基于基因表达谱芯片确定前列腺癌致病有关基因及其功能
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摘要
[背景]
前列腺癌是前列腺腺泡细胞异常无序生长的结果,它是一种发生于男性前列腺组织中的恶性肿瘤。目前,前列腺癌是全世界男性第二大最常见的癌症,并且其发病率呈逐年上升趋势。据世界卫生组织(WHO)的统计资料,在2008年,全世界大约有899000个前列腺癌病例,约占到所有男性新增癌症病例的14%。根据WHO的预测,到2030年,全球前列腺癌患者将会在此基础上翻倍(一百七十万个病例)。流行病学研究发现,前列腺癌的发病率具有明显的地理和种族差异。在欧美等发达国家,前列腺癌是是最常见的男性癌症,其死亡率居各种癌症的第二位,仅次于肺癌。在亚非等发展中国家,其发病率虽然低于欧美国家,但近年来的调查表明,随着平均年龄的增加以及生活方式,主要是饮食结构的改变,前列腺癌在亚非等发展中国家的发病率呈现迅速上升的趋势。在我国,前列腺癌在泌尿生殖系统恶性肿瘤的发病率已经从第三位跃居首位,成为危害我国老年男性生命健康的重要疾病。
随着分子生物学研究的迅速发展,对大多数肿瘤的发生和发展,在细胞水平变化和分子水平的变化上,人们都有了更深的认识。研究表明前列腺癌是一种十分复杂的癌症,其发生发展过程存在多因素、多基因相互作用。前列腺癌的发生是由于基因组的不稳定导致基因表达出现异常。已经鉴定出了多条染色体上存在前列腺癌易感基因位点,其中高频出现的染色体有X染色体、1号染色体、3号染色体、8号染色体、15号染色体、17号染色体、19号染色体、20号染色体等。在前列腺癌的发生发展过程中,许多基因产物表现出异常的调控功能,大量的生长因子和它们的受体是过表达的,例如雌激素、雄激素受体、上皮生长因子、白细胞介素6等。这些基因表达的改变可能增强肿瘤细胞的生长、转移和侵袭能力,尤其是Wnt／pcatenin、Hedgehog等多条信号通路的激活可能赋予了它们侵袭的表型。然而,研究人员对于前列腺癌发生发展过程中涉及的机制了解还远远不够。所以,研究良性前列腺组织和前列腺癌的差异表达基因,可以为前列腺细胞由正常状态转变为恶性肿瘤状态提供重要基因水平的依据。
前列腺癌的早期诊断对于前列腺癌的治疗具有重要的临床意义。许多前列腺癌患者在发病过程中不表现任何症状,因而没有及时治疗,最终导致患者死于由前列腺癌引起的其他疾病。这是由于前列腺癌在很多病例中(约占三分之二)呈现缓慢增殖,并且无症状。另一方面,大约三分之一的前列腺癌具有侵袭性,发展迅速的特点,该种类型的前列腺癌是除肺癌以外的第二大致死癌症。因此,前列腺癌的发生发展过程中的差异基因的鉴定对于早期诊断和及时治疗前列腺癌具有重要意义。目前,PSA(prostate specific antigen,前列腺特异抗原)是用于前列腺癌诊断的重要标志物。PSA具有组织特异性,只存在于人前列腺腺泡及导管上皮细胞胞浆中,在人的其它细胞中不表达。但是,PSA并没有肿瘤特异性,良性前列腺增生和前列腺炎也会出现PSA阳性的结果。而且,用基因治疗的手段治疗前列腺癌时,需要在与正常前列腺组织相比,前列腺癌组织中发生差异表达的基因中筛选有效的合适的靶分子。
基因芯片技术的产生使人们可以一次性检测上万个基因的表达谱,面对如此海量的数据,传统的单个基因的分析研究方法已经不适用。基因芯片数据分析是对从基因芯片高密度杂交点阵图中提取的杂交点荧光强度信号进行的定性和定量的分析,通过有效数据筛选、相关基因聚类等方法,最终将海量的芯片数据整合,发现基因表达谱与生物学功能之间可能存在的联系。基因芯片表达谱数据分析将无机的信息数据有有机的生命活动联系起来,解释基因的功能,疾病的分子机理,是生物信息学研究的重要课题。基因芯片技术能够同时、快速、准确地分析数以千计基因组信息,给研究者研究基因表达谱提供了很大的便利,极大的减轻了大规模的筛选前列腺癌差异表达基因的工作量。目前,该技术已经广泛的应用于多种癌症基因表达谱分析、寻找疾病特异基因等方面研究中。
[目的]
本研究利用基因芯片数据分析软件包bioconductor对来自基因表达数据库Gene Expression Omnibus(GEO)的19个前列腺癌基因表达谱芯片数据(良性前列腺组织,原发性前列腺癌,转移性前列腺癌)作进一步生物信息学分析,以了解前列腺癌在各阶段的基因表达变化,并进一步探讨前列腺癌发生、发展过程中肿瘤相关基因表达的变化及其生物学特性,同时通过系统的研究差异表达基因的转录调控网络、蛋白质互作网络和其参与的生物学通路的差异,阐述前列腺癌发展的分子机制。本研究旨在发现前列腺癌治疗和诊断的分子标记物及探讨前列腺癌发生发展的分子机制,有重要的现实意义。本研究为进一步了解前列腺癌发生发展的分子机制和前列腺癌的诊断治疗提供了有用的基础科研资料。
[方法]
首先从NCBI GEO中下载基因芯片GSE3325。通过对该芯片进行分析,分别筛选出原发性前列腺癌、转移性前列腺癌与良性前列腺组织中差异表达有显著性意义的基因。基因表达差异有显著性意义的判定标准为：原发性前列腺癌组织或转移性前列腺癌组织与良性前列腺组织相比,同一条基因的差异表达值(fold change value)大于2或者小于—2,t检验的概率值(p-value)小于0.05。
通过收集整理已有的转录因子与目的基因调控关系数据,结合我们鉴定出的差异表达基因,分别构建原发性前列腺癌和转移性前列腺癌的差异调控网络,并通过GO功能富集分析及生物学通路富集分析,比较这两个网络的功能差异；通过收集整理已有蛋白质互作数据库里的蛋白质相互作用数据,结合我们鉴定出的差异表达基因,分别构建原发性前列腺癌和转移性前列腺癌的蛋白质相互作用网络,并通过GO功能富集分析及生物学通路富集分析比较两个互作网络的功能差异；通过计算任意2个生物学通路之间相互作用的蛋白对来反应任意2个生物学通路的交互作用的显著性。
[结果]
1、在原发性前列腺癌的基因表达谱中筛选出5847个差异表达基因,在转移性前列腺癌的基因表达谱中筛选出2026个差异表达基因,其中两个集合的交集有977个基因,即转移性前列腺癌与原发性前列腺癌相比,有977个基因发生了差异表达。
