CAR-T 与纳米载体肿瘤疗法的通用逻辑门控框架：逻辑架构及其分子实现策略的跨平台比较分析

Logic-gated targeted therapies represent an emerging strategy to enhance specificity in cancer treatment by integrating multiple biological inputs to control therapeutic activation. Inspired by digital electronics, these systems apply Boolean logic operations such as AND, OR, and NOT to restrict therapeutic activity within defined cellular or microenvironmental contexts, based on combinations of tumor-associated cues such as antigen co-expression, acidity, or oxidative stress.

This review develops a generalized logic-gating framework that unifies terminology, design principles, and mechanistic features across two major therapeutic modalities: CAR-T cells, which implement protein-based logic using antigen-derived input signals, and nanocarriers, which encode logic chemically in response to tumor microenvironmental cues. The framework formalizes key design dimensions, including logic architecture, molecular implementation, logic behavior, and the stage within the therapeutic mechanism at which gating occurs.

Together, these dimensions provide a shared vocabulary for describing, comparing, and designing logic-gated therapies across platforms. Considering logic behavior as a distinct design dimension reveals how logic-gated therapeutic systems translate input signal intensity into activation output. Within the proposed framework, logic behavior captures both qualitative features, such as sharp (digital-like) versus graded (analog-like) activation, and quantitative aspects of the activation response, including threshold behavior and how activation dynamically unfolds over time.

Differences in logic behavior across therapeutic modalities arise from the nature of the input signals and from the molecular implementations that govern signal propagation and amplification. Formalizing logic behavior in this way provides a basis for systematic comparison of logic-gated systems beyond logic architecture and structural features alone and for interpreting differences in system behavior across platforms.

Overall, this work positions molecular logic gating and multimarker targeting within a unified conceptual structure, clarifies current limitations and variability across platforms, and outlines opportunities for designing next-generation programmable cancer therapies with improved specificity and reduced on-target, off-tumor toxicity.