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Prediction and Identification of GPCRs Targeting for Drug Repurposing in Osteosarcoma
BACKGROUND: Osteosarcoma (OS) is a malignant bone tumor common in children and adolescents. The 5-year survival rate is only 67-69% and there is an urgent need to explore novel drugs effective for the OS. G protein-coupled receptors (GPCRs) are the common drug targets and have been found to be assoc...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9021700/ https://www.ncbi.nlm.nih.gov/pubmed/35463319 http://dx.doi.org/10.3389/fonc.2022.828849 |
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author | Tan, Manli Gao, Shangzhi Ru, Xiao He, Maolin Zhao, Jinmin Zheng, Li |
author_facet | Tan, Manli Gao, Shangzhi Ru, Xiao He, Maolin Zhao, Jinmin Zheng, Li |
author_sort | Tan, Manli |
collection | PubMed |
description | BACKGROUND: Osteosarcoma (OS) is a malignant bone tumor common in children and adolescents. The 5-year survival rate is only 67-69% and there is an urgent need to explore novel drugs effective for the OS. G protein-coupled receptors (GPCRs) are the common drug targets and have been found to be associated with the OS, but have been seldom used in OS. METHODS: The GPCRs were obtained from GPCRdb, and the GPCRs expression profile of the OS was downloaded from the UCSC Xena platform including clinical data. 10-GPCRs model signatures related to OS risk were identified by risk model analysis with R software. The predictive ability and pathological association of the signatures in OS were explored by bio-informatics analysis. The therapeutic effect of the target was investigated, followed by the investigation of the targeting drug by the colony formation experiment were. RESULTS: We screened out 10 representative GPCRs from 50 GPCRs related to OS risk and established a 10-GPCRs prognostic model (with CCR4, HCRTR2, DRD2, HTR1A, GPR158, and GPR3 as protective factors, and HTR1E, OPN3, GRM4, and GPR144 as risk factors). We found that the low-risk group of the model was significantly associated with the higher survival probability, with the area under the curve (AUC) of the ROC greater than 0.9, conforming with the model. Moreover, both risk-score and metastasis were the independent risk factor of the OS, and the risk score was positively associated with the metastatic. Importantly, the CD8 T-cells were more aggregated in the low-risk group, in line with the predict survival rate of the model. Finally, we found that DRD2 was a novel target with approved drugs (cabergoline and bromocriptine), and preliminarily proved the therapeutic effects of the drugs on OS. These novel findings might facilitate the development of OS drugs. CONCLUSION: This study offers a satisfactory 10-GPCRs model signature to predict the OS prognostic, and based on the model signature, candidate targets with approved drugs were provided. |
format | Online Article Text |
id | pubmed-9021700 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90217002022-04-22 Prediction and Identification of GPCRs Targeting for Drug Repurposing in Osteosarcoma Tan, Manli Gao, Shangzhi Ru, Xiao He, Maolin Zhao, Jinmin Zheng, Li Front Oncol Oncology BACKGROUND: Osteosarcoma (OS) is a malignant bone tumor common in children and adolescents. The 5-year survival rate is only 67-69% and there is an urgent need to explore novel drugs effective for the OS. G protein-coupled receptors (GPCRs) are the common drug targets and have been found to be associated with the OS, but have been seldom used in OS. METHODS: The GPCRs were obtained from GPCRdb, and the GPCRs expression profile of the OS was downloaded from the UCSC Xena platform including clinical data. 10-GPCRs model signatures related to OS risk were identified by risk model analysis with R software. The predictive ability and pathological association of the signatures in OS were explored by bio-informatics analysis. The therapeutic effect of the target was investigated, followed by the investigation of the targeting drug by the colony formation experiment were. RESULTS: We screened out 10 representative GPCRs from 50 GPCRs related to OS risk and established a 10-GPCRs prognostic model (with CCR4, HCRTR2, DRD2, HTR1A, GPR158, and GPR3 as protective factors, and HTR1E, OPN3, GRM4, and GPR144 as risk factors). We found that the low-risk group of the model was significantly associated with the higher survival probability, with the area under the curve (AUC) of the ROC greater than 0.9, conforming with the model. Moreover, both risk-score and metastasis were the independent risk factor of the OS, and the risk score was positively associated with the metastatic. Importantly, the CD8 T-cells were more aggregated in the low-risk group, in line with the predict survival rate of the model. Finally, we found that DRD2 was a novel target with approved drugs (cabergoline and bromocriptine), and preliminarily proved the therapeutic effects of the drugs on OS. These novel findings might facilitate the development of OS drugs. CONCLUSION: This study offers a satisfactory 10-GPCRs model signature to predict the OS prognostic, and based on the model signature, candidate targets with approved drugs were provided. Frontiers Media S.A. 2022-04-07 /pmc/articles/PMC9021700/ /pubmed/35463319 http://dx.doi.org/10.3389/fonc.2022.828849 Text en Copyright © 2022 Tan, Gao, Ru, He, Zhao and Zheng https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Tan, Manli Gao, Shangzhi Ru, Xiao He, Maolin Zhao, Jinmin Zheng, Li Prediction and Identification of GPCRs Targeting for Drug Repurposing in Osteosarcoma |
title | Prediction and Identification of GPCRs Targeting for Drug Repurposing in Osteosarcoma |
title_full | Prediction and Identification of GPCRs Targeting for Drug Repurposing in Osteosarcoma |
title_fullStr | Prediction and Identification of GPCRs Targeting for Drug Repurposing in Osteosarcoma |
title_full_unstemmed | Prediction and Identification of GPCRs Targeting for Drug Repurposing in Osteosarcoma |
title_short | Prediction and Identification of GPCRs Targeting for Drug Repurposing in Osteosarcoma |
title_sort | prediction and identification of gpcrs targeting for drug repurposing in osteosarcoma |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9021700/ https://www.ncbi.nlm.nih.gov/pubmed/35463319 http://dx.doi.org/10.3389/fonc.2022.828849 |
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