Eliciting a potent antitumor immune response by expressing tumor antigens in a skin commensal
Chen, Y. E.; Atabakhsh, K.; Dimas, A.; Nagashima, K.; Fischbach, M. A.
Show abstract
Immune modulation has become central to treating cancer. However, global immune stimulation is only effective in a subset of patients and can lead to serious complications, including colitis and type I diabetes. Newer modalities like engineered T cells and tumor vaccines are more specific, but they have shown limited efficacy in solid tumors and are difficult to scale. Bacterial strains from the human microbiome can induce antigen-specific T cells to help maintain barrier function. Here, we redirect CD8+ and CD4+ T cells elicited by the skin commensal Staphylococcus epidermidis to recognize tumor cells by expressing tumor-derived antigens in the bacterial cell. S. epidermidis expressing the model antigen ovalbumin (S. epidermidis-OVA) stimulates antigen-specific CD8+ and CD4+ T cells in vitro. The subcellular localization of the antigen skews the response: cell wall-attached OVA preferentially stimulates CD8+ T cells whereas secreted OVA predominantly induces CD4+ T cells. In a syngeneic tumor model (OVA-expressing B16 melanoma), mice colonized topically with S. epidermidis-OVA exhibit a marked reduction in subcutaneous tumor volume compared to mice colonized with S. epidermidis expressing mCherry; this effect is dependent on live bacteria and a combination of CD8+ and CD4+ T cells. S. epidermidis-OVA also reduces tumor burden when tumor cells are injected intravenously (a model of metastasis), demonstrating that the antitumor effect operates in tissues distant from the site of bacterial colonization. S. epidermidis strains expressing neoantigen peptides from the B16 tumor cell line exhibit potent antitumor efficacy without inducing an autoimmune response against melanocytes in healthy tissue. Antigen-expressing colonists are a simple but powerful strategy to elicit a targeted T cell response in the context of cancer and other diseases.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Mosaic sarbecovirus nanoparticles elicit cross-reactive responses in pre-vaccinated animals 94%
- Immune factor of bacterial origin protects ticks against host microbial commensals 94%
- Single-dose respiratory mucosal delivery of next-generation viral-vectored COVID-19 vaccine provides robust protection against both ancestral and variant strains of SARS-CoV-2 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.