The Interplay between Cancer Biology and the Endocannabinoid System-Significance for Cancer Risk, Prognosis and Response to Treatment

Abstract

The various components of the endocannabinoid system (ECS), such as the cannabinoid receptors (CBRs), cannabinoid ligands, and the signalling network behind it, are implicated in several tumour-related states, both as favourable and unfavourable factors. This review analyses the ECS's complex involvement in the susceptibility to cancer, prognosis, and response to treatment, focusing on its relationship with cancer biology in selected solid cancers (breast, gastrointestinal, gynaecological, prostate cancer, thoracic, thyroid, CNS tumours, and melanoma). Changes in the expression and activation of CBRs, as well as their ability to form distinct functional heteromers affect the cell's tumourigenic potential and their signalling properties, leading to pharmacologically different outcomes. Thus, the same ECS component can exert both protective and pathogenic effects in different tumour subtypes, which are often pathologically driven by different biological factors. The use of endogenous and exogenous cannabinoids as anti-cancer agents, and the range of effects they might induce (cell death, regulation of angiogenesis, and invasion or anticancer immunity), depend in great deal on the tumour type and the specific ECS component that they target. Although an attractive target, the use of ECS components in anti-cancer treatment is still interlinked with many legal and ethical issues that need to be considered.

Keywords: anti-cancer treatment; cancer risk; cannabinoid receptors; cannabinoids.

Figure 1

STRING interaction analysis of cannabinoid receptors. (a) Direct STRING analysis network was built based on high confidence (0.7) evidence from experimental interaction data (pink), co-expression (black), gene neighbourhood (green) and co-occurrence (blue) data, curated databases (light blue), protein homology (purple), and predictive and knowledge text mining (light green); (b) The network was extended to 5 primary-interaction shell genes to explore their indirect interactions and clustering (PPI enrichment p-value: 2.39 × 10⁻¹²) using the intersection of 12 genes present on all analysed platforms. Red nodes—CNR1/CNR2 cluster, green nodes—GPR119 cluster, blue nodes—TRPV2 cluster. Nodes are labelled with Human Gene Nomenclature Committee (HGNC) gene symbols: CNR1—Cannabinoid receptor 1 gene, CNR2—Cannabinoid receptor 2 gene, DRD2—dopamine receptor D2, DRD3—dopamine receptor D3, GCG—glucagon, GPR18—N-arachidonyl glycine receptor (G-protein coupled receptor 18), GPR55—G-protein coupled receptor 55, GPR119—Glucose-dependent insulinotropic receptor (G protein-coupled receptor 119), OPRD1—Opioid Receptor Delta 1, OPRL1—Opioid Related Nociceptin Receptor 1, TRPV1 and TRPV2—transient receptor potential cation channel subfamily V members 1 and 2.

Figure 2

The expression of CNR1, CNR2, GPR119 and TRPV2 in cancer according to the Human Protein Atlas database [13]. (a) Expression of CNR1 in cancer subtypes; (b) expression of CNR2 in cancer subtypes; (c) survival curves of pancreatic cancer patients according to the expression of GPR119 favourable prognostic factor, p < 0.001); (d) survival curves of renal cancer patients according to the expression of TRPV2 (unfavourable prognostic factor, p < 0.001); (e) survival curves of testicular cancer according to the expression of TRPV2 (unfavourable prognostic factor, p < 0.001).