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Immune infiltration patterns and identification of new diagnostic biomarkers GDF10, NCKAP5, and RTKN2 in non-small cell lung cancer

This study aimed to identify potential biomarkers for non-small cell lung cancer (NSCLC) and analyze the role of immune cell infiltration in NSCLC. R software was used to screen differentially expressed genes (DEGs) from NSCLC datasets obtained from the Gene Expression Omnibus (GEO) database, and fu...

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Autores principales: Chen, Kaiqin, Ye, Chun, Gao, Zihan, Hu, Jue, Chen, Chunjing, Xiao, Rong, Lu, Fangguo, Wei, Ke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Neoplasia Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9843486/
https://www.ncbi.nlm.nih.gov/pubmed/36628881
http://dx.doi.org/10.1016/j.tranon.2023.101618
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author Chen, Kaiqin
Ye, Chun
Gao, Zihan
Hu, Jue
Chen, Chunjing
Xiao, Rong
Lu, Fangguo
Wei, Ke
author_facet Chen, Kaiqin
Ye, Chun
Gao, Zihan
Hu, Jue
Chen, Chunjing
Xiao, Rong
Lu, Fangguo
Wei, Ke
author_sort Chen, Kaiqin
collection PubMed
description This study aimed to identify potential biomarkers for non-small cell lung cancer (NSCLC) and analyze the role of immune cell infiltration in NSCLC. R software was used to screen differentially expressed genes (DEGs) from NSCLC datasets obtained from the Gene Expression Omnibus (GEO) database, and functional correlation analysis was performed. The machine learning algorithms were used to screen the potential biomarkers of NSCLC. The diagnostic values were assessed through receiver operating characteristic (ROC) curves. The protein and mRNA expression levels of potential biomarkers were verified based on the Human Protein Atlas (HPA) database and qRT-PCR. CIBERSORT was used to evaluate the infiltration of immune cells in NSCLC tissues, and the correlation between potential biomarkers and infiltrated immune cell was analyzed. Finally, specific siRNAs were utilized to reduce the GDF10, NCKAP5, and RTKN2 expression in A549 and H1975 cells. The proliferation ability of A549 and H1975 cells was detected by MTT assay. A total of 848 upregulated DEGs and 1308 downregulated DEGs were identified. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that the DEGs were mainly related to cell division. Disease ontology (DO) enrichment analysis showed that the diseases with these DEGs were mainly lung diseases, including NSCLC. In addition,three potential biomarkers were identified: GDF10, NCKAP5, and RTKN2. Immune cell infiltration analysis showed that resting NK cells, activated dendritic cells, and Tregs may be involved in the pathogenesis of NSCLC. Meanwhile, GDF10, NCKAP5, and RTKN2 were negatively correlated with Tregs and naïve B cells but were positively correlated with activated dendritic cells and resting NK cells. Immunohistochemical staining showed that the expression of GDF10, NCKAP5, and RTKN2 in the lung tissue of patients with NSCLC was lower than that of normal lung tissue. qRT-PCR also confirmed that the mRNA expression of three biomarkers in NSCLC cell lines A549 and H1975 were significantly lower than those in human normal lung epithelial cells BEAS-2B. An MTT assay showed that GDF10, NCKAP5, and RTKN2 knockdown significantly promoted the proliferation of A549 and H1975 cells. The in vitro experiments showed that GDF10, NCKAP5, and RTKN2 played the inhibitory effects on NSCLC cell lines proliferation. Hence, GDF10, NCKAP5, and RTKN2 can be used as diagnostic biomarkers for NSCLC.
