherapeutic and apoptosis, and may play important role in the process of small cell lung cancer drug resistance.
The relationship between the abnormal of membrane protein drug pump expression and multi-drug resistant. The multi-drug resistant formatiing are related membrane proteins, such as the over-expression of the ABCC family members of P-gp, MDR-related protein (MDR1, MRP1, MRP2). That the P-gp and MRP-1express higher in the resistant SCLC tissues and cultured SCLC cell lines in vitro. The formation of the MDR is related to LRP high expression. LRP can mediated DNA-targeting chemotherapy drugs cisplatin, carboplatin and other alkylating agents, such as block into the nucleus, and played the role of intermediate checkpoints. Import drugs into the nucleus, or re-transported out of the drug that had entered into the nuclear and the cytoplasm So that the drug was the atrioventricular distribution, and through exocytosis mechanism washout cells and reduce the concentration of the drug in the cell, ultimately resulting in the resistance. Scholars confirmed FZD1of GLI1and FRZB resistant SCLC cell lines and present patients of the drug phenomenon in significantly high expression from gene chip. FZD1is involved. In the curl protein gene encoding that is transmembrane Wnt receptor.10gene (FZD1-FZD10) are involved in the Wnt receptor curl Protein encoding. That plays a very important role in the development of malignant tumors occur. The gene chip confirmed that the FZD1expressied higher emerged both in vitro H69AR cells or in vivo. FZD1involving curl protein of Wnt receptor coding genes is a reversal of the SCLC multi-drug resistance ideal target. GLI is an important transcription factor of the Sonic hedgehog (Shh) signaling pathway. Shh signaling pathway is abnormally activated in pancreatic cancer, basal cell carcinoma, SCLC tumor. Shh signaling pathway mediated the target cells by ultimating Patched (PTC) on the cell membrane and two transcription originals and activate a transcription factor GLI. Chemotherapy drugs stimulation the upstream gene of the Shh signaling pathway, and triggering the biological function change in the downstream transcription factor. GLI1as the end of the Shh signaling pathway, illustrated fully that the GLI1not only involved in tumor development and involved in tumor cell resistance to chemotherapeutic drugs. FRZB is a negative regulator of the Wnt signaling pathway. The study found that FRZB was significantly higher expressed in resistant SCLC cell lines and present patients of the drug phenomenon. The resistant cell line was significantly higher expression than the parental cell line, indicating that the gene is involved in tumor resistance. These gene changes involved in the drug resistance of tumor cells as well as how to avoid these resistance genes play the role still requires a deep level of research.
Relationship between the abnormal enzyme system with multi-drug resistant cells. Topoisomerase (TOP) is the main cell DNA replication and transcription ribozyme. Top inhibitor is one of the most commonly used chemotherapy drugs SCLC. Down-regulation expression levels of the Top as well as the change of expression is a the SCLC Top inhibitor resistant reason. A new study found that liposome transfect of synthetic siRNA can effectively inhibit human small cell lung cancer cell line H446Top Ⅰ expression and significantly improve the sensitivity of VP16. Top Ⅰ levels decreased after transfection of the cell line, the same time the expression of elevated levels of the Top Ⅱ. The experiments of the vivo and the in vitro have confirmed that Top I inhibitors and Top II inhibitor combined application has obvious synergies. Lawson et screening SCLC multi-drug resistance-related genes by cDNA microarray analysis, and changed candidate target gene expression levels, observe the SCLC drug sensitivity. The results showed high expression of DNA polymerase β and neuroendocrine transcription factor NKX may caused SCLC resistant to etoposide, also confirmed this conclusion in a the SCLC tissue microarray results.
The relationship between cell repair system with multi-drug resistance. Recent studies show that the DNA mismatch repair gene (MMR) plays a very important role in SCLC acquired drug resistance. Scholars have found that the MMR genes MLH1and MSH2downregulation may occur with the SCLC and its MDR. The specific mechanism of MMR genes downregulated is not yet clear, May go with histone acetylation, phosphorylation or to start hypermethylation and that caused by MMR gene silencing.
Proteomics is a hot spot in the clinical oncology and basic research. Have an important role in for understanding tumor mechanisms, diagnosis and treatment and other multifaceted. Proteomics is the subject that used large-scale application technology for protein separation and identification. It is also a high-throughput protein screening technology, including structural proteomics and functional proteomics, exploring the essence of life and its laws from the overall protein level. Proteomics technologies include protein separation technology, identification technology and bio-informatics technology. Available cells, tissues, blood, body fluids samples can be used for the proteomics research. In recent years, Laser capture micro-dissection technology applications, both to ensure the tumor tissue drawn from the availability of a sufficient amount of a single cell components, but also to maintain the cells in the original form. The key technology of protein separation is two-dimensional polyacry lamide gel electrophoresis (2D-PAGE). Its principle is based on isoelectric point and the different molecular weight, by way of electrophoresis to protein separation.
The role of identification technology for protein is the Mass spectrometry. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALD-TOF-FMS) was most commonly used. The principle of MS analysis is converted the protein to ions using the ionization source, then separating protein molecule with proportion of M/Z in the electric field and the magnetic field by means of the mass spectrometer. The separated ions were collected through the ion detector, determine the M/Z value of ion, analysis and identify the unknown protein. The advantage of MS is high-resolution, high-sensitivity, high-throughput and direct detection of complex biological samples, etc. That has become the special technology of proteomics research.
Bioinformatics is also an important part of the proteomics research. In the study of proteomics, bio-information technology plays an important role in constructing and analyzing of2-DE maps, database search and construction. Proteome database is the logo and the basis of the level of proteome research. Proteomics must be combined with bioinformatics to extract valuable information in the complexity of the data, provide effective guidelines for research.
Objectives
To analysis the differences express protein in SCLC multi-drug resistant cell line H69AR and sensitive cell lines H69, and select the significantly different express protein DJ-1and confilin-1(CFL-1) for further study. Drug sensitivity of the expression levels of the two proteins through RNA interference technology down and observe resistant strains Doxorubicin (ADM), of Cisplatin (DDP), Etoposide (VP-16) changes. Observe the relationship between the express of DJ-1and CFL-1in SCLC tissues with the clinicopathological features. To explore the possibility of biomarkers as SCLC therapeutic targets and prognosis. Further enrich the SCLC multidrug resistance molecular mechanisms, and provide theoretical and experimental basis for clinical treatment.
Materials and methods
1. Analyzed the differences of protein expression between small cell lung cancer cell line H69and its multi-drug resistant cell line H69AR
Investigated the difference of protein expression between SCLC multi-drug resistant cell line H69AR and sensitive cell lines H69,2-DE and Matrix-assisted laser adsorption ionization time-of-flight mass spectrometry (MALD-TOF-FMS) were used in the study. And selected the significantly different express protein DJ-1and confilin-1(CFL-1) for further study. Using the Western Blot techniques to verify the differential expression of the two proteins in the two cell lines.
2. Down regulation DJ-1or CFL-1expression in the cell lines of H69AR by siRNA
We synthesized of DJ-1-siRNA, CFL-1-siRNA and control siRNA, and transfected into H69AR cells by the liposomes2000. Total protein was extracted after24h of cell culture. Detecting of the differences of DJ-1or CFL-1protein expression in the group, that transfected DJ-1-siRNA, CFL-1-siRNA and control siRNA, using western blotting technology.
3. Analysis of the effect of multidrug resistance in H69AR cell lines after down regulation the DJ-1or CFL-1expression.
Chemo-sensitivity to different concentration of ADM, DDP and VP-16were determined by using CCK-8assay in H69AR-DJ1-siRNA394cells and H69AR-CFL1-siRNA523cells.
4. The expression of DJ-1and CFL-1in SCLC tissues and clinical significance
116cases of SCLC paraffin-embedded tissues were collected in our study. The average age of the patients was58.92±10.09, and followed up for0-128months. Male101cases, female15cases.58cases aged less then60years,58cases were60years or more. Clinical limited stage72cases, extensive stage46cases;95cases undergoing chemotherapy,21cases abcent chemotherapy. DJ-1and CFL-1expression were detected by immunohistochemistry stain in SCLC tissue, observed the relationship between the DJ-1or CFL-1expression levels and clinicopathological characteristics and prognosis.
5. Statistical analysis
Data are represented as mean±s.e.m. All statistical analyses were carried out with SPSS13.0software. Factorial experiment ANOVA was used to analyze results of CCK-8experiment. The association between DJ-1and CFL-1expression and clinicopathological features were analyzed by Chi-square test. Survival curves were obtained by Kaplain-Meier method. Prognostic factors were examined by univariate and multivariate analyses (Cox proportional hazards model). P value <0.05was considered significant.
Results
1. Differentially expressed protein screening of SCLC in the multi-drug resistant cell line H69AR and sensitive cell line H69
We adopted a2-DE analysis to quantitatively compare the protein profilings of SCLC mutidrug resistant cell ling H69AR and cell line H69. The differently expressed proteins were more than2fold changes between the two groups.25protein spots in H69AR were higher than H69, but10spots were less.25higher proteins spots were slected to perform protein identification by MALDI-TOF-MS. A total of16proteins were successfully identified including molecular chaperones (HSPB1), Glucose metabolism enzyme (IMPDH2, Alpha-enolase), Cytoskeletal proteins (Cytoskeletal9, Cytoskeletal1, Cofilin-1), Calcium-binding protein (Annexin-A2, Sorcin, S100A6), Cell cycle and apoptosis-related proteins (14-3-3epsilon, PCNA, Stathmin), others (Protein DJ-1, PPIA, GIPC1, vinculin).
The different expression of DJ-1and CFL-1between H69AR and H69cells identified in proteomic study was further validated by Western blot analysis. H69AR cells had increased expressed level of DJ-1and CFL-1compared to H69cells.
2. Selection of efficient siRNA for interference the DJ-1and CFL-1expression
We designed and synthesized three pairs of siRNA oligonucleotides targeting DJ-1and CFL-1respectively, included DJ-1-homo-394, DJ-1-homo-483, DJ-1-homo-612, CFL-1-homo-326, CFL-1-homo-523, CFL-1-homo-579. Transfected them and control siRNA into H69AR cells by using lipofectamin2000. Study showed that sharply down express of DJ-1and CFL-1in cells that transfected DJ-1-homo-394-siRNA and CFL-1-homo-523-siRNA, and select DJ-1-homo-394-siRNA and CFL-1-homo-523-siRNA for fellow research.
3. Down-regulation DJ-1and CFL-1expression and the effect of SCLC multi drug resistance
After interfered, DJ-1and CFL-1expression level decreased sharply in H69ARcells. CKK-8assay results showed that, after treatment of ADM, DDP, VP-16, the survival rate of H69AR-DJ-1-siRNA394decreased significantly compared with that mock control. Similarly, the survival rate of H69AR-CFL-1-siRNA394decreased significantly compared with that mock control.
4. Relationship between DJ-1and CFL-1expression and clinical pathological features in SCLC tissues.
Positive DJ-1expression in SCLC tissues was located in the cytoplasm. Its positive rate was51.7%(60/116). Positive rate of DJ-1expression in male patients was52.5%(53/101), while in female ones46.7%(7/15). There was no significant difference between them (χ2=0.176> P=0.674). Positive rate of DJ-1expression in patients younger than60-year-old was53.4%(31/58), while in over60-years old50.0%(29/58). There was no significant difference between them (x2=0.138, P=0.710). Positive rate of DJ-1expression in patients in limited stage was52.8%(38/72), while in extensive stage50.0%(22/44). There was significant difference between them (χ2=0.084, P=0.771). Positive rate of DJ-1expression in95patients undergone chemotherapy was50.5%(48/95), while in21patients with no chemotherapy51.7%(12/21). There was significant difference between them (χ2=0.302, P=0.583). Positive rate of DJ-1expression in survival patients was15.4%(2/13), while in dead57.1%(52/93). There was significant difference between them (χ2=7.946, P=0.005).
Positive CFL-1expression in SCLC tissues was located in the cytoplasm nucleus. Its positive rate was51.7%(60/116) in all cases. Positive rate of DJ-1expression in male patients was52.5%(53/101), while in female ones46.7%(7/15). There was no significant difference between them (χ2=0.176, P=0.674). Positive rate of CFL-1expression in patients younger than60-year-old was53.4%(31/58), while in over56-years old50.0%(29/58). There was no significant difference between them (χ2=0.138, P=0.710). Positive rate of CFL-1expression in patients in limited stage was52.8%(38/72), while in extensive stage50.0%(22/44). There was significant difference between them (χ2=0.084, P=0.771). Positive rate of CFL-1expression in 95patients undergone chemotherapy was50.5%(48/95), while in21patients with no chemotherapy51.7%(12/21). There was significant difference between them (χ2=0.302, P=0.583). Positive rate of CFL-1expression in survival patients was15.4%(2/13), while in dead57.1%(52/93). There was significant difference between them (χ2=7.946, P=0.005).
5. Survival analysis of SCLC patients
(1)COX regression model By using stepwise COX regression model analysis, DJ-1over-express (HR=2.509, P<0.001,95%CI:1.622-3.880) and CLF-1over-express (HR=2.000, P=0.001,95%CI:1.304-3.068) were high death risk for SCLC patients. Chemotherapy is also a clearly factor for progression (HR=0.488, P=0.012,95%CI:0.278-0.856).
(2) Estimation of survival time
We used Kaplan-Meier method to estimate the survival time of patients. DJ-1expression was one independent poor prognosis factor in SCLC patients(HR=2.960, P=0.001,95%CI:1.519-5.767).
Conclusions
1. Two dimensional gel electrophoresis and mass spectrometry analysis of proteomic technology can be used for screening out SCLC multidrug resistance-associated protein.
2. DJ-1and CFL-1expressed higher in SCLC multidrug resistant cell line H69AR and lower in the drug-sensitive cell line H69. Down regulated the expression of DJ-1and CFL-1can cause H69AR drug sensitivity change, DJ-1and CFL-1involved in drug resistance in SCLC.
