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Establishment of a Nomogram by Integrating Molecular Markers and Tumor-Node-Metastasis Staging System for Predicting the Prognosis of Hepatocellular Carcinoma

Aims: This study aimed to develop a valuable nomogram by integrating molecular markers and tumor-node-metastasis (TNM) staging system for predicting the long-term outcome of patients with hepatocellular carcinoma (HCC). Methods: The gene expression profiles of HCC patients undergoing liver resection were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. One hundred and ninety-nine patients from TCGA and 94 patients from GEO were selected to be part of the training cohort and validation cohort respectively. Univariate and multivariate cox analyses were performed to identify genes with independent prognostic values for overall survival (OS) of HCC patients in training cohort. Risk score was calculated based on the coefficients and Z-score of 3 genes for each patient. The nomogram was developed based on the risk score and TNM staging system. Discrimination and predictive accuracy of the nomogram were measured by using the concordance index (C-index) and calibration curve. The efficacy of the nomogram was tested in the external validation cohort. Results: Univariate and multivariate cox analyses revealed that EXT2 (p = 0.035, hazard ratio 13.412), ETV5 (p = 0.010, hazard ratio 4.325), and CHODL (p < 0.001, hazard ratio 6.286) were independent prognostic factors and chosen for further nomogram establishment. The C-index of the nomogram for predicting the OS in the training cohort was superior to that of the TNM staging system (0.77 vs. 0.64, p < 0.01). The calibration curve of predicted 1-, 3-, and 5-year OS showed satisfactory accuracy. The external validation cohort showed good performance of comprehensive nomogram as well. Conclusion: The novel nomogram by integrating the molecular markers and TNM staging system has better performance in predicting long-term prognosis in HCC patients than the TNM staging system alone.