基于文献挖掘的前列腺癌蛋白组学与基因组学差异基因的生物信息学分析

发布时间：2017-12-31 06:40

本文关键词：基于文献挖掘的前列腺癌蛋白组学与基因组学差异基因的生物信息学分析　出处：《中国全科医学》2015年32期 　论文类型：期刊论文

【摘要】：目的通过前列腺癌(PCa)蛋白组学与基因组学文献,挖掘与PCa存在相关性并缺乏具体研究的差异基因,并分析其参与的生物过程与通路。方法计算机检索Pub Med数据库,检索策略:"(prostate cancer[Title])AND Proteomics""(prostate cancer[Title])AND Genomics",时间限定为建库至2015年1月。按照PCa与前列腺增生(BPH)组织(A组)、PCa与邻近良性组织(B组)、PCa高Gleason评分与低Gleason评分(C组)蛋白谱和基因谱的比较提取差异蛋白或基因,输入"The Protein Information Resource(PIR,Georgetown University Medical Center,Washington,DC 20007,USA)",按照"official gene symbol"统一名称。采用"DAVID Bioinformatics Resources 6.7(National Institute of Allergy and Infectious Diseases,NIH,USA)"在线工具对差异基因进行GO(Gene Ontology)、KEGG等生物信息学分析。结果共纳入35篇文献,提取差异基因764个,其中A组差异基因162个,B组差异基因423个,C组差异基因209个,3组共同差异基因21个。A组差异基因中DES报道最多,为6次;B组差异基因ACPP报道最多,为4次;C组差异基因ACTN1、HSPB1、LMNA报道最多,均为3次。GO分析结果显示,差异基因涉及的生物过程主要有细胞死亡调控、细胞增殖调控、创伤反应、蛋白质转运、稳态过程(差异基因频数≥72,频率≥9.4%),细胞成分主要涉及胞外区、膜封闭腔、细胞骨架、囊泡以及线粒体(差异基因频数≥85,频率≥11.1%),分子功能主要涉及核苷酸结合、钙离子结合、相同蛋白结合以及酶结合(差异基因频数≥60,频率≥7.9%)。KEGG通路分析发现,差异基因主要参与癌症通路、黏着斑、肌动蛋白细胞骨架调控、MAPK信号等生物学通路(差异基因频数≥29,频率≥3.8%)。对各组差异基因进行KEGG通路分析结果显示,各组差异基因共同参与的KEGG通路主要有黏着斑、补体及凝血级联、ECM受体相互作用等生物学通路。结论差异基因DES、ACTN1、ATP5B、TLN1、COL6A2、MYH9、OGN、PGAM1报道次数较多,而其参与PCa发生发展的具体机制未见报道,值得进一步实验验证。黏着斑、肌动蛋白细胞骨架的调控以及MAPK信号通路可能在PCa发生发展过程中发挥重要作用,对其进一步分析将为临床治疗PCa提供新的靶点。
[Abstract]:Objective to prostate cancer (PCa) proteomics and genomics literature, mining and the relationship of PCa gene and the difference is lack of specific research, and analysis of biological processes and pathways involved. Methods we searched the Pub Med database, retrieval strategy: "(prostate cancer[Title]) AND Proteomics" (prostate cancer[Title]) AND Genomics "the time limit for up to January 2015. According to PCa and benign prostatic hyperplasia (BPH) group (group A), PCa and the adjacent benign tissue (group B), PCa Gleason high score and low Gleason score (group C) compare the differential extraction of gene or protein protein gene spectrum and the spectrum of the input" The Protein Information Resource (PIR Georgetown, University Medical Center, Washington, DC 20007, USA), in accordance with the "official gene symbol" unified name. By "DAVID Resources 6.7 Bioinformatics (National Institute of Allergy and Infectious Diseases, NIH, USA) "online tools for GO (Gene Ontology) of different genes, bioinformatics analysis of KEGG. Results a total of 35 articles were included, of which 764 genes of differential extraction, A gene group 162, B gene group differences between the 423 groups of 209, C gene, gene gene the common difference between the 3 groups in 21.A group DES reported most, 6; group B ACPP gene reported the most, 4 times; the difference of group C gene ACTN1, HSPB1, LMNA reported the most, 3 times as a result of.GO analysis shows that biological processes are the main differences in genes involved in the regulation of cell death, cell proliferation regulation, trauma, protein transport, steady process (the difference of gene frequency is more than 72, the frequency is greater than or equal to 9.4%), the main cellular components involved extracellular domain, membrane enclosed cavity, cytoskeleton, vesicles and mitochondria (the difference of gene frequency is more than 85, the frequency is greater than or equal to 11.1%), the molecular functions involved in nucleotide binding, calcium ion. Combined with the same protein binding and enzyme (the difference of gene frequency is more than 60, the frequency is greater than or equal to 7.9%).KEGG pathway analysis showed that these genes mainly involved in cancer pathways, focal adhesion, regulation of actin cytoskeleton, MAPK signal pathways (the difference of gene frequency is more than 29, frequency = 3.8%). The difference of KEGG gene pathway the analysis results show that the difference of KEGG pathway genes involved mainly in focal adhesion, complement and coagulation cascade, ECM receptor interaction pathway. Conclusion the difference of DES gene, ACTN1, ATP5B, TLN1, COL6A2, MYH9, OGN, PGAM1 reported more times, and its participation in the development of PCa specific mechanism has not been reported. Worthy of further experiments. Focal adhesion, actin cytoskeleton regulation and MAPK signaling pathway may play an important role in the development of PCa, the further analysis for the clinical treatment of PCa Provide new targets.

【作者单位】：华北理工大学研究生院;天津市滨海新区汉沽第一中学;华北理工大学附属医院泌尿外科;华北理工大学医学实验研究中心老年医学国际科技合作基地;
【分类号】：R737.25
【正文快照】： Bioinformatics Analysis of Differentially Expressed Genes of Prostate Cancer Proteomics and Genomics Based onLiterature Mining CHEN Chen,CAO Xiao-ge,ZHANG Li-guo,et al.School of Graduate,North China University ofScience and Technology,Tangshan 063000,Chi

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