AUTHOR=Feng Haijun , Wang Liping , Liu Jie , Wang Shengbao 

TITLE=The bioinformatic approach identifies PARM1 as a new potential prognostic factor in osteosarcoma

JOURNAL=Frontiers in Oncology

VOLUME=Volume 12 - 2022

YEAR=2023

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.1059547

DOI=10.3389/fonc.2022.1059547

ISSN=2234-943X

ABSTRACT=To explore the key factors affecting the prognosis of patients with osteosarcoma, we performed differential expression analysis between normal and osteosarcoma tissues based on the Gene Expression Omnibus (GEO) dataset. We screened gene modules related to the prognosis of osteosarcoma patients by weighted gene co-expression network analysis (WGCNA) and obtained 9 common genes by hybridizing with differential expressed genes (DEGs). The least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct the risk and prognosis model of osteosarcoma patients. The prognostic factor PARM1 of osteosarcoma patients was obtained by survival analysis, and then the low expression of PARM1 in osteosarcoma cells was verified by cell experiments. Pan-cancer analysis showed that PARM1 is under-expressed in most cancers, and low expression of PARM1 predicts poor patient prognosis. Therefore, our study suggests that PARM1 is closely related to the prognosis of patients with osteosarcoma, and PARM1 may serve as a new potential prognostic target for osteosarcoma and provide guidance for the prevention and treatment of osteosarcoma.