口腔鳞状细胞癌的生物信息学分析
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摘要
口腔鳞状细胞癌是口腔颌面部最常见的恶性肿瘤。它具有恶性程度高,淋巴结易转移,预后差等特点。从分子水平研究口腔鳞状细胞癌的发生发展,对于口腔鳞状细胞癌的预防、控制和治疗具有重要意义。
生物信息学是一门交叉学科。它整合了信息学、统计学和计算机学等多种技术分析海量生物数据所包含的信息。它先对生物芯片的海量数据进行筛选,再采用序列比对、统计分析、生物聚类、通路分析、可视化作图等方式,进行数据挖掘,从而对疾病从分子水平进行分析,丰富对疾病进展的认识。随着生物信息学的发展,形成了新的生物学研究模式,即利用现有的数据信息,先作理论推测,再行实验验证。
本研究课题以GEO及TCGA数据库为研究基础,采用BRB-ArrayTools软件分别筛选口腔鳞状细胞癌中差异表达的基因、microRNA及lncRNA,联合生物信息软件和文献挖掘等方法对他们之间相互作用关系进行分析,从而探索与口腔鳞状细胞癌相关的基因、microRNA及lncRNA,为更好地理解口腔鳞状细胞癌发生、发展的分子机制提供重要的信息,为进一步研究口腔鳞状细胞癌的发生、发展提供新的方向。
第一部分：口腔鳞状细胞癌差异表达基因的生物信息学分析
研究背景：口腔鳞状细胞癌是目前我国常见的肿瘤之一。我国口腔鳞状细胞癌的发病率约在3.6/10万-8.0/10万人。现已证实,口腔鳞状细胞癌是复杂的多基因疾病,环境因素和遗传因素共同参与了疾病的发生和发展。基因芯片因其具有高通量、高特异性、快速等特点,可检测基因的丰度和种类,并从整个基因组层面进行相关分析。
目的：通过对多个口腔鳞状细胞癌表达芯片的生物信息学分析,筛选与该肿瘤相关的差异表达基因,对差异表达基因进行功能注释、通路分析及蛋白质互作网络分析,为探索口腔鳞状细胞癌发生、发展的分子机制提供理论基础。
方法：本课题整理GEO公共数据库的基因芯片数据集,以针对口腔鳞状细胞癌目标的Affymetrix芯片表达谱数据作为研究对象,系统地分析口腔鳞状细胞癌的基因表达谱芯片数据,进行数据预处理后,选择非配对t检验统计方法筛选差异表达基因,应用DAVID软件选取GO数据库进行功能注释、KEGG数据库进行通路分析,导入STRING在线数据库绘制差异表达基因编码蛋白互作网络图,并应用Cytoscape软件计算网络及各节点的拓扑特性。
结果：(1)本研究在口腔鳞状细胞癌中发现92个基因表达异常,其中表达上调的61个,表达下调的31个。(2)GO分析发现表达上调的差异表达基因主要集中在对损伤的反应、胶原代谢过程、多细胞生物大分子代谢过程等。其中参与胶原代谢过程有MMP9、MMP1、MMP10、MMP11、MMP3、MMP7等基因。KEGG通路分析发现,表达上调的差异表达基因主要集中在细胞外基质受体相互作用、黏着斑、肿瘤通路、Toller样受体通路等通路。(3)GO分析发现表达下调的差异表达基因主要集中在上皮细胞分化、上皮发育、表皮发育、外胚层发育等过程。KEGG通路分析发现,表达下调的差异表达基因主要集中在通过视黄醇的代谢、细胞色素p450外源性物质代谢、药物代谢等通路。(4)经STRING软件共筛选出35个差异表达基因编码的蛋白产物存在相互作用,构建差异表达基因互作网络图,Cytoscape软件共筛选五个关键基因,分别为MMP-9、MMP-1、 COL1A2、MMP-7、PLAU。
结论：(1)成功筛选出口腔鳞状细胞癌中差异表达的92个基因,并对其进行功能注释与通路分析,为该疾病的实验室研究提供了理论基础。(2)成功构建口腔鳞状细胞癌差异表达基因的蛋白质相互作用网络,并筛选出五个关键基因,提示MMPs家族成员可能参与在口腔鳞状细胞癌发展过程,有利于进一步研究差异表达基因的相互作用关系,并为该疾病的诊断和治疗提供了研究方向。
第二部分口腔鳞状细胞癌差异表达microRNA的生物信息学分析
研究背景：microRNA是内源性非编码小RNA(18-25nt)的总称。microRNA通过转录后抑制基因的表达。它可以通过与靶基因mRNA的3’端非翻译区(3'-untranslationalregion,3'-UTR)结合达到抑制蛋白翻译的作用。目前发现miRNA可调节约60%的基因,且可能与多种不同的靶基因有调控关系。越来越多的研究发现,miRNA在细胞的生长、分化、增殖和调亡等重要过程发挥了重要的作用,并参与了肿瘤的发生发展过程。
