通过挖掘美国癌症基因图谱计划（TCGA）和中国脑胶质瘤基因图谱计划（CGGA）中胶质瘤基因谱数据库，分析KIF15在胶质瘤中的表达及临床意义。

通过人类蛋白数据库探究KIF15在神经系统中的表达特征。获取TCGA和CGGA中胶质瘤患者肿瘤样本全基因转录组（mRNAseq）数据，分析KIF15在不同级别和病理类型胶质瘤中的转录水平差异，及其与患者中位生存期的关系。通过胶质瘤标本芯片进行KIF15的免疫组织化学染色，分析KIF15在胶质瘤不同级别中的蛋白水平差异，通过转录组数据分析KIF15与肿瘤增殖指标Ki67的相关性，并通过差异基因（DEGs）进行基因本体（GO）分析和信号通路富集（KEGG）分析探讨KIF15在胶质瘤中参与调控的分子信号通路。

在中枢神经系统大脑中，各部位组织可检测到KIF15的蛋白水平和转录水平均较低。TCGA和CGGA转录组数据分析显示，胶质瘤WHO级别越高，KIF15的mRNA水平显著增高，WHO Ⅳ级相较于WHO Ⅱ级和Ⅲ级，差异有统计学意义（P<0.05）；并且，在胶质母细胞瘤中KIF15的mRNA水平最高，相比较于星形胶质细胞、少突胶质细胞瘤、少突星形胶质细胞瘤、间变性星形胶质细胞瘤、间变性少突胶质细胞瘤，差异均有统计学意义（P<0.05）。KIF15高水平组患者的中位生存期较KIF15低水平组更短，差异有统计学意义（P<0.05）。胶质瘤组织芯片染色结果显示，WHO级别越高，胶质瘤组织染色强度评分趋向更高，WHO Ⅳ级胶质瘤评分以2、3分为主，而WHO Ⅱ级以0、1分为主。KIF15和Ki67的mRNA水平之间为显著性正相关关系，在TCGA转录组数据和CGGA转录组数据库中r值分别为0.725、0.706。TCGA转录组数据共筛选到707个DEGs，KIF15高水平组相比较于KIF15低水平组，表达水平升高的DEGs有328个，表达水平降低的DEGs有379个。GO分析显示这些DEGs参与的生物学过程前10位包括有细胞周期转换和细胞有丝分裂调控。分子信号通路KEGG分析显示DEGs参与的分子信号通路包括细胞周期、P53通路和DNA复制。

KIF15在胶质瘤中高表达，并且高水平KIF15预示胶质瘤恶性程度高，患者生存期较差。KIF15参与调控了肿瘤细胞周期通路，可能是一个潜在的胶质瘤基因治疗靶点。

To explore the expression and clinical significance of KIF15 in glioma were analyzed by mining The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) glioma gene profiling databases.

The expression characteristics of KIF15 in the nervous system were explored through the human protein database. The mRNAseq data of tumor samples from glioma patients in TCGA and CGGA were obtained to analyze the differences in the transcription level of KIF15 in glioma of different grades and pathological types, as well as the relationship between the differences in the transcription level of KIF15 and the median survival time of patients. Immunohistochemical staining of KIF15 was performed on the glioma specimen chip to analyze the difference of KIF15 protein level in different glioma levels, and the correlation between KIF15 and tumor proliferation index Ki67 was analyzed by transcriptome data, and the molecular signaling pathway of KIF15 involved in regulation in glioma was discussed by gene ontology (GO) analysis and kyoto encyclopedia of genes and genomes (KEGG) analysis of differentially expressed genes (DEGs).

Low levels of KIF15 protein and transcription were detected in various parts of the brain of the central nervous system. Analysis of TCGA and CGGA transcriptome data showed that the higher the level of glioma WHO was, the higher the mRNA level of KIF15 was, and the difference was statistically significant when compared with WHO grade Ⅳ and WHO grade Ⅱ and Ⅲ (P<0.05); Moreover, KIF15 mRNA level was the highest in glioblastoma, which was statistically different from that in astrocytes, oligodendrogliomas, oligoastrocytoma, anaplastic astrocytoma, and anaplastic oligodendrogliomas (P<0.05). The median survival time of patients with high KIF15 transcription level was shorter than that of patients with low KIF15 transcription level, and the difference was statistically significant (P<0.05). The results of glioma tissue chip staining showed that the higher the WHO grade was, the higher the staining intensity score of glioma tissue tended to be. The WHO grade Ⅳ glioma score was mainly 2 points and 3 points, while the WHO grade Ⅱ score was mainly 0 and 1 point. The mRNA levels of KIF15 and Ki67 were significantly positively correlated, with r values of 0.725 and 0.706 in the TCGA transcriptome data and the CGGA transcriptome database, respectively. A total of 707 DEGs were screened from the TCGA transcriptomic data. Compared with the low KIF15 group, 328 DEGs with increased expression level and 379 DEGs with decreased expression level were detected in the high KIF15 group. GO analysis showed that the top 10 biological processes in which these DEGs are involved include cell cycle transformation and cell mitosis regulation. Molecular signaling pathways KEGG analysis showed that DEGs was involved in molecular signaling pathways including cell cycle, P53 pathway, and DNA replication.

KIF15 is highly expressed in gliomas, and a high level of KIF15 indicates a high degree of glioma malignancy and a poor survival. KIF15 is involved in the regulation of tumor cell cycle pathways and may be a potential target for glioma gene therapy.