T cells sit at the center of modern immunotherapy, yet many of the rules that govern their activation, differentiation, dysfunction (e.g., exhaustion), and long-term performance remain difficult to predict—and even harder to control. This Research Topic will highlight how systems-level approaches can convert T cell complexity into testable hypotheses, predictive frameworks, and actionable strategies for immunotherapy and immune modulation.
We welcome contributions that model, measure, or engineer T cell behavior across scales, from molecular signaling and gene regulation to cell–cell interactions, tissue organization, and whole‑patient responses. Submissions may draw on multi-omics and multi-scale data, including but not limited to single-cell and spatial profiling, time-resolved measurements, lineage tracing, perturbation screens, imaging, and clinical datasets. We encourage work that addresses cell-to-cell variability, stochasticity, and microenvironmental constraints (e.g., cytokines, antigen, nutrients, metabolites, hypoxia, biomechanical cues), and that clarifies how these factors shape T cell fate decisions and functional outcomes.
This Topic also aims to showcase engineering and translational directions informed by quantitative understanding. Areas of interest include, but are not limited to: synthetic receptors and gene circuits; programmable cytokine and co-stimulation control; logic-gated activation; tunable persistence and memory formation; resistance to exhaustion and suppression; improved trafficking and tissue infiltration; safety mechanisms; and approaches that modulate T cell interactions with other immune and stromal cells (e.g., dendritic cells, macrophages, tumor cells). We also welcome studies on manufacturing, quality control, and standardization, including predictive tools for potency, durability, safety, and batch comparability.
Contributions may be experimental, computational, theoretical, or integrative, and may take the form of Original Research, Methods, Reviews, or Perspectives, provided they advance generalizable insight or practical design principles. Overall, this collection will provide a forum for research that connects foundational immunology with quantitative modeling and engineering—advancing our ability to understand, forecast, and shape T cell responses for cancer, autoimmunity, infection, vaccination, and beyond.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Case Report
Community Case Study
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
General Commentary
Hypothesis and Theory
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Case Report
Community Case Study
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
General Commentary
Hypothesis and Theory
Methods
Mini Review
Opinion
Original Research
Perspective
Policy and Practice Reviews
Policy Brief
Review
Systematic Review
Technology and Code
Keywords: T cell immunotherapy, systems immunology, T cell exhaustion, multi-omics, single-cell sequencing, spatial transcriptomics, gene regulatory networks, synthetic gene circuits, logic-gated activation, predictive modeling
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.