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...

Descripción completa

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
_version_ 1784830551166812160
author Liu, Yanan
Gao, Zhiguang
Peng, Cheng
Jiang, Xingli
author_facet Liu, Yanan
Gao, Zhiguang
Peng, Cheng
Jiang, Xingli
author_sort Liu, Yanan
collection PubMed
description 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.
format Online
Article
Text
id pubmed-9661785
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-96617852022-11-15 Construction of a 10-gene prognostic score model of predicting recurrence for laryngeal cancer Liu, Yanan Gao, Zhiguang Peng, Cheng Jiang, Xingli Eur J Med Res Research 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. BioMed Central 2022-11-14 /pmc/articles/PMC9661785/ /pubmed/36376905 http://dx.doi.org/10.1186/s40001-022-00829-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Liu, Yanan
Gao, Zhiguang
Peng, Cheng
Jiang, Xingli
Construction of a 10-gene prognostic score model of predicting recurrence for laryngeal cancer
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 Research
url 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
work_keys_str_mv AT liuyanan constructionofa10geneprognosticscoremodelofpredictingrecurrenceforlaryngealcancer
AT gaozhiguang constructionofa10geneprognosticscoremodelofpredictingrecurrenceforlaryngealcancer
AT pengcheng constructionofa10geneprognosticscoremodelofpredictingrecurrenceforlaryngealcancer
AT jiangxingli constructionofa10geneprognosticscoremodelofpredictingrecurrenceforlaryngealcancer

Ejemplares similares