Objective:Osteosarcoma is a highly aggressive primary malignant bone tumor commonly seen in children and adolescents,with a poor prognosis.Anchorage-dependent cell death(anoikis)has been proven to be indispensable in ...Objective:Osteosarcoma is a highly aggressive primary malignant bone tumor commonly seen in children and adolescents,with a poor prognosis.Anchorage-dependent cell death(anoikis)has been proven to be indispensable in tumor metastasis,regulating the migration and adhesion of tumor cells at the primary site.However,as a type of programmed cell death,anoikis is rarely studied in osteosarcoma,especially in the tumor immune microenvironment.This study aims to clarify prognostic value of anoikis and tumor immune microenvironment-related gene in the treatment of osteosarcoma.Methods:Anoikis-related genes(ANRGs)were obtained from GeneCards.Clinical information and ANRGs expression profiles of osteosarcoma patients were sourced from the therapeutically applicable research to generate effective therapies and Gene Expression Omnibus(GEO)databases.ANRGs highly associated with tumor immune microenvironment were identified by the estimate package and the weighted gene coexpression network analysis(WGCNA)algorithm.Machine learning algorithms were performed to construct long-term survival predictive strategy,each sample was divided into high-risk and low-risk subgroups,which was further verified in the GEO cohort.Finally,based on single-cell RNA-seq from the GEO database,analysis was done on the function of signature genes in the osteosarcoma tumor microenvironment.Results:A total of 51 hub ANRGs closely associated with the tumor microenvironment were identified,from which 3 genes(MERTK,BNIP3,S100A8)were selected to construct the prognostic model.Significant differences in immune cell activation and immune-related signaling pathways were observed between the high-risk and low-risk groups based on tumor microenvironment analysis(all P<0.05).Additionally,characteristic genes within the osteosarcoma microenvironment were identified in regulation of intercellular crosstalk through the GAS6-MERTK signaling pathway.Conclusion:The prognostic model based on ANRGs and tumor microenvironment demonstrate good predictive power and provide more personalized treatment options for patients with osteosarcoma.展开更多
在各树种不同配置方式试验研究的基础上,提出了大面积农田林网杨树与其它树种的多样性与稳定性混交型构架,建立了各种混交林带.试验得出杨榆、杨柳混交的"对称式行混"(U P P U和S P P S)形式较佳,结构较合理;运用"边行...在各树种不同配置方式试验研究的基础上,提出了大面积农田林网杨树与其它树种的多样性与稳定性混交型构架,建立了各种混交林带.试验得出杨榆、杨柳混交的"对称式行混"(U P P U和S P P S)形式较佳,结构较合理;运用"边行效应原理"营造的林带,通过不同株行距试验对比,内行距为3m的林带树木胸径生长分化程度弱于内行距为2 4m的林带,而内行距为2m的林带树木胸径生长分化较为严重.展开更多
基金This work was supported by the National Natural Science Foundation(82172594 and 82373046)the Hunan Graduate Research Innovation Project(CX20230318),China.
文摘Objective:Osteosarcoma is a highly aggressive primary malignant bone tumor commonly seen in children and adolescents,with a poor prognosis.Anchorage-dependent cell death(anoikis)has been proven to be indispensable in tumor metastasis,regulating the migration and adhesion of tumor cells at the primary site.However,as a type of programmed cell death,anoikis is rarely studied in osteosarcoma,especially in the tumor immune microenvironment.This study aims to clarify prognostic value of anoikis and tumor immune microenvironment-related gene in the treatment of osteosarcoma.Methods:Anoikis-related genes(ANRGs)were obtained from GeneCards.Clinical information and ANRGs expression profiles of osteosarcoma patients were sourced from the therapeutically applicable research to generate effective therapies and Gene Expression Omnibus(GEO)databases.ANRGs highly associated with tumor immune microenvironment were identified by the estimate package and the weighted gene coexpression network analysis(WGCNA)algorithm.Machine learning algorithms were performed to construct long-term survival predictive strategy,each sample was divided into high-risk and low-risk subgroups,which was further verified in the GEO cohort.Finally,based on single-cell RNA-seq from the GEO database,analysis was done on the function of signature genes in the osteosarcoma tumor microenvironment.Results:A total of 51 hub ANRGs closely associated with the tumor microenvironment were identified,from which 3 genes(MERTK,BNIP3,S100A8)were selected to construct the prognostic model.Significant differences in immune cell activation and immune-related signaling pathways were observed between the high-risk and low-risk groups based on tumor microenvironment analysis(all P<0.05).Additionally,characteristic genes within the osteosarcoma microenvironment were identified in regulation of intercellular crosstalk through the GAS6-MERTK signaling pathway.Conclusion:The prognostic model based on ANRGs and tumor microenvironment demonstrate good predictive power and provide more personalized treatment options for patients with osteosarcoma.
文摘在各树种不同配置方式试验研究的基础上,提出了大面积农田林网杨树与其它树种的多样性与稳定性混交型构架,建立了各种混交林带.试验得出杨榆、杨柳混交的"对称式行混"(U P P U和S P P S)形式较佳,结构较合理;运用"边行效应原理"营造的林带,通过不同株行距试验对比,内行距为3m的林带树木胸径生长分化程度弱于内行距为2 4m的林带,而内行距为2m的林带树木胸径生长分化较为严重.