3. DJ-1and CFL-1expression in SCLC tissue were related to survival time of patients. DJ-1and CFL-1were expected to be prognostic indicators and targets of the drug treatment of patients with SCLC.
据全球癌症发病的最新统计资料显示肺癌的发病率居恶性肿瘤的首位,在我国情况也是如此。每年因为肺癌死亡的人数超过100万,是严重威胁人类健康的疾病。更另人担忧的是肺癌的发病率呈明显上升趋势,这与人口的老龄化、城市的工业化、农村的城市化、环境污染以及不良生活习惯如吸烟相关。根据肿瘤组织形态学的不同,肺癌主要分为小细胞肺癌(small cell lung cancer, SCLC)和非小细胞肺癌(non-small cell lung cancer, NSCLC),后者包括腺癌、鳞癌和大细胞癌。SCLC发病率约占原发性肺癌的15%,分化程度低,易较早发生血行转移,预后极差。虽然SCLC对初始化疗比较敏感,但极易发生多药耐药(multi-drug resistance, MDR)现象,从而导致化疗失败,肿瘤进展较快,患者早期出现了复发与转移,最终因多器官功能衰竭而死亡,5年存活率不足5%。因此,SCLC的多药耐药性是目前SCLC基础应用研究和临床治疗亟待解决的问题之一。
恶性肿瘤化疗治疗失败的主要原因是多药耐药,是指对已经接触过抗肿瘤药物无论在功能上或结构上都不相关的多种药物具有获得性耐药。肿瘤多药耐药机制主要有包括下面几种因素：(1)药理性耐药(pharmacological resistance):指由机体本身对药物的影响所导致的耐药,如药物进入机体后代谢活动增强或药物活化障碍,肿瘤组织血供不足,药物与组织亲透力差等；(2)微环境耐药(microenvironment resistance):指肿瘤细胞的存活和生长有赖于器官微环境,而器官微环境可以通过不同的耐药基因表达来影响肿瘤细胞对化疗药物的敏感性从而产生；(3)凋亡耐药(apoptosis resistance):参与控制的细胞凋亡基因如P53、BCL-2、C-myc等受到了抑制；(4)生化耐药(biochemical resistance):指肿瘤细胞的遗传性及生化特性发生变化,使细胞通过不同途径对药物产生耐药,其中研究最为广泛的是ABCC膜转运蛋白超家族成员即药物输出泵,如P-糖蛋白(P-gp)、多药耐药相关蛋白(MP)、肺耐药相关蛋白(LRP)、谷胱甘肽转移酶等。这些蛋白既然参与肿瘤细胞的多药耐药,但是如何发现这些蛋白质,进行鉴定,并研究其作用机制以及想办法改变其功能是蛋白质组学研究的重要内容。
细胞凋亡异常：凋亡逃逸是肿瘤细胞的共同特性,也是SCLC产生化疗抗性的重要原因。在细胞黏附介导的耐药中,胞外基质蛋白可对抗细胞毒性药物诱导的凋亡信号。细胞外基质(extracellular matrix, ECM)在β1整合素(β lintegrin)介导下,通过激活P13K信号通路,从而使下游靶区PKB、GSK3β表达增高,阻断细胞凋亡。CD9是四次跨膜蛋白Tetraspanin家族成员之一,在转移性SCLC组织以及顺铂或依托泊苷耐药的SCLC细胞系中具有高表达。CD9阳性的耐药SCLC细胞在β1整合素(β1integrin)的介导下,与纤连蛋白(fibronectin)的连接更为紧密,通过激活PI3K/AKT/mTOR信号通路,引起肿瘤对化疗诱导的凋亡不敏感。使用靶向CD9的特异性单克隆抗体ALB6或小干扰RNA(small interfering RNA, siRNA)可成功触发上述耐药细胞发生凋亡。抑癌基因p53蛋白可应答DNA损伤信号,激活生长阻滞通路(抑制DNA修复)和凋亡通路。p53基因缺失或突变的肺癌患者预后不良,常伴有对放、化疗的抗性。在超过80%的SCLC中均发现野生型p53蛋白活性的缺失,通过抑制细胞周期依赖性激酶抑制剂p21wafl表达,引起细胞周期检查点异常,最终导致细胞增殖失控、凋亡受阻,与疾病进展、预后不良及化疗耐药相关。Bcl-2基因定位于染色体的18q21,编码相对分子质量为26000的蛋白,Bcl-2属凋亡调节基因家族成员。在SCLC中常有Bcl-2表达上调,体外诱导的耐药SCLC细胞系中亦可见Bcl-2表达增加。
郭用microRNA芯片技术发现,小细胞肺癌耐药细胞株H69AR细胞与药物敏感细胞株H69细胞相比,有61种microRNA存在差别,其中24种表达增高,37种表达下调。48种microRNA首次报道与肿瘤的耐药相关,包括miR-134, miR-379与miR-495。用miR-134miR-379与miR-495的类似物转染到H69AR细胞中,其对DDP、ADM及VP-16的药物敏感性增加。进一步研究发现,miR-134调节的靶蛋白是MRPA/ABCC1,转染miR-134类似物MRPA/ABCC1蛋白表达下降,并且H69AR细胞对DDP、ADM及VP-16的药物敏感性。同源异型盒(homeobox)基因(HOXA1)是细胞分化、增殖和凋亡等生物学过程的关键调节基因,参与胚胎发育和个体生长的调节。有研究表明同源异形盒基因可以调节肿瘤的凋亡或耐药性。肖以SCLC多药耐药细胞株H69AR和敏感细胞株H69作为研究对象,采用cDNA基因芯片分析两株细胞中具有差异表达的基因,结果显示HOXA1在SCLC细胞株H69中的表达是多药耐药细胞株H69AR中的表达的4.16倍,实时荧光定量PCR结果和Western Blot检测结果验证了基因芯片的结果。上调HOXA1的表达明显增加H69AR细胞的药物敏感性,下调HOXA1的表达显著增加H69细胞的耐药性。免疫组化染色结果显示,HOXA1在存活患者中的阳性表达率为91.7%(11/12),在死亡患者中的阳性表达率为35.3%(18/51),两者的HOXA1阳性表达率具有统计学差异(x2=12.427, P<0.001), HOXA1阳性表达者生存时间显著高于HOXA1阴性表达患者。HOXA1是miR-100的靶基因,可受到miR-100调控,转染miR-100的抑制物,可使HOXA1表达增加,并增加H69细胞的耐药性。上皮和内皮细胞酪氨酸激酶(Epethelial and endothelial tyrosine kinase, Ekt)是BTK家庭中的重要成员之一,研究发现它在上皮增值、分化、凋亡和肿瘤发生过程中有着重要的调控作用。周应用荧光定量PCR和Western blot技术证实H69AR细胞中Ekt表达水平明显高于H69细胞,基因沉默降低H69AR中Ekt水平后,H69AR对阿霉素的敏感性显著增加,进一步证实Ekt有抵抗药物诱导细胞凋亡的作用,并且在小细胞耐药性产生过程可能有重要作用。
细胞膜蛋白药泵表达异常：MDR的形成与膜蛋白如ABC家族成员P-gp、 MDR相关蛋白(MDR1、MRP1、MRP2)等的过度表达有关。在耐药的SCLC组织和体外培养SCLC细胞系中都发现P-gp和MRP-1表达水平的增高。MDR的形成也与LRP高度表达相关,它能介导以DNA为靶点的化疗药物,如阻止顺铂、卡铂等烷化剂进入细胞核,起到中间关卡的作用,组织药物进入细胞核内或者将已进入核内的药物通过转运载体重新运出细胞核或将细胞浆中的药物转运至运输囊泡,从而使药物呈房室性分布,并通过胞吐机制将药物排出细胞,降低细胞内的药物浓度,最终产生耐药。有学者从基因芯片证实FZD1、GLI1和FRZB在SCLC的耐药细胞株及呈现耐药现象的患者中显著高表达。FZD1是参与编码跨膜Wnt受体卷曲蛋白的基因。参与编码Wnt受体卷曲蛋白的基因共10种(FZD1～FZD10),其在恶性肿瘤的发生发展中起着非常重要的作用。该研究基因芯片证实FZD1无论在离体H69AR细胞还是活体内,都呈现出较高的表达水平。FZD1作为Wnt受体卷曲蛋白的重要编码基因可作为逆转SCLC多耐药的理想靶标。GLI是Sonic hedgehog(Shh)信号通路重要的转录因子。Shh信号通路在胰腺癌、基底细胞癌、SCLC等肿瘤中异常激活。Shh信号通路对靶细胞的作用是通过细胞膜上的Patched(PTC)(?)(?)2个转录原件所介导,最终激活一种转录因子GLI。化疗药物反复刺激Shh信号通路的上游基因,引发下游转录因子出现生物功能的改变。GLI1作为Shh信号通路的终点,充分说明GLI1不仅参与肿瘤的发生发展而且参与了肿瘤细胞对化疗药物的耐药。FRZB是Wnt信号通路的负性调节因子,该研究发现FRZB在SCLC的耐药细胞株及呈现耐药现象的患者中显著高表达,在细胞学研究中,耐药细胞株的表达显著高于亲本细胞株,说明该基因参与了肿瘤的耐药性。但这些基因的变化是如何参与肿瘤细胞的耐药以及如何避免这些耐药基因作用的发挥仍需要深层次的研究。
细胞内酶系统异常：DNA拓扑异构酶(topoisomerase, Top)是细胞DNA复制和转录的主要核酶。Top抑制剂是SCLC最常用的化疗药物之一,Top表达水平下调以及表达类型的改变是SCLC对Top抑制剂耐药的重要原因。最近一项研究发现,脂质体介导的人工合成siRNA瞬时转染可有效抑制人小细胞肺癌细胞株H446的TopⅠ表达并显著提高对VP16的敏感性,提示转染后的细胞株TopⅠ水平下降的同时有Top Ⅱ的表达水平升高。体内、外实验均已经证实TopⅠ抑制剂和Top Ⅱ抑制剂联合应用时具有明显的协同作用。Lawson等通过cDNA芯片分析筛选SCLC耐药相关基因,并人为改变候选靶基因表达水平以观察其对SCLC药物敏感性的影响,结果发现,DNA聚合酶β (DNA polymerase β)和神经内分泌转录因子NKX的高表达可能与SCLC对依托泊苷的耐药有关,这一结论在SCLC组织芯片结果中亦得到证实。
细胞修复系统增强：近年来研究表明,DNA错配修复(mismatch repair, MMR)在SCLC的获得性耐药中起着非常重要的作用。有学者发现MMR基因MLH1和MSH2的表达下调可能与SCLC的发生及其MDR有关。至于MMR基因表达下调的具体机制目前尚不清楚,可能与组蛋白去乙酰化、磷酸化或启动子超甲基化造成的MMR基因沉默有关。
蛋白质学是肿瘤临床和基础研究中的热点,对于了解肿瘤尤其是发病机制,诊断和治疗等多方面都有重要作用。“蛋白质组学”则是应用大规模蛋白质分离和鉴定技术,从蛋白质水平探索生命的本质及其规律的一门学科,是高通量的蛋白质筛选技术。包括结构蛋白质组学和功能蛋白质组学。蛋白质组学研究技术主要包括蛋白质分离技术、鉴定技术和生物信息学技术。蛋白质组学研究的样品可用细胞、组织、血液、体液等。近年来,激光捕获显微切割技术(LCM)的应用,既保证了肿瘤组织取材可获得足够量的单一细胞成分,也能保持细胞原有形态。蛋白质分离的关键技术是二维聚丙烯酰胺凝胶电泳(2D-PAGE),其原理是根据蛋白质等电点与分子量的不同,通过电泳的方式把蛋白质分离。
蛋白质鉴定技术主要是质谱分析法(massspectrometry, MS),最常用的是基质辅助激光解析电离飞行时间质谱(matrix-assisted laserdesorption/ionization-time of flight-mass spectrometry, MALDI—TOF—MS)。质谱分析的原理是利用电离源将蛋白质转化为离子,然后借助于质谱仪的电场与磁场将具有特定质量与电荷比例(M/Z)的蛋白质分子分离开来,经过离子检测器收集分离的离子,确定离子的M/Z值,分析鉴定未知的蛋白质。具有高分辨、高敏感、高通量及直接检测复杂的生物学样本等优点,已成为蛋白质组学研究的特色技术。
生物信息学也是蛋白质组学研究的重要部分,其在蛋白质组学的研究中对构建和分析2-DE图谱,数据库的搜索与构建等方面有重要作用。蛋白质组数据库是蛋白质组研究水平的标志和基础。蛋白组学必须结合生物信息学才能在复杂的数据里提取有价值的信息,为研究工作提供有效指引。
目的
通过比较SCLC多药耐药细胞株(H69AR)和敏感细胞株(H69)中蛋白表达差异,从多种表达差异的蛋白中选取表达差异显著的蛋白DJ-1和confilin-1(CFL-1)进行进一步研究。利用RNA干扰技术下调此蛋白的表达水平,并观察耐药株对阿霉素(Doxorubicin，ADM)、顺铂(Csiplatin,DDP)、足叶乙甙(Etoposid,VP-16)等的药物敏感性变化；分析DJ-1和CFL-1在SCLC组织中表达以及与临床病理资料关系,探讨其作为SCLC治疗靶点和预后判断的生物学指标可能性,进一步丰富SCLC多药耐药性的分子机制,为临床治疗提供理论和实验依据。
内容与方法
一、分析SCLC多药耐药细胞株H69AR和敏感细胞株H69中蛋白组表达差异性
以SCLC多药耐药细胞株H69AR和敏感细胞株H69作为研究对象,应用双相电泳(2D-PAGE)和质谱分析技术,分析两株细胞中具有差异表达的蛋白。从多种表达差异的蛋白质中选取表达差异显著的DJ-1与CFL-1进一步研究,采用Western Blot技术验证两种蛋白在两株细胞中的表达差异。
二、利用RNA干扰技术下调DJ-1与CFL-1在H69AR细胞株的表达
首先合成DJ-1与CFL-1的siRNA以及control siRNA,然后通过脂质体法转染H69AR细胞与H69细胞,培养24h后提取总蛋白。利用western blotting技术检测转染DJ-1-siRNA、CFL-1-siRNA和control siRNA组中DJ-1、CFL-1的蛋白表达差异。
三、分析下调DJ-1与CFL-1表达后对H69AR细胞株耐药性的影响
利用CCK-8法分析H69AR-DJ1-siRNA394细胞与H69AR-CFL1-siRNA523细胞对不同浓度的小细胞肺癌常用化疗药物阿霉素(ADM)、顺铂(DDP)、足叶乙苷(VP16)药物敏感性变化。
四、DJ-1与CFL-1在SCLC组织中的表达及临床意义
收集116例SCLC的石蜡包埋组织,患者平均年龄60岁(58.92±10.09),随访时间0-128月。其中男性101例,女性15例；年龄<60岁有58例,年龄≥60岁也是58例；临床分期局限期72例,广泛期46例；接受化疗或放疗95例,未进行化疗或放疗的21例。免疫组织化学染色S-P法检测SCLC组织中DJ-1与CFL-1的表达情况,并分析DJ-1与CFL-1的表达水平与临床病理特征及患者预后的关系。
五、统计分析
数据以均数±标准差(Mean±SD)表示,所有结果均经SPSS13.0统计软件处理。CCK8采用两因素析因设计的方差分析,多重比较用SNK法。同一组内不同浓度间比较和同一浓度不同组间比较用one-way ANOVA。参数比较前均先进行方差齐性检验,若方差不齐用基于方差不齐的近似F检验Welch法。免疫组化染色强度的比较采用Mann-Whitney U检验;小细胞肺癌组织中DJ-1与CFL-1表达水平与生存率的关系采用Kaplain-Meier分析。应用Chi-square test分析DJ-1与CFL-1表达水平与临床病理特征的关系。应用Cox回归模型分析分析DJ-1与CFL-1临床病理特征参数与SCLC患者预后的关系。以P<0.05为差异有统计学意义。
结果
一、SCLC沛癌多药耐药细胞株H69AR与敏感细胞株H69中差异表达蛋白的筛选双相电泳分析发现有35蛋白质斑点在两组凝胶中有显著性差异表达,表达量相差两倍以上,其中在H69AR细胞中表达量升高的蛋白质斑点有25个,表达量下降的蛋白质斑点有10个。取25个表达量显著增高的斑点进行MALDI-TOF-MS分析,结果显示质谱鉴定最终得到16个H69AR/H69差异表达蛋白质,主要包括分子伴侣蛋白(HSPB1)、葡萄糖代谢酶(IMPDH2, Alpha-enolase)、细胞骨架蛋白(Cytoskeletal9, Cytoskeletal1, Cofilin-1)、钙结合蛋白(Annexin-A2、Sorcin、 S100A6)、细胞周期和凋亡相关蛋白(14-3-3epsilon, PCNA, Stathmin)及其它(Protein DJ-1, GIPC1,PPIA, vinculin)等。
进一步采用Western blot验证多药耐药细胞株H69AR与敏感细胞株H69中DJ-1与CFL-1蛋白表达水平,结果发现H69AR细胞株中DJ-1与CFL-1蛋白水平显著高于H69细胞株。
二、DJ-1与CFL-1siRNA干扰效率的鉴定针对DJ-1与CFL-1基因各设计3条siRNA (DJ-1-homo-394、DJ-1-homo-483、 DJ-1-homo-612; CFL-1-homo-326、CFL-1-homo-523、CFL-1-homo-579),在小细胞肺癌耐药细胞株H69AR中转染上述的siRNA以及control siRNA,结果显示转染DJ1-siRNA394与CFL1-siRNA523组DJ-1和CFL-1的表达水平下调最为显著,选取作为后续研究的siRNA。
三、下调DJ-1与CFL-1表达后对SCLC多药耐药性的影响
