1.从人胚胎肺发育研究人原发性肺腺癌预后相关基因表达谱 2.深测序和基因芯片技术用于mRNA表达谱检测的比较研究
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摘要
该博士学位论文由相对独立的两部分工作组成。
第一部分从人胚胎肺发育研究人原发性肺腺癌预后相关基因表达谱
发育与肿瘤具有一定程度的相似性。从胚胎发育中探索和挖掘隐藏在肿瘤细胞内的恶性信息,为肿瘤基础及临床研究提供新的线索,正逐步成为一个新的研究方向。本研究从三个方面观察了影响原发性肺癌预后的分子事件在胚胎肺发育过程中的变化规律：1)人胚胎肺发育的mRNA表达特征：2)人胚胎肺发育与原发性肺癌基因表达谱相似性比较；3)人胚胎肺发育相关基因对原发性肺癌预后的影响。研究结果显示,胚胎肺发育在组织学层面的时空变化与分子水平的mRNA表达具有动态联系,在我们所关注的两个基因簇中,其mRNA表达随发育的进程而呈现此消彼长、互呈X状走向的表达模式。高开低走型表达模式的基因簇与细胞增殖相关；而低开高走型基因簇则和细胞与细胞、细胞与间质通讯,胞膜成熟相关。根据基因表达特征,将原发性肺腺癌与肺鳞癌投射到胚胎肺发育的动态模式中,发现肿瘤样本间的异质性明显大于正常组织；与非肿瘤成人肺相比,肺腺癌的基因表达特征与胚胎肺组织相似,肺鳞癌则与更早期肺组织相似。根据基因表达的动态分布特征,以SMC4为代表的、在胚胎肺发育过程中表达丰度呈高开低走型的基因群在肺癌组织中的表达则重新上调。进一步分析发现,SMC4基因群总体表达水平与肺腺癌患者临床预后有关,并且不依赖于患者的临床分期、淋巴结转移情况等；但却未发现它们与肺鳞癌患者临床预后有关。SMC4基因群作为分子表型与肺腺癌患者临床表型的相关性,在多组公共数据库来源的独立样本中均得到了验证。本研究结果提示,人胚胎肺发育组织与原发性肺癌在分子水平存在共性；与肺癌患者预后相关的恶性分子事件可能是胚胎记忆的重新唤起。以胚胎发育作为切入点,系统整合分析胚胎发育与肿瘤的内在联系,不失为一条探索肿瘤发生与发展机理的新途径。
第二部分深测序和基因芯片技术用于mRNA表达谱检测的比较研究
基于第二代测序的数字表达谱技术(next-generation sequencing based Digital Gene Expression tag profiling, DGE)已经开始用于基因表达谱研究。为了评价DGE测序平台和基因芯片平台对mRNA表达谱的检测质量,我们分别对这两个平台在基因表达谱检测能力、技术重复性、动态范围和检测结果间的一致程度等主要技术指标进行了测评。检测对象是转染了DENND2D基因和空载体的NCI-H1299细胞系的mRNA表达谱。结果显示,在两种细胞内,基因芯片平台共检测到17,362个基因,DGE测序平台共检测到15,938个,其中13,221个基因为两平台共同检测到的基因。两技术平台内两次技术重复间的相关系数均大于0.99,变异系数小于9%。基因芯片平台的动态范围固定在4个数量级,而DGE平台的动态范围根据其测序深度的不同是可拓展的。两平台检测结果的一致性高,特别是对于那些丰度较高的基因。相比于DGE测序平台,基因芯片平台更难检测出表达丰度低的基因。虽然基因芯片技术或许最终会被深测序(deep sequencing)技术取代,但由于基因芯片的成本优势,以及已经建立的硬件和数据分析基础,短期内该平台还将是基因表达谱研究领域的重要技术手段。
This PhD degree project is composed of two parts of study.
