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Allele frequency deviation (AFD) as a new prognostic model to predict overall survival in lung adenocarcinoma (LUAD)
BACKGROUND: Lung adenocarcinoma (LUAD) remains one of the world’s most known aggressive malignancies with a high mortality rate. Molecular biological analysis and bioinformatics are of great importance as they have recently occupied a large area in the studies related to the identification of variou...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8390239/ https://www.ncbi.nlm.nih.gov/pubmed/34446004 http://dx.doi.org/10.1186/s12935-021-02127-z |
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author | Al-Dherasi, Aisha Liao, Yuwei Al-Mosaib, Sultan Hua, Rulin Wang, Yichen Yu, Ying Zhang, Yu Zhang, Xuehong Jalayta, Raeda Mousa, Haithm Al-Danakh, Abdullah Alnadari, Fawze Almoiliqy, Marwan Baldi, Salem Shi, Leming Lv, Dekang Li, Zhiguang Liu, Quentin |
author_facet | Al-Dherasi, Aisha Liao, Yuwei Al-Mosaib, Sultan Hua, Rulin Wang, Yichen Yu, Ying Zhang, Yu Zhang, Xuehong Jalayta, Raeda Mousa, Haithm Al-Danakh, Abdullah Alnadari, Fawze Almoiliqy, Marwan Baldi, Salem Shi, Leming Lv, Dekang Li, Zhiguang Liu, Quentin |
author_sort | Al-Dherasi, Aisha |
collection | PubMed |
description | BACKGROUND: Lung adenocarcinoma (LUAD) remains one of the world’s most known aggressive malignancies with a high mortality rate. Molecular biological analysis and bioinformatics are of great importance as they have recently occupied a large area in the studies related to the identification of various biomarkers to predict survival for LUAD patients. In our study, we attempted to identify a new prognostic model by developing a new algorithm to calculate the allele frequency deviation (AFD), which in turn may assist in the early diagnosis and prediction of clinical outcomes in LUAD. METHOD: First, a new algorithm was developed to calculate AFD using the whole-exome sequencing (WES) dataset. Then, AFD was measured for 102 patients, and the predictive power of AFD was assessed using Kaplan–Meier analysis, receiver operating characteristic (ROC) curves, and area under the curve (AUC). Finally, multivariable cox regression analyses were conducted to evaluate the independence of AFD as an independent prognostic tool. RESULT: The Kaplan–Meier analysis showed that AFD effectively segregated patients with LUAD into high-AFD-value and low-AFD-value risk groups (hazard ratio HR = 1.125, 95% confidence interval CI 1.001–1.26, p = 0.04) in the training group. Moreover, the overall survival (OS) of patients who belong to the high-AFD-value group was significantly shorter than that of patients who belong to the low-AFD-value group with 42.8% higher risk and 10% lower risk of death for both groups respectively (HR for death = 1.10; 95% CI 1.01–1.2, p = 0.03) in the training group. Similar results were obtained in the validation group (HR = 4.62, 95% CI 1.22–17.4, p = 0.02) with 41.6%, and 5.5% risk of death for patients who belong to the high and low-AFD-value groups respectively. Univariate and multivariable cox regression analyses demonstrated that AFD is an independent prognostic model for patients with LUAD. The AUC for 5-year survival were 0.712 and 0.86 in the training and validation groups, respectively. CONCLUSION: AFD was identified as a new independent prognostic model that could provide a prognostic tool for physicians and contribute to treatment decisions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-021-02127-z. |
format | Online Article Text |
