DNA replication stress stratifies prognosis and enables exploitable therapeutic vulnerabilities of HBV-associated hepatocellular carcinoma: An in-silico precision oncology strategy

Xiaofan Lu; Jialin Meng; Haitao Wang; Yujie Zhou; Jianguo Zhou; Xinjia Ruan; Yi Chen; Yuqing Ye; Liwen Su; Xiaole Fan; Hangyu Yan; Liyun Jiang; Fangrong Yan

doi:10.59717/j.xinn-med.2023.100014

The Innovation Medicine > 2023 Vol. 1 > No. 1 > 100014

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DNA replication stress stratifies prognosis and enables exploitable therapeutic vulnerabilities of HBV-associated hepatocellular carcinoma: An in-silico precision oncology strategy

1.
Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing 211198, China
2.
Department of Cancer and Functional Genomics, Institute of Genetics and Molecular and Cellular Biology, CNRS/INSERM/UNISTRA, Illkirch 67400, France
3.
Department of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
4.
Cancer Center, Faculty of Health Sciences, Center for Precision Medicine Research and Training, University of Macau, Macau SAR 999078, China
5.
Division of Gastroenterology and Hepatology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China
6.
Department of Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi 563000, China
7.
Department of Radiation Oncology, Universitätsklinikum Erlangen, Erlangen 91054, Germany
8.
Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
9.
Department of Radiology, The Second Affiliated Hospital of Nantong University, Nantong 226001, China
10.
Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
11.
These authors contributed equally
12.
Current Address: Thoracic Surgery Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20814, USA

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Corresponding authors: ljiang.cpu@foxmail.com (L.J.); f.r.yan@outlook.com (F.Y.)
Received Date: 20 February 2023

Accepted Date: 12 May 2023

Published Online: 06 June 2023

The Innovation Medicine 1(1), https://doi.org/10.59717/j.xinn-med.2023.100014 | Cite this article

GRAPHICAL ABSTRACT

GRAPHICAL ABSTRACT

PUBLIC SUMMARY

PUBLIC SUMMARY
1. 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 (PI_RS) improves population-based prognostication.
  
  PI_RS enables exploitable therapeutic vulnerabilities.
  
  Four therapeutic targets and five agents were identified for HBV+ HCC.

ABSTRACT

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 (PI_RS) for HBV-associated HCC. Transcriptomic expression profiles from 606 HCC cases were used to construct PI_RS, which outperformed population-based predictors, demonstrating superior prognostic prediction in HBV-associated HCC. Lower PI_RS scores were associated with higher expression of HBV oncoproteins, activated immune/metabolism pathways, and increased responsiveness to immunotherapy. Conversely, higher PI_RS 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 PI_RS 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 PI_RS 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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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

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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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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