通过干扰技术下调DJ-1与CFL-1表达后,在H69AR细胞和H69细胞中DJ-1与CFL-1的表达水平明显下降。利用CCK-8法分析显示H69AR-DJ-1-siRNA394细胞对不同浓度的ADM (F=8981.090, P<0.001)、DDP (F=2670.697, P<0.001)、 VP16(F=2693.832, P<0.001)的生存率较mock组细胞的生存率明显降低。同样,H69AR-CFL1-siRNA523细胞对不同浓度的ADM、DDP、VP16的生存率较]mock组细胞的生存率也明显降低。
四、DJ-1与CFL-1表达水平与SCLCI临床病理特征的关系
(1)免疫组化染色显示DJ-1主要定位于肿瘤细胞质,在116例SCLC组织中,DJ-1蛋白阳性的60例,阳性率为51.7%(60/116),其中男性患者DJ-1中阳性表达率52.5%(53/101),女性患者中的阳性表达率为46.7%(7/15),两者阳性表达率的差异无显著性(X2=0.176,P=0.674)。60岁以下患者中DJ-1阳性表达率为53.4%(31/58),60岁以上患者中阳性表达率为50.0%(29/58),两者阳性表达率差异无统计学(X2=0.138,P=0.710)。局限期患者中DJ-1阳性表达率为52.8%(38/72),广泛期患者中阳性表达率为50.0%(22/44),两者的DJ-1阳性表达率差异无显著性(X2=0.084,P=0.771)。95例接受化疗患者中,DJ-1阳性表达率为50.5%(48/95),21例未接受化疗患者中阳性表达率为51.7%(12/21)，两者的DJ-1阳性表达率差异无显著性(χ2=0.302, P=0.583)。DJ-1在存活患者中的阳性表达率为15.4%(2/13),在死亡患者中的阳性表达率为57.1%(52/93),两者的DJ-1阳性表达率有显著性(X2=7.946,P=0.005)。
(2)免疫组化染色显示CFL-1主要定位于肿瘤细胞质,116例SCLC组织中CFL-1阳性表达61例,阳性表达率为52.6%(61/116),其中在男性患者中CFL-1阳性表达率55.4%(56/101),在女性患者中的阳性表达率为33.3%(5/15),两者的阳性表达率差异无显著性(X2=2.561,P=0.110)。在60岁以下患者中CFL-1阳性表达率为51.7%(30/58),60岁以上患者中阳性表达率为53.4%(31/58),两者的CFL-1阳性表达率差异无显著性(X2=0.035,P=0.852)。局限期患者中CFL-1的阳性表达率为50.0%(36/72),广泛期患者中的阳性表达率为58.8%(25/44),两者的CFL-1阳性表达率差异无显著性(#=0.509,P=0.475)。在95例接受化疗的患者中CFL-1阳性表达率为51.6%(49/95),21例未接受化疗的患者中阳性表达率为51.7%(12/21),两者的CFL-1阳性表达率差异无显著性(X2=0.214,P=0.664)。在存活患者中CFL-1的阳性表达率为23.1%(3/13),在死亡患者中的阳性表达率为57.1%(52/93),两者的CFL1阳性表达率差异有显著性(X2=5.298,P<0.05)。
五、SCLC患者预后因素分析
Kaplan-Meier生存分析结果显示,DJ-1(10g-rank test,χ2:19.084,P<0.001)和CFL-1(log rank test,χ2=11.035,P=0.001)高表达预示SCLC预后不良。
对116例SCLC病例进行单因素Cox回归分析,结果表明,DJ-1高表达(HR=2.509,P<0.001,95%CI:1.622-3.880)和CFL-1高表达(HR=2.000,P=0.001,95%CI:1.304-3.068)分别是SCLC预后不良的指标之一,此外接受化疗(HR=0.488,P:0.012,95%CI:0.278-0.856)也是SCLC的预后指标。
Cox多重回归分析(Enter)表明,DJ-1高表达(HR:2.960,P=0.001,95%CI:1.519-5.767)是SCLC预后不良的独立指标之一,接受化疗是SCLC患者的保护性因素(HR=0.488,P=0.012,95%CI:0.278-0.856)。
Cox回归全变量模型分析患者的性别、年龄、疾病分期、手术、化疗、转移、DJ-1及Confilin表达与患者预后的关系,发现DJ-1、手术治疗及疾病的转移与患者的预后相关。DJ-1高表达患者的预后较差,可作为独立的预后因子,差异具有统计学意义(W=13.594,P<0.001),高表达DJ-1患者的相对风险度为3.861,95%相对风险度的可信区间为1.883-7.919；无转移患者的相对风险度较转移患者降低,RR=0.414,95%相对风险度的可信区间为0.175-0.977,差异具有统计学意义(W=4.053,P=0.044),进行手术治疗患者的相对危险度为2.195，95%相对危险度的可信区间为1.275-3.776，差异具有统计学意义(W=8.057,P=0.005)。Cox回归逐步回归模型与全变量回归模型的结果一致
结论
1、应用蛋白质组学的双相电泳技术与质谱分析技术可筛查出SCLC多药耐药相关蛋白。
2、DJ-1和CFL-1在SCLC多药耐药细胞株H69AR中高表达,而在药物敏感细胞株H69中低表达,下调DJ-1和CFL-1的表达可引起多药耐药细胞株H69AR对药物敏感性的变化,说明了DJ-1与CFL-1参与了SCLC的耐药。
3、DJ-1和CFL-1在SCLC组织中表达与患者的生存时间相关,而与患者的性别、年龄、临床分期等无统计学意义,这两种蛋白有望成为SCLC患者的预后指标及药物治疗的靶点。
Background
According to the latest global cancer statistics, the incidence of lung cancer ranks first in all malignant. So does the situation in China. More than one million people die from lung cancer. It is a serous threat to human health. More worrisome is clear upward trend in the incidence of lung cancer. This is related to the aging of population, the city's industrialization, urbanization in rural areas, environmental pollution and unhealthy habits such as smoking. According to the morphology under microscope, lung cancer can be divided into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). The latter include adenocarcinoma, squamous cell carcinoma and large cell lung cancer. SCLC accouts for about15%of primary lung cancers. It is poorly differentiated and easy to hematogenous metastasis at early stage, which leads to poor prognosis. Although sensitive to chemotherapy initially, SCLC develop multi-drug resistance (MDR) soon, which resulted in failure of chemotherapy and rapid progression. Recurrence and metastasis will be found in patients with early stage. Eventually died of multiple organ failure.5-year survival rate of SCLC is less than5%. Therefore, MDR is one of the problems to be conquered in the basic research and clinical treatment of SCLC.
Multi-drug resistance is the main reason for the failure of chemotherapy treatment of malignant tumors. The tumors have acquired resistance to contact anticancer drugs regardless of function or structure not related to a variety of drugs. Multi-drug resistance mechanisms include the following factors. The first factor is pharmacological resistance. The resistance caused by the body itself and the influence of drugs. Such as enhanced metabolic activity of the drug into the body or drug activation barrier, insufficient blood supply of the tumor tissue, poor affinity and penetration between the drug and the organization. The second factor is microenvironment resistance. The survival and growth of tumor cells depends on the organ microenvironment, Organ microenvironment can influence gene expression by different drug sensitivity of tumor cells to chemotherapeutic agents resulting in. The third is apoptosis resistance which involved in the control of apoptosis genes was inhibited, such as P53, BCL-2, C-myc. In addition, biochemical resistance factor is also important.
Changes in the genetic and biochemical characteristics of the tumor cells allows the cells to the emergence of drug resistance through different channels. ABCC membrane transporter protein super-family members, that is drug export pump, get the most extensively studied. The family include P-glycoprotein (P-gp), Multidrug resistance-associated protein (MRP), Lung resistance-related protein (LRP), and Glutathione S-transferase. These proteins are involved in multidrug resistance of tumor cells, but how to find and identify these proteins is important content. Subsequent study of its mechanism of action, changing its function by molecular biology techniques proteomics research is also important.
Abnormal apoptosis:Apoptosis escape is the common characteristics of the tumor cells, that also play important role in SCLC chemotherapy resistant. In cell adhesion mediated drug, extracellular matrix proteins against cytotoxic drug-induced apoptosis signal. The extracellular matrix (ECM) mediated by β1integrin and activate the PI3K signaling pathway, upregulateing the target PKB of GSK3β expression and blocking apoptosis. CD9is the protein of the four transmembrane family members. CD9expressed higher in metastatic SCLC tissues, and the SCLC cell lines with cisplatin-resistant or etoposide-resistant was higher expression. The SCLC cell with CD9-positive resistant mediated β1integrin (β1integrin), and fibronectin protein (fibronectin) connection closer, by activating PI3K/AKT/mTOR signaling pathway, caused to chemotherapy-induced withered death not sensitive. The specificity using targeting CD9the monoclonal antibody ALB6small interference RNA (siRNA) can successfully trigger apoptosis in the resistant cells. The tumor suppressor gene p53protein response to DNA damage signal activation of growth arrest pathway and apoptosis pathway. Deletion or mutation of the p53gene in lung cancer patients with poor prognosis, often accompanied by radiotherapy and chemotherapy resistance. More than80%of the SCLC patients absented of wild-type p53protein, activity through the inhibition of cyclin-dependent kinase inhibitor p21wafl expression caused abnormal cell cycle checkpoint, eventually leading to uncontrolled cell proliferation, apoptosis blocked and caused disease progression. poor prognosis and resistance to chemotherapy related. Bcl-2gene is located on chromosome18q21, encoding the relative molecular mass of26,000protein, Bcl-2gene family members is a regulation of apoptosis. In SCLC often Bcl-2expression, which can also be found in the increased expression of Bcl-2in vitro induced resistant SCLC cell lines.
