Dataset Information

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.

SUBMITTER: Kubler E

PROVIDER: S-EPMC5982759 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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

Kübler Eric E Albrecht Hugo H

Oncotarget 20180518 38

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 ...[more]

PMID: 29861840

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Project description:BACKGROUND: The Pubchem Database is a large-scale resource for chemical information, containing millions of chemical compound activities derived by high-throughput screening (HTS). The ability to extract characteristic substructures from such enormous amounts of data is steadily growing in importance. Compounds with shared basic active structures (BASs) exhibiting G-protein coupled receptor (GPCR) activity and repeated dose toxicity have been mined from small datasets. However, the mining process employed was not applicable to large datasets owing to a large imbalance between the numbers of active and inactive compounds. In most datasets, one active compound will appear for every 1000 inactive compounds. Most mining techniques work well only when these numbers are similar. RESULTS: This difficulty was overcome by sampling an equal number of active and inactive compounds. The sampling process was repeated to maintain the structural diversity of the inactive compounds. An interactive KNIME workflow that enabled effective sampling and data cleaning processes was created. The application of the cascade model and subsequent structural refinement yielded the BAS candidates. Repeated sampling increased the ratio of active compounds containing these substructures. Three samplings were deemed adequate to identify all of the meaningful BASs. BASs expressing similar structures were grouped to give the final set of BASs. This method was applied to HIV integrase and protease inhibitor activities in the MDL Drug Data Report (MDDR) database and to procaspase-3 activators in the PubChem BioAssay database, yielding 14, 12, and 18 BASs, respectively. CONCLUSIONS: The proposed mining scheme successfully extracted meaningful substructures from large datasets of chemical structures. The resulting BASs were deemed reasonable by an experienced medicinal chemist. The mining itself requires about 3 days to extract BASs with a given physiological activity. Thus, the method described herein is an effective way to analyze large HTS databases.

Dataset Information

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

Publications

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

Similar Datasets

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