CELL INTELLIGENCE · 肿瘤细胞治疗研究

Development of successful cancer therapeutics requires exploration of the differences in genetics, metabolism, and interactions with the immune system among malignant and normal cells. The clinical observation of spontaneous tumor regression following natural infection with microorganism has created the premise of their use as cancer therapeutics. Oncolytic viruses (OVs) originate from viruses with attenuated virulence in humans, well-characterized vaccine strains of known human pathogens, or engineered replication-deficient viral vectors.

Their selectivity is based on receptor expression level and post entry restriction factors that favor replication in the tumor, while keeping the normal cells unharmed. Clinical trials have demonstrated a wide range of patient responses to virotherapy, with subgroups of patients significantly benefiting from OV administration. Tumor-specific gene signatures, including antiviral interferon-stimulated gene (ISG) expression profile, have demonstrated a strong correlation with tumor permissiveness to infection.

Furthermore, the combination of OVs with immunotherapeutics, including anticancer vaccines and immune checkpoint inhibitors [ICIs, such as anti-PD-1/PD-L1 or anti-CTLA-4 and chimeric antigen receptor (CAR)-T or CAR-NK cells], could synergistically improve the therapeutic outcome.

Creating response prediction algorithms represents an important step for the transition to individualized immunovirotherapy approaches in the clinic. Integrative predictors could include tumor mutational burden (TMB), inflammatory gene signature, phenotype of tumor-infiltrating lymphocytes, tumor microenvironment (TME), and immune checkpoint receptor expression on both immune and target cells.

Additionally, the gut microbiota has recently been recognized as a systemic immunomodulatory factor and could further be used in the optimization of individualized immunovirotherapy algorithms.