Viral persistence and host-state remodeling in virus-associated cancers

Jiaqi Ma1, Jianchao Guo2, Guohao Li2

  • 1College of Basic Medicine and Forensic Medicine, Henan University of Science and Technology, Luoyang, 471023, China. Mjq13633944270@163.com.

Insights

Mechanistic understanding of virus-associated cancers requires more than viral detection. This review proposes four analytical axes to organize evidence, guiding research on viral persistence and host immune responses.

Area of Science:

  • Oncology
  • Virology
  • Immunology

Background:

  • Virus-associated cancers are complex, with mechanisms not solely defined by viral detection.
  • Current research often focuses on individual viruses, hindering a unified mechanistic understanding.

Purpose of the Study:

  • To propose a novel framework for organizing evidence on virus-associated cancers.
  • To guide experimental design for studying viral persistence and host-state remodeling.
  • To differentiate therapeutic targets from biomarkers in cancer research.

Main Methods:

  • Organizing evidence around four analytical axes: retained-product dependence, regulatory architecture of viral material, host-state memory, and tissue-level selection.
  • Reviewing evidence across diverse tumor-virus systems.
  • Highlighting the importance of matching evidence type to the research question (e.g., detection vs. functional testing).

Main Results:

  • The four axes provide a structured approach to analyze complex viral oncogenesis.
  • This framework encompasses various viral states (expression, latency, genome maintenance) and host responses (immune/stromal selection).
  • Distinguishes between biomarkers and true therapeutic dependencies.

Conclusions:

  • A systematic, multi-axis approach is crucial for advancing the mechanistic understanding of virus-associated cancers.
  • This framework aids in designing targeted experiments and interpreting complex data.
  • It facilitates the identification of actionable therapeutic strategies beyond simple viral detection.

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