A Whole Exon Screening-Based Score Model Predicts Prognosis and Immune Checkpoint Inhibitor Therapy Effects in Low-Grade Glioma

OBJECTIVE: This study aims to identify prognostic factors for low-grade glioma (LGG) via different machine learning methods in the whole genome and to predict patient prognoses based on these factors. We verified the results through in vitro experiments to further screen new potential therapeutic ta...

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Detalles Bibliográficos
Autores principales: Luo, Cheng, Wang, Songmao, Shan, Wenjie, Liao, Weijie, Zhang, Shikuan, Wang, Yanzhi, Xin, Qilei, Yang, Tingpeng, Hu, Shaoliang, Xie, Weidong, Xu, Naihan, Zhang, Yaou
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Immunology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9234137/
https://www.ncbi.nlm.nih.gov/pubmed/35769464
http://dx.doi.org/10.3389/fimmu.2022.909189

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9234137/
https://www.ncbi.nlm.nih.gov/pubmed/35769464
http://dx.doi.org/10.3389/fimmu.2022.909189

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