Identification of the shared gene signatures in retinoblastoma and osteosarcoma by machine learning DOI Creative Commons

Rongjie Ye,

Quan Yuan,

Wenkang You

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Dec. 28, 2024

Osteosarcoma (OS) is the most prevalent secondary sarcoma associated with retinoblastoma (RB). However, molecular mechanisms driving interactions between these two diseases remain incompletely understood. This study aims to explore transcriptomic commonalities and pathways shared by RB OS, identify biomarkers that predict OS prognosis effectively. RNA sequences patient information for were obtained from University of California Santa Cruz (UCSC) Xena Gene Expression Omnibus databases. When first identified, a common gene expression profile was discovered. Weighted Co-expression Network Analysis (WGCNA) revealed co-expression networks after immunotyping patients. To evaluate genes univariate multivariate Cox regression analysis then carried out. Three machine learning methods used pick key genes, risk models created verified. Next, medications target independent prognostic found using Cellminer database. The comparison differential 1216 primarily linked activation proliferation immune cells. WGCNA identified 12 modules related immunotyping, grey module showing strong correlation immune-inflamed phenotype. intersected RB, producing 65 RB-associated Immune-inflamed Genes (ROIGs). 6 hub model construction through three techniques. A based on established, demonstrating significant value OS. contribute progression both cancers multiple pathways. ROIGs score independently predicts overall survival Additionally, this highlights potential as therapeutic targets or clinical use.

Language: Английский

Advances on immunotherapy for osteosarcoma DOI Creative Commons
Shengnan Yu, Xudong Yao

Molecular Cancer, Journal Year: 2024, Volume and Issue: 23(1)

Published: Sept. 9, 2024

Language: Английский

Citations

37
NETs-related genes predict prognosis and are correlated with the immune microenvironment in osteosarcoma DOI Creative Commons

Dawei Chu,

Rui Huang, Jiandang Shi

et al.

Frontiers in Oncology, Journal Year: 2025, Volume and Issue: 15

Published: April 10, 2025

Background Osteosarcoma is the most common primary bone tumor. It has a high rate of early metastasis, and its treatment one challenging topics in tumor field. Recent studies have shown that neutrophil extracellular traps play an important role metastasis may provide new horizons for exploring osteosarcoma. Methods OS data were downloaded from TARGET database Gene Expression Omnibus datasets. Univariate Cox regression was conducted to assess NETRGs. Patients subsequently categorized into high- low-risk groups on basis risk score values derived multivariate analysis, prognostic models established. The immune infiltration relevant genes drug sensitivity key also analyzed. Results A total 15 NETs-related associated with osteosarcoma metastases identified. Among them, 4 related prognosis, namely, MAPK1, CFH, ATG7 DDIT4, model based these prognosis worse high-risk group, whose areas under ROC curves (AUCs) 0.857, 0.779, 0.689 at 1, 3, 5 years, respectively. found be 20 types cells. Finally, small-molecule toxin c 10, approximately 6700 mw protein, target genes. validated histological level by combining results validation group dataset analysis. Conclusions NETRDEGs reliable predictor patients, CFH serve as diagnostic therapeutic target.

Language: Английский

Citations

0
Development and Validation of Diagnostic Models for Transcriptomic Signature Genes for Multiple Tissues in Osteoarthritis DOI Creative Commons

Qichang Gao,

Yiming Ma,

Tuo Shao

et al.

Journal of Inflammation Research, Journal Year: 2024, Volume and Issue: Volume 17, P. 5113 - 5127

Published: July 1, 2024

Background: Progress in research on expression profiles osteoarthritis (OA) has been limited to individual tissues within the joint, such as synovium, cartilage, or meniscus. This study aimed comprehensively analyze common gene characteristics of various structures OA and construct a diagnostic model. Methods: Three datasets were selected: meniscus, knee joint cartilage. Modular clustering differential analysis genes used for further functional analyses construction protein networks. Signature with highest potential identified verified using external datasets. The these was validated clinical samples by Real-time (RT)-qPCR immunohistochemistry (IHC) staining. investigated status immune cells examining their infiltration. Results: merged dataset included 438 DEGs clustered into seven modules WGCNA. intersection WGCNA 190 genes. Using Least Absolute Shrinkage Selection Operator (LASSO) Random Forest algorithms, nine signature ( CDADC1, PPFIBP1, ENO2, NOM1, SLC25A14, METTL2A, LINC01089, L3HYPDH, NPHP3 ), each demonstrating substantial (areas under curve from 0.701 0.925). Furthermore, dysregulation also observed. Conclusion: demonstrated significant efficacy are involved cell Keywords: osteoarthritis, machine learning, infiltration, model

Language: Английский

Citations

0
The role of neutrophils in osteosarcoma: insights from laboratory to clinic DOI Creative Commons
Ming Xia, Yu Han,

Lihui Sun

et al.

Frontiers in Immunology, Journal Year: 2024, Volume and Issue: 15

Published: Nov. 8, 2024

Osteosarcoma, a highly aggressive malignant bone tumor, is significantly influenced by the intricate interactions within its tumor microenvironment (TME), particularly involving neutrophils. This review delineates multifaceted roles of neutrophils, including tumor-associated neutrophils (TANs) and neutrophil extracellular traps (NETs), in osteosarcoma’s pathogenesis. TANs exhibit both pro- anti-tumor phenotypes, modulating growth immune evasion, while NETs facilitate cell adhesion, migration, immunosuppression. Clinically, neutrophil-related markers such as neutrophil-to-lymphocyte ratio (NLR) predict patient outcomes, highlighting potential for neutrophil-targeted therapies. Unraveling these complex crucial developing novel treatment strategies that harness TME to improve osteosarcoma management.

Language: Английский

Citations

0
Using β-Elemene to reduce stemness and drug resistance in osteosarcoma: A focus on the AKT/FOXO1 signaling pathway and immune modulation DOI Creative Commons
Shaochun Zhang,

Zhijie Xing,

Jing Ke

et al.

Journal of bone oncology, Journal Year: 2024, Volume and Issue: 50, P. 100655 - 100655

Published: Dec. 20, 2024

Language: Английский

Citations

0
Identification of the shared gene signatures in retinoblastoma and osteosarcoma by machine learning DOI Creative Commons

Rongjie Ye,

Quan Yuan,

Wenkang You

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Dec. 28, 2024

Osteosarcoma (OS) is the most prevalent secondary sarcoma associated with retinoblastoma (RB). However, molecular mechanisms driving interactions between these two diseases remain incompletely understood. This study aims to explore transcriptomic commonalities and pathways shared by RB OS, identify biomarkers that predict OS prognosis effectively. RNA sequences patient information for were obtained from University of California Santa Cruz (UCSC) Xena Gene Expression Omnibus databases. When first identified, a common gene expression profile was discovered. Weighted Co-expression Network Analysis (WGCNA) revealed co-expression networks after immunotyping patients. To evaluate genes univariate multivariate Cox regression analysis then carried out. Three machine learning methods used pick key genes, risk models created verified. Next, medications target independent prognostic found using Cellminer database. The comparison differential 1216 primarily linked activation proliferation immune cells. WGCNA identified 12 modules related immunotyping, grey module showing strong correlation immune-inflamed phenotype. intersected RB, producing 65 RB-associated Immune-inflamed Genes (ROIGs). 6 hub model construction through three techniques. A based on established, demonstrating significant value OS. contribute progression both cancers multiple pathways. ROIGs score independently predicts overall survival Additionally, this highlights potential as therapeutic targets or clinical use.

Language: Английский

Citations

0