2、分别构建了良性前列腺组织与原发性前列腺癌差异表达基因调控网络和良性前列腺组织与转移性前列腺癌差异表达基因调控网络,并对这两个网络中的基因进行GO功能富集及生物学通路富集。良性前列腺组织与原发性前列腺癌差异表达基因调控网络中,转录因子MYC在调控网络中起着至关重要的核心作用,转录因子E2F1和TP53、ESRl在调控关系中也起着很重要的作用。良性前列腺组织与转移性前列腺癌差异表达基因调控网络中,MYC在调控网络中起着至关重要的核心作用。本结果说明转录因子MYC在前列腺癌的发生、发展、转移整个过程中都起作用,而转录因子E2F1、TP53和ESR1的调控关系对于前列腺癌由原发性向转移性发展有着重要的作用。
3、分别构建了原发性前列腺癌和转移性前列腺癌的蛋白质相互作用网络,并进行了比较分析,发现只有MMP9与IL8的相互作用只在转移性前列腺癌中出现。另外662个蛋白之间的775个相互作用对只在原发性前列腺癌的相互作用网络中出现。GO功能富集分析发现,原发性前列腺癌和转移性前列腺癌的蛋白质互作网络中基因的功能主要富集细胞周期上。另外,分别对上调基因和下调基因进行GO功能富集发现,原发性前列腺癌的上调基因也集中在细胞周期上,而下调基因主要富集在免疫应答上；转移性前列腺癌的上调基因主要集中在细胞分化上,下调基因主要富集在细胞周期上。
4、原发性前列腺癌与良性前列腺组织相比共有16条显著表达的生物学通路,这16条生物学通路多与细胞增殖和肿瘤发生有关,例如hsa04114(卵母细胞减数分裂),hsa04062(趋化因子信号通路),hsa04330(Notch信号通路),hsa05218(黑素瘤),hsa04310(Wnt信号通路)等等。转移性前列腺癌与良性前列腺组织相比共有8条显著表达的生物学通路,这8条生物学通路中,有7条也存在于原发性前列腺癌与良性前列腺组织相比显著表达的生物学通路中,只有1条不存在,是hsa00534(葡萄胺聚糖生物合成—硫酸乙酰肝素)
Background:
Prostate cancer(PC) is the result of acinus cell growth without control. It is the malignancy only developed in males. To date, PC is the most frequent cancer in males in western countries. As the age indication increases and the dietary ingredient changes in Asia and African, the incidence and death rate of prostate cancer raises gradually in the past decades. Although previous studies revealed that prostate cancer progression is a process involving multiple molecular alterations and interactions, the precise molecular mechanisms of prostate cancer remain poorly understood. The development of prostate cancer is because of the instability of genome. Therefore, comparative analysis of gene expression in prostate cancer and benign prostatic specimens may provide important information relating to malignant transformation of prostatic cells. Nowadays, serum PSA is widely used as a diagnostic marker for prostate cancer. PSA has tissue specificity and only found in prostatic acinus and ductal epithelial cells. However, it had no tumor specificity. Sometimes the benign prostatic hyperplasia and prostatitis could detect positive PSA, therefore, it is hard to predict the presence of prostate cancer from benign prostatic hyperplasia and prostatitis. Thus there is an urgent need for identifying new prostate cancer markers. The gene therapy for prostate cancer need the ideal therapeutic targets too. Recently the emerging technology of DNA microarray provide a powerful tool to investigate the gene expression profile of thousands of genes in prostate cancer.
Objective:
In this present study, we identified the differentially expressed genes between prostate cancer(primary and metastatic) and benign prostate based on DNA microarray. Further, we constructed the regulation networks, protein-protein interaction networks and pathway crosstalk networks to explore the molecular mechanisms of prostate cancer development and progression. We hope our study could aid in detecting the biomarkers of prostate cancer for diagnosis and treatment with prostate cancer.
