Lei Cui, Shuai Zhao, Hai Long Teng, Biao Yang, Qian Liu, An Qin
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引用次数: 0
Abstract
Osteosarcoma represents 20% of primary malignant bone tumors globally. Assessing its prognosis is challenging due to the complex roles of integrins in tumor development and metastasis. This study utilized 209,268 osteosarcoma cells from the GEO database to identify integrin-associated genes using advanced analysis methods. A novel machine learning framework combining 10 algorithms was developed to construct an Integrin-related Signature (IRS), which demonstrated robust predictive power across multiple datasets. The IRS's utility in predicting overall survival was confirmed using data from The Cancer Genome Atlas, underscoring its potential in personalized cancer management.
期刊介绍：
Online-only and open access, npj Precision Oncology is an international, peer-reviewed journal dedicated to showcasing cutting-edge scientific research in all facets of precision oncology, spanning from fundamental science to translational applications and clinical medicine.
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