Part I A Study on Expression Signature Prognostic for Survival of Lung Adenocarcinoma from mRNA Profiling in Human Lung Development
Purpose:It is demonstrated that embryonic development to some extent resembles tumorigenesis. Thus, it would be helpful to better understand molecular feature of tumors which is characterized by gene expression signatures in embryonic developmental process. In this study, we tried to identify the development signature as being survival related gene expression profile by following observations:1) the mRNA expression profile in human embryonic development; 2) similarity comparison of gene expression signature between human embryonic development and primary non-small cell lung cancer (NSCLC); and 3) the association between embryonic development gene signature and risk stratification of NSCLC. Results:Two sets of genes which exhibited "X" expression pattern were identified. Gene ontology analysis showed that the genes activated in early stage of development associated with cell proliferation, while another set of genes up-regulated in late stage was implicated in cell-cell, cell-matrix communication and cell membrane maturation. By gene expression profiling, we defined a human fetal lung developmental landscape on which the gene expression data from NSCLC were projected. It was found that the gene signatures from adenocarcinoma and squamous cell carcinoma were similar to gene expression profiles in developing lung tissues. The expression of SMC4 represented gene set activated in early stage and gradually abated in mid-late stage of development was up-regulated in NSCLC tissue. Further, independent of TNM staging parameters, the expression of SMC4-gene set correlated with overall survival of lung adenocarcinoma patients, and the phenomenon was subsequently validated by multiple independent sample sets. However, there was no association between developmental signature and the prognosis of patients with lung squamous cell cancer. Conclusion:Part of lung adenocarcinoma transcriptome is composed of developmental gene signatures and survival related malignant features may be reminiscent of embryonic behavior. Comprehensive analysis on development signatures of cancers would be a meaningful approach to uncover critical clues to tumorigenesis.
Part II Power of Deep Sequencing and Agilent Microarray for Gene Expression Profiling Study
Next-generation sequencing based Digital Gene Expression tag profiling (DGE) has been used to study changes in gene expression profiling. To compare the quality of the data generated by microarray and DGE, we examined the gene expression profiles of an in vitro cell model with both platforms. In this study,17,362 and 15,938 genes were detected by microarray and DGE, respectively, with 13,221 overlapping genes. The correlation coefficients between the technical replicates were>0.99 and the detection variance was<9% for both platforms. The dynamic range of microarray was fixed with 4 orders of magnitude, while the dynamic range of DGE was extendable. The consistency of the two platforms was high, especially for those abundant genes. It was more difficult for the microarray to distinguish the expression variation of less abundant genes. Although microarrays might be eventually replaced by DGE or transcriptome sequencing (RNA-seq) in the near future, microarrays are still stable, practical and feasible, which renders the same useful for most biological researchers.
第一部分从人胚胎肺发育研究人原发性肺腺癌预后相关基因表达谱
发育与肿瘤具有一定程度的相似性。从胚胎发育中探索和挖掘隐藏在肿瘤细胞内的恶性信息,为肿瘤基础及临床研究提供新的线索,正逐步成为一个新的研究方向。本研究从三个方面观察了影响原发性肺癌预后的分子事件在胚胎肺发育过程中的变化规律：1)人胚胎肺发育的mRNA表达特征：2)人胚胎肺发育与原发性肺癌基因表达谱相似性比较；3)人胚胎肺发育相关基因对原发性肺癌预后的影响。研究结果显示,胚胎肺发育在组织学层面的时空变化与分子水平的mRNA表达具有动态联系,在我们所关注的两个基因簇中,其mRNA表达随发育的进程而呈现此消彼长、互呈X状走向的表达模式。高开低走型表达模式的基因簇与细胞增殖相关；而低开高走型基因簇则和细胞与细胞、细胞与间质通讯,胞膜成熟相关。根据基因表达特征,将原发性肺腺癌与肺鳞癌投射到胚胎肺发育的动态模式中,发现肿瘤样本间的异质性明显大于正常组织；与非肿瘤成人肺相比,肺腺癌的基因表达特征与胚胎肺组织相似,肺鳞癌则与更早期肺组织相似。根据基因表达的动态分布特征,以SMC4为代表的、在胚胎肺发育过程中表达丰度呈高开低走型的基因群在肺癌组织中的表达则重新上调。进一步分析发现,SMC4基因群总体表达水平与肺腺癌患者临床预后有关,并且不依赖于患者的临床分期、淋巴结转移情况等；但却未发现它们与肺鳞癌患者临床预后有关。SMC4基因群作为分子表型与肺腺癌患者临床表型的相关性,在多组公共数据库来源的独立样本中均得到了验证。本研究结果提示,人胚胎肺发育组织与原发性肺癌在分子水平存在共性；与肺癌患者预后相关的恶性分子事件可能是胚胎记忆的重新唤起。以胚胎发育作为切入点,系统整合分析胚胎发育与肿瘤的内在联系,不失为一条探索肿瘤发生与发展机理的新途径。
