Identification of an Individualized Metabolism Prognostic Signature and Related Therapy Regimens in Early Stage Lung Adenocarcinoma
ObjectiveThe choice of adjuvant therapy for early stage lung adenocarcinoma (LUAD) remains controversial. Identifying the metabolism characteristics leading to worse prognosis may have clinical utility in offering adjuvant therapy.MethodsThe gene expression profiles of LUAD were collected from 22 pu...
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doaj-6b62811e491643fb8baf9be92b56f3c62021-04-28T07:19:40ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2021-04-011110.3389/fonc.2021.650853650853Identification of an Individualized Metabolism Prognostic Signature and Related Therapy Regimens in Early Stage Lung AdenocarcinomaJunjie Hu0Huansha Yu1Liangdong Sun2Yilv Yan3Lele Zhang4Gening Jiang5Peng Zhang6Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, ChinaExperimental Animal Center, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, ChinaDepartment of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, ChinaDepartment of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, ChinaCentral Laboratory of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, ChinaDepartment of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, ChinaDepartment of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, ChinaObjectiveThe choice of adjuvant therapy for early stage lung adenocarcinoma (LUAD) remains controversial. Identifying the metabolism characteristics leading to worse prognosis may have clinical utility in offering adjuvant therapy.MethodsThe gene expression profiles of LUAD were collected from 22 public datasets. The patients were divided into a meta-training cohort (n = 790), meta-testing cohort (n = 716), and three independent validation cohorts (n = 345, 358, and 321). A metabolism-related gene pair index (MRGPI) was trained and validated in the cohorts. Subgroup analyses regarding tumor stage and adjuvant chemotherapy (ACT) were performed. To explore potential therapeutic targets, we performed in silico analysis of the MRGPI.ResultsThrough machine learning, MRGPI consisting of 12 metabolism-related gene pairs was constructed. MRGPI robustly stratified patients into high- vs low-risk groups in terms of overall survival across and within subpopulations with stage I or II disease in all cohorts. Multivariable analysis confirmed that MRGPI was an independent prognostic factor. ACT could not improve prognosis in high-risk patients with stage I disease, but could improve prognosis in the high-risk patients with stage II disease. In silico analysis indicated that B3GNT3 (overexpressed in high-risk patients) and HSD17B6 (down-expressed in high-risk patients) may make synergic reaction in immune evasion by the PD-1/PD-L1 pathway. When integrated with clinical characteristics, the composite clinical and metabolism signature showed improved prognostic accuracy.ConclusionsMRGPI could effectively predict prognosis of the patients with early stage LUAD. The patients at high risk may get survival benefit from PD-1/PD-L1 blockade (stage I) or combined with chemotherapy (stage II).https://www.frontiersin.org/articles/10.3389/fonc.2021.650853/fulllung adenocarcinomaearly stagemetabolism genesprognostic signatureadjuvant therapy |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Junjie Hu Huansha Yu Liangdong Sun Yilv Yan Lele Zhang Gening Jiang Peng Zhang |
spellingShingle |
Junjie Hu Huansha Yu Liangdong Sun Yilv Yan Lele Zhang Gening Jiang Peng Zhang Identification of an Individualized Metabolism Prognostic Signature and Related Therapy Regimens in Early Stage Lung Adenocarcinoma Frontiers in Oncology lung adenocarcinoma early stage metabolism genes prognostic signature adjuvant therapy |
author_facet |
Junjie Hu Huansha Yu Liangdong Sun Yilv Yan Lele Zhang Gening Jiang Peng Zhang |
author_sort |
Junjie Hu |
title |
Identification of an Individualized Metabolism Prognostic Signature and Related Therapy Regimens in Early Stage Lung Adenocarcinoma |
title_short |
Identification of an Individualized Metabolism Prognostic Signature and Related Therapy Regimens in Early Stage Lung Adenocarcinoma |
title_full |
Identification of an Individualized Metabolism Prognostic Signature and Related Therapy Regimens in Early Stage Lung Adenocarcinoma |
title_fullStr |
Identification of an Individualized Metabolism Prognostic Signature and Related Therapy Regimens in Early Stage Lung Adenocarcinoma |
title_full_unstemmed |
Identification of an Individualized Metabolism Prognostic Signature and Related Therapy Regimens in Early Stage Lung Adenocarcinoma |
title_sort |
identification of an individualized metabolism prognostic signature and related therapy regimens in early stage lung adenocarcinoma |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Oncology |
issn |
2234-943X |
publishDate |
2021-04-01 |
description |
ObjectiveThe choice of adjuvant therapy for early stage lung adenocarcinoma (LUAD) remains controversial. Identifying the metabolism characteristics leading to worse prognosis may have clinical utility in offering adjuvant therapy.MethodsThe gene expression profiles of LUAD were collected from 22 public datasets. The patients were divided into a meta-training cohort (n = 790), meta-testing cohort (n = 716), and three independent validation cohorts (n = 345, 358, and 321). A metabolism-related gene pair index (MRGPI) was trained and validated in the cohorts. Subgroup analyses regarding tumor stage and adjuvant chemotherapy (ACT) were performed. To explore potential therapeutic targets, we performed in silico analysis of the MRGPI.ResultsThrough machine learning, MRGPI consisting of 12 metabolism-related gene pairs was constructed. MRGPI robustly stratified patients into high- vs low-risk groups in terms of overall survival across and within subpopulations with stage I or II disease in all cohorts. Multivariable analysis confirmed that MRGPI was an independent prognostic factor. ACT could not improve prognosis in high-risk patients with stage I disease, but could improve prognosis in the high-risk patients with stage II disease. In silico analysis indicated that B3GNT3 (overexpressed in high-risk patients) and HSD17B6 (down-expressed in high-risk patients) may make synergic reaction in immune evasion by the PD-1/PD-L1 pathway. When integrated with clinical characteristics, the composite clinical and metabolism signature showed improved prognostic accuracy.ConclusionsMRGPI could effectively predict prognosis of the patients with early stage LUAD. The patients at high risk may get survival benefit from PD-1/PD-L1 blockade (stage I) or combined with chemotherapy (stage II). |
topic |
lung adenocarcinoma early stage metabolism genes prognostic signature adjuvant therapy |
url |
https://www.frontiersin.org/articles/10.3389/fonc.2021.650853/full |
work_keys_str_mv |
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