Rong Zhenxiang, Rong Yi, Li Yingru, Zhang Lei, Peng Jingwen, Zou Baojia, Zhou Nan, Pan Zihao
Department of General Surgery, New Rongqi Hospital, Foshan, China.
Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
Front Oncol. 2020 Feb 21;10:26. doi: 10.3389/fonc.2020.00026. eCollection 2020.
Colon carcinoma is a common malignant tumor worldwide. Accurately predicting prognosis of colon adenocarcinoma (CA) patients may facilitate clinical individual decision-making. Many studies have reported that microRNAs (miRNAs) were associated with prognosis for patients with colon carcinoma. This study aimed to identify the prognosis-related miRNAs for predicting the overall survival (OS) of CA patients. Firstly, we analyzed the CA datasets from the Cancer Genome Atlas (TCGA), and looked for the prognosis-related miRNAs. Then, we developed a novel prediction model based on these miRNAs and the clinical characteristics. Time-dependent receiver operating characteristics (ROC) curves and calibration plots were used to evaluate the discrimination and accuracy of the signature and model. Finally, cell function assays and bioinformatics analyses were performed to evaluate the role of these selected miRNAs in modulating biological process in CA. Six prognosis-related miRNAs were included in the miRNA-based signature, and it could effectively distinguish low-risk patients and high-risk patients. Furthermore, we established a prognostic model incorporating the six-miRNA-based signature and clinical characteristics. Areas under curves (AUCs) indicated that the six-miRNA-based model has a better predictive ability than TNM stage (AUC: 0.805 vs. 0.694). The calibration plots suggested close agreement between model predictions and actual observations. GO analysis showed that the target genes of these miRNAs are mainly involved in enrichment in protein binding and regulation of transcript and cytosol. KEGG pathway enrichment analysis indicated that these genes were mainly enriched in PI3K-Akt signaling pathway. Finally, we found that the five miRNAs except miR-152 were upregulated in tumor tissues and CA cells. The functional experiments revealed that miR-1245a, miR-3682, miR-33b, and miR-5683 promoted the migratory abilities and proliferation of CA cell, whereas miR-152 showed opposite effects. However, miR-4444-2 did not influence the migratory ability and proliferation of CA cell. In conclusion, we developed a novel six-miRNA-based model to predict 5-year survival probabilities for CA patients. This model has the potential to facilitate individualized treatment decisions.
结肠癌是全球常见的恶性肿瘤。准确预测结肠腺癌(CA)患者的预后可能有助于临床个体化决策。许多研究报告称,微小RNA(miRNA)与结肠癌患者的预后相关。本研究旨在鉴定与预后相关的miRNA,以预测CA患者的总生存期(OS)。首先,我们分析了来自癌症基因组图谱(TCGA)的CA数据集,并寻找与预后相关的miRNA。然后,我们基于这些miRNA和临床特征开发了一种新的预测模型。采用时间依赖性受试者工作特征(ROC)曲线和校准图来评估特征和模型的辨别力及准确性。最后,进行细胞功能测定和生物信息学分析,以评估这些选定的miRNA在调节CA生物学过程中的作用。基于miRNA的特征包含六个与预后相关的miRNA,它可以有效区分低风险患者和高风险患者。此外,我们建立了一个结合基于六个miRNA的特征和临床特征的预后模型。曲线下面积(AUC)表明,基于六个miRNA的模型比TNM分期具有更好的预测能力(AUC:0.805对0.694)。校准图表明模型预测与实际观察结果之间吻合度良好。基因本体(GO)分析表明,这些miRNA的靶基因主要富集于蛋白质结合以及转录和胞质溶胶的调控。京都基因与基因组百科全书(KEGG)通路富集分析表明,这些基因主要富集于PI3K-Akt信号通路。最后,我们发现除miR-152外的五个miRNA在肿瘤组织和CA细胞中上调。功能实验表明,miR-1245a、miR-3682、miR-33b和miR-5683促进了CA细胞的迁移能力和增殖,而miR-152则表现出相反的作用。然而,miR-4444-2不影响CA细胞的迁移能力和增殖。总之,我们开发了一种基于六个miRNA的新模型来预测CA患者的5年生存概率。该模型具有促进个体化治疗决策的潜力。