The renaissance of Salmonella-based cancer therapy: convergence of AI, synthetic circuits, and TME remodeling
Year: 2026
Type: article
Abstract: Attenuated Salmonella has become a candidate bacterium for cancer immunotherapy, as it possesses tumor-targeting activity and is able to penetrate the hypoxic, immune-suppressive TME. However, preclinical successes were not successfully translated into early clinical trials (e.g., VNP20009) due to a critical “immunogenicity-safety trade-off,” in which the attenuation required to ensure safety compromised the ability to generate effective anti-tumor immunity. Here, we provide an updated perspective on the renaissance of the field and discuss how the integration of synthetic biology and artificial intelligence (AI) is overcoming these historical barriers, including AI-driven tools such as Cello and SHASI-ML. We outline the progression from static attenuation to dynamic, rational design, where programmable genetic circuits (e.g., synchronized lysis systems and hypoxia-responsive logic gates) enable bacteria to be engineered as intelligent microrobots that can be used for the safe delivery of therapeutics while inducing precise, on-target immune stimulation. In addition to cytotoxicity effects, we focus on how Salmonella reprograms the metabolic environment of the TME and discuss specific metabolic pathways, such as asparagine depletion-mediated T-cell paralysis, that contribute to rescuing exhausted effector cells. Finally, linking preclinical advances with recent clinical successes (e.g., Saltikva), we hypothesize that next-generation engineered Salmonella is more than just a vector but rather a full immunological modulator delivering the potential to convert “cold” tumors into “hot” environments capable of providing a synergistic platform to enhance checkpoint inhibitors and chemotherapeutics.
Source: Frontiers in Immunology
Institution: Jilin University
Language: English
Subfield: Biotechnology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7155203784