Li K, Zang C, Zhao Y, Guo D, Shi W, Mei T, Li A, Zhang Y. The methylation signature of hepatocellular carcinoma trajectory based on pseudotime and chronological time for predicting
precancerous patients.
Oncologist 2024:oyae292. [PMID:
39589232 DOI:
10.1093/oncolo/oyae292]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 09/17/2024] [Indexed: 11/27/2024] Open
Abstract
BACKGROUND
Early screening of hepatocellular carcinoma (HCC) is strongly recommended for hepatitis B virus (HBV)-infected patients. We aimed to develop and validate a predictive nomogram based on HCC occurrence trajectory for screening precancerous patients with HCC.
METHODS
Peripheral blood mononuclear cells (PBMC) samples from 22 patients with HCC with their precancerous stage (n = 55) and 18 healthy controls were measured using HumanMethylation EPIC BeadChip assay. HCC trajectory was assessed by pseudotime based on TimeAx algorithm and chronological time. The 43 candidate CpG sites were selected from the methylation signature and measured using multiplex bisulfite sequencing in a retrospective cohort of HBV-infected patients (n = 604). A 5-CpG-classifier was built using the LASSO Cox regression model, based on the association between the methylation level of every CpG and the duration from enrollment to HCC occurrence of individual patient. We validated the risk stratification and predictive accuracy of this classifier in both the primary cohort (n = 300) and independent validation cohort (n = 304).
RESULTS
Pseudotime and chronological time of HCC trajectory analysis revealed that the PD-1/PD-L1 pathway underwent changes in the precancerous stage. Based on the trajectory of methylation signature, we built a 5-CpG-classifier which remained powerful and independent predictive efficiency after stratified analysis by clinicopathological risk factors in both primary cohort and independent validation cohort. A predicting nomogram including the 5-CpG-classifier was constructed after multivariate analysis. One-year cumulative hazard of HCC in low- and high-risk groups of HBV-infected patients was 3.0% (0.1%-5.8%) and 17.90% (11.00%-24.3%) (P < .0001) in primary cohort, 4.5% (1.20%-7.80%) and 27.3 (18.90-34.90) (P < .0001) in the independent validation cohort.
CONCLUSIONS
One-year before HCC was a critical period of transitional time when parts of the methylation profile underwent shifting toward HCC like. The nomogram could identify precancerous stage patients with HCC who should be screened for early diagnosis and intervention.
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