Among all malignant tumors that threaten human health, virus-related tumors account for a large proportion. The treatment of these tumors is still an urgent problem to be resolved. The immune system is the “guard” of the human body, resisting the invasion of foreign substances such as viruses. Studies have shown that immunotherapy has clinical significance in the treatment of a variety of tumors. In particular, the emergence of immune checkpoint inhibitors (ICIs) in recent years has opened a new door to cancer therapy. Considering the potential role of ICIs in the treatment of virus-related cancers, we focused on their therapeutic effect in virus-associated cancers and explored whether the therapeutic effect in virus-associated cancers was related to virus infection status. Although there is no clear statistical significance indicates that ICIs are more effective in virus-associated cancers than non-virus infections, the efficacy of checkpoint inhibitors in the treatment of virus-related cancers is promising. We believe that this research provides a good direction for the implementation of individualized precision medicine.

Summary: System-wide molecular characteristics of COVID-19, especially in those patients without comorbidities, have not been fully investigated. We compared extensive molecular profiles of blood samples from 231 COVID-19 patients, ranging from asymptomatic to critically ill, importantly excluding those with any comorbidities. Amongst the major findings, asymptomatic patients were characterized by highly activated anti-virus interferon, T/natural killer (NK) cell activation, and transcriptional upregulation of inflammatory cytokine mRNAs. However, given very abundant RNA binding proteins (RBPs), these cytokine mRNAs could be effectively destabilized hence preserving normal cytokine levels. In contrast, in critically ill patients, cytokine storm due to RBPs inhibition and tryptophan metabolites accumulation contributed to T/NK cell dysfunction. A machine-learning model was constructed which accurately stratified the COVID-19 severities based on their multi-omics features. Overall, our analysis provides insights into COVID-19 pathogenesis and identifies targets for intervening in treatment.