Guo used microRNA microarray to analysis the differences microRNA in SCLC multidrug resistant cell line H69AR and sensitive cell lines H69. The results showed that61miRNAs are presented significanty including up-regulation of24miRNAs and down-regulation of37miRNA. Among these miRNAs,48of61differentially expressed miRNAs were firstly reported to be closely associated with drug resistance, including miR-134, miR-379and miR-495. Following transfection of H69AR cells with the mimics of miR-134, miR-379and miR-495, respectively, the sensitivity to Cisplatin, Etoposides and Doxorubicin was significantly increased. MRPA/ABCC1was the target of miR-134. After transfecting of H69AR cells with the mimics of miR-134, that the MRPA/ABCC1protein was considerably decreased, and the sensitivity to Cisplatin, Etoposides and Doxorubicin was also increased. Homeobox genes are critical genes that modulate biological processes, such as cell differentiation, proliferation and apoptosis. They involved in embryonic development and ontogeny. Studies have shown that homeobox genes can regulate apoptosis and multi-drug resistance of cancers. Xiao analyzed the differences of gene expression between H69 and H69AR by using cDNA microarray. The studies showed that HOXA1expression in SCLC cell lines H69was4.16-fold of that in multi-drug resistant cell line H69AR. The result was verified by using quantitive real-time PCR and Western Blot. Forced HOXA1expression increased chemo-sensitivity of H69AR cells, reduction of HOXA1expression in H69cell increased its chemo-resistance. HOXA1is the target genes of miR-100. After transfection of miR-100inhibitor into H69AR cell, miR-100expression reduced, but HOXA1protein levels increased. Up-regulation of miR-100in H69cell resulted in increase of resistance to ADM, DDP and VP-16. Epithelial and endothelial tyrosine kinase (Ekt) is one of the important members of the Btk family. Studies found that plays an important role in epithelial proliferation, differentiation, apoptosis and tumorigenesis. Zhow Confirmed that the Etk expression levels in H69AR cell was significantly higher than in H69cells by real-time PCR and western blotting. After the gene silencing to reduce Etk level in H69AR cells, the sensitivity to doxorubicin increased significantly. That further confirmed the Etk resistance to chemotherapeutic and apoptosis, and may play important role in the process of small cell lung cancer drug resistance.
The relationship between the abnormal of membrane protein drug pump expression and multi-drug resistant. The multi-drug resistant formatiing are related membrane proteins, such as the over-expression of the ABCC family members of P-gp, MDR-related protein (MDR1, MRP1, MRP2). That the P-gp and MRP-1express higher in the resistant SCLC tissues and cultured SCLC cell lines in vitro. The formation of the MDR is related to LRP high expression. LRP can mediated DNA-targeting chemotherapy drugs cisplatin, carboplatin and other alkylating agents, such as block into the nucleus, and played the role of intermediate checkpoints. Import drugs into the nucleus, or re-transported out of the drug that had entered into the nuclear and the cytoplasm So that the drug was the atrioventricular distribution, and through exocytosis mechanism washout cells and reduce the concentration of the drug in the cell, ultimately resulting in the resistance. Scholars confirmed FZD1of GLI1and FRZB resistant SCLC cell lines and present patients of the drug phenomenon in significantly high expression from gene chip. FZD1is involved. In the curl protein gene encoding that is transmembrane Wnt receptor.10gene (FZD1-FZD10) are involved in the Wnt receptor curl Protein encoding. That plays a very important role in the development of malignant tumors occur. The gene chip confirmed that the FZD1expressied higher emerged both in vitro H69AR cells or in vivo. FZD1involving curl protein of Wnt receptor coding genes is a reversal of the SCLC multi-drug resistance ideal target. GLI is an important transcription factor of the Sonic hedgehog (Shh) signaling pathway. Shh signaling pathway is abnormally activated in pancreatic cancer, basal cell carcinoma, SCLC tumor. Shh signaling pathway mediated the target cells by ultimating Patched (PTC) on the cell membrane and two transcription originals and activate a transcription factor GLI. Chemotherapy drugs stimulation the upstream gene of the Shh signaling pathway, and triggering the biological function change in the downstream transcription factor. GLI1as the end of the Shh signaling pathway, illustrated fully that the GLI1not only involved in tumor development and involved in tumor cell resistance to chemotherapeutic drugs. FRZB is a negative regulator of the Wnt signaling pathway. The study found that FRZB was significantly higher expressed in resistant SCLC cell lines and present patients of the drug phenomenon. The resistant cell line was significantly higher expression than the parental cell line, indicating that the gene is involved in tumor resistance. These gene changes involved in the drug resistance of tumor cells as well as how to avoid these resistance genes play the role still requires a deep level of research.
Relationship between the abnormal enzyme system with multi-drug resistant cells. Topoisomerase (TOP) is the main cell DNA replication and transcription ribozyme. Top inhibitor is one of the most commonly used chemotherapy drugs SCLC. Down-regulation expression levels of the Top as well as the change of expression is a the SCLC Top inhibitor resistant reason. A new study found that liposome transfect of synthetic siRNA can effectively inhibit human small cell lung cancer cell line H446Top Ⅰ expression and significantly improve the sensitivity of VP16. Top Ⅰ levels decreased after transfection of the cell line, the same time the expression of elevated levels of the Top Ⅱ. The experiments of the vivo and the in vitro have confirmed that Top I inhibitors and Top II inhibitor combined application has obvious synergies. Lawson et screening SCLC multi-drug resistance-related genes by cDNA microarray analysis, and changed candidate target gene expression levels, observe the SCLC drug sensitivity. The results showed high expression of DNA polymerase β and neuroendocrine transcription factor NKX may caused SCLC resistant to etoposide, also confirmed this conclusion in a the SCLC tissue microarray results.
The relationship between cell repair system with multi-drug resistance. Recent studies show that the DNA mismatch repair gene (MMR) plays a very important role in SCLC acquired drug resistance. Scholars have found that the MMR genes MLH1and MSH2downregulation may occur with the SCLC and its MDR. The specific mechanism of MMR genes downregulated is not yet clear, May go with histone acetylation, phosphorylation or to start hypermethylation and that caused by MMR gene silencing.
Proteomics is a hot spot in the clinical oncology and basic research. Have an important role in for understanding tumor mechanisms, diagnosis and treatment and other multifaceted. Proteomics is the subject that used large-scale application technology for protein separation and identification. It is also a high-throughput protein screening technology, including structural proteomics and functional proteomics, exploring the essence of life and its laws from the overall protein level. Proteomics technologies include protein separation technology, identification technology and bio-informatics technology. Available cells, tissues, blood, body fluids samples can be used for the proteomics research. In recent years, Laser capture micro-dissection technology applications, both to ensure the tumor tissue drawn from the availability of a sufficient amount of a single cell components, but also to maintain the cells in the original form. The key technology of protein separation is two-dimensional polyacry lamide gel electrophoresis (2D-PAGE). Its principle is based on isoelectric point and the different molecular weight, by way of electrophoresis to protein separation.
The role of identification technology for protein is the Mass spectrometry. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALD-TOF-FMS) was most commonly used. The principle of MS analysis is converted the protein to ions using the ionization source, then separating protein molecule with proportion of M/Z in the electric field and the magnetic field by means of the mass spectrometer. The separated ions were collected through the ion detector, determine the M/Z value of ion, analysis and identify the unknown protein. The advantage of MS is high-resolution, high-sensitivity, high-throughput and direct detection of complex biological samples, etc. That has become the special technology of proteomics research.
Bioinformatics is also an important part of the proteomics research. In the study of proteomics, bio-information technology plays an important role in constructing and analyzing of2-DE maps, database search and construction. Proteome database is the logo and the basis of the level of proteome research. Proteomics must be combined with bioinformatics to extract valuable information in the complexity of the data, provide effective guidelines for research.
Objectives
To analysis the differences express protein in SCLC multi-drug resistant cell line H69AR and sensitive cell lines H69, and select the significantly different express protein DJ-1and confilin-1(CFL-1) for further study. Drug sensitivity of the expression levels of the two proteins through RNA interference technology down and observe resistant strains Doxorubicin (ADM), of Cisplatin (DDP), Etoposide (VP-16) changes. Observe the relationship between the express of DJ-1and CFL-1in SCLC tissues with the clinicopathological features. To explore the possibility of biomarkers as SCLC therapeutic targets and prognosis. Further enrich the SCLC multidrug resistance molecular mechanisms, and provide theoretical and experimental basis for clinical treatment.
Materials and methods
1. Analyzed the differences of protein expression between small cell lung cancer cell line H69and its multi-drug resistant cell line H69AR
Investigated the difference of protein expression between SCLC multi-drug resistant cell line H69AR and sensitive cell lines H69,2-DE and Matrix-assisted laser adsorption ionization time-of-flight mass spectrometry (MALD-TOF-FMS) were used in the study. And selected the significantly different express protein DJ-1and confilin-1(CFL-1) for further study. Using the Western Blot techniques to verify the differential expression of the two proteins in the two cell lines.
2. Down regulation DJ-1or CFL-1expression in the cell lines of H69AR by siRNA
We synthesized of DJ-1-siRNA, CFL-1-siRNA and control siRNA, and transfected into H69AR cells by the liposomes2000. Total protein was extracted after24h of cell culture. Detecting of the differences of DJ-1or CFL-1protein expression in the group, that transfected DJ-1-siRNA, CFL-1-siRNA and control siRNA, using western blotting technology.
3. Analysis of the effect of multidrug resistance in H69AR cell lines after down regulation the DJ-1or CFL-1expression.
Chemo-sensitivity to different concentration of ADM, DDP and VP-16were determined by using CCK-8assay in H69AR-DJ1-siRNA394cells and H69AR-CFL1-siRNA523cells.
4. The expression of DJ-1and CFL-1in SCLC tissues and clinical significance
116cases of SCLC paraffin-embedded tissues were collected in our study. The average age of the patients was58.92±10.09, and followed up for0-128months. Male101cases, female15cases.58cases aged less then60years,58cases were60years or more. Clinical limited stage72cases, extensive stage46cases;95cases undergoing chemotherapy,21cases abcent chemotherapy. DJ-1and CFL-1expression were detected by immunohistochemistry stain in SCLC tissue, observed the relationship between the DJ-1or CFL-1expression levels and clinicopathological characteristics and prognosis.
5. Statistical analysis
Data are represented as mean±s.e.m. All statistical analyses were carried out with SPSS13.0software. Factorial experiment ANOVA was used to analyze results of CCK-8experiment. The association between DJ-1and CFL-1expression and clinicopathological features were analyzed by Chi-square test. Survival curves were obtained by Kaplain-Meier method. Prognostic factors were examined by univariate and multivariate analyses (Cox proportional hazards model). P value <0.05was considered significant.
Results
1. Differentially expressed protein screening of SCLC in the multi-drug resistant cell line H69AR and sensitive cell line H69
We adopted a2-DE analysis to quantitatively compare the protein profilings of SCLC mutidrug resistant cell ling H69AR and cell line H69. The differently expressed proteins were more than2fold changes between the two groups.25protein spots in H69AR were higher than H69, but10spots were less.25higher proteins spots were slected to perform protein identification by MALDI-TOF-MS. A total of16proteins were successfully identified including molecular chaperones (HSPB1), Glucose metabolism enzyme (IMPDH2, Alpha-enolase), Cytoskeletal proteins (Cytoskeletal9, Cytoskeletal1, Cofilin-1), Calcium-binding protein (Annexin-A2, Sorcin, S100A6), Cell cycle and apoptosis-related proteins (14-3-3epsilon, PCNA, Stathmin), others (Protein DJ-1, PPIA, GIPC1, vinculin).
The different expression of DJ-1and CFL-1between H69AR and H69cells identified in proteomic study was further validated by Western blot analysis. H69AR cells had increased expressed level of DJ-1and CFL-1compared to H69cells.
2. Selection of efficient siRNA for interference the DJ-1and CFL-1expression
We designed and synthesized three pairs of siRNA oligonucleotides targeting DJ-1and CFL-1respectively, included DJ-1-homo-394, DJ-1-homo-483, DJ-1-homo-612, CFL-1-homo-326, CFL-1-homo-523, CFL-1-homo-579. Transfected them and control siRNA into H69AR cells by using lipofectamin2000. Study showed that sharply down express of DJ-1and CFL-1in cells that transfected DJ-1-homo-394-siRNA and CFL-1-homo-523-siRNA, and select DJ-1-homo-394-siRNA and CFL-1-homo-523-siRNA for fellow research.
3. Down-regulation DJ-1and CFL-1expression and the effect of SCLC multi drug resistance
After interfered, DJ-1and CFL-1expression level decreased sharply in H69ARcells. CKK-8assay results showed that, after treatment of ADM, DDP, VP-16, the survival rate of H69AR-DJ-1-siRNA394decreased significantly compared with that mock control. Similarly, the survival rate of H69AR-CFL-1-siRNA394decreased significantly compared with that mock control.
4. Relationship between DJ-1and CFL-1expression and clinical pathological features in SCLC tissues.
Positive DJ-1expression in SCLC tissues was located in the cytoplasm. Its positive rate was51.7%(60/116). Positive rate of DJ-1expression in male patients was52.5%(53/101), while in female ones46.7%(7/15). There was no significant difference between them (χ2=0.176> P=0.674). Positive rate of DJ-1expression in patients younger than60-year-old was53.4%(31/58), while in over60-years old50.0%(29/58). There was no significant difference between them (x2=0.138, P=0.710). Positive rate of DJ-1expression in patients in limited stage was52.8%(38/72), while in extensive stage50.0%(22/44). There was significant difference between them (χ2=0.084, P=0.771). Positive rate of DJ-1expression in95patients undergone chemotherapy was50.5%(48/95), while in21patients with no chemotherapy51.7%(12/21). There was significant difference between them (χ2=0.302, P=0.583). Positive rate of DJ-1expression in survival patients was15.4%(2/13), while in dead57.1%(52/93). There was significant difference between them (χ2=7.946, P=0.005).
Positive CFL-1expression in SCLC tissues was located in the cytoplasm nucleus. Its positive rate was51.7%(60/116) in all cases. Positive rate of DJ-1expression in male patients was52.5%(53/101), while in female ones46.7%(7/15). There was no significant difference between them (χ2=0.176, P=0.674). Positive rate of CFL-1expression in patients younger than60-year-old was53.4%(31/58), while in over56-years old50.0%(29/58). There was no significant difference between them (χ2=0.138, P=0.710). Positive rate of CFL-1expression in patients in limited stage was52.8%(38/72), while in extensive stage50.0%(22/44). There was significant difference between them (χ2=0.084, P=0.771). Positive rate of CFL-1expression in 95patients undergone chemotherapy was50.5%(48/95), while in21patients with no chemotherapy51.7%(12/21). There was significant difference between them (χ2=0.302, P=0.583). Positive rate of CFL-1expression in survival patients was15.4%(2/13), while in dead57.1%(52/93). There was significant difference between them (χ2=7.946, P=0.005).
