Identification And validation of transcription factor genes involved in prostate cancer metastasis

Metastasis is one of the most significant independent risk factors that can negatively affect prostate cancer (PCa) patients. However, the exact mechanisms have not been fully elucidated. To illustrate the mechanisms underlying PCa metastasis, we conducted a series of integrated bioinformatics analyses. The essential genes involved in PCa metastasis were obtained by analyzing differentially expressed genes (DEGs) between metastatic PCa and localized PCa. Gene Ontology and KEGG pathway enrichment analysis were performed for functional annotation. Protein–protein interaction networks were constructed for hub gene selection. Three transcription factor genes (<i>FOS</i>, <i>CENPA</i>, and <i>FOXM1</i>) were identified by integrating the hub genes with human transcription factors from The Human Transcription Factors database. Moreover, expression validation and prognostic analysis of the three transcription factor genes were carried out on GEO, TCGA, GEPIA, and the Human Protein Atlas, respectively. Further verification showed that expression variation of the three transcription factor genes existed between metastatic PCa and localized PCa as well as between localized PCa and normal prostate. In addition, different expressions of the three transcription factor genes were associated with the prognosis of localized PCa. In summary, the three transcription factor genes can serve as potential prognostic biomarkers as well as therapeutic targets for PCa. <b>Abbreviations:</b> PCa: prostate cancer; DEGs: differentially expressed genes; TFs: transcription factors; GEO: Gene Expression Omnibus; FC: fold change; DAVID: Database for Annotation, Visualization, and Integrated Discovery; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; BP: biological process; CC: cell component; MF: molecular function; PPI: protein–protein interaction; MCODE: Molecular Complex Detection; GEPIA: Gene Expression Profiling Interactive Analysis; GTEx: Genotype-Tissue Expression; TCGA: The Cancer Genome Atlas Program; MCC: Maximal Clique Centrality; DMNC: Density of Maximum Neighborhood Component; MNC: Maximum neighborhood component; EPC: Edge Percolated component; DFS: disease-free survival; OS: overall survival; MAPK: mitogen-activated protein kinases

转移是影响前列腺癌（prostate cancer, PCa）患者预后的最重要独立危险因素之一，但其具体分子机制尚未完全阐明。为阐明前列腺癌转移的潜在机制，本研究开展了一系列整合生物信息学分析。通过分析转移性前列腺癌与局限性前列腺癌之间的差异表达基因（differentially expressed genes, DEGs），筛选得到与前列腺癌转移相关的核心基因。对核心基因进行基因本体（Gene Ontology, GO）功能富集分析与京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）通路富集分析，完成功能注释。构建蛋白质-蛋白质相互作用（protein–protein interaction, PPI）网络以筛选关键枢纽基因。通过将枢纽基因与来自《人类转录因子数据库》（The Human Transcription Factors database）的人类转录因子集进行整合，最终鉴定出3个转录因子基因：FOS、CENPA与FOXM1。分别在GEO、TCGA、GEPIA以及人类蛋白质图谱（Human Protein Atlas）数据库中对这3个转录因子基因进行表达验证与预后分析。进一步验证结果显示，这3个转录因子基因的表达水平在转移性前列腺癌与局限性前列腺癌之间，以及局限性前列腺癌与正常前列腺组织之间均存在显著差异。此外，这3个转录因子基因的表达差异与局限性前列腺癌患者的预后密切相关。综上，这3个转录因子基因可作为前列腺癌潜在的预后生物标志物与治疗靶点。**缩写说明**：PCa：前列腺癌；DEGs：差异表达基因；TFs：转录因子；GEO：基因表达综合数据库（Gene Expression Omnibus）；FC：倍数变化；DAVID：注释、可视化和整合发现数据库；GO：基因本体；KEGG：京都基因与基因组百科全书；BP：生物过程；CC：细胞组分；MF：分子功能；PPI：蛋白质-蛋白质相互作用；MCODE：分子复合物检测算法；GEPIA：基因表达谱交互分析数据库；GTEx：基因型-组织表达数据库；TCGA：癌症基因组图谱计划；MCC：最大团中心性；DMNC：最大邻域组分密度；MNC：最大邻域组分；EPC：边缘渗滤组分；DFS：无病生存期；OS：总生存期；MAPK：丝裂原活化蛋白激酶