Immune-related prognosis biomarkers associated with osteosarcoma microenvironment

Abstract

Background Osteosarcoma is a highly aggressive bone tumor that most commonly affects children and adolescents. Treatment and outcomes for osteosarcoma have remained unchanged over the past 30 years. The relationship between osteosarcoma and the immune microenvironment may represent a key to its undoing. Methods We calculated the immune and stromal scores of osteosarcoma cases from the Target database using the ESTIMATE algorithm. Then we used the CIBERSORT algorithm to explore the tumor microenvironment and analyze immune infiltration of osteosarcoma. Differentially expressed genes (DEGs) were identified based on immune scores and stromal scores. Search Tool for the Retrieval of Interacting Genes Database (STRING) was utilized to assess protein–protein interaction (PPI) information, and Molecular Complex Detection (MCODE) plugin was used to screen hub modules of PPI network in Cytoscape. The prognostic value of the gene signature was validated in an independent GSE39058 cohort. Gene set enrichment analysis (GSEA) was performed to study the hub genes in signaling pathways. Results From 83 samples of osteosarcoma obtained from the Target dataset, 137 DEGs were identified, including 134 upregulated genes and three downregulated genes. Functional enrichment analysis and PPI networks demonstrated that these genes were mainly involved in neutrophil degranulation and neutrophil activation involved in immune response, and participated in neuroactive ligand–receptor interaction and staphylococcus aureus infection. Conclusions Our study established an immune-related gene signature to predict outcomes of osteosarcoma, which may be important targets for individual treatment.

Bioinformatics analysis reveals the ceRNA co-expression network in tumor microenvironment and prognostic biomarkers in Sarcomas

“…We rst used the ESTIMATE algorithm and found that SARCs patients with high immune scores had longer overall survival time. This was similar to a previous study which reported the high immune scores has favorable outcomes in bone SARCs patients [13]. While for the correlation between stromal scores and survival in SARCs samples, we failed to nd any signi cant difference.…”

“…Recently, the ESTIMATE has been applied in several cancers, such as head and neck squamous cell carcinoma [10], glioblastoma [11] and acute myeloid leukemia [12]. A previous study used ESTIMATE algorithm to reveal the immune-related gene signature in bone SARCs [13], however, whether this algorithm could be used to investigate prognostic biomarkers in SARCs remains to be elucidated.…”

Development of a novel immune-related genes prognostic signature for osteosarcoma

“…In recent years, biomolecules and risk models have been used to evaluate the prognosis of OS 8 – 11 . However, they have not yet been used in clinical practice because of unavoidable limitations, such as overfitting due to small samples 12 .…”

Differentially expressed genes SNRPC and PRPF38A are potential biomarkers candidates for osteosarcoma

“…Early diagnosis and timely treatment contribute to improving the prognosis of sarcoma (29)(30)(31)(32). In this study, we analyzed GSE9508 dataset downloaded from GEO Additionally, re-analysis 8 novel genes by using DAVID shown that SNRPC and PRPF38A as potential biomarkers and spliceosome had a significant, which provided a new effective target to improve the prognosis of OS patients.…”