AUTHOR=Tan Manli , Gao Shangzhi , Ru Xiao , He Maolin , Zhao Jinmin , Zheng Li 

TITLE=Prediction and Identification of GPCRs Targeting for Drug Repurposing in Osteosarcoma

JOURNAL=Frontiers in Oncology

VOLUME=Volume 12 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.828849

DOI=10.3389/fonc.2022.828849

ISSN=2234-943X

ABSTRACT=Abstract
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 OS. GPCRs are the common drug targets and have been found to be associated with OS, but have been seldom used in OS.
Methods: The GPCRs were obtained from GPCRdb, and the GPCRs expression profile of 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 bioinformatics analysis. The therapeutic effect of the target and the target drug through the clone formation experiment.
Results: We screened out 10 representative GPCRs from 50 GPCRs related to OS risk and established a 10-GPCRs prognostic model (among them, CCR4, HCRTR2, DRD2, HTR1A, GPR158, and GPR3 as protective factors, however, HTR1E, OPN3，GRM4, and GPR144 as risk factors),  the low-risk group of the model was significantly associated with the high survival probability, and the area under the curve (AUC) of the ROC was greater than 0.9, which means an accuracy predictive effect of the model. The univariate and multivariate Cox regression analysis revealed that both model and metastasis were the independent risk factor of OS, and the risk score was positively associated with the metastatic. Importantly, the CD8 T-cell was more abundant in the low-risk group, which simply explained the underlying mechanism of the model to predict survival rate. Finally, we found that DRD2 was a novel target with approved drugs (cabergoline and bromocriptine), and its target drugs were proven to work on OS in this study. These novel findings might facilitate the development of OS drugs.
Conclusion: This study offers a satisfactory 10-GPCRs signature model to predict the OS prognostic, and based on the model signature, candidate targets with approved drugs were provided.