Background: Aberrant DNA methylation patterns play a critical role in the development of hepatocellular carcinoma (HCC). However, the molecular mechanisms associated with these aberrantly methylated genes remain unclear. This study aimed to comprehensively investigate the methylation-driven gene expression alterations in HCC using a multi-omics dataset. Methods: Whole genome bisulfite sequencing (WGBS) and RNA sequencing (RNA-seq) techniques were used to assess the methylation and gene expression profiles of HCC tissues (HCCs) and normal adjacent tissues (NATs). The candidate genes’ potential function was further investigated using single-cell RNA sequencing (scRNA seq) data. Results: We observed widespread hypomethylation in HCCs compared to NATs. Methylation levels in distinct genomic regions exhibited significant differences between HCCs and NATs. We identified 247,632 differentially methylated regions (DMRs) and 4,926 differentially expressed genes (DEGs) between HCCs and NATs. Integrated analysis of DNA methylation and RNA-seq data identified 987 methylation-driven candidate genes, with 970 showing upregulation and 17 showing downregulation. Four genes involved in the retinol metabolic pathway, namely ADH1A, CYP2A6, CYP2C8, and CYP2C19, were identified as hyper-downregulated genes. Their expression levels could stratify HCCs into three subgroups with distinct survival outcomes, immune cell infiltration, and tumor microenvironments. Validation of these findings in an independent dataset yielded similar outcomes, confirming the high concordance and potential prognostic value of these genes. ScRNA seq data revealed the low expression of these genes in immune cells, emphasizing their role in promoting malignant cell proliferation and migration. In conclusion, this study provides insights into the molecular characteristics of HCC, revealing the involvement of retinol metabolism-related genes in the development and progression of HCC. These findings have implications for HCC diagnosis, prognosis prediction, and the development of therapeutic targets.

Early detection is crucial for increasing the survival rate of gastric cancer (GC). We aimed to identify a methylated cell-free DNA (cfDNA) marker panel for detecting GC. The differentially methylated CpGs (DMCs) were selected from datasets of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The selected DMCs were validated and further selected in tissue samples (40 gastric cancer and 36 healthy white blood cell samples) and in a quarter sample volume of plasma samples (37 gastric cancer, 12 benign gastric disease, and 43 healthy individuals). The marker combination selected was then evaluated in a normal sample volume of plasma samples (35 gastric cancer, 39 control diseases, and 40 healthy individuals) using real-time methylation-specific PCR (MSP). The analysis of the results compared methods based on 2^-ΔΔCt values and Ct values. In the results, 30 DMCs were selected through bioinformatics methods, and then 5 were selected for biological validation. The marker combination of two fragments of IRF4 (IRF4-1 and IRF4-2) and one of ZEB2 was selected due to its good performance. The Ct-based method was selected for its good results and practical advantages. The assay, IRF4-1 and IRF4-2 in one fluorescence channel and ZEB2 in another, obtained 74.3% sensitivity for the GC group at any stage, at 92.4% specificity. In conclusion, the panel of IRF4 and ZEB2 in plasma cfDNA demonstrates good diagnostic performance and application potential in clinical settings.

Background: Surveillance approaches with high sensitivity and specificity for hepatocellular carcinoma (HCC) are still urgently needed. Previous studies have shown that methylation of GNB4 and Riplet can effectively diagnose HCC.Aims: This study plan to analyze the performance of a blood test for detecting HCC using GNB4 and Riplet methylation.Methods and Results: This study mainly investigated the analytical performance of the dual‐target HCC blood test (DT‐HBT), including cut‐off value, limit of detection (LOD), precision, analytical specificity, and coincidence rate. In addition, the detection performance for HCC was validated in 1030 clinical plasma samples (214 HCC and 816 non‐HCC). Plasma samples from 25 HCC patients after hepatectomy were collected to assess the feasibility of the kit for postoperative recurrence monitoring. All analytical performance of the DT‐HBT met prespecified requirements. The LOD for GNB4, Riplet, and β‐actin was 1% methylation/100 copies/μL with cut‐offs of 43, 43, and 35, respectively. The DT‐HBT showed excellent precision, within 5% CV. It had a specificity of 91.5% for detecting other cancers, and 100% for breast, lung, and bladder cancer. No cross‐reactions were observed with 9 potential interfering substances. The DT‐HBT achieved a 100% coincidence rate in detecting reference and clinical samples. The clinical performance study found that the kit showed a sensitivity of 81.7% for stage I HCC, and an overall sensitivity and specificity of 87.4% and 92.3%, respectively. The detection sensitivity for postoperative recurrent patients was 95.8%, with a specificity of 100%.Conclusion: The analytical performance of the DT‐HBT met prespecified criteria. It provided HCC patients with a reliable and high‐performing new blood test for the HCC diagnosis and surveillance.Trial Registration: ClinicalTrials.govidentifier: NCT05685524