5. Survival analysis of SCLC patients
(1)COX regression model By using stepwise COX regression model analysis, DJ-1over-express (HR=2.509, P<0.001,95%CI:1.622-3.880) and CLF-1over-express (HR=2.000, P=0.001,95%CI:1.304-3.068) were high death risk for SCLC patients. Chemotherapy is also a clearly factor for progression (HR=0.488, P=0.012,95%CI:0.278-0.856).
(2) Estimation of survival time
We used Kaplan-Meier method to estimate the survival time of patients. DJ-1expression was one independent poor prognosis factor in SCLC patients(HR=2.960, P=0.001,95%CI:1.519-5.767).
Conclusions
1. Two dimensional gel electrophoresis and mass spectrometry analysis of proteomic technology can be used for screening out SCLC multidrug resistance-associated protein.
2. DJ-1and CFL-1expressed higher in SCLC multidrug resistant cell line H69AR and lower in the drug-sensitive cell line H69. Down regulated the expression of DJ-1and CFL-1can cause H69AR drug sensitivity change, DJ-1and CFL-1involved in drug resistance in SCLC.
3. DJ-1and CFL-1expression in SCLC tissue were related to survival time of patients. DJ-1and CFL-1were expected to be prognostic indicators and targets of the drug treatment of patients with SCLC.
引文
1. NCCN Clinical Practice Guidline in Oncology:Small Cell Lung Cancer Vision 1,2008.
2. Jemal A, Siegel R, Ward E, et al. Cancer stastistics,2009 CA Cancer J Clin,2009, 59:225-249.
3. Hechi SS, Biochemitry, biology, and carcinogenicity of tobacco-specific N-nitrosamines. Chem Res Toxicol,1998,11:559-603.
4. Travis.2004. Pathlogy and Genetics of Tumors of the Lung, Pleura, Thymus and Heart. Lyon IARC Press,15-30.
5. Govindan R, Page N, Morgensztern D, et al. Changing epidemiology of small cell lung cancer in the United States over the lase 30 years analysis of the surviveillance. epidemiologyic, and end results database. J Clin Oncol, 2006,24:4539-4544.
6. Sethi T, Rintoul RC, Moore SM, et al. Extracellulae matrix proteins protect small cell lung cancer cells against:a mechanism for small cell lung cancer growth and drug resistance in vivo. Nat Med.1999,5:662-668.
7. Kim R,Tanabe K,Emi M,et al.Modulation of tamoxifen sensitivity by antisense Bcl-2 and trastuzumab in breast carcinoma cells.Cancer,2005,103 (10): 2199-2207.
8. Tsuruo T, Nato M, Tomida A, et al. Molecular targeting therapy of cancer; drug resistance, apoptosis and survival signa. Cancer Sci,2003,94(1):1-15.
9. Ruiz Gomez MJ, Souviron RA, Morillo M. P-glycoprotein, a membrane pump that represent a barrier to chemotherapy in cancer patients. An Med Interna,2002, 19(9):477-485.
10. Eid H, Mingfang L, Institoris E, et al. Mrp expression of testicular cancer and its clinical relevance. Anticancer Res,2000,20(5):4019-4022.
11. Izquierdo MA, Shoemaker RH, Flens MJ, et al. Overlapping phenotypes of multidrug resistance among panels human cancer cell lines. Int J Cancer,1996, 65(2):230-237.
12. Goto S, Kamada K, Soh Y, et al. Significance of nuclear glutathione S-transferase pi in resistance to anti-cancer drugs. Jpn J Cancer Res, 2002,93(9):1047-1056.
13. Goto S, Kamada K, Soh Y, et al. Significance of nuclear glutathione S-transferase pi in resistance to anti-cancer drugs. Jpn J Cancer Res, 2002,93(9):1047-1056.
14. Kohmo S, Kijima T, Otani Y, et al. Cell surface tetraspanin CD9 mediates chemoresistance in small cell lung cancer. Cancer Res,2010,70(20): 8025-8035.
15. Mason EF, Zhao Y, Goraksha-Hicks P, et al. Aerobic glycolysis suppresses p53 activity to provide selective protection from apoptosis upon loss of growth signals or inhibition of BCR-Abl. Cancer Res,2010,70(20):8066-8076.
16. Sartorius UA, Krammer PH. Upregulation of Bcl-2 is involved in the mediation of chemotherapy resistance in human small cell lung cancer cell lines. Int J Cancer,2002,97(5):584-592.
17. Linlang Guo, Yongguang Liu, Yifeng Bai, et al. Gene expression profiling of drug-resistant small cell lung cancer cells by combining microRNA and cDNA expression analysis. European Journal of Cancer,2010,46:1692-1702.
18. Faman Xiao, Yifeng Bai, Linlang Guo, et al. HOXA1 is involed in multi-drug resistance of small cell lung cancer. European Journal of Cancer,2013, 68:1150-1202.
19. Yuanyuan Zhou, Yanqin Sun, Linlang Guo, The Apoptosis Regulation Mechanism of Protein-tyrosin Kinase Etk and Drug Resistance Studying on Tumors Chemotherapy in Small Cell Lung Cancer. BMJ,2009,45:1452-1463
20. Yeh JJ, Hsu NY, Hsu WH, et al. Comparison of chemotherapy response with P-glycoprotein, multidrug resistance-related protein, and lung resistance-related protein expression in untreated small cell lung cancer. Lung,2005,183(3): 177-183.
21.关俊明,闫玉生,郭琳琅,等. 人小细胞肺癌细胞新耐药基因的探索. 广东医学,2011,32(8)：999-1001.
22. Song Y, Qi Y, Zhang W, et al. Evolutionary trace analysis of eukaryotic DNA topoisomerase I superfamily:identification of novel antitumor drug binding site. Sci China C Life Sci,2005,48(4):375-384.
23. Pectasides D, Samantas E, Fountzilas G, et al. Combination chemotherapy with cisplatin, etoposide and irinotecan in patients with extensive small cell lung cancer:A phase II study of the Hellenic Co2 operative Oncology Group. Lung Cancer,2007,58(3):355-361.
24. Knez L, Sodja E, Kern I, et al. Predictive value of multidrug resistance proteins, topoisomerases II and ERCC1 in small cell lung cancer:a systematic review. Lung Cancer,2011,72 (3):271-279.
25. Lawson MH, Cummings NM, Rassl DM, et al. Two novel determinants of Etoposide resistance in small cell lung cancer. Cancer Res,2011,71(14): 4877-4887.
26. Morimoto H, Tsukada J, Kominato Y, et al. Reduced expression of human mismatch repair genes in adult T-cell leukemia. Am J He-mato,2005,78(2): 100-107.
27. Gong, F.; Peng, X.; Zeng, Z.et al. Proteomic analysis of cisplatin resistance in human ovarian cancer using 2-DE method. Mol. Cell. Biochem.2011,348, 141-147.
28. Li, SL.; Ye, F, Cai, WJ, et al. Quantitative proteome analysis of multidrug resistance in human ovarian cancer cell line. J. Cell. Biochem.2010,109, 625-633.
29. Pazos F, Steinberg MJ. Automated prediction of protein function and detection of functional sites from structure. Proe Natl Acad Sci,2010,101:14754-14759.
30. Wilkins MR, Sanchez JC, Cooley AA. et al. Progress with proteome projects: why all proteins expressed by a genome should be identified and how to do it. Biotechnol Genet Eng Rev,1996.13(1):19-50.
31.李国庆,肖哲锋,刘健平,等.肿瘤：一种蛋白质组病.中国科学.生命科学,2010,40(9)：788-794.
32. Smith-Beckerman DM, Fung KW, Williams KE, et al. Proteome changes in ovarian epithelial cells derived from women with BRCA1 mutations and family histories of cancer. Mol Cell Proteomics.2005;4:156-68.
33. Keshamouni VG, Michailidis G, Grasso CS, et al. Differential protein expression profiling by iTRAQ-2DLC-MS/MS of lung cancer cells undergoing epithelial-mesenchymal transition reveals a migratory/invasive phenotype. J Proteome Res.2006;5:1143-54.
34. W u X, Xiao Z, Chen Z, et al. Differential analysis of two-dimension gel electrOphOresis profiles from the normal, metaplasial, dysplasia and carcinoma tissue of human bronchial epithelium. Pathol Int,2004,54(10):765-773.
35. Cicek M, Samant RS, Kinter M, et al. Identification of metastasis associated proteins through protein analysis of metastatic M DA—MB-435 and M etastasis suppressed BRM S1 transfected—M DA—M B-435 cells. Clin Exp M etastasis, 2004.21(2):149-157.
36. Chang JW, Jeon HB, Lee JH, et al. Augmented expression of peroxiredoxin I in lung cancer. Biochem Biophy Res Commun,2001,289(2):507-512.
37. Yanagiswa K, Shyr Y, Xu BJ, et al. Proteomic patterns of tumor subsets in non-sm all cell lung cancer. Lancet,2003.362(9382):433-439.
38. Nagakubo D, Taira T, Kitaura H, et al. DJ-1, a novel oncogene which transforms mouse NIH3T3 ceils in cooperation with ras. Biol Chem Biophys Res Commun, 1997,231(2):509-513.
39. Taira T, Takahashi K, Kitagawa R, et al. Molecular cloning of human and mouse DJ-1 genes and identification of Spl-dependentactivationof the human DJ-1 promoter. Gene,2001,263:285-292
40. Kahle PJ, Waak J, Gasser T. DJ-1 and prevention of oxidative stress in Parkinson's disease and other age-related disorders. Free Radic Biol Med,2009, 47(10):1354-1361.
41. Marcondes AM, Li X, Gooley TA, et al. Identification of DJ-1/PARK-7 as a determinant of stroma-dependent and TNF-alpha-induced apoptosis in MDS using mass spectrometry and phosphopeptide analysis. Blood,2010,115(10): 1993-2002.
42. Yokota T, Sugawara K, Ito K, et al. Down regulation of DJ-1 enhances cell death by oxidative stress, ER stress, and proteasome inhibition. Biochem Biophys Res Commun,2003,312(4):1342-1348.
43. Mo JS, Kim MY, Anil EJ, et al. DJ-1 modulates UV induced oxidative stresssignaling through the suppression of MEKK1 and cell death. Cell d eath Difer,2008,15 (6):1030-1041.
44. Yuen HF, Chan YP, Law S, et al. DJ-1 could predict worse prognosis in esophageal squamous cell carcinoma. Cancer Epidemiol Biomarkers Prev,2008, 17(12):3593-3602.
45. Karunakaran S, Diwakar L, Saecd U, et al. Activation of apoptosis signal regulating kinase 1(ASK1) and translocation of death-associted protein, Bax, in substantia nigra pars compacta in a mouse model of Parkinson's disease: protection by alpha-lipoic acid. FASEB J,2007,21(9):2226 - 2236.
46. Bretaud S, Allen C, Ingham PW, et al. p53 - dependent neuronal cell death in a DJ-1 deficient zebrafish model of Parkinson's diseases. J Neurochem,2007, 100(6):1626-1635.
47. Fan J, Ren H, Jin N, et al. DJ-1 decreases Bax expression through repressing p53 transcriptional activity [J]. Biol Chem,2008,283(7):4022 - 4030.
48. Amouk H, Merkley MA, Podolsky RH, et al Characterization of molecular markers indicative of cervical cancer progression. Proteomics Clin Appl,2009, 3(5):516-527.
49. Liu H, Wang M, Li M, et al. Expression and role of DJ-1 in leukemia. Biochem Biophys Res Commun,2008,375 (3):477-483.
50. Zhang HY, Wang HQ, Liu HM, et al. Regulation of tumour necrosis factor-related apoptosis-inducing ligand-induced apoptosis by DJ-1 in thyroid cancer cells. Endoer Relat Cancer,2008,15(2):535-544.
51. Benio Tsuchiya, Keiichi Iwaya, Norio Kohno, et al. Clinical significance of DJ-1 as a secretory molecule:retrospective study of DJ-1 expression at mRNA and protein levels in ductal carcinoma of the breast. Histopathology,2012,10(111): 365-374
52. Prado M, Garc AA, Thomas B, et al. The characterization of the invasion phenotype of uveal melanoma tumour cells shows the presence of MUC18 and HMG metastasis markers and leads to the identification of DJ-1 as a potential serum biomarker. Int J Cancer,2006,119(5):1014-1022.
53. Lenaour F, Misek DE, Krause MC, et al. Proteomics-based identification of RS /DJ-1 as a novel circulating tumor antigen in breast cancer. Clin Cancer Res, 2001,7(11):3328-3335.
54. Haigang Ren, Kai Fu, Chenchen Mu, et al. DJ-1, a cancer and Parkinson's disease associated protein, regulates autophagy through JNK pathway in cancer cells. Cancer Letters 297:101-108
55. Mackeigan JP, Clements CM, Lich JD, et al, Proteomic profiling drug induced apoptosis in non small cell lung carcinoma:identification of DJ-1. Cancer Res, 2003,63(20):6928-6934.
56. Hua-Zong Zeng, Yi-Qing Qu, Wen-Jun Zhang, et al. Proteomic Analysis Identified DJ-1 as a Cisplatin Resistant Marker in Non-Small Cell Lung Cancer. Int. J. Mol. Sci.2011,12:3489-3499
57. Chow SN, Chen R J, Chen CH, et al. Analysis of protein profiles in human epithelial ovarian cancer tissues by proteomic technology. Eur J Gynaecol Oncol,2010,31(1):55-62.
58. Dos CG, Chhabra D, Kekic M, et al. Actin binding proteins:regulation of cytoskeletal microf ilaments. Physiological Reviews.2003,83(2):433-473.
