دورية أكاديمية

Integrating artificial intelligence in osteosarcoma prognosis: the prognostic significance of SERPINE2 and CPT1B biomarkers

التفاصيل البيبلوغرافية
العنوان: Integrating artificial intelligence in osteosarcoma prognosis: the prognostic significance of SERPINE2 and CPT1B biomarkers
المؤلفون: Haishun Qu, Jie Jiang, Xinli Zhan, Yunxiao Liang, Quan Guo, Peifeng Liu, Ling Lu, Yanwei Yang, Weicheng Xu, Yitian Zhang, Shaohang Lan, Zeshan Chen, Yuanhong Lu, Yufu Ou, Yijue Qin
المصدر: Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)
بيانات النشر: Nature Portfolio, 2024.
سنة النشر: 2024
المجموعة: LCC:Medicine
LCC:Science
مصطلحات موضوعية: Osteosarcoma, Artificial intelligence, Immune cell dysregulation, Prognostic model, Immunohistochemistry, Medicine, Science
الوصف: Abstract The principal aim of this investigation is to identify pivotal biomarkers linked to the prognosis of osteosarcoma (OS) through the application of artificial intelligence (AI), with an ultimate goal to enhance prognostic prediction. Expression profiles from 88 OS cases and 396 normal samples were procured from accessible public databases. Prognostic models were established using univariate COX regression analysis and an array of AI methodologies including the XGB method, RF method, GLM method, SVM method, and LASSO regression analysis. Multivariate COX regression analysis was also employed. Immune cell variations in OS were examined using the CIBERSORT software, and a differential analysis was conducted. Routine blood data from 20,679 normal samples and 437 OS cases were analyzed to validate lymphocyte disparity. Histological assessments of the study's postulates were performed through immunohistochemistry and hematoxylin and eosin (HE) staining. AI facilitated the identification of differentially expressed genes, which were utilized to construct a prognostic model. This model discerned that the survival rate in the high-risk category was significantly inferior compared to the low-risk cohort (p
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2045-2322
Relation: https://doaj.org/toc/2045-2322
DOI: 10.1038/s41598-024-54222-6
URL الوصول: https://doaj.org/article/11f01d7968d54a0da3a468fe6d2df927
رقم الأكسشن: edsdoj.11f01d7968d54a0da3a468fe6d2df927
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20452322
DOI:10.1038/s41598-024-54222-6