Dong, Y. E. | bioRxiv Science

bioRxiv2026

Characterization of Cytochrome P450-Mediated Metabolism of Δ8-tetrahydrocannabinol in vitro

{Delta}-tetrahydrocannabinol ({Delta}8-THC) is a pharmacologically active isomer of {Delta}9-THC, the main psychoactive component of cannabis. {Delta}8-THC use has increased rapidly, but the metabolism of {Delta}8-THC has been incompletely characterized. This study identified metabolites of {Delta}8-THC formed by cytochrome P450 (CYP) enzymes in human liver microsomes (HLM), assigned the main CYPs responsible for the metabolic pathways, and evaluated the impact of genetic polymorphisms on {Delta}8-THC metabolism in vitro. Five monohydroxylated {Delta}8-THC metabolites, identified as 11-OH-{Delta}8-THC, two aliphatic side-chain hydroxylated products (M1, M2), and two ring hydroxylated products (M3, M4) were detected in HLM. 11-OH-{Delta}8-THC was the most abundant metabolite. Unbound binding constants for metabolite formation in HLM ranged from 3.6 nM to >121 nM, suggesting multiple enzymes contribute to {Delta}8-THC metabolism. The contributing enzymes were identified using recombinant CYPs, inhibition studies, and correlation analyses. 11-OH-{Delta}8-THC was predominantly formed by CYP2C9 with a minor contribution from CYP2C19. CYP2C9 genotype-based activity scores across donors correlated with 11-OH-{Delta}8-THC formation (p = 0.0315). An 80% decrease in 11-OH-{Delta}8-THC formation clearance was predicted in CYP2C9*3/*3 carriers. The ring-hydroxylated M3 and M4 were mainly formed by CYP3A. CYP2D6, CYP1A2, and CYP3A4 activities were associated with formation of the pentyl side-chain oxidized metabolites M1 and M2. Although C11 hydroxylation appeared more important metabolic pathway for {Delta}8-THC than for {Delta}9-THC, the catalytic efficiency of CYP2C9 towards {Delta}8-THC was lower than towards {Delta}9-THC. In the presence of CYP2C9 inhibitors or genetic polymorphisms, {Delta}8-THC clearance is likely mediated by CYP3A4 and CYP2C19. This study shows that 11-OH-{Delta}8-THC, a psychoactive metabolite, is the primary oxidation product of {Delta}8-THC in HLM and that CYP2C9 predominantly catalyzes its formation. This work expands the limited literature on {Delta}8-THC metabolism, and shows that reduced-function CYP2C9 variants substantially impair formation of 11-OH-{Delta}8-THC. The characterization of {Delta}8-THC metabolism in HLM provides the foundation for risk assessment of drug-drug interactions and establishes the metabolic profile of {Delta}8-THC in the human liver.

pharmacology and toxicology↗

bioRxiv2025

From Transcripts to Cells: Dissecting Sensitivity, Signal Contamination, and Specificity in Xenium Spatial Transcriptomics

Spatial transcriptomics has transformed our ability to map gene expression within intact tissues at cellular and subcellular resolution. Among current platforms, Xenium is widely adopted for its reliability, accessibility, and high data quality. Yet, the properties and limitations of Xenium-derived data remain poorly characterized. Here, we present one of the most comprehensive Xenium datasets to date, encompassing over 40 breast and lung tumor sections profiled using a diverse set of gene panels. Leveraging this resource, we systematically dissect technical noise--including transcript diffusion--alongside assay specificity, panel performance, and segmentation strategies. Our comparison of targeted panels with the newer 5K panel reveals that although the latter captures more transcripts overall, it suffers from reduced per-gene sensitivity and persistent diffusion, even with enhanced chemistry. We demonstrate that single-nucleus RNA-seq (snRNA-seq) markedly improves cell type annotation and enables more precise quantification of diffusion. Building on this, we introduce SPLIT (Spatial Purification of Layered Intracellular Transcripts), a novel method that integrates snRNA-seq with RCTD deconvolution to enhance signal purity. SPLIT effectively resolves mixed transcriptomic signals, improving background correction and cell-type resolution. Together, our findings provide a critical benchmark for Xenium performance and introduce a scalable strategy for signal refinement--advancing the accuracy and utility of spatial transcriptomics.

cancer biology↗