第二部分深测序和基因芯片技术用于mRNA表达谱检测的比较研究
基于第二代测序的数字表达谱技术(next-generation sequencing based Digital Gene Expression tag profiling, DGE)已经开始用于基因表达谱研究。为了评价DGE测序平台和基因芯片平台对mRNA表达谱的检测质量,我们分别对这两个平台在基因表达谱检测能力、技术重复性、动态范围和检测结果间的一致程度等主要技术指标进行了测评。检测对象是转染了DENND2D基因和空载体的NCI-H1299细胞系的mRNA表达谱。结果显示,在两种细胞内,基因芯片平台共检测到17,362个基因,DGE测序平台共检测到15,938个,其中13,221个基因为两平台共同检测到的基因。两技术平台内两次技术重复间的相关系数均大于0.99,变异系数小于9%。基因芯片平台的动态范围固定在4个数量级,而DGE平台的动态范围根据其测序深度的不同是可拓展的。两平台检测结果的一致性高,特别是对于那些丰度较高的基因。相比于DGE测序平台,基因芯片平台更难检测出表达丰度低的基因。虽然基因芯片技术或许最终会被深测序(deep sequencing)技术取代,但由于基因芯片的成本优势,以及已经建立的硬件和数据分析基础,短期内该平台还将是基因表达谱研究领域的重要技术手段。
This PhD degree project is composed of two parts of study.
Part I A Study on Expression Signature Prognostic for Survival of Lung Adenocarcinoma from mRNA Profiling in Human Lung Development
Purpose:It is demonstrated that embryonic development to some extent resembles tumorigenesis. Thus, it would be helpful to better understand molecular feature of tumors which is characterized by gene expression signatures in embryonic developmental process. In this study, we tried to identify the development signature as being survival related gene expression profile by following observations:1) the mRNA expression profile in human embryonic development; 2) similarity comparison of gene expression signature between human embryonic development and primary non-small cell lung cancer (NSCLC); and 3) the association between embryonic development gene signature and risk stratification of NSCLC. Results:Two sets of genes which exhibited "X" expression pattern were identified. Gene ontology analysis showed that the genes activated in early stage of development associated with cell proliferation, while another set of genes up-regulated in late stage was implicated in cell-cell, cell-matrix communication and cell membrane maturation. By gene expression profiling, we defined a human fetal lung developmental landscape on which the gene expression data from NSCLC were projected. It was found that the gene signatures from adenocarcinoma and squamous cell carcinoma were similar to gene expression profiles in developing lung tissues. The expression of SMC4 represented gene set activated in early stage and gradually abated in mid-late stage of development was up-regulated in NSCLC tissue. Further, independent of TNM staging parameters, the expression of SMC4-gene set correlated with overall survival of lung adenocarcinoma patients, and the phenomenon was subsequently validated by multiple independent sample sets. However, there was no association between developmental signature and the prognosis of patients with lung squamous cell cancer. Conclusion:Part of lung adenocarcinoma transcriptome is composed of developmental gene signatures and survival related malignant features may be reminiscent of embryonic behavior. Comprehensive analysis on development signatures of cancers would be a meaningful approach to uncover critical clues to tumorigenesis.
Part II Power of Deep Sequencing and Agilent Microarray for Gene Expression Profiling Study
Next-generation sequencing based Digital Gene Expression tag profiling (DGE) has been used to study changes in gene expression profiling. To compare the quality of the data generated by microarray and DGE, we examined the gene expression profiles of an in vitro cell model with both platforms. In this study,17,362 and 15,938 genes were detected by microarray and DGE, respectively, with 13,221 overlapping genes. The correlation coefficients between the technical replicates were>0.99 and the detection variance was<9% for both platforms. The dynamic range of microarray was fixed with 4 orders of magnitude, while the dynamic range of DGE was extendable. The consistency of the two platforms was high, especially for those abundant genes. It was more difficult for the microarray to distinguish the expression variation of less abundant genes. Although microarrays might be eventually replaced by DGE or transcriptome sequencing (RNA-seq) in the near future, microarrays are still stable, practical and feasible, which renders the same useful for most biological researchers.
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