Modeling hepatitis C virus protein and p53 interactions in hepatocytes: Implications for carcinogenesis

Maria I. Poole, Inmaculada Sorribes, Harsh Vardhan Jain

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Hepatitis C virus (HCV) infection has reached epidemic proportions worldwide. Individuals with chronic HCV infection and without access to treatment are at high risk for developing hepatocellular carcinoma (HCC), a liver cancer that is rapidly fatal after diagnosis. A number of factors have been identified that contribute to HCV-driven carcinogenesis such as scarring of the liver, and chronic inflammation. Recent evidence indicates a direct role for HCV-encoded proteins themselves in oncogenesis of infected hepatocytes. The viral protein HCV core has been shown to interact directly with the host tumor suppressor protein p53, and to modulate p53-activity in a biphasic manner. Here, biochemically-motivated mathematical models of HCV-p53 interactions are developed to elucidate the mechanisms underlying this phenomenon. We show that by itself, direct interaction between HCV core and p53 is insufficient to recapitulate the experimental data. We postulate the existence of an additional factor, activated by HCV core that inhibits p53 function. We present experimental evidence in support of this hypothesis. The model including this additional factor reproduces the experimental results, validating our assumptions. Finally, we investigate what effect HCV core-p53 interactions could have on the capacity of an infected hepatocyte to repair damage to its DNA. Integrating our model with an existing model of the oscillatory response of p53 to DNA damage predicts a biphasic relationship between HCV core and the transformative potential of infected hepatocytes. In addition to providing mechanistic insights, these results suggest a potential biomarker that could help in identifying those HCV patients most at risk of progression to HCC.

Original languageEnglish (US)
Pages (from-to)186-196
Number of pages11
JournalMathematical Biosciences
StatePublished - Dec 2018
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2018 Elsevier Inc.


  • DNA damage
  • FUBP1
  • HCC
  • HCV
  • Mathematical model
  • p53


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