Six-gene signature for predicting survival in patients with head and neck squamous cell carcinoma
Author(s) -
Juncheng Wang,
Xun Chen,
Yuxi Tian,
Gangcai Zhu,
Yuexiang Qin,
Xuan Chen,
Leiming Pi,
Ming Wei,
Guancheng Liu,
Zhexuan Li,
ChangHan Chen,
Yunxia Lv,
Gengming Cai
Publication year - 2020
Publication title -
aging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 90
ISSN - 1945-4589
DOI - 10.18632/aging.102655
Subject(s) - head and neck squamous cell carcinoma , gene signature , oncology , random forest , proportional hazards model , gene , medicine , single nucleotide polymorphism , survival analysis , feature selection , head and neck cancer , cancer , computational biology , biology , computer science , gene expression , genotype , artificial intelligence , genetics
The prognosis of head and neck squamous cell carcinoma (HNSCC) patients remains poor. High-throughput sequencing data have laid a solid foundation for identifying genes related to cancer prognosis, but a gene marker is needed to predict clinical outcomes in HNSCC. In our study, we downloaded RNA Seq, single nucleotide polymorphism, copy number variation, and clinical follow-up data from TCGA. The samples were randomly divided into training and test. In the training set, we screened genes and used random forests for feature selection. Gene-related prognostic models were established and validated in a test set and GEO verification set. Six genes ( PEX11A, NLRP2, SERPINE1, UPK, CTTN, D2HGDH ) were ultimately obtained through random forest feature selection. Cox regression analysis confirmed the 6-gene signature is an independent prognostic factor in HNSCC patients. This signature effectively stratified samples in the training, test, and external verification sets (P < 0.01). The 5-year survival AUC in the training and verification sets was greater than 0.74. Thus, we have constructed a 6-gene signature as a new prognostic marker for predicting survival of HNSCC patients.
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