Evolution of Aggregation-Induced Emission Materials in Cancer Diagnosis and Therapy: Toward Clinical Translation

Conspectus As one of the most formidable threats to human health, cancer demands technologies that can sensitively detect malignancies, precisely guide intervention, adapt to dynamic disease states, and support clinical decision-making. Phototheranostics based on organic fluorophores have shown great promise in cancer management owing to their tunable structural design, tumor-targeting capability, real-time imaging output, and biocompatibility with diverse therapeutic modalities. However, conventional fluorophores often suffer from aggregation-caused quenching in concentrated or biological aggregate states, leading to weakened signals, insufficient sensitivity, and limited therapeutic efficacy. The discovery of aggregation-induced emission (AIE) provides a conceptually distinct solution to this problem. AIE materials are weakly emissive in the molecularly dispersed state but become highly luminescent upon aggregation, thereby turning aggregation from a detrimental process into a useful photophysical mechanism. By precisely controlling molecular motion, AIE materials can exhibit advantages including high signal-to-noise ratio, large Stokes shifts, and excellent photostability, making them a versatile molecular toolbox for tumor-oriented phototheranostic systems. Over the past two decades, they have evolved beyond simple fluorescent probes into integrated platforms for cancer theranostics. In this Account, we propose a concept-driven framework, termed AIMS (Analyze-Intervene-Modulate-Select), to organize the evolution of AIE materials in cancer diagnosis and therapy according to their distinctive roles within cancer management. The first generation, “Analyze”, refers to AIE materials used mainly as diagnostic tools. These systems enable sensitive detection of tumor-associated biomarkers, in vivo lesion visualization, and multimodal intraoperative identification. The second generation, “Intervene”, generates all-in-one theranostic platforms that couple imaging with phototherapy, facilitating radiotherapy sensitization, immune activation, or postoperative control. The third generation, “Modulate”, describes intelligent and adaptive AIE platforms that respond to therapy-induced stress, microenvironmental shifts, or dynamic biological feedback during treatment, transforming static theranostics into systems capable of modulating therapeutic trajectories. The emerging fourth generation, “Select”, represents a data-driven paradigm linking the design of AIE materials with artificial intelligence, multiomics, patient stratification, model selection, and indication prioritization. Through AIMS, we organize the accumulated capabilities of AIE materials around four functional roles. By clarifying which role is most relevant to a given application, AIMS guides future research in prioritizing design objectives, integrating the functions needed for the intended task, and matching material innovation to specific needs in cancer management.