前列腺癌差异表达基因的筛选及相互作用的生物信息学分析

Screening for differential genes of the prostate cancer and bioinformatics analysis of their interaction

背景与目的:基因芯片技术是利用杂交测序方法,可大规模高通量地检测不同组织、细胞中的基因表达水平的技术。该研究采用基因芯片技术筛选前列腺癌及前列腺炎症穿刺组织中差异表达的基因并对其进行生物学信息分析。方法:采用美国Affymetrix Human U133 plus 2.0基因表达谱芯片,按一步法分别抽提恶性程度较高的前列腺癌及前列腺炎症组织的总RNA,并分离纯化这两种组织的m RNA。经逆转录合成掺入生物素标记的c DNA合成探针,与芯片杂交和严格洗片后,用荧光扫描仪扫描芯片荧光信号图像。用生物信息学方法分析前列腺癌及前列腺炎症组织中差异表达基因。结果:按照表达差异倍数大于等于2,P<0.05的筛选条件,筛选出差异基因1 819条,其中上调表达基因1 025条和下调表达基因794条。采用GO富集分析发现这些差异基因主要涉及细胞周期、分子代谢等分子功能以及生物学过程;KEGG信号通路分析发现,这些差异基因主要涉及嘌呤核苷酸代谢等代谢通路。STING在线工具分析对差异基因编码的蛋白质间的相互作用进行分析,结果发现这些基因编码的蛋白间的相互作用主要集中在TPX2、ANLN、NUSAP1、MELK、DLGAP5、KIF11、TOP2A及RRM2等20个关键节点基因。最后对重要节点基因进行文献挖掘,发现CEP55和ANLN基因可能与前列腺癌的发生和转移有关。结论:在前列腺癌的发生、发展中,促使细胞进入增殖周期的相关基因的活化、代谢相关酶类基因活性的异常、细胞黏附功能相关基因的抑制以及细胞移行相关基因的激活等因素发挥了重要的作用。系统的分析这些基因发现,CEP55和ANLN基因与前列腺癌的发生和预后关系密切,为下一步研究实验提供有价值的线索。进一步研究相关差异基因将有望发现新的早期诊断指标,为建立个体化治疗方案和预后评估系统提供帮助。

Background and purpose： Gene chip is a nucleic acid sequence analysis method which is based on hybridization. It is a high-through put assay which can widely detect the level of gene expression in different tissues and cell types. This study aimed to compare and bioinformatically analyze differentially expressed genes between higher malignant degree of prostate cancer tissues and prostate inflammation tissues. Methods： The total RNAs were isolated from tissues of prostate cancer and prostate inflammation by TRIzol method and then purified, reversely tran- scribed to cDNA with incorporating biotin labeling probe, hybridized with Affymetrix Human U133 Plus 2.0 （covering 47 000 transcripts, representing 38 500 distinct genes）. Picture signals of fluorescence in gene array were scanned and differential expression of gene in two tissues were compared by Command Console Software 4.0. These differential expressed genes were analyzed by bioinformatics methods finally. Results： According to the fold change /〉2, P〈0.05, 1 819 differential expression genes including 1 025 up-regulated genes and 794 down-regulated genes were discovered. GO enrichment analysis displayed that these differentially expressed genes were mainly involved in cell cycle, cell metabolism, etc. KEGG pathway analysis found that these genes were mainly involved in some metabolism pathways including purine nucleotide metabolism. The interactions between the proteins encoded by these genes were analyzed by STING. Twenty key nodes genes including TPX2, ANLN, NUSAP1, MELK, DLGAP5, KIF11, TOP2A, RM2 were dis- covered. Then this study revealed CEP55 and ANLN might be related to the occurrence and metastasis of prostate cancer by looking through literature. Conclusion： During the development of prostate cancer, the activation of genes related to cell cycle and cell migration, the abnormalities of genes related to metabolism and the inhibition of genes related to cell adhesion play critical roles in the development of prostate cancer. CEP55 and ANLN were related to the occurrence and prognosis of prostate cancer by systematic analysis which provided a valuable clue for the next experiment.