59.赵微,苏玉虹,巴彩凤,等.Cofilin蛋白功能及活性调节.中国生物化学与分子生物学报,2007,23(9)：706-710.
60. W angW, Eddy R, Condelis J. The cofilin pathway in breast cancer invasion and metastasis. Nat Rev Cancer,2007,7(6):429-440.
61. GhoshM, Song X, Mouneimne G, et a 1. Cofilin promotes actin polymerization and defines the direction of cell motility. Science,2004,304 (5671):743-746.
62. Yamaquchi H, Lorenz M, Kempiak S, et a 1. Molecular mechanisms of in vadopodium form ation:the role of the N-WASP-A rp complex pathway and cofilin. J Cell Biol.2005,168(3):441-452.
63. Horita Y, Ohashi K, Mukai M, et al. Suppression of the invasion capacity of rat hepatoma cells by knockdown of slingshot or LIM Kinase. J Biol Chem,2008, 283(10):6013-6022.
64. Shoichi Nagai, Orlando Moreno, Christian A, et al. Role of the Cofilin Activity Cycle in Astrocytoma Migration and Invasion. Genes & Cancer/2(9): 859-869.
65. Yam H, Condeelis J. R egulat ion of the actin cytoskeleton in cancer cell migrat ion and invasion. Biochem Biophys Acta,.2007,1773(5):642-652.
66. Leong S, Mckay MJ, Christopherson RI, et al. Biomarkers of breast cancer apoptosis induced by chenmotherapy and TRAIL. J Proteome Res.2012,3 (12): 1240-1250.
67. Unwin RD, Craven RA, Harnden P, et al. Proteomic changes in renal cancer and co-ordinate demonstration of both the glycolytic and mitochondrial aspects of the Warburg effect. Proteomics.2003;3:1620-32.
68. Martoglio AM, Tom BD, Starkey M, et al. Changes in tumorigenesis-and angiogenesis-related gene transcript abundance profiles in ovarian cancer detected by tailored high density cDNA arrays. Mol Med.2000;6:750-65.
69. Turhani D, Krapfenbauer K, Thurnher D, et al. Identification of differentially expressed, tumor-associated proteins in oral squamous cell carcinoma by proteomic analysis. Electrophoresis.2006;27:1417-23.
70. Rui Wei, Yingjin Zhang, Liangfang Shen, et al. Comparative proteomic and radiobiological analyses in human lung adenocarcinoma cells. Mol Cell Biochem (2012)359:151-159.
71. Yang DY, Jiang WZ, Wei Rui. The relationship between the cisplatin resistance and the expression of confilin in lung adenocarcinom. Cancer.2010, 548:1220-1231.
72. Lee YJ, Mazzatti DJ, Yun Z, et al. Inhibition of invasiveness of human lung cancer cell line H1299 by over-expression of cofilin. Cell Biol Int. 2005;29:877-83.
73. Carolina B. Muller, Rafael L. S et al. Validation of cofilin-1 as a biomarker in non-small cell lung cancer:application of quantitative method in a retrospective cohort. J Cancer Res Clin Oncol (2011) 137:1309-1316
74. Mauro Antonio AC, Felipe Dal-Pizzolb, Stephanie Zdanovc. CFL1 expression levels as a prognostic and drug resistance marker in non small cell lung cancer. Cancer.2010 August 1; 116(15):3645-3655.
75. Yu J.-Y., DeRuiter S.L., Turner, D.L. RNA interference by expression of short-interfering RNAs and hairpin RNAs in mammalian cells. Proc Natl Acad Sci USA,2002,99(9):6047-6052.
76. Brown D, Jarvis R, Pallotta V, et al. RNA interference in mammalian cell culture:design, execution, and analysis of the siRNA effect. Ambion TechNotes 9(1):3-5.
77. Bartel DP. MicroRNAs:genomics, biogenesis, mechanism and function. Cell,2004; 116:281-297.
78. Calin GA, Croce CM. MicroRNA signatures in human cancers. Nat Rev Cancer. 2006;6:857-66.
79. Johnson SM, Grosshans H, Shingara J, et al. RAS is regulated by the let-7 microRNA family. Cell 2005;120:35-47.
80. Cimmino A, Calin GA, Fabbri M, et al. miR-15 and miR-16 induce apoptosis by targeting BCL2. Proc Natl Acad Sci U S A 2005; 102:13944-9.
81. Kovalchuk O, Fikowski J, Mwservy J, et al. Involvement of microRNA-451 in resistance of the MCF-7 breast cancer cells to chemotherapeutic drug doxorubicin. Mol Cancer Ther.2008,7(7):2152-9.
82. Tsang WP, Kwok TT. Let-7a microRNA suppresses therapeutics-induced cancer cell death by targeting caspase-3. Apoptosis.2008,13(10):1215-22.
83. Fronari F, Gramantieri L, Giovannini C, et al. MiR-122/Cyclin G1 Interaction Modulates p53 Activity and Affects Doxorubicin Sensitivity of Human Hepatocarcinoma Cells. Cancer res.2009,69(14):5761-7.
84. Weiss GJ, Bemis LT, Nakajiama E, et al. EGFR regulation by microRNA in lung cancer:correlation with clinical response and survival to gefitinib and EGFR expression in cell lines. Ann Oncol.2008,19(6):1053-9.
85. Valeri N, Gasparini P, Braconi C, MicroRNA-21 induces resistance to 5-fluorouracil by down-regulating human DNA MutS homolog 2 (hMSH2). Proc Natl Acad Sci U S A 2010; 107:21098-103.
86. Yang H, Kong W, He L, et al. MicroRNA expression profiling in human ovarian cancer:miR-214 induces cell survival and cisplatin resistance by targeting PTEN. Cancer Res 2008;68:425-33.
87. Voorhoeve PM, le Sage C, Schrier M, et al. A genetic screen implicates siRNA-372 and miRNA-373 as oncogenes in testicular germ cell tumors. Cell 2006; 124:1169-81.
88. Mueller DW, Bosserhoff AK. MicroRNA miR-196a controls melanoma-associated genes by regulating HOX-C8 expression. Int J Cancer 2011;129:1064-74.
89. Calin GA, Sevignani C, Dumitru CD, et al. Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers. ProcNatl Acad Sci USA,2004; 101:2999-3004.
90. Hua-Zong Zeng, Yi-Qing Qu, Wen-Jun Zhang, et al. Proteomic Analysis Identified DJ-1 as a Cisplatin Resistant Marker in Non-Small Cell Lung Cancer. Int. J. Mol. Sci.2011,12:3489-3499
1. NCCN Clinical Practice Guidline in Oncology:Small Cell Lung Cancer Vision 1,2008.
2. Jemal A, Siegel R, Ward E, et al. Cancer statistics,2009 CA Cancer J Clin,2009, 59:225-249.
3. Hechi SS, Biochemitry, biology, and carcinogenicity of tobacco-specific N-nitrosamines. Chem Res Toxicol,1998,11:559-603.
4. Travis.2004. Pathlogy and Genetics of Tumors of the Lung, Pleura, Thymus and Heart. Lyon IARC Press,15-30.
5. Govindan R, Page N, Morgensztern D, et al. Changing epidemiology of small cell lung cancer in the United States over the lase 30 years analysis of the surviveillance. epidemiologyic, and end results database. J Clin Oncol, 2006,24:4539-4544.
6. Sethi T, Rintoul RC, Moore SM, et al. Extracellulae matrix proteins protect small cell lung cancer cells against:a mechanism for small cell lung cancer growth and drug resistance in vivo. Nat Med.1999,5:662-668.
7. Mason EF, Zhao Y, Goraksha-Hicks P, et al. Aerobic glycolysis suppresses p53 activity to provide selective protection from apoptosis upon loss of growth signals or inhibition of BCR-Abl. Cancer Res,2010,70(20):8066-8076.
8. Tsuruo T, Nato M, Tomida A, et al. Molecular targeting therapy of cancer; drug resistance, apoptosis and survival signa. Cancer Sci,2003,94(1):1-15.
9. Ruiz Gomez MJ, Souviron RA, Morillo M. P-glycoprotein, a membrane pump that represent a barrier to chemotherapy in cancer patients. An Med Interna,2002, 19(9):477-485.
10. Eid H, Mingfang L, Institoris E, et al. Mrp expression of testicular cancer and its clinical relevance. Anticancer Res,2000,20(5):4019-4022.
11. Izquierdo MA, Shoemaker RH, Flens MJ, et al. Overlapping phenotypes of multidrug resistance among panels human cancer cell lines. Int J Cancer,1996, 65(2):230-237.
12. Hodkinson PS, Mackinnon AC, Sethie T. Extracellular matrix regulation of drug resistance in small-cell lung. Int J Radiat Biol,2007,83(11):733-741.
13. Goto S, Kamada K, Soh Y, et al. Significance of nuclear glutathione S-transferase pi in resistance to anti-cancer drugs. Jpn J Cancer Res, 2002,93(9):1047-1056.
14. Kohmo S, Kijima T, Otani Y, et al. Cell surface tetraspanin CD9 mediates chemoresistance in small cell lung cancer. Cancer Res,2010,70(20): 8025-8035.
15. Mason EF, Zhao Y, Goraksha-Hicks P, et al. Aerobic glycolysis suppresses p53 activity to provide selective protection from apoptosis upon loss of growth signals or inhibition of BCR-Abl. Cancer Res,2010,70(20):8066-8076.
16. Sartorius UA, Krammer PH. Upregulation of Bcl-2 is involved in the mediation of chemotherapy resistance in human small cell lung cancer cell lines. Int J Cancer,2002,97(5):584-592.
17. Linlang Guo, Yongguang Liu, Yifeng Bai, et al. Gene expression profiling of drug-resistant small cell lung cancer cells by combining microRNA and cDNA expression analysis. European Journal of Cancer,2010,46:1692-1702.
18. Faman Xiao, Yifeng Bai, Linlang Guo, et al. HOXA1 is involed in multi-drug resistance of small cell lung cancer. European Journal of Cancer,2013, 68:1150-1202.
19. Yuanyuan Zhou, Yanqin Sun, Linlang Guo, The Apoptosis Regulation Mechanism of Protein-tyrosin Kinase Etk and Drug Resistance Studying on Tumors Chemotherapy in Small Cell Lung Cancer. BMJ,2009,45:1452-1463
20. Yeh JJ, Hsu NY, Hsu WH, et al. Comparison of chemotherapy response with P-glycoprotein, multidrug resistance-related protein, and lung resistance-related protein expression in untreated small cell lung cancer. Lung,2005,183(3): 177-183.
21.关俊明,闫玉生,郭琳琅,等.人小细胞肺癌细胞新耐药基因的探索. 广 东医学,2011,32(8)：999-1001.
22. Song Y, Qi Y, Zhang W, et al. Evolutionary trace analysis of eukaryotic DNA topoisomerase I superfamily:identification of novel antitumor drug binding site. Sci China C Life Sci,2005,48(4):375-384.
23. Pectasides D, Samantas E, Fountzilas G, et al. Combination chemotherapy with cisplatin, etoposide and irinotecan in patients with extensive small cell lung cancer:A phase II study of the Hellenic Co2 operative Oncology Group. Lung Cancer,2007,58(3):355-361.
24. Knez L, Sodja E, Kern I, et al. Predictive value of multidrug resistance proteins, topoisomerases II and ERCC1 in small cell lung cancer:a systematic review. Lung Cancer,2011,72(3):271-279.
25. Lawson MH, Cummings NM, Rassl DM, et al. Two novel determinants of Etoposide resistance in small cell lung cancer. Cancer Res,2011,71 (14): 4877-4887.
26. Morimoto H, Tsukada J, Kominato Y, et al. Reduced expression of human mismatch repair genes in adult T-cell leukemia. Am J He-mato,2005,78(2): 100-107.
27. Wilkins MR, Sanchez JC, Cooley AA. et al. Progress with proteome projects: why all proteins expressed by a genome should be identified and how to do it. Biotechnol Genet Eng Rev,1996.13(1):19-50.
28. Alfonso P, Catala M, Rico—Morales M L, et al. Proteomic analysis of lung biopsies:differential protein expression profile between peritum oral and tumoral tissue. Proteomies,2004,4(2):442-447.
29. Liotta LA, Kohn EC 。Petricoin EF. Clinical promeoties:personalized molecular medicine. JAMA,2001,286(18):2211-2214.
30. WuX, Xiao Z, Chen Z, et al. Differential analysis of two—dim ension gel electrOphOresis profiles from the norm al—m etaplasial-dysplasia-carcinoma tissue of human bronchial epithelium. Pathol Int,2004,54(10):765-773.
31. Ying W, Zhang K. Qian X, et al. Proteome analysis on an early transformed human bronchial epithelial cell line, BEP2D, after alpha particle irradiation. Proteom ics,2003,3(1):64-72.
32. He QY, Yip TT, Li M。et al. Proteomic analysis of arsenic— induced cell transformation with SEI DI—TOF protein chip technology. J Cell Biochem.2003,88(1):1-8.
33. Zhukov TA, Johanson RA, Cantor AB, et al. Discovery of distinct protein profiles specific for lung tumors and premalignantlung lesions by SELDI—M S. Lung Cancer.2003,40(3):267-279.
34. Yang SY, Xiao XY, Zhang W G, et al. Application of serum surface-enhanced laser desorption ionization proteomic patterns in distinguishing small cell lung cancer patients from healthy people. Chin Med J,2005,118(12): 1036-1039.
35. Chen G, Charib TG, H uang CC, et al. Proteomic analysis of lung adenocarcinoma:identification of highly expressed set of proteins in tumors. Clin Cancer Res,2002,8(7):2298-2305.
36. Chuman Y, Bergman A, Ueno T, et al. NapsinA, a m ember of the aspartic protease family, is abundantly expressed in normal lung and kidney tissue and is expressed in lung adenocarcinomas. FEBS Lett,1999,462(1-2):129-134.
37. Macid CM, Paschoal M E, Kawamur M T, et al. Serum protein profiling of lung cancer patients. J Exp Ther Oncol,2004,4(4):327-334.