目的：通过整理TCGA数据库的口腔鳞状细胞癌miRNA数据,并进行生物信息学分析,探索口腔鳞状细胞癌差异表达miRNA,进一步研究其靶基因的作用。
方法：本研究利用BRB-ArrayTools对来自TCGA数据库的口腔鳞状细胞癌miRNA进行分析,得到差异表达miRNA;通过miRecords预测差异miRNA的靶基因,对差异靶基因进行GO功能注释、KEGG通路分析,应用STRING在线数据库绘制靶基因编码蛋白互作网络图,并应用Cytoscape软件计算网络及各节点的拓扑特性。
结果：(1)采用BRB-ArrayTools分析TCGA数据集中miRNA表达谱的数据,我们发现了53个显著差异的miRNA。(2)针对差异靶基因的GO功能注释发现,差异表达的靶基因参与细胞增殖的调节、内源性刺激应答、有机物质应答、激素刺激应答等功能。(3)KEGG通路分析中,差异表达靶基因主要参与了细胞因子及其受体的相互作用、MAPK信号通路、Wnt信号通路、Jak-STAT信号通路。(4)经STRING软件在线数据库分析共筛选出73个差异表达microRNA的靶基因存在相互作用,构建靶基因编码蛋白互作网络图；Cytoscape软件共筛选出十二个关键靶基因,分别为STAT3, CCND1, PTGS2, IL8, PPARG, ERBB2, MMP2, PLAU, FGF1, CASP3, FASLG和IL10.
结论：(1)成功筛选口腔鳞状细胞癌中差异表达的microRNA。其中,miR-375可能是口腔鳞状细胞癌分子标志物。miR-21、miR-101、let-7c和mir-200c表达异常为研究口腔鳞状细胞癌EMT过程提供了生物信息学证据。(2)差异表达microRNA的靶基因主要参与细胞增殖的调节、内源性刺激应答、有机物质应答、激素刺激应答等功能。(3)差异表达microRNA的靶基因主要参与了细胞因子及其受体的相互作用、MAPK信号通路、Wnt信号通路、Jak-STAT信号通路。(4)成功构建差异表达microRNA对应靶基因的蛋白质相互作用网络图,并筛选出12个关键靶基因。
第三部分口腔鳞状细胞癌差异表达长链非编码RNA的生物信息学分析
研究背景：长链非编码RNA (long non-coding RNA, lncRNA)因其在生物基因调控方面的潜在巨大作用,在近几年获得广泛关注。研究显示长链非编码RNA和疾病发生及发展进程相关,但是其发挥作用的具体机制尚不十分清楚。目前lncRNA在口腔鳞状细胞癌中作用及机制知之甚少。
目的：本研究拟通过生物信息学的方法,分析GEO数据库中的口腔鳞状细胞癌数据,探索口腔鳞状细胞癌中的差异表达lncRNA,为后续研究lncRNA在口腔鳞状细胞癌中的作用机制提供了新的思路。
方法：本研究利用BRB-ArrayTools对GEO数据库的口腔鳞状细胞癌数据集进行分析,筛选得到差异lncRNA。
结果：本部分研究发现,与正常组织相比,口腔鳞状细胞癌17个lncRNA的表达出现差异。其中表达上调的有4个,表达下调的有13个。H19在口腔鳞状细胞癌中表达显著下调。
结论：(1)成功筛选出口腔鳞状细胞癌中差异表达的lncRNA17个,为进一步研究lncRNA在该疾病中的作用提供了方向。(2)LncRNA H19在口腔鳞状细胞癌中表达下调,提示其可能与mir-200家族作用,调控了口腔鳞状细胞癌上皮-间质转变(EMT)的生物学过程。
Oral squamous cell carcinoma (OSCC) is the most common malignant oral cancer. It has properties of aggressive malignancy, high likelihood of lymphatic metastasis and poor prognosis. Research on the occurrence and development of OSCC plays an important role in the tumor prevention, control and treatment.
