Identifying 8-mRNAsi Based Signature for Predicting Survival in Patients With Head and Neck Squamous Cell Carcinoma via Machine Learning

Identifying 8-mRNAsi Based Signature for Predicting Survival in Patients With Head and Neck Squamous Cell Carcinoma via Machine Learning

Cancer stem cells (CSCs) have been characterized by several exclusive features that include differentiation, self-renew, and homeostatic control, which allows tumor maintenance and spread. Recurrence and therapeutic resistance of head and neck squamous cell carcinomas (HNSCC) have been identified to...

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Bibliographic Details
Main Authors: Yuxi Tian, Juncheng Wang, Chao Qin, Gangcai Zhu, Xuan Chen, Zhixiang Chen, Yuexiang Qin, Ming Wei, Zhexuan Li, Xin Zhang, Yunxia Lv, Gengming Cai
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-10-01
Series:Frontiers in Genetics
Subjects:
cancer cell stemness indices
head and neck squamous cell carcinomas
The Cancer Genome Atlas
weighted gene co-expression network analysis
predictive models
Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2020.566159/full

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