Combined DNA Methylation and Transcriptomic Assessments to Determine a Prognostic Model for PD-1-Negative Hepatocellular Carcinoma

Abstract

Hepatocellular carcinoma (HCC) has the highest incidence and mortality of any malignancy in the world. Immunotherapy has been a major breakthrough for HCC treatment, but immune checkpoint inhibitors (ICIs) are effective in only a small percentage of HCC patients. In the present study, we screened programmed cell death protein 1 (PD-1) -negative HCC samples, which are frequently resistant to ICIs, and identified their methylation and transcription characteristics through the assessment of differential gene methylation and gene expression. We also screened for potential targeted therapeutic drugs using the DrugBank database. Finally, we used a LASSO (least absolute shrinkage and selection operator) regression analysis to construct a prognostic model based on three differentially methylated and expressed genes (DMEGs). The results showed that ESTIMATE (Estimation of Stromal and Immune Cells in Malignant Tumors using Expression Data) scores for the tumor samples were significantly lower compared to normal sample ESTIMATE scores. In addition, we identified 31 DMEGs that were able to distinguish PD-1-negative samples from normal samples. A functional enrichment analysis showed that these genes were involved in a variety of tumor-related pathways and immune-related pathways, and the DrugBank screening identified potential therapeutic drugs. Finally, the prognostic model based on three DMEGs (UBD, CD5L, and CD213A2) demonstrated good predictive power for HCC prognosis and was verified using an independent cohort. The present study demonstrated the methylation characteristics of PD-1-negative HCC samples, identified several potential therapeutic drugs, and proposed a prognostic model based on UBD, CD5L, and CD213A2 methylation expression. In conclusion, this work provides an in-depth understanding of methylation in HCC samples that are not sensitive to ICIs.

A novel DNA methylation‐driver gene signature for long‐term survival prediction of hepatitis‐positive hepatocellular carcinoma patients

“…2,[38][39][40] The DNA methylation probe and MDGs signatures have shown a good prediction efficiency of all-cause HCC and nonviral HCC. [27][28][29][30] patients, [28][29][30] suggesting that DNA methylation plays a role in HCC of different etiologies through different mechanisms.…”

“…2 , 38 , 39 , 40 The DNA methylation probe and MDGs signatures have shown a good prediction efficiency of all‐cause HCC and nonviral HCC. 27 , 28 , 29 , 30 However, whether there is an efficient MDGs signature used to predict hepatitis‐positive HCC remains unclear. In this study, integrated analysis was performed by DNA methylation data and transcription data of HBV/HCV positive patients from the TCGA‐HCC cohort, and 608 DNA methylation‐driver genes were identified.…”

“…The pathological process of HCC develops from hepatitis is different from other causes, such as alcoholic liver disease and NAFLD 2,38–40 . The DNA methylation probe and MDGs signatures have shown a good prediction efficiency of all‐cause HCC and nonviral HCC 27–30 . However, whether there is an efficient MDGs signature used to predict hepatitis‐positive HCC remains unclear.…”

“…Furthermore, recent researches have showed that DNA methylation can used for prognosis prediction and treatment of HCC 25,26 . In addition, the prediction models constructed by DNA methylation probes or MDGs also showed good prediction efficiency in all‐cause induced HCC and nonviral HCC 27–30 . Considering that HCC developed from hepatitis has different pathogenesis and pathological characteristics from HCC caused by other causes, we studied whether MDGs can be used for prognosis prediction of hepatitis‐positive HCC.…”

A hypoxia-related prognostic model predicts overall survival and treatment response in hepatocellular carcinoma

“…Consistent with our findings, Zhang et al found that immune-related lncRNA pairs could be used to construct a prognostic risk model in pancreatic cancer, and the three lncRNA pairs could be novel tumor treatment targets through the regulation of immune cells and tumor migration [ 32 ]. In a recent study, they developed a novel prognostic model based on the methylated and expressed genes in PD-1-negative patients with HCC, and the model had predictive power for 1-, 3-, and 5-year survival [ 33 ]. Therefore, further investigation of the roles of these core genes could provide clues for a deeper understanding of tumor progression.…”