Methods:
First, we downloaded the transcription profile of GSE3325from GEO, and performed microarray analysis to screen the differentially expressed genes between prostate cancer (primary and metastatic) and benign prostate. The DEGs only with fold change value larger than2or less than-2and p-value less than0.05were selected.
Then we constructed two regulation networks of primary prostate cancer and metastatic prostate cancer by integrating the DEGs and the existing regulation data collected from the database, and analysed the difference of the two networks. In the same way, we constructed the protein-protein interaction networks of primary prostate cancer and metastatic prostate cancer. By calculating the interactive proteins between any two biological pathways, we obtained the interaction significance between any biological pathways.
Results:
1、There are5847differentially expressed genes between the gene expression profiles of primary prostate cancer and the benign prostate tissue, There are2026differentially expressed genes between the gene expression profiles of metastatic prostate cancer and the benign prostate tissue. Total977genes were overlapping, i.e.,977genes were differentially expressed between metastatic prostate cancer compared with primary prostate cancer.
2、We constructed two regulation networks of primary prostate cancer and metastatic prostate cancer by integrating the DEGs and the existing regulation data collected from the database, and performed GO enrichment analysis of genes in the two networks. In the regulation network of primary prostate cancer, the TF MYC with high degree form a local network, and the other TFs, such as E2F1, TP53, ESR1are also hub nodes in the network. In the regulation network of metastatic prostate cancer, the TF MYC plays a vital role as the core of the regulation network.
3、We constructed two protein-protein interaction networks of primary prostate cancer and metastatic prostate cancer. By analyzing the difference of the two networks, we found that the interaction between MMP9and IL8only appeared in metastatic prostate cancer. Total775interactions between662proteins only existed in primary prostate cancer.
4、Total16significant expressed pathways were identified between primary prostate cancer and benign prostate. The GO enrichment analysis of these16pathways shows that a majority of them are related to cell proliferation and tumorigenesis. Compared to benign prostate, there are8significant expressed pathways in metastatic prostate cancer. Seven out of the8pathways also existed in the primary prostate cancer.