Bioinformatics is an interdisciplinary subject that integrates the knowledge of biology, information and computer science to analyze the biological information contained massive biological data. By filtering massive data of biological chips and utilizing techniques such as sequence alignment, statistical analysis, clustering, visualization, and biological pathway analysis etc. to implement data mining, bioinformatics enriches the understandings about tumor occurrence and progression from molecular level. With the development of bioinformatics, a new biological research pattern is emerged. In this research pattern, researchers propose hypothesis based on the existing data and test the hypothesis.
Based on GEO and TCGA database, this research screens microRNA,and lncRNA expression in OSCC by using BRB-ArrayTools software, analyzes the interaction between them by combining with bioinformatics software and text mining techniques, so that explores gene, microRNA and lncRNA associated with OSCC. It provides critical information for better understanding on the molecular mechanism of OSCC occurrence and development.
Part Ⅰ:Bioinformatics analysis of differentially expressed genes in oral squamous cell carcinoma
Background:Oral squamous cell carcinoma (OSCC) is one of the common tumors national wide. The incidence of OSCC is about3.6to8.0per100thousands people. It has been confirmed that OSCC is a complex multi-gene diseases. The occurrence and development of this disease are influenced by both environmental and genetic factors. Gene chip is useful in detecting the abundance of genes in the genome level of gene analysis because of its high throughput, high speed and high specificity properties.
Objective:To provide theoretical base for the mechanism of the development of OSCC by screening differential genes related to this tumor based on bioinformatics analysis of multiple chips of OSCC and implementing GO analysis> KEGG pathway analysis、protein-protein interaction network analysis.
Methodology:In this research, we chose microarray datasets from GEO and analyzed OSCC microarray data thoroughly using the Affymetrix microarray gene expression data. After pre-processing the data, we used unpaired t-test to screen differential genes. Finally, we used analysis tools in DAVID software for GO analysis and KEGG pathway analysis, imported STRING online database for protein-protein interaction network analysis, and computed the network topology through Cytoscape software.
Results:(1) We discovered92differentially expressed genes in OSCC in which61are up-regulated and31are down-regulated.(2) GO analysis indicated that up-regulated genes are mainly enriched in response to wounding, collagen metabolic process and multicellular organismal macromolecule metabolic process. MMP9, MMP1, MMP10, MMP11, MMP3, MMP7genes are involved in collagen metabolism. KEGG pathway analysis showed that these up-regulated genes are mainly enriched in the ECM-receptor interaction, focal adhesion,pathways in cancer, Toller-like receptor signaling pathway and other pathways.(3) Down-regulated genes mainly enriched in GO categories including epithelial cell differentiation, epithelium development, epidermis development, ectoderm development. KEGG pathway analysis revealed that these down-regulated genes are mainly enriched in retinol metabolism, metabolism of xenobiotics by cytochrome p450, drug metabolism.(4)35genes were screened to constructing interaction network though STRING software. Cytoscape software screened five key genes:MMP-9, MMP-1, COL1A2, MMP-7, PLAU.
