采用全基因组表达谱芯片筛选肺腺癌TNM分期标志基因的实验研究
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摘要
背景:
肺癌是世界范围内癌症致死中最常见的原因,其主要由非小细胞肺癌(Non-small cell lung cancer,NSCLC)组成(占80%),肺腺癌是NSCLC中的最主要的组织类型。尽管手术切除后肺癌患者的治疗得到了提高(如辅助治疗)和针对转移采用更有效的治疗(如分子靶向治疗),但是肺癌的治愈率仍然很低。正如其他实体瘤一样,肺癌是经过长期的遗传和后生的改变而形成的。发掘肺癌新的预后标志物、预测标志物或开发新的检测工具是癌症研究的主要领域之一。然而,肺癌的发生是一个多因素过程且具有疾病遗传异质性的特点,仅仅检测一个或一些基因是不够的,全基因组分析将更有效的解释肺癌的复杂性。近年来,基因芯片技术以其高通量平行检测的优势使我们能从基因组范围内对组织细胞的基因表达谱进行研究,为研究肿瘤发生发展中多基因改变的分子机制提供了有力的工具。
目的:
通过比较肺腺癌不同TNM分期的手术组织标本的基因表达差异,筛选肺腺癌各TNM分期中的标志基因;对显著差异基因在mRNA水平上进行RT-PCR技术验证,并分析其与临床病理因素的关系。
方法:
采用含25,100个人类功能基因的Oligo芯片,比较10例未经放、化疗的肺腺癌患者手术癌组织和癌旁组织标本的基因表达谱差异,筛选有2倍以上表达差异的基因;用筛选得到的差异表达基因,再使用SAM软件分析不同TNM分期(Ⅰ期3例、Ⅱ期3例和ⅢA期4例)的差异表达基因;使用GoMiner软件分析差异基因的功能;使用KEGG软件对差异基因进行通路分析;采用半定量RT-PCR方法对差异表达基因进行临床病例验证。
结果:
1.10例肺腺癌患者的癌组织和癌旁组织基因表达谱比较,筛选出640个基因在10例样本中有2倍以上差异表达,其中289个基因在癌组织中上调表达,351个基因下调表达。
2.通过对10例不同分期肺腺癌患者的癌组织基因表达谱比较分析,结果提示:从640个差异表达基因中筛选出在不同分期中呈不同水平表达的差异基因,共得到16个有意义的基因。7个基因在Ⅰ期显著差异表达,1个基因在ⅢA期显著差异表达,4个基因在Ⅱ期显著差异表达,4个基因在Ⅱ期和ⅢA期均差异表达,特别是本研究首次发现MIF1IP、CENPN、CBFA2T2、ANKRD36B、GINS2、ZMIZ2、LDLR七个基因在肺腺癌中差异表达,推测其中MIF1IP、CENPN、ANKRD36B、GINS2可能与肺腺癌转移有关。
3.通过GoMiner和KEGG对16个差异基因进行功能检索和通路分析发现:2个基因与细胞间信号转导有关,3个基因与细胞生长代谢有关,4个基因为转录因子。16个基因与五条通路相关,其中与丝裂原活化蛋白激酶(MAPK)显著相关(P=0.006),不同TNM分期差异表达基因通过参与或调节MAPK信号通路中相关酶的活性,从而达到抑癌或促癌的作用。再次证明MAPK信号转导通路与肿瘤细胞的发生、侵袭和转移等有着重要关系,将为肿瘤的治疗提供新的靶点。
4.通过半定量RT-PCR和Western blot对差异表达基因进行临床病例验证。结果显示:MMP-12 mRNA在癌旁组织中无表达,在Ⅰ期和Ⅱ、ⅢA期癌组织中呈不同程度的表达,其半定量均值分别为(0.551±0.140)和为(1.082±0.424),差异有显著性(P=0.001); MMP-12蛋白在癌旁组织中无表达,而在Ⅰ期癌组织中低表达,在Ⅱ、Ⅲ期癌组织中高表达。
结论:
通过筛选肺腺癌不同TNM分期的差异表达基因,推测Ⅰ期肺腺癌显著差异表达基因有利于肺腺癌早期诊断,Ⅱ、ⅢA期显著差异表达基因可能与肺腺癌转移有关,是潜在的预后评估生物标记物和药物开发的新靶标。通过检测差异表达基因,监测疾病的变化趋势,为制定治疗方案和判断预后提供依据。
Background:
Lung cancer is the leading causes of cancer worldwide. The main component of it is non-small cell lung cancer (NSCLC)(80%), and lung Adenocarcinoma is the most important pathohistology type of NSCLC. Although after resection, The treatment to patients with lung cancer has been enhanced (as adjuvant therapy) and Some more effective therapy used for inhibiting metastasis (such as molecular targeted therapy), but the cure rate of lung cancer remains low. As other solid tumors, lung cancer were formed after long-term genetic heredity and changes of time. Identify new prognostic markers, new predictive markers, or developing new detection tools is one of the main areas of lung cancer research. However, the mobility of lung cancer is a multi-factor and complicated process which characterized by genetic heterogeneity, so detected only one or a few genes is not enough, the whole genome analysis will be more effective to demonstrate the complexity of lung cancer. In recent years, with the advantages of gene chip technology of high-throughput parallel detection of the genome, we can study the gene expression spectrum of the desired tissue and cells within the whole genome which provides a powerful tool for the study of tumor development and progression of multiple gene changes in the molecular mechanism. Thus, it has a special advantage in the research of molecular classification of lung cancer.