id | pubmed-8390239 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-83902392021-08-27 Allele frequency deviation (AFD) as a new prognostic model to predict overall survival in lung adenocarcinoma (LUAD) Al-Dherasi, Aisha Liao, Yuwei Al-Mosaib, Sultan Hua, Rulin Wang, Yichen Yu, Ying Zhang, Yu Zhang, Xuehong Jalayta, Raeda Mousa, Haithm Al-Danakh, Abdullah Alnadari, Fawze Almoiliqy, Marwan Baldi, Salem Shi, Leming Lv, Dekang Li, Zhiguang Liu, Quentin Cancer Cell Int Primary Research BACKGROUND: Lung adenocarcinoma (LUAD) remains one of the world’s most known aggressive malignancies with a high mortality rate. Molecular biological analysis and bioinformatics are of great importance as they have recently occupied a large area in the studies related to the identification of various biomarkers to predict survival for LUAD patients. In our study, we attempted to identify a new prognostic model by developing a new algorithm to calculate the allele frequency deviation (AFD), which in turn may assist in the early diagnosis and prediction of clinical outcomes in LUAD. METHOD: First, a new algorithm was developed to calculate AFD using the whole-exome sequencing (WES) dataset. Then, AFD was measured for 102 patients, and the predictive power of AFD was assessed using Kaplan–Meier analysis, receiver operating characteristic (ROC) curves, and area under the curve (AUC). Finally, multivariable cox regression analyses were conducted to evaluate the independence of AFD as an independent prognostic tool. RESULT: The Kaplan–Meier analysis showed that AFD effectively segregated patients with LUAD into high-AFD-value and low-AFD-value risk groups (hazard ratio HR = 1.125, 95% confidence interval CI 1.001–1.26, p = 0.04) in the training group. Moreover, the overall survival (OS) of patients who belong to the high-AFD-value group was significantly shorter than that of patients who belong to the low-AFD-value group with 42.8% higher risk and 10% lower risk of death for both groups respectively (HR for death = 1.10; 95% CI 1.01–1.2, p = 0.03) in the training group. Similar results were obtained in the validation group (HR = 4.62, 95% CI 1.22–17.4, p = 0.02) with 41.6%, and 5.5% risk of death for patients who belong to the high and low-AFD-value groups respectively. Univariate and multivariable cox regression analyses demonstrated that AFD is an independent prognostic model for patients with LUAD. The AUC for 5-year survival were 0.712 and 0.86 in the training and validation groups, respectively. CONCLUSION: AFD was identified as a new independent prognostic model that could provide a prognostic tool for physicians and contribute to treatment decisions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-021-02127-z. BioMed Central 2021-08-26 /pmc/articles/PMC8390239/ /pubmed/34446004 http://dx.doi.org/10.1186/s12935-021-02127-z Text en © The Author(s) 2021 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 | Primary Research Al-Dherasi, Aisha Liao, Yuwei Al-Mosaib, Sultan Hua, Rulin Wang, Yichen Yu, Ying Zhang, Yu Zhang, Xuehong Jalayta, Raeda Mousa, Haithm Al-Danakh, Abdullah Alnadari, Fawze Almoiliqy, Marwan Baldi, Salem Shi, Leming Lv, Dekang Li, Zhiguang Liu, Quentin Allele frequency deviation (AFD) as a new prognostic model to predict overall survival in lung adenocarcinoma (LUAD) |
title | Allele frequency deviation (AFD) as a new prognostic model to predict overall survival in lung adenocarcinoma (LUAD) |
title_full | Allele frequency deviation (AFD) as a new prognostic model to predict overall survival in lung adenocarcinoma (LUAD) |
title_fullStr | Allele frequency deviation (AFD) as a new prognostic model to predict overall survival in lung adenocarcinoma (LUAD) |
title_full_unstemmed | Allele frequency deviation (AFD) as a new prognostic model to predict overall survival in lung adenocarcinoma (LUAD) |
title_short | Allele frequency deviation (AFD) as a new prognostic model to predict overall survival in lung adenocarcinoma (LUAD) |
title_sort | allele frequency deviation (afd) as a new prognostic model to predict overall survival in lung adenocarcinoma (luad) |
topic | Primary Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8390239/ https://www.ncbi.nlm.nih.gov/pubmed/34446004 http://dx.doi.org/10.1186/s12935-021-02127-z |
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