Abstract / Summary
Cancer is a complex and heterogeneous disease characterized by dynamic genetic, metabolic, and microenvironmental alterations. In addition to established classical biological mechanisms, quantum-scale processes such as proton tunneling, electron transfer, and spin-dependent reactions have been proposed to contribute to selected molecular events relevant to cancer biology. This review examines the current evidence supporting these mechanisms and discusses their possible implications for mutagenesis, mitochondrial metabolism, and reactive oxygen species regulation. We also review quantum dot-based approaches for tumor imaging, biosensing, targeted drug delivery, and photodynamic therapy, together with emerging applications of quantum computing and quantum machine learning in molecular simulation, cancer classification, and treatment optimization. Although these approaches have generated substantial experimental and theoretical interest, most remain at the preclinical, proof-of-concept, or computational stage, and their clinical relevance has not yet been firmly established. Important limitations include biological decoherence, uncertainty regarding the magnitude and functional significance of quantum effects in complex cellular environments, toxicity and biodistribution concerns associated with some quantum materials, limitations of current quantum hardware, and the need for rigorous external and clinical validation. Future progress will depend on multidisciplinary research that clearly distinguishes established molecular-scale quantum phenomena from speculative interpretations and evaluates whether quantum-informed technologies provide measurable advantages over conventional approaches. Overall, quantum science may offer complementary perspectives and technological tools for oncology, but its clinical impact remains to be determined.