Object:
By comparing the surgical tissue gene expression of different TNM staging of lung cancer, Filter and select the marker genes from each TNM staging of lung adenocarcinoma; Validation the genes which shows significant difference in the mRNA level using RT-PCR, analysis the contact with the corresponding clinical pathological factors and the meaning as a molecular type related genes of lung cancer.
Method:
Using the Oligo chip with 25,100 individual genes, compared 10 cases of gene expression profiles between cancer tissues and paraneoplastic tissue without chemotherapy and radiotherapy in patients and selected the genes which has tend of express two times common differences. Then, analyzed the differentially expressed genes in different TNM stages (Ⅰ, 3 cases,ⅡandⅢA of 3 cases of 4 patients) using SAM software form those genes acquired from last step and to analyze the function of the differential genes using GoMiner software. KEGG software and semi-quantitative RT-PCR were for the analysis of the differential gene circuit and validation on the clinical cases.
Result:
1. comparison of gene expression profiles between cancer tissues and paraneoplastic tissue in ten patients, 640 genes were found in 10 samples was 2 more times differentially expressed, of which 289 genes up regulated in cancer tissue, 351 genes were down.
2. Then we divided cancer into stageⅠ,Ⅱ,ⅢA, and screened genes express differences at different levels in various stages from the 640 differentially expressed genes. The result showed total of 16 genes, of which two genes were down-regulated, 14 were up-regulated. Seven genes in stageⅠshowed significantly differentia; 4 genes in phaseⅡshowed significantly differentia; 4 genes expressed differentially both in PhaseⅡandⅢA. In addition, we first found seven genes which were MIF1IP, CENPN, CBFA2T2, ANKRD36B, GINS2, ZMIZ2, LDLR differentially expressed in lung adenocarcinoma, suggesting MIF1IP, CENPN, ANKRD36B, GINS2 may be associated with lung cancer metastasis.
3. Searching the function of 16 genes differentially expressed using GoMiner, of which two were related to cell signal transduction, three were related to growth, metabolism of cell, and four genes were transcription factor. The pathway 16 differentially expressed genes were analyzed using KEGG and obtained five-related pathway: MAPK signaling pathway (P = 0.006), B cell receptor signaling pathway (P = 0.032), colorectal cancer pathway (P = 0.036). T cell receptor signaling pathway (P = 0.043), Toll-like receptor signaling pathway (P = 0.046). In this study we found that differentially expressed genes in different TNM stages, or by participating in MAPK signaling pathway regulating the activity of enzymes to inhibit or promote the growth of tumor and Once again prove that mitogen-activated protein kinase (MAPK) signal transduction pathway has an important relationship with the occurrence, invasion and metastasis of cancerous cell which will become a new target of cancer therapy.