Conclusion:(1) We screened92differentially expressed genes in OSCC and conducted GO analysis and KEGG pathway analysis. We provided theoretical base for the lab research on OSCC.(2) We constructed protein-protein interaction network of differentially expressed genes and identified five key genes. We discovered that MMPs family may be involved in the development of OSCC so that provided direction for further research.
Part II:Bioinformatics analysis of differentially expressed microRNAs in oral squamous cell carcinoma
Background:microRNA is endogenous non-coding RNA (18-25nt). It represses gene expression through post-transcription. It can bind the3'untranslated region (3'-untranslationalregion,3'UTR) to inhibit protein translation. MicroRNA are found to regulate60%of human genes, and may have regulating relationship among different target genes. More and more studies discovered that microRNA could play an important role in cell growth, differentiation, proliferation and apoptosis, and participate in occurrence and progression of OSCC.
Objective:To implement bioinformatics analysis and explore differential microRNA in OSCC based on the organized microRNA data of OSCC from TCGA database. Furthermore, support the study on the role of target genes in the future.
Methodology:To obtain the differential microRNA, we use BRB-Arraytools to analyze microRNA in OSCC from TCGA. MiRecords was used to predict microRNA target genes. Furthermore, we applied GO analysis and KEGG pathway analysis, imported STRING online database for protein-protein interaction network analysis, and computed the network topology through Cytoscape software.
Results:(1) We obtained53differentially expressed miRNA, and miR-375may be a molecular marker of OSCC.Differential expression of miR-21、miR-101、let-7c and miR-200c provide bio-informational evidence for EMT process in OSCC.(2) GO analysis of target gene expression showed that target gene are involved in the regulation of cell proliferation, response to endogenousstimulus, response to organic substance and response to hormone stimulus.(3) KEGG pathway analysis disclosed that the target gene primarily participated in cell factor and its receptor interaction, MAPK signaling pathway, Wnt signaling pathway, and Jak-STAT signaling pathway.(4)73differentially expressed microRNA target genes have interactions and the protein-protein interaction network has been constructed by STRING software. Twelve key target genes were screened by Cytoscape software:STAT3,CCND1, PTGS2,IL8,PPARG,ERBB2,MMP2,PLAU,FGF1,CASP3,FASLG and IL10.
Conclusions:(1) Differentially expressed microRNA of OSCC were identified. MiR-375may be the molecular markers in oral squamous cell carcinoma. The results that mir-200c is down-related suggest it may involves in EMT of OSCC.(2)Target genes of differentially expressed microRNA play a part in the regulation of cell proliferation, stimulation of the endogenous response, the response of organic substances, and hormones stimulate the response functions.(3)Target genes of differentially expressed microRNA primarily participate in the interaction of cytokines and their receptors, MAPK signaling pathway, Wnt signaling pathway, and Jak-STAT signaling pathway.(4) Protein-protein interaction network of target genes in OSCC was constructed and twelve key genes were identified.
Part Ⅲ:Bioinformatic analysis of differentially expressed lncRNA in oral squamous cell carcinoma
Background:Long-chain non-coding RNA (long non-coding RNA) plays a potentially critical role in the biological aspects of gene regulation. Researches have publicized that lncRNA are related in the occurrence and progression of diseases. However, its functional mechanism is still unclear. Currently, the influence of lncRNA in OSCC is still poorly understood.
Objective:To implement bioinformatics analysis and explore differentially expressed lncRNA in OSCC based on organized lncRNA data of oral squamous cell from GEO database. Moreover, to provide a new researching methodology in studying the mechanism of lncRNA in OSCC.
Methodology:We use BRB Arraytools to analyze and screen the differentially expressed lncRNA of OSCC from the GEO database.
Results:Comparing with normal tissue, we discovered17differentially expressed lncRNAs in oral squamous cell carcinoma, in which4up-regulated lncRNAs and13down-regulated lncRNAs. H19was significantly down-regulated in OSCC.
