Construction of a 10-gene prognostic score model of predicting recurrence for laryngeal cancer

We constructed a prognostic score (PS) model to predict the recurrence risk in patients previously diagnosed with laryngeal cancer (LC). Here the training dataset, consisting of 82 LC samples, was downloaded from The Cancer Genome Atlas (TCGA). The PS model then divided the LC samples into high- and...

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Detalles Bibliográficos
Autores principales: Liu, Yanan, Gao, Zhiguang, Peng, Cheng, Jiang, Xingli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9661785/
https://www.ncbi.nlm.nih.gov/pubmed/36376905
http://dx.doi.org/10.1186/s40001-022-00829-2
Descripción
Sumario:We constructed a prognostic score (PS) model to predict the recurrence risk in patients previously diagnosed with laryngeal cancer (LC). Here the training dataset, consisting of 82 LC samples, was downloaded from The Cancer Genome Atlas (TCGA). The PS model then divided the LC samples into high- and low-risk groups, which predicted well the survival time of LC in three datasets (TCGA dataset: AUC = 0.899; GSE27020: AUC = 0.719; and GSE25727: AUC = 0.662). Therefore, the PS model based on the 10 genes and its nomogram is proposed to help predict the recurrence risk in patients with LC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40001-022-00829-2.

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