DNA replication stress stratifies prognosis and enables exploitable therapeutic vulnerabilities of HBV-associated hepatocellular carcinoma: An in-silico precision oncology strategy
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GRAPHICAL ABSTRACT
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PUBLIC SUMMARY
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Host genome-integrated hepatitis B virus (HBV) causes chronic DNA replication stress.
Prognostic DNA replication stress contributes heterogeneity of HBV+ hepatocellular carcinoma (HCC).
A tailored prognostic index (PIRS) improves population-based prognostication.
PIRS enables exploitable therapeutic vulnerabilities.
Four therapeutic targets and five agents were identified for HBV+ HCC.
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ABSTRACT
Hepatitis B virus (HBV) is a major risk factor for hepatocellular carcinoma (HCC), characterized by genomic instability and chronic DNA replication stress. This study presents a robust machine-learning framework using random survival forest to develop a DNA replication stress-related prognostic index (PIRS) for HBV-associated HCC. Transcriptomic expression profiles from 606 HCC cases were used to construct PIRS, which outperformed population-based predictors, demonstrating superior prognostic prediction in HBV-associated HCC. Lower PIRS scores were associated with higher expression of HBV oncoproteins, activated immune/metabolism pathways, and increased responsiveness to immunotherapy. Conversely, higher PIRS scores correlated with elevated Ki-67 marker, cancer stemness, and enrichment in DNA replication stress, cell cycle pathways, and chromatin remodelers, resulting in an 'immune-cold' phenotype and unfavorable clinical outcomes. Through large-scale in-silico drug screening, potential therapeutic targets (TOP2A, PRMT1, CSNK1D, and PPIH) and five agents, including topoisomerase and CDK inhibitors, were identified for patients with high PIRS scores. These findings hold promise for optimizing therapeutic strategies in HCC and providing insights into the management of HBV carriers. In summary, our machine-learning approach yielded PIRS as a powerful predictor for assessing prognosis in HBV-associated HCC. This analytic framework improves population-based therapeutic strategies, facilitates personalized treatment, and ushers in a new era of precision medicine in HCC. -
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REFERENCES
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Lu X., Meng J., Wang H., et al., (2023). DNA replication stress stratifies prognosis and enables exploitable therapeutic vulnerabilities of HBV-associated hepatocellular carcinoma: An in-silico precision oncology strategy. The Innovation Medicine 1(1), 100014. https://doi.org/10.59717/j.xinn-med.2023.100014
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Lu X., Meng J., Wang H., et al., (2023). DNA replication stress stratifies prognosis and enables exploitable therapeutic vulnerabilities of HBV-associated hepatocellular carcinoma: An in-silico precision oncology strategy. The Innovation Medicine 1(1), 100014. https://doi.org/10.59717/j.xinn-med.2023.100014
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Figure 1.
Experimental design
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Figure 2.
Performance of prognostic prediction based on
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Figure 3.
Landscape of
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Figure 4.
Association between immune/metabolism pathways, molecular features and
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Figure 5.
Identification of
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Figure 6.
Identification of candidate therapeutic agents with higher sensitivity in patients with high
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