14-CpG-Based Signature Improves the Prognosis Prediction of Hepatocellular Carcinoma Patients

Abstract EN

Background.

Epigenetic dysregulation via alteration of DNA methylation often occurs during the development and progression of cancer, including hepatocellular carcinoma (HCC).

In the past, many patterns of single-gene DNA methylation have been extensively explored in the context of HCC prognosis prediction.

However, the combined model of a mixture of CpGs has rarely been evaluated.

In the present study, we aimed to develop and validate a CpG-based signature model for HCC patient prognosis.

Methods.

Data from methylation profiling of GSE73003, GSE37988, and GSE57958 from the Gene Expression Omnibus (GEO) database and 371 HCC patients from the Cancer Genome Atlas (TCGA) were downloaded.

The 371 HCC patients were randomly divided into a development cohort (N = 263) and a validation cohort (N = 108).

Two algorithms, least absolute shrinkage and selection operator (LASSO) and robust likelihood-based survival analysis, were used to select the most significant CpGs associated with overall survival (OS) time and were used to develop and validate a methylation-based signature (MSH) for HCC patient prognosis.

In addition, the prognostic efficacy of the MSH was compared with that of AJCC TNM classification and other CpG-based MSHs from TCGA.

Finally, a nomogram incorporating the MSH and clinicopathologic factors was also developed.

Results.

Fourteen differential CpGs associated with OS were identified in HCC patients.

The MSH, based on these 14 differential CpGs, could effectively divide HCC patients into two distinct subgroups with high risk or low risk of death (P<0.0001) in the development cohort (26.35 vs 83.18 months, HR = 3.83, 95% CI: 2.56–5.90, P<0.0001) and in the validation cohort (40.37 vs 107.03 months, HR = 2.23, 95% CI: 1.22–4.17, P=0.01).

Univariate analysis showed that the MSH was significantly associated with OS, and the multivariate analysis also showed that the MSH was an independent prognostic factor for the OS of HCC patients in the two cohorts.

In addition, stratified survival analysis indicated that the MSH still exhibited good prognostic value in different subgroups classified by AFP, cirrhosis, Child-Pugh A, tumor histologic grade, and AJCC stage.

Moreover, time-dependent ROC analysis showed better performance of the MSH in predicting 3-year and 5-year survival of HCC patients than of AJCC stage and other CpG-based signatures from TCGA.

The MSH-based nomogram also performed well in predicting 1-year, 3-year, and 5-year OS (C-index: 0.709).

Conclusion.

The 14-CpG-based signature is significantly associated with OS and may be used as a novel prognostic biomarker for HCC patients.