Cargando…
An integrated prognosis model of pharmacogenomic gene signature and clinical information for diffuse large B-cell lymphoma patients following CHOP-like chemotherapy
BACKGROUND: As the most common form of lymphoma, diffuse large B-cell lymphoma (DLBCL) is a clinical highly heterogeneous disease with variability in therapeutic outcomes and biological features. It is a challenge to identify of clinically meaningful tools for outcome prediction. In this study, we d...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7106727/ https://www.ncbi.nlm.nih.gov/pubmed/32228625 http://dx.doi.org/10.1186/s12967-020-02311-1 |
_version_ | 1783512672467156992 |
---|---|
author | Hu, Jinglei Xu, Jing Yu, Muqiao Gao, Yongchao Liu, Rong Zhou, Honghao Zhang, Wei |
author_facet | Hu, Jinglei Xu, Jing Yu, Muqiao Gao, Yongchao Liu, Rong Zhou, Honghao Zhang, Wei |
author_sort | Hu, Jinglei |
collection | PubMed |
description | BACKGROUND: As the most common form of lymphoma, diffuse large B-cell lymphoma (DLBCL) is a clinical highly heterogeneous disease with variability in therapeutic outcomes and biological features. It is a challenge to identify of clinically meaningful tools for outcome prediction. In this study, we developed a prognosis model fused clinical characteristics with drug resistance pharmacogenomic signature to identify DLBCL prognostic subgroups for CHOP-based treatment. METHODS: The expression microarray data and clinical characteristics of 791 DLBCL patients from two Gene Expression Omnibus (GEO) databases were used to establish and validate this model. By using univariate Cox regression, eight clinical or genetic signatures were analyzed. The elastic net-regulated Cox regression analysis was used to select the best prognosis related factors into the predictive model. To estimate the prognostic capability of the model, Kaplan–Meier curve and the area under receiver operating characteristic (ROC) curve (AUC) were performed. RESULTS: A predictive model comprising 4 clinical factors and 2 pharmacogenomic gene signatures was established after 1000 times cross validation in the training dataset. The AUC of the comprehensive risk model was 0.78, whereas AUC value was lower for the clinical only model (0.68) or the gene only model (0.67). Compared with low-risk patients, the overall survival (OS) of DLBCL patients with high-risk scores was significantly decreased (HR = 4.55, 95% CI 3.14–6.59, log-rank p value = 1.06 × 10(−15)). The signature also enables to predict prognosis within different molecular subtypes of DLBCL. The reliability of the integrated model was confirmed by independent validation dataset (HR = 3.47, 95% CI 2.42–4.97, log rank p value = 1.53 × 10(−11)). CONCLUSIONS: This integrated model has a better predictive capability to ascertain the prognosis of DLBCL patients prior to CHOP-like treatment, which may improve the clinical management of DLBCL patients and provide theoretical basis for individualized treatment. |
format | Online Article Text |
id | pubmed-7106727 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-71067272020-04-01 An integrated prognosis model of pharmacogenomic gene signature and clinical information for diffuse large B-cell lymphoma patients following CHOP-like chemotherapy Hu, Jinglei Xu, Jing Yu, Muqiao Gao, Yongchao Liu, Rong Zhou, Honghao Zhang, Wei J Transl Med Research BACKGROUND: As the most common form of lymphoma, diffuse large B-cell lymphoma (DLBCL) is a clinical highly heterogeneous disease with variability in therapeutic outcomes and biological features. It is a challenge to identify of clinically meaningful tools for outcome prediction. In this study, we developed a prognosis model fused clinical characteristics with drug resistance pharmacogenomic signature to identify DLBCL prognostic subgroups for CHOP-based treatment. METHODS: The expression microarray data and clinical characteristics of 791 DLBCL patients from two Gene Expression Omnibus (GEO) databases were used to establish and validate this model. By using univariate Cox regression, eight clinical or genetic signatures were analyzed. The elastic net-regulated Cox regression analysis was used to select the best prognosis related factors into the predictive model. To estimate the prognostic capability of the model, Kaplan–Meier curve and the area under receiver operating characteristic (ROC) curve (AUC) were performed. RESULTS: A predictive model comprising 4 clinical factors and 2 pharmacogenomic gene signatures was established after 1000 times cross validation in the training dataset. The AUC of the comprehensive risk model was 0.78, whereas