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

Abstract 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...

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Main Authors: Yanan Liu, Zhiguang Gao, Cheng Peng, Xingli Jiang
Format: Article
Language:English
Published: BMC 2022-11-01
Series:European Journal of Medical Research
Subjects:
Online Access:https://doi.org/10.1186/s40001-022-00829-2
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author Yanan Liu
Zhiguang Gao
Cheng Peng
Xingli Jiang
author_facet Yanan Liu
Zhiguang Gao
Cheng Peng
Xingli Jiang
author_sort Yanan Liu
collection DOAJ
description Abstract 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.
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spelling doaj.art-46822423c793459e843a6cb79097e7482022-12-22T02:46:21ZengBMCEuropean Journal of Medical Research2047-783X2022-11-0127111010.1186/s40001-022-00829-2Construction of a 10-gene prognostic score model of predicting recurrence for laryngeal cancerYanan Liu0Zhiguang Gao1Cheng Peng2Xingli Jiang3Department of Gastroenterology, Harbin Institute of Technology Heilongjiang HospitalDepartment of Otorhinolaryngology, Heilongjiang Provincial Hospital Affiliated to Harbin Institute of TechnologyDepartment of Otorhinolaryngology, Heilongjiang Provincial Hospital Affiliated to Harbin Institute of TechnologyDepartment of Otorhinolaryngology, Heilongjiang Provincial Hospital Affiliated to Harbin Institute of TechnologyAbstract 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.https://doi.org/10.1186/s40001-022-00829-2Laryngeal cancerRecurrencePrognosis
spellingShingle Yanan Liu
Zhiguang Gao
Cheng Peng
Xingli Jiang
Construction of a 10-gene prognostic score model of predicting recurrence for laryngeal cancer
European Journal of Medical Research
Laryngeal cancer
Recurrence
Prognosis
title Construction of a 10-gene prognostic score model of predicting recurrence for laryngeal cancer
title_full Construction of a 10-gene prognostic score model of predicting recurrence for laryngeal cancer
title_fullStr Construction of a 10-gene prognostic score model of predicting recurrence for laryngeal cancer
title_full_unstemmed Construction of a 10-gene prognostic score model of predicting recurrence for laryngeal cancer
title_short Construction of a 10-gene prognostic score model of predicting recurrence for laryngeal cancer
title_sort construction of a 10 gene prognostic score model of predicting recurrence for laryngeal cancer
topic Laryngeal cancer
Recurrence
Prognosis
url https://doi.org/10.1186/s40001-022-00829-2
work_keys_str_mv AT yananliu constructionofa10geneprognosticscoremodelofpredictingrecurrenceforlaryngealcancer
AT zhiguanggao constructionofa10geneprognosticscoremodelofpredictingrecurrenceforlaryngealcancer
AT chengpeng constructionofa10geneprognosticscoremodelofpredictingrecurrenceforlaryngealcancer
AT xinglijiang constructionofa10geneprognosticscoremodelofpredictingrecurrenceforlaryngealcancer