38. Cicek M, Samant RS, Kinter M, et al. Identification of metastasis associated proteins through protein analysis of metastatic M DA—MB-435 and M etastasis suppressed BRM S1 transfected—M DA—M B-435 cells. Clin Exp M etastasis,2004.21(2):149-157.
39. Chang JW, Jeon HB, Lee JH, et al. Augmented expression of peroxiredoxin I in lung cancer. Biochem Biophy Res Commun,2001,289(2):507-512.
40. Yanagiswa K, Shyr Y, Xu BJ, et al. Proteomic patterns of tumor subsets in non-sm all cell lung cancer. Lancet,2003.362(9382):433-439.
41. Hua-Zong Zeng, Yi-Qing Qu, Wen-Jun Zhang, et al. Proteomic Analysis Identified DJ-1 as a Cisplatin Resistant Marker in Non-Small Cell Lung Cancer. Int. J. Mol. Sci.2011,12:3489-3499
2. Jemal A, Siegel R, Ward E, et al. Cancer stastistics,2009 CA Cancer J Clin,2009, 59:225-249.
3. Hechi SS, Biochemitry, biology, and carcinogenicity of tobacco-specific N-nitrosamines. Chem Res Toxicol,1998,11:559-603.
4. Travis.2004. Pathlogy and Genetics of Tumors of the Lung, Pleura, Thymus and Heart. Lyon IARC Press,15-30.
5. Govindan R, Page N, Morgensztern D, et al. Changing epidemiology of small cell lung cancer in the United States over the lase 30 years analysis of the surviveillance. epidemiologyic, and end results database. J Clin Oncol, 2006,24:4539-4544.
6. Sethi T, Rintoul RC, Moore SM, et al. Extracellulae matrix proteins protect small cell lung cancer cells against:a mechanism for small cell lung cancer growth and drug resistance in vivo. Nat Med.1999,5:662-668.
7. Kim R,Tanabe K,Emi M,et al.Modulation of tamoxifen sensitivity by antisense Bcl-2 and trastuzumab in breast carcinoma cells.Cancer,2005,103 (10): 2199-2207.
8. Tsuruo T, Nato M, Tomida A, et al. Molecular targeting therapy of cancer; drug resistance, apoptosis and survival signa. Cancer Sci,2003,94(1):1-15.
9. Ruiz Gomez MJ, Souviron RA, Morillo M. P-glycoprotein, a membrane pump that represent a barrier to chemotherapy in cancer patients. An Med Interna,2002, 19(9):477-485.
10. Eid H, Mingfang L, Institoris E, et al. Mrp expression of testicular cancer and its clinical relevance. Anticancer Res,2000,20(5):4019-4022.
11. Izquierdo MA, Shoemaker RH, Flens MJ, et al. Overlapping phenotypes of multidrug resistance among panels human cancer cell lines. Int J Cancer,1996, 65(2):230-237.
12. Goto S, Kamada K, Soh Y, et al. Significance of nuclear glutathione S-transferase pi in resistance to anti-cancer drugs. Jpn J Cancer Res, 2002,93(9):1047-1056.
13. Goto S, Kamada K, Soh Y, et al. Significance of nuclear glutathione S-transferase pi in resistance to anti-cancer drugs. Jpn J Cancer Res, 2002,93(9):1047-1056.
14. Kohmo S, Kijima T, Otani Y, et al. Cell surface tetraspanin CD9 mediates chemoresistance in small cell lung cancer. Cancer Res,2010,70(20): 8025-8035.
15. Mason EF, Zhao Y, Goraksha-Hicks P, et al. Aerobic glycolysis suppresses p53 activity to provide selective protection from apoptosis upon loss of growth signals or inhibition of BCR-Abl. Cancer Res,2010,70(20):8066-8076.
16. Sartorius UA, Krammer PH. Upregulation of Bcl-2 is involved in the mediation of chemotherapy resistance in human small cell lung cancer cell lines. Int J Cancer,2002,97(5):584-592.
17. Linlang Guo, Yongguang Liu, Yifeng Bai, et al. Gene expression profiling of drug-resistant small cell lung cancer cells by combining microRNA and cDNA expression analysis. European Journal of Cancer,2010,46:1692-1702.
18. Faman Xiao, Yifeng Bai, Linlang Guo, et al. HOXA1 is involed in multi-drug resistance of small cell lung cancer. European Journal of Cancer,2013, 68:1150-1202.
19. Yuanyuan Zhou, Yanqin Sun, Linlang Guo, The Apoptosis Regulation Mechanism of Protein-tyrosin Kinase Etk and Drug Resistance Studying on Tumors Chemotherapy in Small Cell Lung Cancer. BMJ,2009,45:1452-1463
20. Yeh JJ, Hsu NY, Hsu WH, et al. Comparison of chemotherapy response with P-glycoprotein, multidrug resistance-related protein, and lung resistance-related protein expression in untreated small cell lung cancer. Lung,2005,183(3): 177-183.
21.关俊明,闫玉生,郭琳琅,等. 人小细胞肺癌细胞新耐药基因的探索. 广东医学,2011,32(8)：999-1001.
22. Song Y, Qi Y, Zhang W, et al. Evolutionary trace analysis of eukaryotic DNA topoisomerase I superfamily:identification of novel antitumor drug binding site. Sci China C Life Sci,2005,48(4):375-384.
23. Pectasides D, Samantas E, Fountzilas G, et al. Combination chemotherapy with cisplatin, etoposide and irinotecan in patients with extensive small cell lung cancer:A phase II study of the Hellenic Co2 operative Oncology Group. Lung Cancer,2007,58(3):355-361.
24. Knez L, Sodja E, Kern I, et al. Predictive value of multidrug resistance proteins, topoisomerases II and ERCC1 in small cell lung cancer:a systematic review. Lung Cancer,2011,72 (3):271-279.
25. Lawson MH, Cummings NM, Rassl DM, et al. Two novel determinants of Etoposide resistance in small cell lung cancer. Cancer Res,2011,71(14): 4877-4887.
26. Morimoto H, Tsukada J, Kominato Y, et al. Reduced expression of human mismatch repair genes in adult T-cell leukemia. Am J He-mato,2005,78(2): 100-107.
27. Gong, F.; Peng, X.; Zeng, Z.et al. Proteomic analysis of cisplatin resistance in human ovarian cancer using 2-DE method. Mol. Cell. Biochem.2011,348, 141-147.
28. Li, SL.; Ye, F, Cai, WJ, et al. Quantitative proteome analysis of multidrug resistance in human ovarian cancer cell line. J. Cell. Biochem.2010,109, 625-633.
29. Pazos F, Steinberg MJ. Automated prediction of protein function and detection of functional sites from structure. Proe Natl Acad Sci,2010,101:14754-14759.
30. Wilkins MR, Sanchez JC, Cooley AA. et al. Progress with proteome projects: why all proteins expressed by a genome should be identified and how to do it. Biotechnol Genet Eng Rev,1996.13(1):19-50.
31.李国庆,肖哲锋,刘健平,等.肿瘤：一种蛋白质组病.中国科学.生命科学,2010,40(9)：788-794.
32. Smith-Beckerman DM, Fung KW, Williams KE, et al. Proteome changes in ovarian epithelial cells derived from women with BRCA1 mutations and family histories of cancer. Mol Cell Proteomics.2005;4:156-68.
33. Keshamouni VG, Michailidis G, Grasso CS, et al. Differential protein expression profiling by iTRAQ-2DLC-MS/MS of lung cancer cells undergoing epithelial-mesenchymal transition reveals a migratory/invasive phenotype. J Proteome Res.2006;5:1143-54.
34. W u X, Xiao Z, Chen Z, et al. Differential analysis of two-dimension gel electrOphOresis profiles from the normal, metaplasial, dysplasia and carcinoma tissue of human bronchial epithelium. Pathol Int,2004,54(10):765-773.
35. Cicek M, Samant RS, Kinter M, et al. Identification of metastasis associated proteins through protein analysis of metastatic M DA—MB-435 and M etastasis suppressed BRM S1 transfected—M DA—M B-435 cells. Clin Exp M etastasis, 2004.21(2):149-157.
36. Chang JW, Jeon HB, Lee JH, et al. Augmented expression of peroxiredoxin I in lung cancer. Biochem Biophy Res Commun,2001,289(2):507-512.
37. Yanagiswa K, Shyr Y, Xu BJ, et al. Proteomic patterns of tumor subsets in non-sm all cell lung cancer. Lancet,2003.362(9382):433-439.
38. Nagakubo D, Taira T, Kitaura H, et al. DJ-1, a novel oncogene which transforms mouse NIH3T3 ceils in cooperation with ras. Biol Chem Biophys Res Commun, 1997,231(2):509-513.
39. Taira T, Takahashi K, Kitagawa R, et al. Molecular cloning of human and mouse DJ-1 genes and identification of Spl-dependentactivationof the human DJ-1 promoter. Gene,2001,263:285-292
40. Kahle PJ, Waak J, Gasser T. DJ-1 and prevention of oxidative stress in Parkinson's disease and other age-related disorders. Free Radic Biol Med,2009, 47(10):1354-1361.
41. Marcondes AM, Li X, Gooley TA, et al. Identification of DJ-1/PARK-7 as a determinant of stroma-dependent and TNF-alpha-induced apoptosis in MDS using mass spectrometry and phosphopeptide analysis. Blood,2010,115(10): 1993-2002.
42. Yokota T, Sugawara K, Ito K, et al. Down regulation of DJ-1 enhances cell death by oxidative stress, ER stress, and proteasome inhibition. Biochem Biophys Res Commun,2003,312(4):1342-1348.
43. Mo JS, Kim MY, Anil EJ, et al. DJ-1 modulates UV induced oxidative stresssignaling through the suppression of MEKK1 and cell death. Cell d eath Difer,2008,15 (6):1030-1041.
44. Yuen HF, Chan YP, Law S, et al. DJ-1 could predict worse prognosis in esophageal squamous cell carcinoma. Cancer Epidemiol Biomarkers Prev,2008, 17(12):3593-3602.
45. Karunakaran S, Diwakar L, Saecd U, et al. Activation of apoptosis signal regulating kinase 1(ASK1) and translocation of death-associted protein, Bax, in substantia nigra pars compacta in a mouse model of Parkinson's disease: protection by alpha-lipoic acid. FASEB J,2007,21(9):2226 - 2236.
46. Bretaud S, Allen C, Ingham PW, et al. p53 - dependent neuronal cell death in a DJ-1 deficient zebrafish model of Parkinson's diseases. J Neurochem,2007, 100(6):1626-1635.
47. Fan J, Ren H, Jin N, et al. DJ-1 decreases Bax expression through repressing p53 transcriptional activity [J]. Biol Chem,2008,283(7):4022 - 4030.
48. Amouk H, Merkley MA, Podolsky RH, et al Characterization of molecular markers indicative of cervical cancer progression. Proteomics Clin Appl,2009, 3(5):516-527.
49. Liu H, Wang M, Li M, et al. Expression and role of DJ-1 in leukemia. Biochem Biophys Res Commun,2008,375 (3):477-483.
50. Zhang HY, Wang HQ, Liu HM, et al. Regulation of tumour necrosis factor-related apoptosis-inducing ligand-induced apoptosis by DJ-1 in thyroid cancer cells. Endoer Relat Cancer,2008,15(2):535-544.
51. Benio Tsuchiya, Keiichi Iwaya, Norio Kohno, et al. Clinical significance of DJ-1 as a secretory molecule:retrospective study of DJ-1 expression at mRNA and protein levels in ductal carcinoma of the breast. Histopathology,2012,10(111): 365-374
52. Prado M, Garc AA, Thomas B, et al. The characterization of the invasion phenotype of uveal melanoma tumour cells shows the presence of MUC18 and HMG metastasis markers and leads to the identification of DJ-1 as a potential serum biomarker. Int J Cancer,2006,119(5):1014-1022.
53. Lenaour F, Misek DE, Krause MC, et al. Proteomics-based identification of RS /DJ-1 as a novel circulating tumor antigen in breast cancer. Clin Cancer Res, 2001,7(11):3328-3335.
54. Haigang Ren, Kai Fu, Chenchen Mu, et al. DJ-1, a cancer and Parkinson's disease associated protein, regulates autophagy through JNK pathway in cancer cells. Cancer Letters 297:101-108
55. Mackeigan JP, Clements CM, Lich JD, et al, Proteomic profiling drug induced apoptosis in non small cell lung carcinoma:identification of DJ-1. Cancer Res, 2003,63(20):6928-6934.
56. Hua-Zong Zeng, Yi-Qing Qu, Wen-Jun Zhang, et al. Proteomic Analysis Identified DJ-1 as a Cisplatin Resistant Marker in Non-Small Cell Lung Cancer. Int. J. Mol. Sci.2011,12:3489-3499
57. Chow SN, Chen R J, Chen CH, et al. Analysis of protein profiles in human epithelial ovarian cancer tissues by proteomic technology. Eur J Gynaecol Oncol,2010,31(1):55-62.
58. Dos CG, Chhabra D, Kekic M, et al. Actin binding proteins:regulation of cytoskeletal microf ilaments. Physiological Reviews.2003,83(2):433-473.
59.赵微,苏玉虹,巴彩凤,等.Cofilin蛋白功能及活性调节.中国生物化学与分子生物学报,2007,23(9)：706-710.
60. W angW, Eddy R, Condelis J. The cofilin pathway in breast cancer invasion and metastasis. Nat Rev Cancer,2007,7(6):429-440.
61. GhoshM, Song X, Mouneimne G, et a 1. Cofilin promotes actin polymerization and defines the direction of cell motility. Science,2004,304 (5671):743-746.
62. Yamaquchi H, Lorenz M, Kempiak S, et a 1. Molecular mechanisms of in vadopodium form ation:the role of the N-WASP-A rp complex pathway and cofilin. J Cell Biol.2005,168(3):441-452.
63. Horita Y, Ohashi K, Mukai M, et al. Suppression of the invasion capacity of rat hepatoma cells by knockdown of slingshot or LIM Kinase. J Biol Chem,2008, 283(10):6013-6022.
