Abstract
With the development of new advances in hepatocellular carcinoma (HCC) management and noninvasive radiological techniques, high‐risk patient groups such as those with hepatitis virus are closely monitored. HCC is increasingly diagnosed early, and treatment may be successful. In spite of this progress, most patients who undergo a hepatectomy will eventually relapse, and the outcomes of HCC patients remain unsatisfactory. In our study, we aimed to identify potential gene biomarkers based on RNA sequencing data to predict and improve HCC patient survival. The gene expression data and clinical information were acquired from The Cancer Genome Atlas (TCGA) database. A total of 339 differentially expressed genes (DEGs) were obtained between the HCC (n = 374) and normal tissues (n = 50). Four genes (CENPA, SPP1, MAGEB6 and HOXD9) were screened by univariate, Lasso and multivariate Cox regression analyses to develop the prognostic model. Further analysis revealed the independent prognostic capacity of the prognostic model in relation to other clinical characteristics. The receiver operating characteristic (ROC) curve analysis confirmed the good performance of the prognostic model. Then, the prognostic model and the expression levels of the four genes were validated using the Gene Expression Omnibus (GEO) dataset. A nomogram comprising the prognostic model to predict the overall survival was established, and internal validation in the TCGA cohort was performed. The predictive model and the nomogram will enable patients with HCC to be more accurately managed in trials testing new drugs and in clinical practice.
Highlights
Hepatocellular carcinoma (HCC) is one of the most frequently diagnosed malignancies and the third leading cause of cancer‐Junyu Long, Lei Zhang and Xueshuai Wan are Equal contributors.related mortality, and the incidence and mortality of this cancer are increasing yearly.[1]
Many potential and valuable mRNAs must be identified to improve the clinical outcome for HCC patients
The number of specific biomarkers that can be used to show therapeutic effects is still small, and prognostic factors are important for the treatment of HCC patients
Summary
Hepatocellular carcinoma (HCC) is one of the most frequently diagnosed malignancies and the third leading cause of cancer‐. Clinical staging and vascular tumour invasion are important contributors to clinical. There is a strong need to explore new tools, such as molecular markers, to predict patient prognosis more accurately. In this genomic era, a large number of genome‐sequencing technologies and data have emerged.[3] These tools have made great contributions to tumour diagnosis and prognosis prediction. We aimed to explore the difference in the mRNA expression profiles of HCC and the adjacent liver to identify potential gene biomarkers using TCGA data. A predictive nomogram was built and internally validated in the TCGA cohort As a whole, this prognostic model and nomogram might be helpful in guiding the prognostic status of patients with HCC
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