Identification of a novel mitophagy-related signature for predicting clinical prognosis and immunotherapy of osteosarcoma

Author:

Xu Peichuan1,Zhao Jiangminghao1,Zhao Wenrui1,Yuan Jinghong1,Li Kaihui2,Wang Yameng1,Hu Yiming1,Pan Chongzhi1,Pan Huajun1,Wu Tianlong1,Miao Xinxin1,Cheng Xigao1

Affiliation:

1. Department of Orthopaedics, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University

2. Department of stomatology, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University

Abstract

Abstract

Background Osteosarcoma (OS) is a highly aggressive malignancy characterized by a poor prognosis. Mitochondrial autophagy (mitophagy) has been implicated in tumor initiation, progression, and response to therapy, highlighting it a potential prognostic indicator and therapeutic target in cancers. Despite this, the precise mechanisms underlying mitophagy in osteosarcoma remain enigmatic. This research aims to develop a mitophagy-associated signature to guide therapeutic strategies and prognosis estimations. Methods Clinical and transcriptome data for patients with osteosarcoma and skeletal muscle tissue were retrieved from UCSC Xena and GTEx. Mitophagy-related genes (MRGs) were obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG) website. A predictive risk model was constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm and Cox regression analysis. To delve into the fundamental gene expression mechanisms, we employed Gene Ontology (GO), KEGG, and Gene Set Enrichment Analysis (GSEA). Moreover, the different immune-related activities between the two groups were investigated to ascertain the efficacy of immunotherapy. Lastly, the functional analysis of the key risk gene MRAS was carried out via in vitro experiments and a pan-cancer analysis and potential small molecule drugs that may target MRAS were screened through molecular docking. Results Based on seven mitophagy-related prognostic gene signatures, osteosarcoma patients were stratified into high- and low-risk categories. The predictive model exhibited strong prognostic capability, as evidenced by Kaplan-Meier analysis, time-dependent AUC, and Nomogram. Notably, compared to the low-risk group, individuals in the high-risk group exhibited lower stromal, immune, and estimate scores.The infiltration of immune cells in high-risk group decreased. Further evidence supporting MRAS's protective role against osteosarcoma was shown in vitro, where upregulating its expression could suppress the proliferation, migration, and invasion of osteosarcoma cells while stimulating their apoptosis. Pan-cancer analysis further demonstrated its role in a variety of tumors. Conclusion This study identified a mitophagy-related prognostic signature and elucidated the impact of MRAS on osteosarcoma cells. Consequently, it opened up fresh avenues for clinical prognosis prediction and established a basis for precision therapy in osteosarcoma.

Publisher

Research Square Platform LLC

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