{"doi":"10.1002/ctm2.70328","title":"Enhancing the safety and efficacy of cell therapy with programmed sense‐and‐respond function","abstract":"Over the past decade, cell-based therapies have emerged as a transformative pharmaceutical modality, offering unprecedented potential for treating previously incurable diseases.1 Whilst most cell-based therapies rely on intrinsic cell properties to achieve their therapeutic effects, genetic modification has gained traction as a strategy to enhance treatment safety and efficacy.2, 3 Amongst the most impactful therapeutic advancements are genetic engineering of adoptive T cell therapeutics, particularly for liquid tumour malignancies.4 Key breakthroughs include the development of chimeric antigen receptors (CARs) that reprogram T cell cytotoxicity towards tumour cells,5 protein-based safety switches that trigger apoptosis upon administration of a small-molecule drug6 and, most recently, synthetic multi-gene circuits that enable T cells to detect tumour antigens or soluble factors and conditionally deliver anti-tumour or immunomodulatory payloads in response.7 The continued evolution of this dynamic cell technology for broader clinical applications hinges on ongoing engineering innovations that enhance circuit precision and expand target detection capabilities. Towards this goal, we recently reported a circuit engineering toolkit that uses phosphorylation to drive circuit function, opening the door to engineering therapeutic sense-and-respond functionality that operates with the speed and precision of native cellular signalling pathways.8 Advantages of programming therapeutic cells to sense and respond. The implementation of synthetic sense-and-respond circuitry in therapeutic cells represents a paradigm shift in precision medicine, and has the potential to address long-standing challenges in drug delivery.1 Traditional therapeutic modalities, such as small molecules and biologics, can suffer from short in vivo half-lives and unfortunate side effects. Many cell therapies are challenged by invasive administration requirements for hard-to-reach tissues and significant off-target toxicities, including cytokine release syndrome and on-target, off-tissue toxicity.5 Synthetic circuits offer a potential solution to these challenges by furnishing cells with the ability to sense disease- or tissue-specific markers and respond by delivering therapeutic payloads with precisely defined spatial, temporal and dose profiles. Beyond enhancing therapeutic precision and minimising side effects, this approach effectively decouples therapeutic mode-of-action from the intrinsic properties of the host cell, facilitating programmable, context-specific responses to be engineered independently from the myriad complexities of native cellular function (Figure 1). Current state of engineering sense and respond for cell therapies. Pre-clinical efforts to engineer synthetic sense-and-respond circuits have followed two broad design approaches9 (Figure 2A). The first introduces programs that harness the activity of native signalling pathways to drive therapeutic transgene expression.10 Whilst these strategies benefit from the speed and robustness of endogenous signalling networks, they are inherently limited by pathway crosstalk, as native signalling components can be readily activated by non-specific stimuli. A second class of sense-and-respond circuits has been constructed primarily from synthetic protein components. Most of these designs rely on receptor-induced proteolysis to release synthetic transcription factors (TFs) that activate transgene expression or initiate other cellular functions.7 These circuits, some of which have recently advanced into clinical trials (NCT06245915), offer several benefits, including the ability to quantitatively tune the response function, and to configure inputs and outputs for diverse indications. However, the inherent non-reversibility of protease cleavage presents a significant limitation: once the ligand is removed, the cleaved synthetic TF can persist in the cell, resulting in slower rates of activation and deactivation","journal":"Clinical and Translational Medicine","year":2025,"id":543969,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9565,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":655769,"name":"Xiaoyu Yang","orcid":"0000-0001-5636-117X","position":1,"is_corresponding":false},{"id":340215,"name":"Scott D. Olson","orcid":"0000-0001-8032-3755","position":2,"is_corresponding":false},{"id":772441,"name":"Caleb J. Bashor","orcid":"0000-0003-1354-2098","position":3,"is_corresponding":false},{"id":884625,"name":"Andrew J. Walters","orcid":"0000-0002-1302-1738","position":0,"is_corresponding":true}],"reference_count":10,"raw_metadata":null,"created_at":"2026-07-19T02:53:08.338070Z","pmid":"40292750","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}