Tumor microenvironment phenotypes and prognostic evaluation tools for osteosarcoma characterized by different prognostic outcomes and immunotherapy responses

Author:

Tu Zubo1,Li Wang2,Chen Zhigang1,Jiang Dong1,Zhou Shiran1,Lv Shujun1,Cui Haidong1

Affiliation:

1. Orthopedics Hai'an People's Hospital Nantong China

2. Orthopedics Shanghai Zhongye Hospital Shanghai China

Abstract

AbstractBackgroundThe physiological and immunological characteristics of the tumor microenvironment (TME) have a profound impact on the effectiveness of immunotherapy. The present study aimed to define the TME subtype of osteosarcoma according to the signatures representing the global TME of the tumor, as well as create a new prognostic assessment tool to monitor the prognosis, TME activity and immunotherapy response of patients with osteosarcoma.MethodsThe enrichment scores of 29 functional gene expression signatures in osteosarcoma samples were calculated by single sample gene set enrichment analysis (ssGSEA). TME classification of osteosarcoma was performed and a prognostic assessment tool was created based on 29 ssGSEA scores to comprehensively correlate them with TME components, immunotherapy efficacy and prognosis of osteosarcoma.ResultsThree TME subtypes were generated that differed in survival, TME activity and immunotherapeutic response. Four differentially expressed genes between TME subtypes were involved in the development of prognostic assessment tools. The established prognosis assessment tool had strong performance in both training and verification cohorts, could be effectively applied to the survival prediction of samples of different ages, genders and transfer states, and could well distinguish the TME status of different samples.ConclusionsThe present study describes three different TME phenotypes in osteosarcoma, provides a risk stratification tool for osteosarcoma prognosis and TME status assessment, and provides additional information for clinical decision‐making of immunotherapy.

Publisher

Wiley

Subject

Genetics (clinical),Drug Discovery,Genetics,Molecular Biology,Molecular Medicine

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