Conclusions:(1)17differentially expressed lncRNA of OSCC were identified. This discovery provide new research direction in the function of lncRNA in OSCC.(2) H19was down-regulated in OSCC, which suggests that H19may interact with mir-200s and control the process of epithelial-mesenchymal transition (EMT) of OSCC.
生物信息学是一门交叉学科。它整合了信息学、统计学和计算机学等多种技术分析海量生物数据所包含的信息。它先对生物芯片的海量数据进行筛选,再采用序列比对、统计分析、生物聚类、通路分析、可视化作图等方式,进行数据挖掘,从而对疾病从分子水平进行分析,丰富对疾病进展的认识。随着生物信息学的发展,形成了新的生物学研究模式,即利用现有的数据信息,先作理论推测,再行实验验证。
本研究课题以GEO及TCGA数据库为研究基础,采用BRB-ArrayTools软件分别筛选口腔鳞状细胞癌中差异表达的基因、microRNA及lncRNA,联合生物信息软件和文献挖掘等方法对他们之间相互作用关系进行分析,从而探索与口腔鳞状细胞癌相关的基因、microRNA及lncRNA,为更好地理解口腔鳞状细胞癌发生、发展的分子机制提供重要的信息,为进一步研究口腔鳞状细胞癌的发生、发展提供新的方向。
第一部分：口腔鳞状细胞癌差异表达基因的生物信息学分析
研究背景：口腔鳞状细胞癌是目前我国常见的肿瘤之一。我国口腔鳞状细胞癌的发病率约在3.6/10万-8.0/10万人。现已证实,口腔鳞状细胞癌是复杂的多基因疾病,环境因素和遗传因素共同参与了疾病的发生和发展。基因芯片因其具有高通量、高特异性、快速等特点,可检测基因的丰度和种类,并从整个基因组层面进行相关分析。
目的：通过对多个口腔鳞状细胞癌表达芯片的生物信息学分析,筛选与该肿瘤相关的差异表达基因,对差异表达基因进行功能注释、通路分析及蛋白质互作网络分析,为探索口腔鳞状细胞癌发生、发展的分子机制提供理论基础。
方法：本课题整理GEO公共数据库的基因芯片数据集,以针对口腔鳞状细胞癌目标的Affymetrix芯片表达谱数据作为研究对象,系统地分析口腔鳞状细胞癌的基因表达谱芯片数据,进行数据预处理后,选择非配对t检验统计方法筛选差异表达基因,应用DAVID软件选取GO数据库进行功能注释、KEGG数据库进行通路分析,导入STRING在线数据库绘制差异表达基因编码蛋白互作网络图,并应用Cytoscape软件计算网络及各节点的拓扑特性。
结果：(1)本研究在口腔鳞状细胞癌中发现92个基因表达异常,其中表达上调的61个,表达下调的31个。(2)GO分析发现表达上调的差异表达基因主要集中在对损伤的反应、胶原代谢过程、多细胞生物大分子代谢过程等。其中参与胶原代谢过程有MMP9、MMP1、MMP10、MMP11、MMP3、MMP7等基因。KEGG通路分析发现,表达上调的差异表达基因主要集中在细胞外基质受体相互作用、黏着斑、肿瘤通路、Toller样受体通路等通路。(3)GO分析发现表达下调的差异表达基因主要集中在上皮细胞分化、上皮发育、表皮发育、外胚层发育等过程。KEGG通路分析发现,表达下调的差异表达基因主要集中在通过视黄醇的代谢、细胞色素p450外源性物质代谢、药物代谢等通路。(4)经STRING软件共筛选出35个差异表达基因编码的蛋白产物存在相互作用,构建差异表达基因互作网络图,Cytoscape软件共筛选五个关键基因,分别为MMP-9、MMP-1、 COL1A2、MMP-7、PLAU。
结论：(1)成功筛选出口腔鳞状细胞癌中差异表达的92个基因,并对其进行功能注释与通路分析,为该疾病的实验室研究提供了理论基础。(2)成功构建口腔鳞状细胞癌差异表达基因的蛋白质相互作用网络,并筛选出五个关键基因,提示MMPs家族成员可能参与在口腔鳞状细胞癌发展过程,有利于进一步研究差异表达基因的相互作用关系,并为该疾病的诊断和治疗提供了研究方向。
第二部分口腔鳞状细胞癌差异表达microRNA的生物信息学分析
