Hepatitis C virus-associated B-cell non-Hodgkin lymphomas: immune evasion, multistep lymphomagenesis, and candidate biomarkers for risk stratification and disease monitoring
Background Hepatitis C virus (HCV)-associated B-cell non-Hodgkin lymphomas represent a compelling model of virus-driven oncogenesis in which immune evasion and viral persistence sustain chronic antigenic stimulation, B-cell clonal expansion and progressive multistep lymphomagenesis. Methods This minireview focuses on mechanisms that connect HCV immune escape with B-cell lymphomagenesis, antiviral treatment responses, and emerging biomarkers for risk stratification and disease monitoring. Results HCV persistence is sustained by extensive viral genetic variability (quasispecies formation) and by interference with innate and adaptive immune responses, including RIG-I/TLR3 pathway inhibition, suppression of interferon signaling, dendritic cell and natural killer cell dysfunction, and T-cell exhaustion. These mechanisms are relevant to lymphomagenesis because they maintain a persistent antigenic and inflammatory niche that supports chronic antigenic stimulation, clonal B-cell expansion, cytokine and chemokine dysregulation (e.g., BAFF/BLyS axis), apoptotic escape, and the progressive accumulation of genetic alterations and chromosomal aberrations. Lymphomagenesis thus emerges as a complex process consistent with a multistep model. Antiviral therapy provides a clinical indicator of this model, in which regression of some indolent HCV-associated lymphomas after viral eradication supports virus dependence, whereas incomplete lymphoproliferative response and the need for immunochemotherapy in aggressive lymphomas indicate partial independence from the viral trigger at advanced stages. Emerging biomarkers, including B-cell activation markers, immune-inflammatory mediators, immunogenetic susceptibility factors, microRNAs, and genomic alterations, show promise for risk stratification, and disease monitoring, but require further validation. Conclusion Integrating antiviral and antitumor strategies with biomarker-guided patient stratification may improve early cancer diagnosis and treatment prioritization.