Comprehensive multi-omics analysis reveals the prognostic and immune regulatory characteristics of the PTPN family in osteosarcoma

C Changhai Long B Biao Ma X Xingshun Zhong M Mingzhi Zou (Beijing Science and Engineering Center for Nanocarbons, Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering) K Kai Li S Sijing Liu

Abstract

Osteosarcoma is a highly aggressive bone tumor that primarily affects adolescents and young adults, posing significant challenges in therapeutic efficacy, prognostic assessment, and treatment strategies. This study investigates the oncogenic and immune regulatory roles of the PTPN family in osteosarcoma using a comprehensive multi-omics approach. We utilized transcriptomic data, single-cell RNA sequencing (scRNA-seq), and clinical information obtained from publicly available databases. Dimensionality reduction and clustering techniques were employed to subclassify immune cells and analyze the tumor microenvironment characteristics. We identified prognostic genes associated with the PTPN family and stratified osteosarcoma cases into distinct molecular subtypes using consensus clustering. A random forest model revealed that the PTPN family has a significant impact on prognosis and modulates key oncogenic pathways. Furthermore, we analyzed the role of the PTPN family in regulating immune cells and selected PTPN23 for experimental validation. This research not only enhances prognostic assessments in osteosarcoma but also establishes a foundation for personalized therapeutic interventions.

Article Details

Journal PLoS ONE
Volume / Issue Vol. 20, Issue 6
Published June 26, 2025
Pages e0326872
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (6)

C

Changhai Long

B

Biao Ma

X

Xingshun Zhong

M

Mingzhi Zou

Beijing Science and Engineering Center for Nanocarbons, Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering

K

Kai Li

S

Sijing Liu