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Development and validation of a cancer stem cell-related signature for prognostic prediction in pancreatic ductal adenocarcinoma
BACKGROUND: Cancer stem cells (CSCs) are crucial to the malignant behaviour and poor prognosis of pancreatic ductal adenocarcinoma (PDAC). In recent years, CSC biology has been widely studied, but practical prognostic signatures based on CSC-related genes have not been established or reported in PDA...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7507616/ https://www.ncbi.nlm.nih.gov/pubmed/32958051 http://dx.doi.org/10.1186/s12967-020-02527-1 |
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author | Feng, Zengyu Shi, Minmin Li, Kexian Ma, Yang Jiang, Lingxi Chen, Hao Peng, Chenghong |
author_facet | Feng, Zengyu Shi, Minmin Li, Kexian Ma, Yang Jiang, Lingxi Chen, Hao Peng, Chenghong |
author_sort | Feng, Zengyu |
collection | PubMed |
description | BACKGROUND: Cancer stem cells (CSCs) are crucial to the malignant behaviour and poor prognosis of pancreatic ductal adenocarcinoma (PDAC). In recent years, CSC biology has been widely studied, but practical prognostic signatures based on CSC-related genes have not been established or reported in PDAC. METHODS: A signature was developed and validated in seven independent PDAC datasets. The MTAB-6134 cohort was used as the training set, while one local Chinese cohort and five other public cohorts were used for external validation. CSC-related genes with credible prognostic roles were selected to form the signature, and their predictive performance was evaluated by Kaplan–Meier survival, receiver operating characteristic (ROC), and calibration curves. Correlation analysis was employed to clarify the potential biological characteristics of the gene signature. RESULTS: A robust signature comprising DCBLD2, GSDMD, PMAIP1, and PLOD2 was developed. It classified patients into high-risk and low-risk groups. High-risk patients had significantly shorter overall survival (OS) and disease-free survival (DFS) than low-risk patients. Calibration curves and Cox regression analysis demonstrated powerful predictive performance. ROC curves showed the better survival prediction by this model than other models. Functional analysis revealed a positive association between risk score and CSC markers. These results had cross-dataset compatibility. Impact This signature could help further improve the current TNM staging system and provide data for the development of novel personalized therapeutic strategies in the future. |
format | Online Article Text |
id | pubmed-7507616 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-75076162020-09-23 Development and validation of a cancer stem cell-related signature for prognostic prediction in pancreatic ductal adenocarcinoma Feng, Zengyu Shi, Minmin Li, Kexian Ma, Yang Jiang, Lingxi Chen, Hao Peng, Chenghong J Transl Med Research BACKGROUND: Cancer stem cells (CSCs) are crucial to the malignant behaviour and poor prognosis of pancreatic ductal adenocarcinoma (PDAC). In recent years, CSC biology has been widely studied, but practical prognostic signatures based on CSC-related genes have not been established or reported in PDAC. METHODS: A signature was developed and validated in seven independent PDAC datasets. The MTAB-6134 cohort was used as the training set, while one local Chinese cohort and five other public cohorts were used for external validation. CSC-related genes with credible prognostic roles were selected to form the signature, and their predictive performance was evaluated by Kaplan–Meier survival, receiver operating characteristic (ROC), and calibration curves. Correlation analysis was employed to clarify the potential biological characteristics of the gene signature. RESULTS: A robust signature comprising DCBLD2, GSDMD, PMAIP1, and PLOD2 was developed. It classified patients into high-risk and low-risk groups. High-risk patients had significantly shorter overall survival (OS) and disease-free survival (DFS) than low-risk patients. Calibration curves and Cox regression analysis demonstrated powerful predictive performance. ROC curves showed the better survival prediction by this model than other models. Functional analysis revealed a positive association between risk score and CSC markers. These results had cross-dataset compatibility. Impact This signature could help further improve the current TNM staging system and provide data for the development of novel personalized therapeutic strategies in the future. BioMed Central 2020-09-21 /pmc/articles/PMC7507616/ /pubmed/32958051 http://dx.doi.org/10.1186/s12967-020-02527-1 Text en © The Author(s) 2020 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/. The Creative Commons Public Domain Dedication waiver (http://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 Feng, Zengyu Shi, Minmin Li, Kexian Ma, Yang Jiang, Lingxi Chen, Hao Peng, Chenghong Development and validation of a cancer stem cell-related signature for prognostic prediction in pancreatic ductal adenocarcinoma |
title | Development and validation of a cancer stem cell-related signature for prognostic prediction in pancreatic ductal adenocarcinoma |
title_full | Development and validation of a cancer stem cell-related signature for prognostic prediction in pancreatic ductal adenocarcinoma |
title_fullStr | Development and validation of a cancer stem cell-related signature for prognostic prediction in pancreatic ductal adenocarcinoma |
title_full_unstemmed | Development and validation of a cancer stem cell-related signature for prognostic prediction in pancreatic ductal adenocarcinoma |
title_short | Development and validation of a cancer stem cell-related signature for prognostic prediction in pancreatic ductal adenocarcinoma |
title_sort | development and validation of a cancer stem cell-related signature for prognostic prediction in pancreatic ductal adenocarcinoma |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7507616/ https://www.ncbi.nlm.nih.gov/pubmed/32958051 http://dx.doi.org/10.1186/s12967-020-02527-1 |
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