生物信息学分析鉴定了前列腺癌发生和转移中的枢纽基因。
Bioinformatics analysis identified hub genes in prostate cancer tumorigenesis and metastasis.
机构信息
Department of Urology, Second Affiliated Hospital of Soochow University, 1055 Sanxiang Road, Suzhou 215000, China.
Department of Urology, Wuxi Xishan People's Hospital, 1128 Dacheng Road, Wuxi 214000, China.
出版信息
Math Biosci Eng. 2021 Apr 6;18(4):3180-3196. doi: 10.3934/mbe.2021158.
OBJECTIVE
Prostate cancer (PCa) is the most frequent cancer found in males worldwide, and its mortality rate is increasing every year. To discover key molecular changes in PCa development and metastasis, we analyzed microarray data of localized PCa, metastatic PCa and normal prostate tissue samples from clinical specimens.
METHODS
Gene expression profiling datasets of PCa were analyzed online. The DAVID was used to perform GO functional and KEGG pathway enrichment analyses. CytoHubba in Cytoscape software was applied to identify hub genes. Survival data were downloaded from GEPIA. Gene expression data were obtained from ONCOMINE and UALCAN.
RESULTS
We obtained 4 sets of differentially expressed genes (DEGs), DEGs 1: a comparison of the gene expression between 4 normal prostate and 5 localized PCa samples in GSE27616; DEGs 2: a comparison of the gene expression between 6 normal prostate and 7 localized PCa samples in GSE3325; DEGs 3: a comparison of the gene expression between 5 localized PCa and 4 metastatic PCa samples in GSE27616; DEGs 4: a comparison of the gene expression between 7 localized PCa and 6 metastatic PCa samples in GSE3325. A comparison of these 4 sets of genes revealed 51 overlapped genes. GO function analysis revealed enrichment of the 51 DEGs in functions related to the proteinaceous extracellular matrix and centrosome, protein homodimerization activity and chromatin binding were the main functions of these genes, which participated in regulating cell division, mitotic nuclear division, proteinaceous extracellular matrix, cell adhesion and apoptotic process. KEGG pathway analysis indicated that these identified DEGs were mainly enriched in progesterone-mediated oocyte maturation, oocyte meiosis and cell cycle. We defined the 16 genes with the highest degree of connectivity as the hub genes in the 51 overlapped DEGs. Cox regression revealed TOP2A, CCNB2, BUB1, CDK1 and EZH2 were related to Disease-free survival (DFS). The expression levels of the 5 genes were 2.232-, 1.786-, 2.303-, 1.699-, and 1.986-fold higher in PCa than the levels in normal tissues, respectively (P < 0.05). We obtained 20 hub genes from DEGs by the comparison of normal prostate tissue vs. localized cancer tissue. Among them, KIF20A, CDKN3, PBK and CDCA2, were expressed higher in PCa than in normal tissues, and were associated with the DFS of PCa patients. Meanwhile, we obtained 20 hub genes from DEGs by the comparison of localized cancer tissue vs. metastatic cancer tissue. Cox regression revealed PLK1, CCNA2 and CDC20, were associated with both the DFS and overall survival of PCa patients.
CONCLUSIONS
The results suggested that the functions of KIF20A, CDKN3, PBK and CDCA2 may contribute to PCa development and the functions of PLK1, CCNA2 and CDC20 may contribute to PCa metastasis. Meanwhile, the functions of TOP2A, CCNB2, BUB1, CDK1 and EZH2 may contribute to both PCa development and metastasis.
目的
前列腺癌（PCa）是全球男性最常见的癌症，其死亡率每年都在上升。为了发现 PCa 发展和转移的关键分子变化，我们分析了来自临床标本的局限性 PCa、转移性 PCa 和正常前列腺组织样本的基因表达谱数据。
方法
在线分析 PCa 的基因表达谱数据集。使用 DAVID 进行 GO 功能和 KEGG 通路富集分析。Cytoscape 软件中的 CytoHubba 用于识别枢纽基因。从 GEPIA 下载生存数据。从 ONCOMINE 和 UALCAN 获取基因表达数据。
结果
我们获得了 4 组差异表达基因（DEGs），DEGs1：比较 4 个正常前列腺和 5 个局限性 PCa 样本在 GSE27616 中的基因表达；DEGs2：比较 6 个正常前列腺和 7 个局限性 PCa 样本在 GSE3325 中的基因表达；DEGs3：比较 5 个局限性 PCa 和 4 个转移性 PCa 样本在 GSE27616 中的基因表达；DEGs4：比较 7 个局限性 PCa 和 6 个转移性 PCa 样本在 GSE3325 中的基因表达。这 4 组基因的比较显示出 51 个重叠基因。GO 功能分析显示，这 51 个 DEGs 的功能富集与蛋白细胞外基质和中心体有关，蛋白质同源二聚化活性和染色质结合是这些基因的主要功能，它们参与调节细胞分裂、有丝分裂核分裂、蛋白细胞外基质、细胞黏附和凋亡过程。KEGG 途径分析表明，这些鉴定出的 DEGs 主要富集在孕激素介导的卵母细胞成熟、卵母细胞减数分裂和细胞周期中。我们定义了 16 个具有最高连接度的基因作为这 51 个重叠 DEGs 中的枢纽基因。Cox 回归显示 TOP2A、CCNB2、BUB1、CDK1 和 EZH2 与无病生存期（DFS）有关。这 5 个基因在 PCa 中的表达水平分别比正常组织高 2.232 倍、1.786 倍、2.303 倍、1.699 倍和 1.986 倍（P<0.05）。我们通过比较正常前列腺组织与局限性癌组织获得了 20 个枢纽基因。其中，KIF20A、CDKN3、PBK 和 CDCA2 在 PCa 中的表达高于正常组织，与 PCa 患者的 DFS 相关。同时，我们通过比较局限性癌组织与转移性癌组织获得了 20 个枢纽基因。Cox 回归显示 PLK1、CCNA2 和 CDC20 与 PCa 患者的 DFS 和总生存期均相关。
结论
结果表明，KIF20A、CDKN3、PBK 和 CDCA2 的功能可能有助于 PCa 的发展，PLK1、CCNA2 和 CDC20 的功能可能有助于 PCa 的转移。同时，TOP2A、CCNB2、BUB1、CDK1 和 EZH2 的功能可能有助于 PCa 的发展和转移。
Zotero 插件