Du Binbin, Wang Fang, Jarad Beers, Wang Zhihui, Zhang Yanzhou
Department of Cardiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
J Transl Med. 2020 Jul 6;18(1):272. doi: 10.1186/s12967-020-02432-7.
In hepatocellular carcinoma (HCC) patients, microvascular invasion (MVI) is associated with worse outcomes regardless of treatment. No single reliable preoperative factor exists to predict MVI. The aim of the work described here was to develop a new MVI- based mRNA biomarker to differentiate between high and low risk patients.
Using The Cancer Genome Atlas (TCGA) database, we collected data from 315 HCC patients, including mRNA expression and complete clinical data. We generated a seven-mRNA signature to predict patient outcomes. The mRNA signature was validated using the GSE36376 cohort. Finally, we tested the formula in our own 53 HCC patients using qPCR for the seven mRNAs and analyzing the computed tomography (CT) features.
This seven-mRNA signature significantly correlated with length of recurrence-free survival (RFS) and overall survival (OS) for both the training and validation groups. RFS and OS were briefer in high risk versus low risk patients. A Kaplan-Meier analysis also indicated that survival time was significantly shortened in the high risk group versus the low risk group. Time-dependent receiver operating characteristic analysis demonstrated good predictive performance for the seven-mRNA signature. The mRNA signature also acts as an independent factor according to a Multivariate analysis. Our results are consistent with the seven-mRNA formula risk score.
Our research showed a novel seven-mRNA biomarker based on MVI predicting RFS and OS in HCC patients. This mRNA signature can stratify patients into subgroups based on their risk of recurrence to help guide individualized treatment and precision management in HCC.
在肝细胞癌(HCC)患者中,无论接受何种治疗,微血管侵犯(MVI)都与较差的预后相关。目前尚无单一可靠的术前因素可预测MVI。本文所述研究的目的是开发一种基于MVI的新型mRNA生物标志物,以区分高风险和低风险患者。
利用癌症基因组图谱(TCGA)数据库,我们收集了315例HCC患者的数据,包括mRNA表达和完整的临床数据。我们生成了一个七mRNA特征来预测患者的预后。该mRNA特征在GSE36376队列中进行了验证。最后,我们在自己的53例HCC患者中使用qPCR检测这七种mRNA并分析计算机断层扫描(CT)特征来测试该公式。
对于训练组和验证组,这种七mRNA特征均与无复发生存期(RFS)和总生存期(OS)显著相关。高风险患者的RFS和OS比低风险患者更短。Kaplan-Meier分析还表明,高风险组的生存时间明显短于低风险组。时间依赖性受试者工作特征分析显示七mRNA特征具有良好的预测性能。根据多变量分析,该mRNA特征也是一个独立因素。我们的结果与七mRNA公式风险评分一致。
我们的研究显示了一种基于MVI的新型七mRNA生物标志物,可预测HCC患者的RFS和OS。这种mRNA特征可以根据患者的复发风险将其分为不同亚组,以帮助指导HCC的个体化治疗和精准管理。