Prognostic Signature in Osteosarcoma Based on Amino Acid Metabolism-Associated Genes

Feng, Liwen; Chen, Yuting; Mei, Xiangping; Wang, Lei; Zhao, Wenjing; Yao, Jiannan

doi:10.1089/cbr.2024.0002

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Cancer Biotherapy and Radiopharmaceuticals

2024

DOI: 10.1089/cbr.2024.0002

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Prognostic Signature in Osteosarcoma Based on Amino Acid Metabolism-Associated Genes

Liwen Feng,

Yuting Chen,

Xiangping Mei

et al.

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2024

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Development and Validation of Diagnostic Models for Transcriptomic Signature Genes for Multiple Tissues in Osteoarthritis

Gao,

Ma,

Shao

et al. 2024

JIR

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

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Development and Validation of Diagnostic Models for Transcriptomic Signature Genes for Multiple Tissues in Osteoarthritis

Gao,

Ma,

Shao

et al. 2024

JIR

View full text Add to dashboard Cite

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Prognostic Signature in Osteosarcoma Based on Amino Acid Metabolism-Associated Genes

Cited by 1 publication

References 58 publications

Development and Validation of Diagnostic Models for Transcriptomic Signature Genes for Multiple Tissues in Osteoarthritis

Development and Validation of Diagnostic Models for Transcriptomic Signature Genes for Multiple Tissues in Osteoarthritis

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