64. Shoichi Nagai, Orlando Moreno, Christian A, et al. Role of the Cofilin Activity Cycle in Astrocytoma Migration and Invasion. Genes & Cancer/2(9): 859-869.
65. Yam H, Condeelis J. R egulat ion of the actin cytoskeleton in cancer cell migrat ion and invasion. Biochem Biophys Acta,.2007,1773(5):642-652.
66. Leong S, Mckay MJ, Christopherson RI, et al. Biomarkers of breast cancer apoptosis induced by chenmotherapy and TRAIL. J Proteome Res.2012,3 (12): 1240-1250.
67. Unwin RD, Craven RA, Harnden P, et al. Proteomic changes in renal cancer and co-ordinate demonstration of both the glycolytic and mitochondrial aspects of the Warburg effect. Proteomics.2003;3:1620-32.
68. Martoglio AM, Tom BD, Starkey M, et al. Changes in tumorigenesis-and angiogenesis-related gene transcript abundance profiles in ovarian cancer detected by tailored high density cDNA arrays. Mol Med.2000;6:750-65.
69. Turhani D, Krapfenbauer K, Thurnher D, et al. Identification of differentially expressed, tumor-associated proteins in oral squamous cell carcinoma by proteomic analysis. Electrophoresis.2006;27:1417-23.
70. Rui Wei, Yingjin Zhang, Liangfang Shen, et al. Comparative proteomic and radiobiological analyses in human lung adenocarcinoma cells. Mol Cell Biochem (2012)359:151-159.
71. Yang DY, Jiang WZ, Wei Rui. The relationship between the cisplatin resistance and the expression of confilin in lung adenocarcinom. Cancer.2010, 548:1220-1231.
72. Lee YJ, Mazzatti DJ, Yun Z, et al. Inhibition of invasiveness of human lung cancer cell line H1299 by over-expression of cofilin. Cell Biol Int. 2005;29:877-83.
73. Carolina B. Muller, Rafael L. S et al. Validation of cofilin-1 as a biomarker in non-small cell lung cancer:application of quantitative method in a retrospective cohort. J Cancer Res Clin Oncol (2011) 137:1309-1316
74. Mauro Antonio AC, Felipe Dal-Pizzolb, Stephanie Zdanovc. CFL1 expression levels as a prognostic and drug resistance marker in non small cell lung cancer. Cancer.2010 August 1; 116(15):3645-3655.
75. Yu J.-Y., DeRuiter S.L., Turner, D.L. RNA interference by expression of short-interfering RNAs and hairpin RNAs in mammalian cells. Proc Natl Acad Sci USA,2002,99(9):6047-6052.
76. Brown D, Jarvis R, Pallotta V, et al. RNA interference in mammalian cell culture:design, execution, and analysis of the siRNA effect. Ambion TechNotes 9(1):3-5.
77. Bartel DP. MicroRNAs:genomics, biogenesis, mechanism and function. Cell,2004; 116:281-297.
78. Calin GA, Croce CM. MicroRNA signatures in human cancers. Nat Rev Cancer. 2006;6:857-66.
79. Johnson SM, Grosshans H, Shingara J, et al. RAS is regulated by the let-7 microRNA family. Cell 2005;120:35-47.
80. Cimmino A, Calin GA, Fabbri M, et al. miR-15 and miR-16 induce apoptosis by targeting BCL2. Proc Natl Acad Sci U S A 2005; 102:13944-9.
81. Kovalchuk O, Fikowski J, Mwservy J, et al. Involvement of microRNA-451 in resistance of the MCF-7 breast cancer cells to chemotherapeutic drug doxorubicin. Mol Cancer Ther.2008,7(7):2152-9.
82. Tsang WP, Kwok TT. Let-7a microRNA suppresses therapeutics-induced cancer cell death by targeting caspase-3. Apoptosis.2008,13(10):1215-22.
83. Fronari F, Gramantieri L, Giovannini C, et al. MiR-122/Cyclin G1 Interaction Modulates p53 Activity and Affects Doxorubicin Sensitivity of Human Hepatocarcinoma Cells. Cancer res.2009,69(14):5761-7.
84. Weiss GJ, Bemis LT, Nakajiama E, et al. EGFR regulation by microRNA in lung cancer:correlation with clinical response and survival to gefitinib and EGFR expression in cell lines. Ann Oncol.2008,19(6):1053-9.
85. Valeri N, Gasparini P, Braconi C, MicroRNA-21 induces resistance to 5-fluorouracil by down-regulating human DNA MutS homolog 2 (hMSH2). Proc Natl Acad Sci U S A 2010; 107:21098-103.
86. Yang H, Kong W, He L, et al. MicroRNA expression profiling in human ovarian cancer:miR-214 induces cell survival and cisplatin resistance by targeting PTEN. Cancer Res 2008;68:425-33.
87. Voorhoeve PM, le Sage C, Schrier M, et al. A genetic screen implicates siRNA-372 and miRNA-373 as oncogenes in testicular germ cell tumors. Cell 2006; 124:1169-81.
88. Mueller DW, Bosserhoff AK. MicroRNA miR-196a controls melanoma-associated genes by regulating HOX-C8 expression. Int J Cancer 2011;129:1064-74.
89. Calin GA, Sevignani C, Dumitru CD, et al. Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers. ProcNatl Acad Sci USA,2004; 101:2999-3004.
90. Hua-Zong Zeng, Yi-Qing Qu, Wen-Jun Zhang, et al. Proteomic Analysis Identified DJ-1 as a Cisplatin Resistant Marker in Non-Small Cell Lung Cancer. Int. J. Mol. Sci.2011,12:3489-3499
1. NCCN Clinical Practice Guidline in Oncology:Small Cell Lung Cancer Vision 1,2008.
2. Jemal A, Siegel R, Ward E, et al. Cancer statistics,2009 CA Cancer J Clin,2009, 59:225-249.
3. Hechi SS, Biochemitry, biology, and carcinogenicity of tobacco-specific N-nitrosamines. Chem Res Toxicol,1998,11:559-603.
4. Travis.2004. Pathlogy and Genetics of Tumors of the Lung, Pleura, Thymus and Heart. Lyon IARC Press,15-30.
5. Govindan R, Page N, Morgensztern D, et al. Changing epidemiology of small cell lung cancer in the United States over the lase 30 years analysis of the surviveillance. epidemiologyic, and end results database. J Clin Oncol, 2006,24:4539-4544.
6. Sethi T, Rintoul RC, Moore SM, et al. Extracellulae matrix proteins protect small cell lung cancer cells against:a mechanism for small cell lung cancer growth and drug resistance in vivo. Nat Med.1999,5:662-668.
7. Mason EF, Zhao Y, Goraksha-Hicks P, et al. Aerobic glycolysis suppresses p53 activity to provide selective protection from apoptosis upon loss of growth signals or inhibition of BCR-Abl. Cancer Res,2010,70(20):8066-8076.
8. Tsuruo T, Nato M, Tomida A, et al. Molecular targeting therapy of cancer; drug resistance, apoptosis and survival signa. Cancer Sci,2003,94(1):1-15.
9. Ruiz Gomez MJ, Souviron RA, Morillo M. P-glycoprotein, a membrane pump that represent a barrier to chemotherapy in cancer patients. An Med Interna,2002, 19(9):477-485.
10. Eid H, Mingfang L, Institoris E, et al. Mrp expression of testicular cancer and its clinical relevance. Anticancer Res,2000,20(5):4019-4022.
11. Izquierdo MA, Shoemaker RH, Flens MJ, et al. Overlapping phenotypes of multidrug resistance among panels human cancer cell lines. Int J Cancer,1996, 65(2):230-237.
12. Hodkinson PS, Mackinnon AC, Sethie T. Extracellular matrix regulation of drug resistance in small-cell lung. Int J Radiat Biol,2007,83(11):733-741.
13. Goto S, Kamada K, Soh Y, et al. Significance of nuclear glutathione S-transferase pi in resistance to anti-cancer drugs. Jpn J Cancer Res, 2002,93(9):1047-1056.
14. Kohmo S, Kijima T, Otani Y, et al. Cell surface tetraspanin CD9 mediates chemoresistance in small cell lung cancer. Cancer Res,2010,70(20): 8025-8035.
15. Mason EF, Zhao Y, Goraksha-Hicks P, et al. Aerobic glycolysis suppresses p53 activity to provide selective protection from apoptosis upon loss of growth signals or inhibition of BCR-Abl. Cancer Res,2010,70(20):8066-8076.
16. Sartorius UA, Krammer PH. Upregulation of Bcl-2 is involved in the mediation of chemotherapy resistance in human small cell lung cancer cell lines. Int J Cancer,2002,97(5):584-592.
17. Linlang Guo, Yongguang Liu, Yifeng Bai, et al. Gene expression profiling of drug-resistant small cell lung cancer cells by combining microRNA and cDNA expression analysis. European Journal of Cancer,2010,46:1692-1702.
18. Faman Xiao, Yifeng Bai, Linlang Guo, et al. HOXA1 is involed in multi-drug resistance of small cell lung cancer. European Journal of Cancer,2013, 68:1150-1202.
19. Yuanyuan Zhou, Yanqin Sun, Linlang Guo, The Apoptosis Regulation Mechanism of Protein-tyrosin Kinase Etk and Drug Resistance Studying on Tumors Chemotherapy in Small Cell Lung Cancer. BMJ,2009,45:1452-1463
20. Yeh JJ, Hsu NY, Hsu WH, et al. Comparison of chemotherapy response with P-glycoprotein, multidrug resistance-related protein, and lung resistance-related protein expression in untreated small cell lung cancer. Lung,2005,183(3): 177-183.
21.关俊明,闫玉生,郭琳琅,等.人小细胞肺癌细胞新耐药基因的探索. 广 东医学,2011,32(8)：999-1001.
22. Song Y, Qi Y, Zhang W, et al. Evolutionary trace analysis of eukaryotic DNA topoisomerase I superfamily:identification of novel antitumor drug binding site. Sci China C Life Sci,2005,48(4):375-384.
23. Pectasides D, Samantas E, Fountzilas G, et al. Combination chemotherapy with cisplatin, etoposide and irinotecan in patients with extensive small cell lung cancer:A phase II study of the Hellenic Co2 operative Oncology Group. Lung Cancer,2007,58(3):355-361.
24. Knez L, Sodja E, Kern I, et al. Predictive value of multidrug resistance proteins, topoisomerases II and ERCC1 in small cell lung cancer:a systematic review. Lung Cancer,2011,72(3):271-279.
25. Lawson MH, Cummings NM, Rassl DM, et al. Two novel determinants of Etoposide resistance in small cell lung cancer. Cancer Res,2011,71 (14): 4877-4887.
26. Morimoto H, Tsukada J, Kominato Y, et al. Reduced expression of human mismatch repair genes in adult T-cell leukemia. Am J He-mato,2005,78(2): 100-107.
27. Wilkins MR, Sanchez JC, Cooley AA. et al. Progress with proteome projects: why all proteins expressed by a genome should be identified and how to do it. Biotechnol Genet Eng Rev,1996.13(1):19-50.
28. Alfonso P, Catala M, Rico—Morales M L, et al. Proteomic analysis of lung biopsies:differential protein expression profile between peritum oral and tumoral tissue. Proteomies,2004,4(2):442-447.
29. Liotta LA, Kohn EC 。Petricoin EF. Clinical promeoties:personalized molecular medicine. JAMA,2001,286(18):2211-2214.
30. WuX, Xiao Z, Chen Z, et al. Differential analysis of two—dim ension gel electrOphOresis profiles from the norm al—m etaplasial-dysplasia-carcinoma tissue of human bronchial epithelium. Pathol Int,2004,54(10):765-773.
31. Ying W, Zhang K. Qian X, et al. Proteome analysis on an early transformed human bronchial epithelial cell line, BEP2D, after alpha particle irradiation. Proteom ics,2003,3(1):64-72.
32. He QY, Yip TT, Li M。et al. Proteomic analysis of arsenic— induced cell transformation with SEI DI—TOF protein chip technology. J Cell Biochem.2003,88(1):1-8.
33. Zhukov TA, Johanson RA, Cantor AB, et al. Discovery of distinct protein profiles specific for lung tumors and premalignantlung lesions by SELDI—M S. Lung Cancer.2003,40(3):267-279.
34. Yang SY, Xiao XY, Zhang W G, et al. Application of serum surface-enhanced laser desorption ionization proteomic patterns in distinguishing small cell lung cancer patients from healthy people. Chin Med J,2005,118(12): 1036-1039.
35. Chen G, Charib TG, H uang CC, et al. Proteomic analysis of lung adenocarcinoma:identification of highly expressed set of proteins in tumors. Clin Cancer Res,2002,8(7):2298-2305.
36. Chuman Y, Bergman A, Ueno T, et al. NapsinA, a m ember of the aspartic protease family, is abundantly expressed in normal lung and kidney tissue and is expressed in lung adenocarcinomas. FEBS Lett,1999,462(1-2):129-134.
37. Macid CM, Paschoal M E, Kawamur M T, et al. Serum protein profiling of lung cancer patients. J Exp Ther Oncol,2004,4(4):327-334.
38. Cicek M, Samant RS, Kinter M, et al. Identification of metastasis associated proteins through protein analysis of metastatic M DA—MB-435 and M etastasis suppressed BRM S1 transfected—M DA—M B-435 cells. Clin Exp M etastasis,2004.21(2):149-157.
39. Chang JW, Jeon HB, Lee JH, et al. Augmented expression of peroxiredoxin I in lung cancer. Biochem Biophy Res Commun,2001,289(2):507-512.
40. Yanagiswa K, Shyr Y, Xu BJ, et al. Proteomic patterns of tumor subsets in non-sm all cell lung cancer. Lancet,2003.362(9382):433-439.
41. Hua-Zong Zeng, Yi-Qing Qu, Wen-Jun Zhang, et al. Proteomic Analysis Identified DJ-1 as a Cisplatin Resistant Marker in Non-Small Cell Lung Cancer. Int. J. Mol. Sci.2011,12:3489-3499
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