Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Identification of RPS28 as a Promising Therapeutic Target for Osteosarcoma Patients with Poor Prognoses Stratified by a Seven-Gene Signature

Yin Sun
,
Juan Zhou
,
Yongjie Wang
,
Lin Zeng
,
Chao Liang
,
Jin Zhou
,
Lan Shao
,
Zhichang Zhang
,
Weiping Ji
,
Yunlong Zhang
,
Shikui Tu
* ,
Zhiyan Liu
* ,
Yang Dong
*
Version 1 : Received: 18 November 2021 / Approved: 22 November 2021 / Online: 22 November 2021 (12:38:38 CET)

How to cite: Sun, Y.; Zhou, J.; Wang, Y.; Zeng, L.; Liang, C.; Zhou, J.; Shao, L.; Zhang, Z.; Ji, W.; Zhang, Y.; Tu, S.; Liu, Z.; Dong, Y. Identification of RPS28 as a Promising Therapeutic Target for Osteosarcoma Patients with Poor Prognoses Stratified by a Seven-Gene Signature. Preprints 2021, 2021110390. https://doi.org/10.20944/preprints202111.0390.v1 Sun, Y.; Zhou, J.; Wang, Y.; Zeng, L.; Liang, C.; Zhou, J.; Shao, L.; Zhang, Z.; Ji, W.; Zhang, Y.; Tu, S.; Liu, Z.; Dong, Y. Identification of RPS28 as a Promising Therapeutic Target for Osteosarcoma Patients with Poor Prognoses Stratified by a Seven-Gene Signature. Preprints 2021, 2021110390. https://doi.org/10.20944/preprints202111.0390.v1

Abstract

Osteosarcoma (OSA) is the most common primary malignant bone tumor. More than 40% of patients with OSA have poor prognoses. We aimed to discover a biomarker for patient stratification and therapeutic targets for these high-risk patients. Using Single Sample Gene Set Enrichment Analysis (ssGSEA) and univariate Cox analysis, six hallmarks were identified as significant prognostic factors for overall survival (OS). Three were selected to construct a multivariate Cox model. Then, WGCNA, univariate Cox regression, Kaplan-Meier (KM) survival analyses, and multivariate Cox analyses were combined to filter promising candidates and establish a seven-gene signature to predict OS, whose prognostic value was validated internally and externally. Subsequently, Differential Expression Analysis was conducted between high- and low-risk patients, and the Robust Rank Aggregation algorithm was used to determine the robust DEGs. Metascape was used to perform pathway and process enrichment analyses as well as construct protein-protein interaction (PPI) networks. Finally, RPS28 was identified as an independent risk factor by using univariate and multivariate Cox regression, which was preliminarily validated as a promising therapeutic target by using RNA interference. In conclusion, we might contribute to optimizing risk stratification and an excellent therapeutic target for high-risk patients with OSA.

Keywords

osteosarcoma; hallmarks of cancer; predictive model; immune escape; ribosome biogenesis; RPS28

Subject

Medicine and Pharmacology, Oncology and Oncogenics

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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