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spelling pubmed-98434862023-01-24 Immune infiltration patterns and identification of new diagnostic biomarkers GDF10, NCKAP5, and RTKN2 in non-small cell lung cancer Chen, Kaiqin Ye, Chun Gao, Zihan Hu, Jue Chen, Chunjing Xiao, Rong Lu, Fangguo Wei, Ke Transl Oncol Original Research This study aimed to identify potential biomarkers for non-small cell lung cancer (NSCLC) and analyze the role of immune cell infiltration in NSCLC. R software was used to screen differentially expressed genes (DEGs) from NSCLC datasets obtained from the Gene Expression Omnibus (GEO) database, and functional correlation analysis was performed. The machine learning algorithms were used to screen the potential biomarkers of NSCLC. The diagnostic values were assessed through receiver operating characteristic (ROC) curves. The protein and mRNA expression levels of potential biomarkers were verified based on the Human Protein Atlas (HPA) database and qRT-PCR. CIBERSORT was used to evaluate the infiltration of immune cells in NSCLC tissues, and the correlation between potential biomarkers and infiltrated immune cell was analyzed. Finally, specific siRNAs were utilized to reduce the GDF10, NCKAP5, and RTKN2 expression in A549 and H1975 cells. The proliferation ability of A549 and H1975 cells was detected by MTT assay. A total of 848 upregulated DEGs and 1308 downregulated DEGs were identified. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that the DEGs were mainly related to cell division. Disease ontology (DO) enrichment analysis showed that the diseases with these DEGs were mainly lung diseases, including NSCLC. In addition,three potential biomarkers were identified: GDF10, NCKAP5, and RTKN2. Immune cell infiltration analysis showed that resting NK cells, activated dendritic cells, and Tregs may be involved in the pathogenesis of NSCLC. Meanwhile, GDF10, NCKAP5, and RTKN2 were negatively correlated with Tregs and naïve B cells but were positively correlated with activated dendritic cells and resting NK cells. Immunohistochemical staining showed that the expression of GDF10, NCKAP5, and RTKN2 in the lung tissue of patients with NSCLC was lower than that of normal lung tissue. qRT-PCR also confirmed that the mRNA expression of three biomarkers in NSCLC cell lines A549 and H1975 were significantly lower than those in human normal lung epithelial cells BEAS-2B. An MTT assay showed that GDF10, NCKAP5, and RTKN2 knockdown significantly promoted the proliferation of A549 and H1975 cells. The in vitro experiments showed that GDF10, NCKAP5, and RTKN2 played the inhibitory effects on NSCLC cell lines proliferation. Hence, GDF10, NCKAP5, and RTKN2 can be used as diagnostic biomarkers for NSCLC. Neoplasia Press 2023-01-09 /pmc/articles/PMC9843486/ /pubmed/36628881 http://dx.doi.org/10.1016/j.tranon.2023.101618 Text en © 2023 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Research
Chen, Kaiqin
Ye, Chun
Gao, Zihan
Hu, Jue
Chen, Chunjing
Xiao, Rong
Lu, Fangguo
Wei, Ke
Immune infiltration patterns and identification of new diagnostic biomarkers GDF10, NCKAP5, and RTKN2 in non-small cell lung cancer
title Immune infiltration patterns and identification of new diagnostic biomarkers GDF10, NCKAP5, and RTKN2 in non-small cell lung cancer
title_full Immune infiltration patterns and identification of new diagnostic biomarkers GDF10, NCKAP5, and RTKN2 in non-small cell lung cancer
title_fullStr Immune infiltration patterns and identification of new diagnostic biomarkers GDF10, NCKAP5, and RTKN2 in non-small cell lung cancer
title_full_unstemmed Immune infiltration patterns and identification of new diagnostic biomarkers GDF10, NCKAP5, and RTKN2 in non-small cell lung cancer
title_short Immune infiltration patterns and identification of new diagnostic biomarkers GDF10, NCKAP5, and RTKN2 in non-small cell lung cancer
title_sort immune infiltration patterns and identification of new diagnostic biomarkers gdf10, nckap5, and rtkn2 in non-small cell lung cancer
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9843486/
https://www.ncbi.nlm.nih.gov/pubmed/36628881
http://dx.doi.org/10.1016/j.tranon.2023.101618
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