前列腺癌是前列腺腺泡细胞异常无序生长的结果,它是一种发生于男性前列腺组织中的恶性肿瘤。目前,前列腺癌是全世界男性第二大最常见的癌症,并且其发病率呈逐年上升趋势。据世界卫生组织(WHO)的统计资料,在2008年,全世界大约有899000个前列腺癌病例,约占到所有男性新增癌症病例的14%。根据WHO的预测,到2030年,全球前列腺癌患者将会在此基础上翻倍(一百七十万个病例)。流行病学研究发现,前列腺癌的发病率具有明显的地理和种族差异。在欧美等发达国家,前列腺癌是是最常见的男性癌症,其死亡率居各种癌症的第二位,仅次于肺癌。在亚非等发展中国家,其发病率虽然低于欧美国家,但近年来的调查表明,随着平均年龄的增加以及生活方式,主要是饮食结构的改变,前列腺癌在亚非等发展中国家的发病率呈现迅速上升的趋势。在我国,前列腺癌在泌尿生殖系统恶性肿瘤的发病率已经从第三位跃居首位,成为危害我国老年男性生命健康的重要疾病。
随着分子生物学研究的迅速发展,对大多数肿瘤的发生和发展,在细胞水平变化和分子水平的变化上,人们都有了更深的认识。研究表明前列腺癌是一种十分复杂的癌症,其发生发展过程存在多因素、多基因相互作用。前列腺癌的发生是由于基因组的不稳定导致基因表达出现异常。已经鉴定出了多条染色体上存在前列腺癌易感基因位点,其中高频出现的染色体有X染色体、1号染色体、3号染色体、8号染色体、15号染色体、17号染色体、19号染色体、20号染色体等。在前列腺癌的发生发展过程中,许多基因产物表现出异常的调控功能,大量的生长因子和它们的受体是过表达的,例如雌激素、雄激素受体、上皮生长因子、白细胞介素6等。这些基因表达的改变可能增强肿瘤细胞的生长、转移和侵袭能力,尤其是Wnt／pcatenin、Hedgehog等多条信号通路的激活可能赋予了它们侵袭的表型。然而,研究人员对于前列腺癌发生发展过程中涉及的机制了解还远远不够。所以,研究良性前列腺组织和前列腺癌的差异表达基因,可以为前列腺细胞由正常状态转变为恶性肿瘤状态提供重要基因水平的依据。
前列腺癌的早期诊断对于前列腺癌的治疗具有重要的临床意义。许多前列腺癌患者在发病过程中不表现任何症状,因而没有及时治疗,最终导致患者死于由前列腺癌引起的其他疾病。这是由于前列腺癌在很多病例中(约占三分之二)呈现缓慢增殖,并且无症状。另一方面,大约三分之一的前列腺癌具有侵袭性,发展迅速的特点,该种类型的前列腺癌是除肺癌以外的第二大致死癌症。因此,前列腺癌的发生发展过程中的差异基因的鉴定对于早期诊断和及时治疗前列腺癌具有重要意义。目前,PSA(prostate specific antigen,前列腺特异抗原)是用于前列腺癌诊断的重要标志物。PSA具有组织特异性,只存在于人前列腺腺泡及导管上皮细胞胞浆中,在人的其它细胞中不表达。但是,PSA并没有肿瘤特异性,良性前列腺增生和前列腺炎也会出现PSA阳性的结果。而且,用基因治疗的手段治疗前列腺癌时,需要在与正常前列腺组织相比,前列腺癌组织中发生差异表达的基因中筛选有效的合适的靶分子。
基因芯片技术的产生使人们可以一次性检测上万个基因的表达谱,面对如此海量的数据,传统的单个基因的分析研究方法已经不适用。基因芯片数据分析是对从基因芯片高密度杂交点阵图中提取的杂交点荧光强度信号进行的定性和定量的分析,通过有效数据筛选、相关基因聚类等方法,最终将海量的芯片数据整合,发现基因表达谱与生物学功能之间可能存在的联系。基因芯片表达谱数据分析将无机的信息数据有有机的生命活动联系起来,解释基因的功能,疾病的分子机理,是生物信息学研究的重要课题。基因芯片技术能够同时、快速、准确地分析数以千计基因组信息,给研究者研究基因表达谱提供了很大的便利,极大的减轻了大规模的筛选前列腺癌差异表达基因的工作量。目前,该技术已经广泛的应用于多种癌症基因表达谱分析、寻找疾病特异基因等方面研究中。
[目的]
本研究利用基因芯片数据分析软件包bioconductor对来自基因表达数据库Gene Expression Omnibus(GEO)的19个前列腺癌基因表达谱芯片数据(良性前列腺组织,原发性前列腺癌,转移性前列腺癌)作进一步生物信息学分析,以了解前列腺癌在各阶段的基因表达变化,并进一步探讨前列腺癌发生、发展过程中肿瘤相关基因表达的变化及其生物学特性,同时通过系统的研究差异表达基因的转录调控网络、蛋白质互作网络和其参与的生物学通路的差异,阐述前列腺癌发展的分子机制。本研究旨在发现前列腺癌治疗和诊断的分子标记物及探讨前列腺癌发生发展的分子机制,有重要的现实意义。本研究为进一步了解前列腺癌发生发展的分子机制和前列腺癌的诊断治疗提供了有用的基础科研资料。
[方法]
首先从NCBI GEO中下载基因芯片GSE3325。通过对该芯片进行分析,分别筛选出原发性前列腺癌、转移性前列腺癌与良性前列腺组织中差异表达有显著性意义的基因。基因表达差异有显著性意义的判定标准为：原发性前列腺癌组织或转移性前列腺癌组织与良性前列腺组织相比,同一条基因的差异表达值(fold change value)大于2或者小于—2,t检验的概率值(p-value)小于0.05。
通过收集整理已有的转录因子与目的基因调控关系数据,结合我们鉴定出的差异表达基因,分别构建原发性前列腺癌和转移性前列腺癌的差异调控网络,并通过GO功能富集分析及生物学通路富集分析,比较这两个网络的功能差异；通过收集整理已有蛋白质互作数据库里的蛋白质相互作用数据,结合我们鉴定出的差异表达基因,分别构建原发性前列腺癌和转移性前列腺癌的蛋白质相互作用网络,并通过GO功能富集分析及生物学通路富集分析比较两个互作网络的功能差异；通过计算任意2个生物学通路之间相互作用的蛋白对来反应任意2个生物学通路的交互作用的显著性。
[结果]
1、在原发性前列腺癌的基因表达谱中筛选出5847个差异表达基因,在转移性前列腺癌的基因表达谱中筛选出2026个差异表达基因,其中两个集合的交集有977个基因,即转移性前列腺癌与原发性前列腺癌相比,有977个基因发生了差异表达。
2、分别构建了良性前列腺组织与原发性前列腺癌差异表达基因调控网络和良性前列腺组织与转移性前列腺癌差异表达基因调控网络,并对这两个网络中的基因进行GO功能富集及生物学通路富集。良性前列腺组织与原发性前列腺癌差异表达基因调控网络中,转录因子MYC在调控网络中起着至关重要的核心作用,转录因子E2F1和TP53、ESRl在调控关系中也起着很重要的作用。良性前列腺组织与转移性前列腺癌差异表达基因调控网络中,MYC在调控网络中起着至关重要的核心作用。本结果说明转录因子MYC在前列腺癌的发生、发展、转移整个过程中都起作用,而转录因子E2F1、TP53和ESR1的调控关系对于前列腺癌由原发性向转移性发展有着重要的作用。