4. The results of clinical verify differentially expressed genes MMP12: RT-PCR showed there was no MMP-12 mRNA expression in paraneoplastic tissue and was expressed different levels in cancers from stageⅠandⅡ,ⅢA, the mean of semi-quantitative was 0.551±0.140 and the summation was (1.082±0.424), Statistics showed the difference was significant (P = 0.001); Western blot results demonstrated that there was no MMP-12 protein expression in paraneoplastic tissue, while it has a low expression in cancer tissue of stageⅠand a high expression in stageⅡ,Ⅲ.
Conclusion:
Through screening of differentially expressed genes of lung adenocacinoma in different TNM stage, suggesting that predict significantly differential expressed genes in stageⅠof lung adenocacinoma could help early diagnosis of it. The significant differential genes expression in stageⅡ,ⅢA may associated with metastasis of lung adenocacinoma which is a potential prognostic biomarkers and new targets for drug therapy. We could monitor the development trends of disease by detecting changes in differentially expressed genes spectrum and Finally make treatment plan and estimate the prognosis.
肺癌是世界范围内癌症致死中最常见的原因,其主要由非小细胞肺癌(Non-small cell lung cancer,NSCLC)组成(占80%),肺腺癌是NSCLC中的最主要的组织类型。尽管手术切除后肺癌患者的治疗得到了提高(如辅助治疗)和针对转移采用更有效的治疗(如分子靶向治疗),但是肺癌的治愈率仍然很低。正如其他实体瘤一样,肺癌是经过长期的遗传和后生的改变而形成的。发掘肺癌新的预后标志物、预测标志物或开发新的检测工具是癌症研究的主要领域之一。然而,肺癌的发生是一个多因素过程且具有疾病遗传异质性的特点,仅仅检测一个或一些基因是不够的,全基因组分析将更有效的解释肺癌的复杂性。近年来,基因芯片技术以其高通量平行检测的优势使我们能从基因组范围内对组织细胞的基因表达谱进行研究,为研究肿瘤发生发展中多基因改变的分子机制提供了有力的工具。
目的:
通过比较肺腺癌不同TNM分期的手术组织标本的基因表达差异,筛选肺腺癌各TNM分期中的标志基因;对显著差异基因在mRNA水平上进行RT-PCR技术验证,并分析其与临床病理因素的关系。
方法:
采用含25,100个人类功能基因的Oligo芯片,比较10例未经放、化疗的肺腺癌患者手术癌组织和癌旁组织标本的基因表达谱差异,筛选有2倍以上表达差异的基因;用筛选得到的差异表达基因,再使用SAM软件分析不同TNM分期(Ⅰ期3例、Ⅱ期3例和ⅢA期4例)的差异表达基因;使用GoMiner软件分析差异基因的功能;使用KEGG软件对差异基因进行通路分析;采用半定量RT-PCR方法对差异表达基因进行临床病例验证。
结果:
1.10例肺腺癌患者的癌组织和癌旁组织基因表达谱比较,筛选出640个基因在10例样本中有2倍以上差异表达,其中289个基因在癌组织中上调表达,351个基因下调表达。
2.通过对10例不同分期肺腺癌患者的癌组织基因表达谱比较分析,结果提示:从640个差异表达基因中筛选出在不同分期中呈不同水平表达的差异基因,共得到16个有意义的基因。7个基因在Ⅰ期显著差异表达,1个基因在ⅢA期显著差异表达,4个基因在Ⅱ期显著差异表达,4个基因在Ⅱ期和ⅢA期均差异表达,特别是本研究首次发现MIF1IP、CENPN、CBFA2T2、ANKRD36B、GINS2、ZMIZ2、LDLR七个基因在肺腺癌中差异表达,推测其中MIF1IP、CENPN、ANKRD36B、GINS2可能与肺腺癌转移有关。
3.通过GoMiner和KEGG对16个差异基因进行功能检索和通路分析发现:2个基因与细胞间信号转导有关,3个基因与细胞生长代谢有关,4个基因为转录因子。16个基因与五条通路相关,其中与丝裂原活化蛋白激酶(MAPK)显著相关(P=0.006),不同TNM分期差异表达基因通过参与或调节MAPK信号通路中相关酶的活性,从而达到抑癌或促癌的作用。再次证明MAPK信号转导通路与肿瘤细胞的发生、侵袭和转移等有着重要关系,将为肿瘤的治疗提供新的靶点。
4.通过半定量RT-PCR和Western blot对差异表达基因进行临床病例验证。结果显示:MMP-12 mRNA在癌旁组织中无表达,在Ⅰ期和Ⅱ、ⅢA期癌组织中呈不同程度的表达,其半定量均值分别为(0.551±0.140)和为(1.082±0.424),差异有显著性(P=0.001); MMP-12蛋白在癌旁组织中无表达,而在Ⅰ期癌组织中低表达,在Ⅱ、Ⅲ期癌组织中高表达。
结论:
通过筛选肺腺癌不同TNM分期的差异表达基因,推测Ⅰ期肺腺癌显著差异表达基因有利于肺腺癌早期诊断,Ⅱ、ⅢA期显著差异表达基因可能与肺腺癌转移有关,是潜在的预后评估生物标记物和药物开发的新靶标。通过检测差异表达基因,监测疾病的变化趋势,为制定治疗方案和判断预后提供依据。
Background:
Lung cancer is the leading causes of cancer worldwide. The main component of it is non-small cell lung cancer (NSCLC)(80%), and lung Adenocarcinoma is the most important pathohistology type of NSCLC. Although after resection, The treatment to patients with lung cancer has been enhanced (as adjuvant therapy) and Some more effective therapy used for inhibiting metastasis (such as molecular targeted therapy), but the cure rate of lung cancer remains low. As other solid tumors, lung cancer were formed after long-term genetic heredity and changes of time. Identify new prognostic markers, new predictive markers, or developing new detection tools is one of the main areas of lung cancer research. However, the mobility of lung cancer is a multi-factor and complicated process which characterized by genetic heterogeneity, so detected only one or a few genes is not enough, the whole genome analysis will be more effective to demonstrate the complexity of lung cancer. In recent years, with the advantages of gene chip technology of high-throughput parallel detection of the genome, we can study the gene expression spectrum of the desired tissue and cells within the whole genome which provides a powerful tool for the study of tumor development and progression of multiple gene changes in the molecular mechanism. Thus, it has a special advantage in the research of molecular classification of lung cancer.
Object:
By comparing the surgical tissue gene expression of different TNM staging of lung cancer, Filter and select the marker genes from each TNM staging of lung adenocarcinoma; Validation the genes which shows significant difference in the mRNA level using RT-PCR, analysis the contact with the corresponding clinical pathological factors and the meaning as a molecular type related genes of lung cancer.
Method:
Using the Oligo chip with 25,100 individual genes, compared 10 cases of gene expression profiles between cancer tissues and paraneoplastic tissue without chemotherapy and radiotherapy in patients and selected the genes which has tend of express two times common differences. Then, analyzed the differentially expressed genes in different TNM stages (Ⅰ, 3 cases,ⅡandⅢA of 3 cases of 4 patients) using SAM software form those genes acquired from last step and to analyze the function of the differential genes using GoMiner software. KEGG software and semi-quantitative RT-PCR were for the analysis of the differential gene circuit and validation on the clinical cases.
Result:
1. comparison of gene expression profiles between cancer tissues and paraneoplastic tissue in ten patients, 640 genes were found in 10 samples was 2 more times differentially expressed, of which 289 genes up regulated in cancer tissue, 351 genes were down.
2. Then we divided cancer into stageⅠ,Ⅱ,ⅢA, and screened genes express differences at different levels in various stages from the 640 differentially expressed genes. The result showed total of 16 genes, of which two genes were down-regulated, 14 were up-regulated. Seven genes in stageⅠshowed significantly differentia; 4 genes in phaseⅡshowed significantly differentia; 4 genes expressed differentially both in PhaseⅡandⅢA. In addition, we first found seven genes which were MIF1IP, CENPN, CBFA2T2, ANKRD36B, GINS2, ZMIZ2, LDLR differentially expressed in lung adenocarcinoma, suggesting MIF1IP, CENPN, ANKRD36B, GINS2 may be associated with lung cancer metastasis.