研究背景：microRNA是内源性非编码小RNA(18-25nt)的总称。microRNA通过转录后抑制基因的表达。它可以通过与靶基因mRNA的3’端非翻译区(3'-untranslationalregion,3'-UTR)结合达到抑制蛋白翻译的作用。目前发现miRNA可调节约60%的基因,且可能与多种不同的靶基因有调控关系。越来越多的研究发现,miRNA在细胞的生长、分化、增殖和调亡等重要过程发挥了重要的作用,并参与了肿瘤的发生发展过程。
目的：通过整理TCGA数据库的口腔鳞状细胞癌miRNA数据,并进行生物信息学分析,探索口腔鳞状细胞癌差异表达miRNA,进一步研究其靶基因的作用。
方法：本研究利用BRB-ArrayTools对来自TCGA数据库的口腔鳞状细胞癌miRNA进行分析,得到差异表达miRNA;通过miRecords预测差异miRNA的靶基因,对差异靶基因进行GO功能注释、KEGG通路分析,应用STRING在线数据库绘制靶基因编码蛋白互作网络图,并应用Cytoscape软件计算网络及各节点的拓扑特性。
结果：(1)采用BRB-ArrayTools分析TCGA数据集中miRNA表达谱的数据,我们发现了53个显著差异的miRNA。(2)针对差异靶基因的GO功能注释发现,差异表达的靶基因参与细胞增殖的调节、内源性刺激应答、有机物质应答、激素刺激应答等功能。(3)KEGG通路分析中,差异表达靶基因主要参与了细胞因子及其受体的相互作用、MAPK信号通路、Wnt信号通路、Jak-STAT信号通路。(4)经STRING软件在线数据库分析共筛选出73个差异表达microRNA的靶基因存在相互作用,构建靶基因编码蛋白互作网络图；Cytoscape软件共筛选出十二个关键靶基因,分别为STAT3, CCND1, PTGS2, IL8, PPARG, ERBB2, MMP2, PLAU, FGF1, CASP3, FASLG和IL10.
结论：(1)成功筛选口腔鳞状细胞癌中差异表达的microRNA。其中,miR-375可能是口腔鳞状细胞癌分子标志物。miR-21、miR-101、let-7c和mir-200c表达异常为研究口腔鳞状细胞癌EMT过程提供了生物信息学证据。(2)差异表达microRNA的靶基因主要参与细胞增殖的调节、内源性刺激应答、有机物质应答、激素刺激应答等功能。(3)差异表达microRNA的靶基因主要参与了细胞因子及其受体的相互作用、MAPK信号通路、Wnt信号通路、Jak-STAT信号通路。(4)成功构建差异表达microRNA对应靶基因的蛋白质相互作用网络图,并筛选出12个关键靶基因。
第三部分口腔鳞状细胞癌差异表达长链非编码RNA的生物信息学分析
研究背景：长链非编码RNA (long non-coding RNA, lncRNA)因其在生物基因调控方面的潜在巨大作用,在近几年获得广泛关注。研究显示长链非编码RNA和疾病发生及发展进程相关,但是其发挥作用的具体机制尚不十分清楚。目前lncRNA在口腔鳞状细胞癌中作用及机制知之甚少。
目的：本研究拟通过生物信息学的方法,分析GEO数据库中的口腔鳞状细胞癌数据,探索口腔鳞状细胞癌中的差异表达lncRNA,为后续研究lncRNA在口腔鳞状细胞癌中的作用机制提供了新的思路。
方法：本研究利用BRB-ArrayTools对GEO数据库的口腔鳞状细胞癌数据集进行分析,筛选得到差异lncRNA。
结果：本部分研究发现,与正常组织相比,口腔鳞状细胞癌17个lncRNA的表达出现差异。其中表达上调的有4个,表达下调的有13个。H19在口腔鳞状细胞癌中表达显著下调。
结论：(1)成功筛选出口腔鳞状细胞癌中差异表达的lncRNA17个,为进一步研究lncRNA在该疾病中的作用提供了方向。(2)LncRNA H19在口腔鳞状细胞癌中表达下调,提示其可能与mir-200家族作用,调控了口腔鳞状细胞癌上皮-间质转变(EMT)的生物学过程。
Oral squamous cell carcinoma (OSCC) is the most common malignant oral cancer. It has properties of aggressive malignancy, high likelihood of lymphatic metastasis and poor prognosis. Research on the occurrence and development of OSCC plays an important role in the tumor prevention, control and treatment.