3、分别构建了原发性前列腺癌和转移性前列腺癌的蛋白质相互作用网络,并进行了比较分析,发现只有MMP9与IL8的相互作用只在转移性前列腺癌中出现。另外662个蛋白之间的775个相互作用对只在原发性前列腺癌的相互作用网络中出现。GO功能富集分析发现,原发性前列腺癌和转移性前列腺癌的蛋白质互作网络中基因的功能主要富集细胞周期上。另外,分别对上调基因和下调基因进行GO功能富集发现,原发性前列腺癌的上调基因也集中在细胞周期上,而下调基因主要富集在免疫应答上；转移性前列腺癌的上调基因主要集中在细胞分化上,下调基因主要富集在细胞周期上。
4、原发性前列腺癌与良性前列腺组织相比共有16条显著表达的生物学通路,这16条生物学通路多与细胞增殖和肿瘤发生有关,例如hsa04114(卵母细胞减数分裂),hsa04062(趋化因子信号通路),hsa04330(Notch信号通路),hsa05218(黑素瘤),hsa04310(Wnt信号通路)等等。转移性前列腺癌与良性前列腺组织相比共有8条显著表达的生物学通路,这8条生物学通路中,有7条也存在于原发性前列腺癌与良性前列腺组织相比显著表达的生物学通路中,只有1条不存在,是hsa00534(葡萄胺聚糖生物合成—硫酸乙酰肝素)
Background:
Prostate cancer(PC) is the result of acinus cell growth without control. It is the malignancy only developed in males. To date, PC is the most frequent cancer in males in western countries. As the age indication increases and the dietary ingredient changes in Asia and African, the incidence and death rate of prostate cancer raises gradually in the past decades. Although previous studies revealed that prostate cancer progression is a process involving multiple molecular alterations and interactions, the precise molecular mechanisms of prostate cancer remain poorly understood. The development of prostate cancer is because of the instability of genome. Therefore, comparative analysis of gene expression in prostate cancer and benign prostatic specimens may provide important information relating to malignant transformation of prostatic cells. Nowadays, serum PSA is widely used as a diagnostic marker for prostate cancer. PSA has tissue specificity and only found in prostatic acinus and ductal epithelial cells. However, it had no tumor specificity. Sometimes the benign prostatic hyperplasia and prostatitis could detect positive PSA, therefore, it is hard to predict the presence of prostate cancer from benign prostatic hyperplasia and prostatitis. Thus there is an urgent need for identifying new prostate cancer markers. The gene therapy for prostate cancer need the ideal therapeutic targets too. Recently the emerging technology of DNA microarray provide a powerful tool to investigate the gene expression profile of thousands of genes in prostate cancer.
Objective:
In this present study, we identified the differentially expressed genes between prostate cancer(primary and metastatic) and benign prostate based on DNA microarray. Further, we constructed the regulation networks, protein-protein interaction networks and pathway crosstalk networks to explore the molecular mechanisms of prostate cancer development and progression. We hope our study could aid in detecting the biomarkers of prostate cancer for diagnosis and treatment with prostate cancer.