3. Searching the function of 16 genes differentially expressed using GoMiner, of which two were related to cell signal transduction, three were related to growth, metabolism of cell, and four genes were transcription factor. The pathway 16 differentially expressed genes were analyzed using KEGG and obtained five-related pathway: MAPK signaling pathway (P = 0.006), B cell receptor signaling pathway (P = 0.032), colorectal cancer pathway (P = 0.036). T cell receptor signaling pathway (P = 0.043), Toll-like receptor signaling pathway (P = 0.046). In this study we found that differentially expressed genes in different TNM stages, or by participating in MAPK signaling pathway regulating the activity of enzymes to inhibit or promote the growth of tumor and Once again prove that mitogen-activated protein kinase (MAPK) signal transduction pathway has an important relationship with the occurrence, invasion and metastasis of cancerous cell which will become a new target of cancer therapy.
4. The results of clinical verify differentially expressed genes MMP12: RT-PCR showed there was no MMP-12 mRNA expression in paraneoplastic tissue and was expressed different levels in cancers from stageⅠandⅡ,ⅢA, the mean of semi-quantitative was 0.551±0.140 and the summation was (1.082±0.424), Statistics showed the difference was significant (P = 0.001); Western blot results demonstrated that there was no MMP-12 protein expression in paraneoplastic tissue, while it has a low expression in cancer tissue of stageⅠand a high expression in stageⅡ,Ⅲ.
Conclusion:
Through screening of differentially expressed genes of lung adenocacinoma in different TNM stage, suggesting that predict significantly differential expressed genes in stageⅠof lung adenocacinoma could help early diagnosis of it. The significant differential genes expression in stageⅡ,ⅢA may associated with metastasis of lung adenocacinoma which is a potential prognostic biomarkers and new targets for drug therapy. We could monitor the development trends of disease by detecting changes in differentially expressed genes spectrum and Finally make treatment plan and estimate the prognosis.
引文
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[1] Parkin DM, Bray F, Ferlay J, et al. Globalcancer statistics, 2002. CA-Cancer J Clin, 2005, 55: 74-107.
[2]李连第,鲁凤珠,张思维,等.中国恶性肿瘤死亡率20年变化趋势和近期预测分析.中华肿瘤杂志.1997,19(1):3-9.
[3] Sobin LH. The world health organiazation’s histological classification of lung tumors: a comparision of the first and second editions.Cancer Detect Pre, 1982, 5: 391-406.
[4] Singhala S, Miller D, Ramalingamc S, et al. Gene expression profiling of Non-small cell lung cancer. Lung Cancer, 2008, 60: 313—324.
[5] Abbitt A. DNA chips intensify the sequence search. Nature, 1996, 379: 392-397.
[6] Persidis A. Biochip. Nature Biotechnology, 1998, 16,: 981 - 983 .
[7] Cojocaru G, Friedman N, Krupsky M, et al. Transcriptional profiling of non-small cell lung cancer using oligonucleotide microarrays. Chest, 2002, 121 (3 Suppl) : 44S.
[8] Wang T, Hopkins D, Schmidt C, et al. Identification of genes differentially overexpressed in lung squamous cell carcinoma using combination of cDNA subtraction and microarray analysis. Oncogene , 2000 ,19: 1519-1528.
[9]何志巍,许亮国,任彩萍,等.人鼻咽与鼻咽癌及肺癌基因表达谱差异[J ] .生物化学与生物物理进展, 1999, 26 (5) : 446-450.
[10]何志巍,许亮国,任彩萍,等.用cDNA阵列研究人肺癌与正常肺及胚肺组织基因表达谱[J ] .癌症, 1999, 18 (5) : 489-491.
[11]张恒,刘芝华,李泽坚,等.利用微阵列技术初步分析肺鳞癌组织中的基因表达谱[J ] .中国肿瘤临床, 2001, 28 (3) : 172-175.
[12] Goodwin LO, Mason JM, Hajdu SI. Gene expression patterns of paired bronchioloalveolar carcinoma and benign lung tissue. Ann Clin Lab Sci , 2001, 31 :369-375.
[13] Garber ME, Olga G. T, Karsten S, et al. Diversity of gene expression in adenocarcinoma of the lung. Proc Nati. Acad. Sci. USA,2001, 98 :13784-13789.
[14] Arindam B, William G. R, Jane S. Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses. Proc Natl. Acad. Sci. USA, 2001, 98: 13790-13795.
