Dataset Information

Interaction gene set between osteoclasts and regulatory CD4⁺ T cells can accurately predict the prognosis of patients with osteosarcoma.

ABSTRACT: Osteoclasts (OCs) and regulatory CD4⁺ T cells (CD4⁺ Tregs) are important components in the tumor microenvironment (TME) of osteosarcoma. In this study, we collected six osteosarcoma samples from our previous study (GSE162454). We also integrated a public database (GSE152048), which included single cell sequencing data of 11 osteosarcoma patients. We obtained 138,192 cells and then successfully identified OCs and CD4⁺ Tregs. Based on the interaction gene set between OCs and CD4⁺ Tregs, patients from GSE21257 were distinguished into two clusters by consensus clustering analysis. Both the tumor immune microenvironment and survival prognosis between the two clusters were significantly different. Subsequently, five model genes were identified by protein-protein interaction network based on differentially upregulated genes of cluster 2. Quantitative RT-PCR was used to detect their expression in human osteoblast and osteosarcoma cells. A prognostic model was successfully established using these five genes. Kaplan-Meier survival analysis found that patients in the high-risk group had worse survival (p = 0.029). Therefore, our study first found that cell-cell communication between OCs and CD4⁺ Tregs significantly alters TME and is connected to poor prognosis of OS. The model we constructed can accurately predict prognosis for osteosarcoma patients.

SUBMITTER: Li F

PROVIDER: S-EPMC10323104 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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Interaction gene set between osteoclasts and regulatory CD4+ T cells can accurately predict the prognosis of patients with osteosarcoma.

Li Feicui F Tang Haijun H Luo Xiaoting X Li Xiangde X Luo Kai K Liu Shangyu S Liang Jiming J Liao Shijie S Zhong Chaoyi C Zhan Xinli X Wei Qingjun Q Feng Wenyu W Liu Yun Y

Cancer science 20230507 7

Osteoclasts (OCs) and regulatory CD4+ T cells (CD4+ Tregs) are important components in the tumor microenvironment (TME) of osteosarcoma. In this study, we collected six osteosarcoma samples from our previous study (GSE162454). We also integrated a public database (GSE152048), which included single cell sequencing data of 11 osteosarcoma patients. We obtained 138,192 cells and then successfully identified OCs and CD4+ Tregs. Based on the interaction gene set betwe ...[more]

PMID: 37150900

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Project description:Osteosarcoma has been the most common malignant bone tumor in children and adolescents, while the 5-y survival of osteosarcoma patients gained no significant improvement over the past decades. This study aimed to explore the role of ferroptosis-related genes (FRGs) in the development and prognosis of osteosarcoma. The datasets of osteosarcoma patients including RNA sequencing data and clinical information were acquired from the TRGET and Gene Expression Omnibus (GEO) databases. The identification of molecular subgroups with different FRG expression patterns was achieved through nonnegative matrix factorization (NMF) clustering. The prognostic model was constructed using the least absolute shrinkage and selection operator (LASSO) algorithm and multivariate Cox regression analysis. The ESTIMATE algorithm was applied for determining the stromal score, immune score, ESTIMA score, and tumor purity of osteosarcoma patients. Functional analyses including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, Gene Set Enrichment Analysis (GSEA), and Gene Set Variation Analysis (GSVA) were conducted to explore the underlying mechanisms in the development and prognosis of osteosarcoma. Two molecular subgroups with different FRGs expression patterns were identified. The molecular subgroups with higher immune score and more active immune status showed better prognostic survival. On the basis of FRGs, a prognostic model and a nomogram integrating clinical characteristics were constructed and their prediction efficiency for osteosarcoma prognosis were well validated. Gene functional enrichment analysis showed that these differentially expressed FRGs were mainly enriched in immunity-related signaling pathways, indicating that FRGs may affect the development and prognosis of osteosarcoma by regulating the immune microenvironment. The expression profiles of FRGs were closely related to the immunity status and prognostic survival of osteosarcoma patients. The interaction between ferroptosis and immunity in the development of osteosarcoma could provide a new insight into the exploration of molecular mechanisms and targeted therapies of osteosarcoma patients.

Dataset Information

Interaction gene set between osteoclasts and regulatory CD4⁺ T cells can accurately predict the prognosis of patients with osteosarcoma.

Publications

Interaction gene set between osteoclasts and regulatory CD4<sup>+</sup> T cells can accurately predict the prognosis of patients with osteosarcoma.

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