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Identification of Immune Subtypes of Lung Squamous Cell Carcinoma by Integrative Genome-Scale Analysis

BACKGROUND: Characterization of the tumor microenvironment is helpful to understand the tumor immune environment of lung cancer and help predict the prognosis. METHODS: First, immune subtypes were identified by consensus subtype among lung squamous carcinoma (LUSC) patients. Immune cell infiltration...

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Autores principales: Yin, Liyuan, Zhang, Wen, Pu, Dan, Zhai, Xiaoqian, Lin, Yiyun, Wu, Qiang, Chang, Tangel, Hu, Jia, Li, Yan, Zhou, Qinghua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8847157/
https://www.ncbi.nlm.nih.gov/pubmed/35186710
http://dx.doi.org/10.3389/fonc.2021.778549
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author Yin, Liyuan
Zhang, Wen
Pu, Dan
Zhai, Xiaoqian
Lin, Yiyun
Wu, Qiang
Chang, Tangel
Hu, Jia
Li, Yan
Zhou, Qinghua
author_facet Yin, Liyuan
Zhang, Wen
Pu, Dan
Zhai, Xiaoqian
Lin, Yiyun
Wu, Qiang
Chang, Tangel
Hu, Jia
Li, Yan
Zhou, Qinghua
author_sort Yin, Liyuan
collection PubMed
description BACKGROUND: Characterization of the tumor microenvironment is helpful to understand the tumor immune environment of lung cancer and help predict the prognosis. METHODS: First, immune subtypes were identified by consensus subtype among lung squamous carcinoma (LUSC) patients. Immune cell infiltration was evaluated by CIBERSORT and ESTIMATE analyses. Then, based on differentially expressed genes (DEGs) identified, a risk score model was constructed. Finally, gene FPR1 was validated by using YTMLC-90. FINDINGS: LUSC samples were divided into four heterogeneous immune subtypes, with significantly different prognoses with subtype 4 having the poorest overall survival (OS). The immune infiltration score showed that subtype 4 was characterized as immune enriched and fibrotic, while subtype 3 was tumor enriched. DEG analysis showed that upregulated genes in subtype 4 were enriched of neutrophil and exhausted T cell-related biological processes. Based on a univariate Cox regression model, prognostic 7 immune-related genes were combined to construct a risk score model and able to predict OS rates in the validation datasets. Wound healing and transwell assay were conducted to evaluate the invasion property after activating the gene FPR1. INTERPRETATION: The analysis of tumor immune microenvironments among LUSC subtypes may provide new insights into the strategy of immunotherapy.
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spelling pubmed-88471572022-02-17 Identification of Immune Subtypes of Lung Squamous Cell Carcinoma by Integrative Genome-Scale Analysis Yin, Liyuan Zhang, Wen Pu, Dan Zhai, Xiaoqian Lin, Yiyun Wu, Qiang Chang, Tangel Hu, Jia Li, Yan Zhou, Qinghua Front Oncol Oncology BACKGROUND: Characterization of the tumor microenvironment is helpful to understand the tumor immune environment of lung cancer and help predict the prognosis. METHODS: First, immune subtypes were identified by consensus subtype among lung squamous carcinoma (LUSC) patients. Immune cell infiltration was evaluated by CIBERSORT and ESTIMATE analyses. Then, based on differentially expressed genes (DEGs) identified, a risk score model was constructed. Finally, gene FPR1 was validated by using YTMLC-90. FINDINGS: LUSC samples were divided into four heterogeneous immune subtypes, with significantly different prognoses with subtype 4 having the poorest overall survival (OS). The immune infiltration score showed that subtype 4 was characterized as immune enriched and fibrotic, while subtype 3 was tumor enriched. DEG analysis showed that upregulated genes in subtype 4 were enriched of neutrophil and exhausted T cell-related biological processes. Based on a univariate Cox regression model, prognostic 7 immune-related genes were combined to construct a risk score model and able to predict OS rates in the validation datasets. Wound healing and transwell assay were conducted to evaluate the invasion property after activating the gene FPR1. INTERPRETATION: The analysis of tumor immune microenvironments among LUSC subtypes may provide new insights into the strategy of immunotherapy. Frontiers Media S.A. 2022-02-02 /pmc/articles/PMC8847157/ /pubmed/35186710 http://dx.doi.org/10.3389/fonc.2021.778549 Text en Copyright © 2022 Yin, Zhang, Pu, Zhai, Lin, Wu, Chang, Hu, Li and Zhou 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
Yin, Liyuan
Zhang, Wen
Pu, Dan
Zhai, Xiaoqian
Lin, Yiyun
Wu, Qiang
Chang, Tangel
Hu, Jia
Li, Yan
Zhou, Qinghua
Identification of Immune Subtypes of Lung Squamous Cell Carcinoma by Integrative Genome-Scale Analysis
title Identification of Immune Subtypes of Lung Squamous Cell Carcinoma by Integrative Genome-Scale Analysis
title_full Identification of Immune Subtypes of Lung Squamous Cell Carcinoma by Integrative Genome-Scale Analysis
title_fullStr Identification of Immune Subtypes of Lung Squamous Cell Carcinoma by Integrative Genome-Scale Analysis
title_full_unstemmed Identification of Immune Subtypes of Lung Squamous Cell Carcinoma by Integrative Genome-Scale Analysis
title_short Identification of Immune Subtypes of Lung Squamous Cell Carcinoma by Integrative Genome-Scale Analysis
title_sort identification of immune subtypes of lung squamous cell carcinoma by integrative genome-scale analysis
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8847157/
https://www.ncbi.nlm.nih.gov/pubmed/35186710
http://dx.doi.org/10.3389/fonc.2021.778549
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