[15] Bangur CS, Switzer A, Fan L, et al. Identification of genes overexpressed in small cell lung carcinoma using suppression subtractive hybridization and cDNA microarray expression analysis. Oncogene, 2002, 21: 3814-3825.
[16] Beer DG, Kardia SL , Huang CC, et al. Gene expression profiles predict survival of patients with lung adenocarcinoma. Nat Med,2002, 8: 816-824.
[17]周向东,钱桂生,刘凌志.采用基因芯片技术筛选人小细胞肺癌SH77/CDDP多药耐药相关基因表达谱的研究.第三军医大学学报,2007,29:279—283.
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[21] Larsen JE, Brown KM, Pavey SJ, et a1. Genomic profiling of tumour recurrence in non-small cell lung carcinoma. J Thorac Oncol, 2007, 2: S376-S377.
[22] Fukumoto S, Yam auchi N, M origuchi H, et a1. 0verexpression of the aldo-ketoreductase family protein AKR1B10 is highly correlated with smokers’non—small cell lung carcinomas. Clin Cancer Res, 2005, 11: 1776-1 785.
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[27] Feng G, Xu X, Youssef EM, et al. Diminished expression of S100A2, a putative tumor suppressor, at early stage of human lung carcinogenesis. Cancer Res, 2001, 61: 7999-8004.
[28] Sakaue M, Adachi H, Dawson M, et al. Induction of Egr-1 expression by the retinoid AHPN in human lung carcinoma cells is dependent on activated ERK1/ 2. Cell Death Differ, 2001, 8: 411-424.
[29] By R. M. Bremnes, R. Veve, E. Gabrielson, et al. High-Through-put Tissue Microarray Analysis Used to Evaluate Biology and Prognostic Significance of the E2Cadherin Pathway in Non2Small2 Cell Lung Cancer. Journal of Clinical Oncology, 2002,10: 2417-2428.
[30]何大澄,肖雪媛,唐颖,等.应用蛋白质芯片技术从血清中筛选肺癌标志蛋白[J ] .中国蛋白质组学首届学术大会论文摘要, 2003, 9.
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[1] Parkin DM, Bray F, Ferlay J, et al. Globalcancer statistics, 2002. CA-Cancer J Clin, 2005, 55: 74-107.
[2]李连第,鲁凤珠,张思维,等.中国恶性肿瘤死亡率20年变化趋势和近期预测分析.中华肿瘤杂志.1997,19(1):3-9.
[3] Sobin LH. The world health organiazation’s histological classification of lung tumors: a comparision of the first and second editions.Cancer Detect Pre, 1982, 5: 391-406.
[4] Singhala S, Miller D, Ramalingamc S, et al. Gene expression profiling of Non-small cell lung cancer. Lung Cancer, 2008, 60: 313—324.
[5] Abbitt A. DNA chips intensify the sequence search. Nature, 1996, 379: 392-397.
[6] Persidis A. Biochip. Nature Biotechnology, 1998, 16,: 981 - 983 .
[7] Cojocaru G, Friedman N, Krupsky M, et al. Transcriptional profiling of non-small cell lung cancer using oligonucleotide microarrays. Chest, 2002, 121 (3 Suppl) : 44S.
[8] Wang T, Hopkins D, Schmidt C, et al. Identification of genes differentially overexpressed in lung squamous cell carcinoma using combination of cDNA subtraction and microarray analysis. Oncogene , 2000 ,19: 1519-1528.
[9]何志巍,许亮国,任彩萍,等.人鼻咽与鼻咽癌及肺癌基因表达谱差异[J ] .生物化学与生物物理进展, 1999, 26 (5) : 446-450.
[10]何志巍,许亮国,任彩萍,等.用cDNA阵列研究人肺癌与正常肺及胚肺组织基因表达谱[J ] .癌症, 1999, 18 (5) : 489-491.
[11]张恒,刘芝华,李泽坚,等.利用微阵列技术初步分析肺鳞癌组织中的基因表达谱[J ] .中国肿瘤临床, 2001, 28 (3) : 172-175.
[12] Goodwin LO, Mason JM, Hajdu SI. Gene expression patterns of paired bronchioloalveolar carcinoma and benign lung tissue. Ann Clin Lab Sci , 2001, 31 :369-375.
