Abstract / Summary
Cannabinoids have gained increasing attention as potential anticancer agents because of their ability to modulate diverse cancer-associated signaling pathways and biological processes.: Cannabinoids, including cannabidiol (CBD) and Δ9-tetrahydrocannabinol (THC), can influence tumor proliferation, apoptosis, angiogenesis, metabolism, immune regulation, and tumor–microenvironment interactions. However, clinical translation remains limited, as evidence of anticancer efficacy is derived predominantly from preclinical studies. Major knowledge gaps include the absence of validated predictive biomarkers, unclear criteria for patient selection, and limited evidence regarding optimal therapeutic and combination strategies. Thus, the central challenge is to identify the patients and tumor contexts most likely to benefit from cannabinoid-based therapy. We propose a precision cannabinoid oncology framework that integrates molecular characterization, molecular classification, predictive biomarker development, rational combination strategies, and prospective clinical validation. This approach may provide a conceptual foundation for moving cannabinoid oncology from broadly empirical investigation toward molecularly informed patient selection and prospective validation of cannabinoid-based therapies in molecularly defined patient populations.