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Identification of Novel Prognostic Biomarkers Relevant to Immune Infiltration in Lung Adenocarcinoma

Background: Programmed death ligand-1 (PD-L1) is a biomarker for assessing the immune microenvironment, prognosis, and response to immune checkpoint inhibitors in the clinical treatment of lung adenocarcinoma (LUAD), but it does not work for all patients. This study aims to discover alternative biom...

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Autores principales: Xia, Zhi, Rong, Xueyao, Dai, Ziyu, Zhou, Dongbo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9092026/
https://www.ncbi.nlm.nih.gov/pubmed/35571056
http://dx.doi.org/10.3389/fgene.2022.863796
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author Xia, Zhi
Rong, Xueyao
Dai, Ziyu
Zhou, Dongbo
author_facet Xia, Zhi
Rong, Xueyao
Dai, Ziyu
Zhou, Dongbo
author_sort Xia, Zhi
collection PubMed
description Background: Programmed death ligand-1 (PD-L1) is a biomarker for assessing the immune microenvironment, prognosis, and response to immune checkpoint inhibitors in the clinical treatment of lung adenocarcinoma (LUAD), but it does not work for all patients. This study aims to discover alternative biomarkers. Methods: Public data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Weighted gene co-expression network analysis (WGCNA) and gene ontology (GO) were used to determine the gene modules relevant to tumor immunity. Protein–protein interaction (PPI) network and GO semantic similarity analyses were applied to identify the module hub genes with functional similarities to PD-L1, and we assessed their correlations with immune infiltration, patient prognosis, and immunotherapy response. Immunohistochemistry (IHC) and hematoxylin and eosin (H&E) staining were used to validate the outcome at the protein level. Results: We identified an immune response–related module, and two hub genes (PSTPIP1 and PILRA) were selected as potential biomarkers with functional similarities to PD-L1. High expression levels of PSTPIP1 and PILRA were associated with longer overall survival and rich immune infiltration in LUAD patients, and both were significantly high in patients who responded to anti–PD-L1 treatment. Compared to PD-L1–negative LUAD tissues, the protein levels of PSTPIP1 and PILRA were relatively increased in the PD-L1–positive tissues, and the expression of PSTPIP1 and PILRA positively correlated with the tumor-infiltrating lymphocytes. Conclusion: We identified PSTPIP1 and PILRA as prognostic biomarkers relevant to immune infiltration in LUAD, and both are associated with the response to anti–PD-L1 treatment.
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spelling pubmed-90920262022-05-12 Identification of Novel Prognostic Biomarkers Relevant to Immune Infiltration in Lung Adenocarcinoma Xia, Zhi Rong, Xueyao Dai, Ziyu Zhou, Dongbo Front Genet Genetics Background: Programmed death ligand-1 (PD-L1) is a biomarker for assessing the immune microenvironment, prognosis, and response to immune checkpoint inhibitors in the clinical treatment of lung adenocarcinoma (LUAD), but it does not work for all patients. This study aims to discover alternative biomarkers. Methods: Public data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Weighted gene co-expression network analysis (WGCNA) and gene ontology (GO) were used to determine the gene modules relevant to tumor immunity. Protein–protein interaction (PPI) network and GO semantic similarity analyses were applied to identify the module hub genes with functional similarities to PD-L1, and we assessed their correlations with immune infiltration, patient prognosis, and immunotherapy response. Immunohistochemistry (IHC) and hematoxylin and eosin (H&E) staining were used to validate the outcome at the protein level. Results: We identified an immune response–related module, and two hub genes (PSTPIP1 and PILRA) were selected as potential biomarkers with functional similarities to PD-L1. High expression levels of PSTPIP1 and PILRA were associated with longer overall survival and rich immune infiltration in LUAD patients, and both were significantly high in patients who responded to anti–PD-L1 treatment. Compared to PD-L1–negative LUAD tissues, the protein levels of PSTPIP1 and PILRA were relatively increased in the PD-L1–positive tissues, and the expression of PSTPIP1 and PILRA positively correlated with the tumor-infiltrating lymphocytes. Conclusion: We identified PSTPIP1 and PILRA as prognostic biomarkers relevant to immune infiltration in LUAD, and both are associated with the response to anti–PD-L1 treatment. Frontiers Media S.A. 2022-04-27 /pmc/articles/PMC9092026/ /pubmed/35571056 http://dx.doi.org/10.3389/fgene.2022.863796 Text en Copyright © 2022 Xia, Rong, Dai 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 Genetics
Xia, Zhi
Rong, Xueyao
Dai, Ziyu
Zhou, Dongbo
Identification of Novel Prognostic Biomarkers Relevant to Immune Infiltration in Lung Adenocarcinoma
title Identification of Novel Prognostic Biomarkers Relevant to Immune Infiltration in Lung Adenocarcinoma
title_full Identification of Novel Prognostic Biomarkers Relevant to Immune Infiltration in Lung Adenocarcinoma
title_fullStr Identification of Novel Prognostic Biomarkers Relevant to Immune Infiltration in Lung Adenocarcinoma
title_full_unstemmed Identification of Novel Prognostic Biomarkers Relevant to Immune Infiltration in Lung Adenocarcinoma
title_short Identification of Novel Prognostic Biomarkers Relevant to Immune Infiltration in Lung Adenocarcinoma
title_sort identification of novel prognostic biomarkers relevant to immune infiltration in lung adenocarcinoma
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9092026/
https://www.ncbi.nlm.nih.gov/pubmed/35571056
http://dx.doi.org/10.3389/fgene.2022.863796
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