Jianyi Zhao, Xuan Zhao, Chaoqi Zhang, Qingyi Zhang, Zhen Zhang, Zhibo Shen, Yang Yang, Xiangnan Li, Y. Qi, Zhan-feng He, Chunyang Zhang, Renyin Chen, Yi Zhang, Song Zhao
{"title":"Significant Role of MCM10 in Lung Adenocarcinoma: Promote Viability and Migration","authors":"Jianyi Zhao, Xuan Zhao, Chaoqi Zhang, Qingyi Zhang, Zhen Zhang, Zhibo Shen, Yang Yang, Xiangnan Li, Y. Qi, Zhan-feng He, Chunyang Zhang, Renyin Chen, Yi Zhang, Song Zhao","doi":"10.4172/1948-5956.1000596","DOIUrl":null,"url":null,"abstract":"Background: Lung cancer is one of the most common cancer in the world, the role of minichromosome maintenance 10 (MCM10) in lung adenocarcinoma (ADC) is still unknown. Methods: Using TCGA (The Cancer Genome Atlas) database, MCM10 RNA-seq and patients’ clinicopathological characteristics were analyzed. The nomogram and Time-dependent area under the curve (AUC) were built from analysis of multivariate Cox regression model in TCGA database. In our patient cohort, the expression of MCM10 in gene and protein were detected, functional studies were further explored. Moreover, Gene Set Enrichment Analysis (GSEA) was performed using TCGA database.Results: In TCGA database and our patient cohort, MCM10 expression was higher in tumor tissues than normal tissues. Overall survival (OS) status revealed that high MCM10 group was poorer than low MCM10 group in TCGA database (p=0.0212) and our patient cohort (p=0.0391). Patients with higher MCM10 expression displayed shorter progression free survival (PFS) time in our patient cohort (p=0.0323). MCM10 could be a diagnostic marker due to receiver operating characteristic (ROC) curve in TCGA database (p<0.0001) and our patient cohort (p=0.0048). Univariate and multivariate cox analysis demonstrated that MCM10 was an independent prognosticator for ADC. The nomogram model combined MCM10 expression, age and pathologic stage could predict the probability of 1108 days OS and it was assessed by C-index and calibration curve in TCGA database. Time-dependent AUC showed this model in predicting OS probability was particularly effective in earlier patients. Silence of MCM10 inhibited the cell proliferation, induced the G0/G1 phase arrest in cell cycle, promoted apoptosis and decreased migration in vitro. GSEA identified that higher expression of MCM10 was positively correlated with cellular mitosis, cell cycle, chromatin assembly, DNA biosynthetic process and DNA replication. Conclusion: Our study reveals that MCM10 plays a crucial role and could be an important marker for prognosis in AD","PeriodicalId":15170,"journal":{"name":"Journal of Cancer Science & Therapy","volume":"37 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cancer Science & Therapy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4172/1948-5956.1000596","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Lung cancer is one of the most common cancer in the world, the role of minichromosome maintenance 10 (MCM10) in lung adenocarcinoma (ADC) is still unknown. Methods: Using TCGA (The Cancer Genome Atlas) database, MCM10 RNA-seq and patients’ clinicopathological characteristics were analyzed. The nomogram and Time-dependent area under the curve (AUC) were built from analysis of multivariate Cox regression model in TCGA database. In our patient cohort, the expression of MCM10 in gene and protein were detected, functional studies were further explored. Moreover, Gene Set Enrichment Analysis (GSEA) was performed using TCGA database.Results: In TCGA database and our patient cohort, MCM10 expression was higher in tumor tissues than normal tissues. Overall survival (OS) status revealed that high MCM10 group was poorer than low MCM10 group in TCGA database (p=0.0212) and our patient cohort (p=0.0391). Patients with higher MCM10 expression displayed shorter progression free survival (PFS) time in our patient cohort (p=0.0323). MCM10 could be a diagnostic marker due to receiver operating characteristic (ROC) curve in TCGA database (p<0.0001) and our patient cohort (p=0.0048). Univariate and multivariate cox analysis demonstrated that MCM10 was an independent prognosticator for ADC. The nomogram model combined MCM10 expression, age and pathologic stage could predict the probability of 1108 days OS and it was assessed by C-index and calibration curve in TCGA database. Time-dependent AUC showed this model in predicting OS probability was particularly effective in earlier patients. Silence of MCM10 inhibited the cell proliferation, induced the G0/G1 phase arrest in cell cycle, promoted apoptosis and decreased migration in vitro. GSEA identified that higher expression of MCM10 was positively correlated with cellular mitosis, cell cycle, chromatin assembly, DNA biosynthetic process and DNA replication. Conclusion: Our study reveals that MCM10 plays a crucial role and could be an important marker for prognosis in AD
背景:肺癌是世界上最常见的癌症之一,小染色体维持10 (MCM10)在肺腺癌(ADC)中的作用尚不清楚。方法:利用TCGA (The Cancer Genome Atlas)数据库,分析MCM10 RNA-seq和患者的临床病理特征。通过对TCGA数据库中的多变量Cox回归模型的分析,建立了nomogram和Time-dependent area under curve (AUC)。在我们的患者队列中,检测了MCM10在基因和蛋白上的表达,并进一步探讨了功能研究。利用TCGA数据库进行基因集富集分析(GSEA)。结果:在TCGA数据库和我们的患者队列中,MCM10在肿瘤组织中的表达高于正常组织。总生存(OS)状况显示,TCGA数据库(p=0.0212)和我们的患者队列(p=0.0391)中,高MCM10组低于低MCM10组。在我们的患者队列中,MCM10表达较高的患者显示出较短的无进展生存期(PFS)时间(p=0.0323)。根据TCGA数据库的受试者工作特征(ROC)曲线(p<0.0001)和我们的患者队列(p=0.0048), MCM10可以作为诊断标志物。单因素和多因素cox分析表明MCM10是ADC的独立预后因子。结合MCM10表达、年龄和病理分期建立的nomogram模型可以预测患者1108天OS的概率,并通过TCGA数据库中的c指数和校准曲线进行评估。随时间变化的AUC表明,该模型在早期患者中预测OS概率特别有效。MCM10沉默抑制细胞增殖,诱导细胞周期G0/G1期阻滞,促进细胞凋亡,减少体外迁移。GSEA发现MCM10的高表达与细胞有丝分裂、细胞周期、染色质组装、DNA生物合成过程和DNA复制呈正相关。结论:我们的研究表明MCM10在AD中起着至关重要的作用,可能是AD预后的重要标志