[13] Garber ME, Olga G. T, Karsten S, et al. Diversity of gene expression in adenocarcinoma of the lung. Proc Nati. Acad. Sci. USA,2001, 98 :13784-13789.
[14] Arindam B, William G. R, Jane S. Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses. Proc Natl. Acad. Sci. USA, 2001, 98: 13790-13795.
[15] Bangur CS, Switzer A, Fan L, et al. Identification of genes overexpressed in small cell lung carcinoma using suppression subtractive hybridization and cDNA microarray expression analysis. Oncogene, 2002, 21: 3814-3825.
[16] Beer DG, Kardia SL , Huang CC, et al. Gene expression profiles predict survival of patients with lung adenocarcinoma. Nat Med,2002, 8: 816-824.
[17]周向东,钱桂生,刘凌志.采用基因芯片技术筛选人小细胞肺癌SH77/CDDP多药耐药相关基因表达谱的研究.第三军医大学学报,2007,29:279—283.
[18] Lin TS, Chiou SH, Wang LS, et a1. Expression spectra of matrix metalloproteinases in metastatic non—small cell lung cancer. 0ncol Rep, 2004, 12: 717-723.
[19] GemIlla A, Takenaka K, Hosoya Y, et a1. Altered expression of several genes in highly metastatic subpopulations of a human pulmonary adenocarcinoma cell line. Eur J Cancer, 2001, 37: 1 554-1561.
[20] Hoang CD, D’Cunha J, Tawfic SH, et a1. Expression profiling of non-small cell lung carcinoma identifies metastatic genotypes based on lymph node tumor burden. J Thorac Cardiovasc Surg, 2004, 127: 1332-1341.
[21] Larsen JE, Brown KM, Pavey SJ, et a1. Genomic profiling of tumour recurrence in non-small cell lung carcinoma. J Thorac Oncol, 2007, 2: S376-S377.
[22] Fukumoto S, Yam auchi N, M origuchi H, et a1. 0verexpression of the aldo-ketoreductase family protein AKR1B10 is highly correlated with smokers’non—small cell lung carcinomas. Clin Cancer Res, 2005, 11: 1776-1 785.
[23] Kobayashi K, Nishioka M, Kohno T, et a1. Identification of genes whose expression is upregulated in lung adenocarcinoma cells in comparison with typeⅡalveolar cells and bronchiolar epithelial cells in vivo. Oncogene, 2004, 17: 3089-3096.
[24] Hofmann H S, Hansen G, Burdach S, et a1. Discrimination of human lung neoplasm from normal lung by two target genes. Am J Respir Crit Care Med, 2004, 170: 516-519.
[25] Bartling B, Hofm ann HS, Boettger T, et a1. Comparative application of antibody and gene array for expression profiling in human squamous cell lung carcinoma. Lung Cancer, 2005, 49: 145-l54.
[26] Kannan K, Amariglio N, Rechavi G, et al. DNA microarrays identification of primary and secondary target genes regulated byp53. Oncogene, 2001, 20 :2225-2234.
[27] Feng G, Xu X, Youssef EM, et al. Diminished expression of S100A2, a putative tumor suppressor, at early stage of human lung carcinogenesis. Cancer Res, 2001, 61: 7999-8004.
[28] Sakaue M, Adachi H, Dawson M, et al. Induction of Egr-1 expression by the retinoid AHPN in human lung carcinoma cells is dependent on activated ERK1/ 2. Cell Death Differ, 2001, 8: 411-424.
[29] By R. M. Bremnes, R. Veve, E. Gabrielson, et al. High-Through-put Tissue Microarray Analysis Used to Evaluate Biology and Prognostic Significance of the E2Cadherin Pathway in Non2Small2 Cell Lung Cancer. Journal of Clinical Oncology, 2002,10: 2417-2428.
[30]何大澄,肖雪媛,唐颖,等.应用蛋白质芯片技术从血清中筛选肺癌标志蛋白[J ] .中国蛋白质组学首届学术大会论文摘要, 2003, 9.
[31] Yanagisawa K, Shy Y, Xu BJ, et al. Proteomic patterns of tumour subsets in non-small-cell lung cancer. Lancet, 2003, 362: 415-416.