AUC value was lower for the clinical only model (0.68) or the gene only model (0.67). Compared with low-risk patients, the overall survival (OS) of DLBCL patients with high-risk scores was significantly decreased (HR = 4.55, 95% CI 3.14–6.59, log-rank p value = 1.06 × 10(−15)). The signature also enables to predict prognosis within different molecular subtypes of DLBCL. The reliability of the integrated model was confirmed by independent validation dataset (HR = 3.47, 95% CI 2.42–4.97, log rank p value = 1.53 × 10(−11)). CONCLUSIONS: This integrated model has a better predictive capability to ascertain the prognosis of DLBCL patients prior to CHOP-like treatment, which may improve the clinical management of DLBCL patients and provide theoretical basis for individualized treatment. BioMed Central 2020-03-30 /pmc/articles/PMC7106727/ /pubmed/32228625 http://dx.doi.org/10.1186/s12967-020-02311-1 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 Hu, Jinglei Xu, Jing Yu, Muqiao Gao, Yongchao Liu, Rong Zhou, Honghao Zhang, Wei An integrated prognosis model of pharmacogenomic gene signature and clinical information for diffuse large B-cell lymphoma patients following CHOP-like chemotherapy |
title | An integrated prognosis model of pharmacogenomic gene signature and clinical information for diffuse large B-cell lymphoma patients following CHOP-like chemotherapy |
title_full | An integrated prognosis model of pharmacogenomic gene signature and clinical information for diffuse large B-cell lymphoma patients following CHOP-like chemotherapy |
title_fullStr | An integrated prognosis model of pharmacogenomic gene signature and clinical information for diffuse large B-cell lymphoma patients following CHOP-like chemotherapy |
title_full_unstemmed | An integrated prognosis model of pharmacogenomic gene signature and clinical information for diffuse large B-cell lymphoma patients following CHOP-like chemotherapy |
title_short | An integrated prognosis model of pharmacogenomic gene signature and clinical information for diffuse large B-cell lymphoma patients following CHOP-like chemotherapy |
title_sort | integrated prognosis model of pharmacogenomic gene signature and clinical information for diffuse large b-cell lymphoma patients following chop-like chemotherapy |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7106727/ https://www.ncbi.nlm.nih.gov/pubmed/32228625 http://dx.doi.org/10.1186/s12967-020-02311-1 |
work_keys_str_mv | AT hujinglei anintegratedprognosismodelofpharmacogenomicgenesignatureandclinicalinformationfordiffuselargebcelllymphomapatientsfollowingchoplikechemotherapy AT xujing anintegratedprognosismodelofpharmacogenomicgenesignatureandclinicalinformationfordiffuselargebcelllymphomapatientsfollowingchoplikechemotherapy AT yumuqiao anintegratedprognosismodelofpharmacogenomicgenesignatureandclinicalinformationfordiffuselargebcelllymphomapatientsfollowingchoplikechemotherapy AT gaoyongchao anintegratedprognosismodelofpharmacogenomicgenesignatureandclinicalinformationfordiffuselargebcelllymphomapatientsfollowingchoplikechemotherapy AT liurong anintegratedprognosismodelofpharmacogenomicgenesignatureandclinicalinformationfordiffuselargebcelllymphomapatientsfollowingchoplikechemotherapy AT zhouhonghao anintegratedprognosismodelofpharmacogenomicgenesignatureandclinicalinformationfordiffuselargebcelllymphomapatientsfollowingchoplikechemotherapy AT zhangwei anintegratedprognosismodelofpharmacogenomicgenesignatureandclinicalinformationfordiffuselargebcelllymphomapatientsfollowingchoplikechemotherapy AT hujinglei integratedprognosismodelofpharmacogenomicgenesignatureandclinicalinformationfordiffuselargebcelllymphomapatientsfollowingchoplikechemotherapy AT xujing integratedprognosismodelofpharmacogenomicgenesignatureandclinicalinformationfordiffuselargebcelllymphomapatientsfollowingchoplikechemotherapy AT yumuqiao integratedprognosismodelofpharmacogenomicgenesignatureandclinicalinformationfordiffuselargebcelllymphomapatientsfollowingchoplikechemotherapy AT gaoyongchao integratedprognosismodelofpharmacogenomicgenesignatureandclinicalinformationfordiffuselargebcelllymphomapatientsfollowingchoplikechemotherapy AT liurong integratedprognosismodelofpharmacogenomicgenesignatureandclinicalinformationfordiffuselargebcelllymphomapatientsfollowingchoplikechemotherapy AT zhouhonghao integratedprognosismodelofpharmacogenomicgenesignatureandclinicalinformationfordiffuselargebcelllymphomapatientsfollowingchoplikechemotherapy AT zhangwei integratedprognosismodelofpharmacogenomicgenesignatureandclinicalinformationfordiffuselargebcelllymphomapatientsfollowingchoplikechemotherapy |