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Updated: May 20, 2025
Preparation of Mitochondria from Ovarian Cancer Tissues and Control Ovarian Tissues for Quantitative Proteomics Analysis
Published on: November 18, 2019
Identification and characterization of mitochondrial autophagy-related genes in osteosarcoma and predicting clinical
Hongliang Zhang1, Jingyu Zhang1, Kai Zhu1
1Department of Bone and Soft Tissue Tumor, Tianjin Hospital, Tianjin University, Tianjin, 300211, China.
Abstract:
Osteosarcoma (OS), the most prevalent primary malignant bone tumor, is characterized by a poor prognosis and high metastatic potential. Mitochondrial autophagy has been implicated in cancer suppression. This study aimed to identify prognostic genes associated with mitochondrial autophagy in OS. Public datasets, including TARGET-OS, GSE99671, and GSE21257, were retrieved for analysis. Differentially expressed genes (DEGs1) between OS and normal samples were identified from GSE99671. Single-sample Gene Set Enrichment Analysis (ssGSEA) was applied to quantify the enrichment scores of 29 mitochondrial autophagy-related genes (MARGs) in OS samples from TARGET-OS, categorizing them into high- and low-score groups to extract DEGs2. The intersection of DEGs1 and DEGs2 yielded mitochondrial autophagy-associated differentially expressed genes (MDGs). Prognostic genes were subsequently screened through a multi-step regression analysis, and a risk score was computed. TARGET-OS samples were stratified into high- and low-risk groups based on the optimal cutoff value of the risk score. GSEA was conducted between the two risk groups. Additionally, associations between prognostic genes and the immune microenvironment were explored. A total of 31 MDGs were identified from the overlap of 3,207 DEGs1 and 622 DEGs2. Five prognostic genes-KLK2, NRXN1, HES5, OR2W3, and HS3ST4-were further selected. Kaplan-Meier survival analysis indicated significantly reduced survival in the high-risk group. GSEA revealed enrichment in ABC transporter activity and glycolysis/gluconeogenesis pathways. Immunoanalysis demonstrated significant differences in 11 immune cell populations and three immune functions between risk groups, notably myeloid-derived suppressor cells (MDSCs) and Type 1 T helper cells. HS3ST4 exhibited the strongest positive correlation with macrophages, whereas NRXN1 showed the most pronounced negative correlation with memory B cells. Expressions of HAVCR2 and PDCD1LG2 were elevated in the low-risk group. Functional analysis indicated significant differences in dysfunction patterns between risk groups. This study identified five mitochondrial autophagy-related prognostic genes and constructed a risk model, offering novel insights into OS diagnosis and therapeutic strategies.