Bioinformatics is an interdisciplinary subject that integrates the knowledge of biology, information and computer science to analyze the biological information contained massive biological data. By filtering massive data of biological chips and utilizing techniques such as sequence alignment, statistical analysis, clustering, visualization, and biological pathway analysis etc. to implement data mining, bioinformatics enriches the understandings about tumor occurrence and progression from molecular level. With the development of bioinformatics, a new biological research pattern is emerged. In this research pattern, researchers propose hypothesis based on the existing data and test the hypothesis.
Based on GEO and TCGA database, this research screens microRNA,and lncRNA expression in OSCC by using BRB-ArrayTools software, analyzes the interaction between them by combining with bioinformatics software and text mining techniques, so that explores gene, microRNA and lncRNA associated with OSCC. It provides critical information for better understanding on the molecular mechanism of OSCC occurrence and development.
Part Ⅰ:Bioinformatics analysis of differentially expressed genes in oral squamous cell carcinoma
Background:Oral squamous cell carcinoma (OSCC) is one of the common tumors national wide. The incidence of OSCC is about3.6to8.0per100thousands people. It has been confirmed that OSCC is a complex multi-gene diseases. The occurrence and development of this disease are influenced by both environmental and genetic factors. Gene chip is useful in detecting the abundance of genes in the genome level of gene analysis because of its high throughput, high speed and high specificity properties.
Objective:To provide theoretical base for the mechanism of the development of OSCC by screening differential genes related to this tumor based on bioinformatics analysis of multiple chips of OSCC and implementing GO analysis> KEGG pathway analysis、protein-protein interaction network analysis.
Methodology:In this research, we chose microarray datasets from GEO and analyzed OSCC microarray data thoroughly using the Affymetrix microarray gene expression data. After pre-processing the data, we used unpaired t-test to screen differential genes. Finally, we used analysis tools in DAVID software for GO analysis and KEGG pathway analysis, imported STRING online database for protein-protein interaction network analysis, and computed the network topology through Cytoscape software.
Results:(1) We discovered92differentially expressed genes in OSCC in which61are up-regulated and31are down-regulated.(2) GO analysis indicated that up-regulated genes are mainly enriched in response to wounding, collagen metabolic process and multicellular organismal macromolecule metabolic process. MMP9, MMP1, MMP10, MMP11, MMP3, MMP7genes are involved in collagen metabolism. KEGG pathway analysis showed that these up-regulated genes are mainly enriched in the ECM-receptor interaction, focal adhesion,pathways in cancer, Toller-like receptor signaling pathway and other pathways.(3) Down-regulated genes mainly enriched in GO categories including epithelial cell differentiation, epithelium development, epidermis development, ectoderm development. KEGG pathway analysis revealed that these down-regulated genes are mainly enriched in retinol metabolism, metabolism of xenobiotics by cytochrome p450, drug metabolism.(4)35genes were screened to constructing interaction network though STRING software. Cytoscape software screened five key genes:MMP-9, MMP-1, COL1A2, MMP-7, PLAU.
Conclusion:(1) We screened92differentially expressed genes in OSCC and conducted GO analysis and KEGG pathway analysis. We provided theoretical base for the lab research on OSCC.(2) We constructed protein-protein interaction network of differentially expressed genes and identified five key genes. We discovered that MMPs family may be involved in the development of OSCC so that provided direction for further research.
