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Immune Microenvironment Signatures as Biomarkers to Predict Early Recurrence of Stage Ia-b Lung Cancer

INTRODUCTION: Approximately 30% of patients diagnosed with stage Ia-b NSCLC die of recurrent disease after surgery. This study aimed to identify immune-related biomarkers that might predict tumor recurrence in stage Ia-b NSCLC within 40 months after curative resection. METHODS: Gene expression data...

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Autores principales: Wang, Qiang, Zhou, Danting, Wu, Fang, Liang, Qingchun, He, Qiongzhi, Peng, Muyun, Yao, Tianyu, Hu, Yan, Qian, Banglun, Tang, Jingqun, Wang, Xiang, Liu, Wenliang, Yu, Fenglei, Chen, Chen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8356052/
https://www.ncbi.nlm.nih.gov/pubmed/34395248
http://dx.doi.org/10.3389/fonc.2021.680287
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author Wang, Qiang
Zhou, Danting
Wu, Fang
Liang, Qingchun
He, Qiongzhi
Peng, Muyun
Yao, Tianyu
Hu, Yan
Qian, Banglun
Tang, Jingqun
Wang, Xiang
Liu, Wenliang
Yu, Fenglei
Chen, Chen
author_facet Wang, Qiang
Zhou, Danting
Wu, Fang
Liang, Qingchun
He, Qiongzhi
Peng, Muyun
Yao, Tianyu
Hu, Yan
Qian, Banglun
Tang, Jingqun
Wang, Xiang
Liu, Wenliang
Yu, Fenglei
Chen, Chen
author_sort Wang, Qiang
collection PubMed
description INTRODUCTION: Approximately 30% of patients diagnosed with stage Ia-b NSCLC die of recurrent disease after surgery. This study aimed to identify immune-related biomarkers that might predict tumor recurrence in stage Ia-b NSCLC within 40 months after curative resection. METHODS: Gene expression data of stage Ia-b NSCLC samples was retrieved from the TCGA database, the GEO databases, and the Second Xiangya hospital (XXEYY) database. 22 types of tumors infiltrating immune cells and the expression of immune-associated genes were investigated using CIBERSORT, immunohistochemical staining, and GSEA analyses in a total of 450 patients (80 in the training cohort and 370 in the validation cohorts). Recurrence-related immune features were selected based on the LASSO Cox regression model. RESULTS: High density of Tregs, Macrophages M0 and M1 cell could be observed in recurrence group while the memory B cell was more frequently enriched in controls, yet Tregs alone was significantly associated with tumor early recurrence in TCGA cohort, XYEYY cohort and GSE37745 dataset. A handful of immune-related genes were identified in the recurrence group. Based on Lasso regression analysis, the expressions of five immune-related genes, RLTPR, SLFN13, MIR4500HG, HYDIN and TPRG1 were closely correlated with tumor early recurrence. In the training cohort (TCGA), the combination of these five genes has sensitivity and specificity of 85% and 85%, with AUC of 0.91 (95% CI 0.84-0.98) for lung cancer early recurrence prediction, whereas in validation cohorts, the sensitivity and specificity using this panel was 61-89% and 54-82%, with AUC of 0.62-0.84. CONCLUSION: Our study demonstrated that the immune microenvironment signatures were closely related to tumor early recurrence. Compared to tumor-infiltrating lymphocytes, the expression of five immune-related genes could be robust biomarkers to predict early recurrence of stage Ia-b NSCLC after curative resection.
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spelling pubmed-83560522021-08-12 Immune Microenvironment Signatures as Biomarkers to Predict Early Recurrence of Stage Ia-b Lung Cancer Wang, Qiang Zhou, Danting Wu, Fang Liang, Qingchun He, Qiongzhi Peng, Muyun Yao, Tianyu Hu, Yan Qian, Banglun Tang, Jingqun Wang, Xiang Liu, Wenliang Yu, Fenglei Chen, Chen Front Oncol Oncology INTRODUCTION: Approximately 30% of patients diagnosed with stage Ia-b NSCLC die of recurrent disease after surgery. This study aimed to identify immune-related biomarkers that might predict tumor recurrence in stage Ia-b NSCLC within 40 months after curative resection. METHODS: Gene expression data of stage Ia-b NSCLC samples was retrieved from the TCGA database, the GEO databases, and the Second Xiangya hospital (XXEYY) database. 22 types of tumors infiltrating immune cells and the expression of immune-associated genes were investigated using CIBERSORT, immunohistochemical staining, and GSEA analyses in a total of 450 patients (80 in the training cohort and 370 in the validation cohorts). Recurrence-related immune features were selected based on the LASSO Cox regression model. RESULTS: High density of Tregs, Macrophages M0 and M1 cell could be observed in recurrence group while the memory B cell was more frequently enriched in controls, yet Tregs alone was significantly associated with tumor early recurrence in TCGA cohort, XYEYY cohort and GSE37745 dataset. A handful of immune-related genes were identified in the recurrence group. Based on Lasso regression analysis, the expressions of five immune-related genes, RLTPR, SLFN13, MIR4500HG, HYDIN and TPRG1 were closely correlated with tumor early recurrence. In the training cohort (TCGA), the combination of these five genes has sensitivity and specificity of 85% and 85%, with AUC of 0.91 (95% CI 0.84-0.98) for lung cancer early recurrence prediction, whereas in validation cohorts, the sensitivity and specificity using this panel was 61-89% and 54-82%, with AUC of 0.62-0.84. CONCLUSION: Our study demonstrated that the immune microenvironment signatures were closely related to tumor early recurrence. Compared to tumor-infiltrating lymphocytes, the expression of five immune-related genes could be robust biomarkers to predict early recurrence of stage Ia-b NSCLC after curative resection. Frontiers Media S.A. 2021-07-28 /pmc/articles/PMC8356052/ /pubmed/34395248 http://dx.doi.org/10.3389/fonc.2021.680287 Text en Copyright © 2021 Wang, Zhou, Wu, Liang, He, Peng, Yao, Hu, Qian, Tang, Wang, Liu, Yu and Chen https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Wang, Qiang
Zhou, Danting
Wu, Fang
Liang, Qingchun
He, Qiongzhi
Peng, Muyun
Yao, Tianyu
Hu, Yan
Qian, Banglun
Tang, Jingqun
Wang, Xiang
Liu, Wenliang
Yu, Fenglei
Chen, Chen
Immune Microenvironment Signatures as Biomarkers to Predict Early Recurrence of Stage Ia-b Lung Cancer
title Immune Microenvironment Signatures as Biomarkers to Predict Early Recurrence of Stage Ia-b Lung Cancer
title_full Immune Microenvironment Signatures as Biomarkers to Predict Early Recurrence of Stage Ia-b Lung Cancer
title_fullStr Immune Microenvironment Signatures as Biomarkers to Predict Early Recurrence of Stage Ia-b Lung Cancer
title_full_unstemmed Immune Microenvironment Signatures as Biomarkers to Predict Early Recurrence of Stage Ia-b Lung Cancer
title_short Immune Microenvironment Signatures as Biomarkers to Predict Early Recurrence of Stage Ia-b Lung Cancer
title_sort immune microenvironment signatures as biomarkers to predict early recurrence of stage ia-b lung cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8356052/
https://www.ncbi.nlm.nih.gov/pubmed/34395248
http://dx.doi.org/10.3389/fonc.2021.680287
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