Large set data mining reveals overexpressed GPCRs in prostate and breast cancer: potential for active targeting with engineered anti-cancer nanomedicines

Abstract

Over 800 G-protein-coupled receptors (GPCRs) are encoded by the human genome and many are overexpressed in tumors. GPCRs are triggered by ligand molecules outside the cell and activate internal signal transduction pathways driving cellular responses. The receptor signals are desensitized by receptor internalization and this mechanism can be exploited for the specific delivery of ligand-linked drug molecules directly into cells. Detailed expression analysis in cancer tissue can inform the design of GPCR-ligand decorated drug carriers for active tumor cell targeting. The active targeting process utilizes ligand receptor interactions leading to binding and in most cases internalization of the ligand-attached drug carrier resulting in effective targeting of cancer cells. In this report public microarray data from the Gene Expression Omnibus (GEO) repository was used to identify overexpressed GPCRs in prostate and breast cancer tissues. The analyzed data confirmed previously known cancer receptor associations and identified novel candidates for potential active targeting. Prioritization of the identified targeting receptors is also presented based on high expression levels and frequencies in cancer samples but low expression in healthy tissue. Finally, some selected examples were used in ligand docking studies to assess the feasibility for chemical conjugation to drug nanocarriers without interference of receptor binding and activation. The presented data demonstrate a large untapped potential to improve efficacy and safety of current and future anti-cancer compounds through active targeting of GPCRs on cancer cells.

Keywords: GPCR; Pathology; cancer; meta-data; nanocarrier; targeted chemotherapy.

Figure 1. Active targeting of cancer cells

Nanoparticles are decorated with ligands for specific docking to GPCRs overexpressed in cancer cells and driving cellular uptake via receptor internalization. (A) ELPs are self-assembling diblock copolymers which can be engineered as fusion proteins with a tethered peptide ligand (depicted as blue sphere). (B) Small molecule ligands can be covalently attached to lipid components such as phosphatidylcholine for display on the surface of drug loaded liposomes.

Figure 2. In silico GPCR gene selection algorithm

Suitable GLP570 based data sets were selected and a diverse set of inclusion criteria were applied to select a final set of 12 GPCR genes.

Figure 3. Gene expression analysis using a scatter plot to compare benign, local and metastatic tumor samples from the GDS1439 data set

(A) Benign vs metastatic (R² = 0.8734) and inset showing benign vs primary local (R² = 0.9760). White dots indicate GPCR genes. (B) Box plot comparing expression of all genes vs GPCRs only. The 2nd and 3rd quartiles are colored in green and red, respectively. The first and fourth quartiles are indicated by error bars. A general lower expression level of GPCR genes can be deduced.

Figure 4. Gene expression analysis using a scatter plot with data from GSE22544

(A) Normal vs node metastasis R² = 0.8663. Inset: Normal vs IDC R² = 0.8657. White dots indicate GPCR genes. (B) Box plot comparing expression of all genes vs GPCRs. The 2nd and 3rd quartiles are colored in green and red, respectively. The first and fourth quartiles are indicated by error bars. A general lower expression level of GPCR genes can be deduced. IDC: infiltrating ductal carcinoma.

Figure 5

Docking of peptide and lipid ligands into their cognate receptors (A) FPR1, (B) KISS1R, (C) GRPR and (D) GPR18. Arrows depict putative anti-cancer agent attachment sites on the N-terminal amino group of uPAR88-92 (A) and neuromedin C (C); the C-terminal carboxy group of kisspeptin14 (B); the C20 atom of arachidonic acid in N-Arachidonylglycine (D).