The induction of ferroptosis is suggested to be a potential therapeutic strategy for cancers. MicroRNAs (miRNAs) are reported to play an important role in cell death processes. This study aims to construct and validate a risk model based on ferroptosis-related miRNAs (FR_miRNAs) to predict prognosis and identify novel therapeutic targets for osteosarcoma. Data from the Therapeutically Applicable Research to Generate Effective Treatments database are used as the training cohort. A prognostic signature based on two FR_miRNAs (miR-635 and miR-593) is developed using univariate Cox regression, least absolute shrinkage and selection operator regression, and multivariate Cox regression analyses. The area under the curve values of the prognostic signature to predict the 1-year, 2-year, 3-year, and 5-year overall survival rates in patients with osteosarcoma are 0.782, 0.781, 0.722, and 0.777, respectively, indicating a good predictive ability. Based on the risk score, patients are divided into low-risk and high-risk groups. Patients with high-risk scores are associated with poor survival. The risk level is determined to be an independent prognostic factor. A nomogram is established for predicting prognosis. The expression levels of (miR-635-related ferroptosis-related gene (FRG); =0.024) and (miR-593-related FRG; =0.025) are significantly different between the low-risk and high-risk groups. All results are validated in an external cohort (GSE39040). The results of the functional assay reveal that miR-635 mimics inhibit osteosarcoma (OS) cell proliferation and migration, whereas miR-593 overexpression exerts the opposite effect. In conclusion, miR-635 and miR-593 exert contrasting regulatory effects on OS cell proliferation and migration.
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http://dx.doi.org/10.3724/abbs.2023236 | DOI Listing |
J Cell Mol Med
January 2025
Department of Andrology, The First Hospital of Jilin University, Changchun, China.
Prostate cancer (PCa) is one of the most common cancers in men worldwide. Autophagy-related genes (ARGs) may play an important role in various biological processes of PCa. The aim of this study was to identify and evaluate autophagy-related features to predict clinical outcomes in patients with PCa.
View Article and Find Full Text PDFNPJ Syst Biol Appl
January 2025
Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, China.
Breast cancer prognosis is complicated by tumor heterogeneity. Traditional methods focus on cancer-specific gene signatures, but cross-cancer strategies that provide deeper insights into tumor homogeneity are rarely used. Immunotherapy, particularly immune checkpoint inhibitors, results from variable responses across cancers, offering valuable prognostic insights.
View Article and Find Full Text PDFBiochim Biophys Acta Mol Basis Dis
January 2025
Ion Channel Biology Laboratory, AU-KBC Research Centre, Madras Institute of Technology Campus, Anna University, Chrompet, Chennai 600 044, Tamil Nadu, India. Electronic address:
Metabolic dysfunction-associated steatotic liver disease [MASLD] is a pervasive multifactorial health burden. Post-translational modifications [PTMs] of amino acid residues in protein domains demonstrate pivotal roles for imparting dynamic alterations in the cellular micro milieu. The crux of identifying novel druggable targets relies on comprehensively studying the etiology of metabolic disorders.
View Article and Find Full Text PDFJ Clin Endocrinol Metab
January 2025
Department of Pediatrics, Ribeirao Preto Medical School - University of Sao Paulo, Ribeirao Preto, Brazil.
Background: Adrenocortical cancer (ACC) is rare and aggressive, with YAP1 overexpression associated with poor outcomes in pediatric patients. In this study, we investigated the mechanisms by which YAP1 drives ACC progression and explored it as a potential target therapy.
Methods: YAP1 expression and methylation in ACC were analyzed from pediatric and adult cohorts.
J Cardiovasc Transl Res
January 2025
Clinical Laboratory of Tianjin Chest Hospital, 261 Taierzhuang South Road, Tianjin, 300222, Jinnan District, China.
The prognostic value of differentially expressed senescence-related genes(DESRGs) in ST-segment elevation myocardial infarction(STEMI) patients is unclear. We used GEO2R to identify DESRGs from GSE60993 and performed functional enrichment analysis. We built an optimal prognostic model with LASSO penalized Cox regression via GSE49925.
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