Methods:
First, we downloaded the transcription profile of GSE3325from GEO, and performed microarray analysis to screen the differentially expressed genes between prostate cancer (primary and metastatic) and benign prostate. The DEGs only with fold change value larger than2or less than-2and p-value less than0.05were selected.
Then we constructed two regulation networks of primary prostate cancer and metastatic prostate cancer by integrating the DEGs and the existing regulation data collected from the database, and analysed the difference of the two networks. In the same way, we constructed the protein-protein interaction networks of primary prostate cancer and metastatic prostate cancer. By calculating the interactive proteins between any two biological pathways, we obtained the interaction significance between any biological pathways.
Results:
1、There are5847differentially expressed genes between the gene expression profiles of primary prostate cancer and the benign prostate tissue, There are2026differentially expressed genes between the gene expression profiles of metastatic prostate cancer and the benign prostate tissue. Total977genes were overlapping, i.e.,977genes were differentially expressed between metastatic prostate cancer compared with primary prostate cancer.
2、We constructed two regulation networks of primary prostate cancer and metastatic prostate cancer by integrating the DEGs and the existing regulation data collected from the database, and performed GO enrichment analysis of genes in the two networks. In the regulation network of primary prostate cancer, the TF MYC with high degree form a local network, and the other TFs, such as E2F1, TP53, ESR1are also hub nodes in the network. In the regulation network of metastatic prostate cancer, the TF MYC plays a vital role as the core of the regulation network.
3、We constructed two protein-protein interaction networks of primary prostate cancer and metastatic prostate cancer. By analyzing the difference of the two networks, we found that the interaction between MMP9and IL8only appeared in metastatic prostate cancer. Total775interactions between662proteins only existed in primary prostate cancer.
4、Total16significant expressed pathways were identified between primary prostate cancer and benign prostate. The GO enrichment analysis of these16pathways shows that a majority of them are related to cell proliferation and tumorigenesis. Compared to benign prostate, there are8significant expressed pathways in metastatic prostate cancer. Seven out of the8pathways also existed in the primary prostate cancer.
引文
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