Part II:Bioinformatics analysis of differentially expressed microRNAs in oral squamous cell carcinoma
Background:microRNA is endogenous non-coding RNA (18-25nt). It represses gene expression through post-transcription. It can bind the3'untranslated region (3'-untranslationalregion,3'UTR) to inhibit protein translation. MicroRNA are found to regulate60%of human genes, and may have regulating relationship among different target genes. More and more studies discovered that microRNA could play an important role in cell growth, differentiation, proliferation and apoptosis, and participate in occurrence and progression of OSCC.
Objective:To implement bioinformatics analysis and explore differential microRNA in OSCC based on the organized microRNA data of OSCC from TCGA database. Furthermore, support the study on the role of target genes in the future.
Methodology:To obtain the differential microRNA, we use BRB-Arraytools to analyze microRNA in OSCC from TCGA. MiRecords was used to predict microRNA target genes. Furthermore, we applied GO analysis and KEGG pathway analysis, imported STRING online database for protein-protein interaction network analysis, and computed the network topology through Cytoscape software.
Results:(1) We obtained53differentially expressed miRNA, and miR-375may be a molecular marker of OSCC.Differential expression of miR-21、miR-101、let-7c and miR-200c provide bio-informational evidence for EMT process in OSCC.(2) GO analysis of target gene expression showed that target gene are involved in the regulation of cell proliferation, response to endogenousstimulus, response to organic substance and response to hormone stimulus.(3) KEGG pathway analysis disclosed that the target gene primarily participated in cell factor and its receptor interaction, MAPK signaling pathway, Wnt signaling pathway, and Jak-STAT signaling pathway.(4)73differentially expressed microRNA target genes have interactions and the protein-protein interaction network has been constructed by STRING software. Twelve key target genes were screened by Cytoscape software:STAT3,CCND1, PTGS2,IL8,PPARG,ERBB2,MMP2,PLAU,FGF1,CASP3,FASLG and IL10.
Conclusions:(1) Differentially expressed microRNA of OSCC were identified. MiR-375may be the molecular markers in oral squamous cell carcinoma. The results that mir-200c is down-related suggest it may involves in EMT of OSCC.(2)Target genes of differentially expressed microRNA play a part in the regulation of cell proliferation, stimulation of the endogenous response, the response of organic substances, and hormones stimulate the response functions.(3)Target genes of differentially expressed microRNA primarily participate in the interaction of cytokines and their receptors, MAPK signaling pathway, Wnt signaling pathway, and Jak-STAT signaling pathway.(4) Protein-protein interaction network of target genes in OSCC was constructed and twelve key genes were identified.
Part Ⅲ:Bioinformatic analysis of differentially expressed lncRNA in oral squamous cell carcinoma
Background:Long-chain non-coding RNA (long non-coding RNA) plays a potentially critical role in the biological aspects of gene regulation. Researches have publicized that lncRNA are related in the occurrence and progression of diseases. However, its functional mechanism is still unclear. Currently, the influence of lncRNA in OSCC is still poorly understood.
Objective:To implement bioinformatics analysis and explore differentially expressed lncRNA in OSCC based on organized lncRNA data of oral squamous cell from GEO database. Moreover, to provide a new researching methodology in studying the mechanism of lncRNA in OSCC.
Methodology:We use BRB Arraytools to analyze and screen the differentially expressed lncRNA of OSCC from the GEO database.
Results:Comparing with normal tissue, we discovered17differentially expressed lncRNAs in oral squamous cell carcinoma, in which4up-regulated lncRNAs and13down-regulated lncRNAs. H19was significantly down-regulated in OSCC.
Conclusions:(1)17differentially expressed lncRNA of OSCC were identified. This discovery provide new research direction in the function of lncRNA in OSCC.(2) H19was down-regulated in OSCC, which suggests that H19may interact with mir-200s and control the process of epithelial-mesenchymal transition (EMT) of OSCC.
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