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Prediction of prognosis and immunotherapy response in lung adenocarcinoma based on CD79A, DKK1 and VEGFC

BACKGROUND: Tumor immune microenvironment (TIME) is crucial for tumor initiation, progression, and metastasis; however, its relationship with lung adenocarcinoma (LUAD) is unknown. Traditional predictive models screen for biomarkers that are too general and infrequently associated with immune genes....

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Autores principales: Zhang, Qilong, Zhao, Mingyuan, Lin, Shuangyan, Han, Qi, Ye, He, Peng, Fang, Li, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10392102/
https://www.ncbi.nlm.nih.gov/pubmed/37534013
http://dx.doi.org/10.1016/j.heliyon.2023.e18503
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author Zhang, Qilong
Zhao, Mingyuan
Lin, Shuangyan
Han, Qi
Ye, He
Peng, Fang
Li, Li
author_facet Zhang, Qilong
Zhao, Mingyuan
Lin, Shuangyan
Han, Qi
Ye, He
Peng, Fang
Li, Li
author_sort Zhang, Qilong
collection PubMed
description BACKGROUND: Tumor immune microenvironment (TIME) is crucial for tumor initiation, progression, and metastasis; however, its relationship with lung adenocarcinoma (LUAD) is unknown. Traditional predictive models screen for biomarkers that are too general and infrequently associated with immune genes. METHODS: RNA sequencing data of LUAD patients and immune-related gene sets were retrieved from public databases. Using the common genes shared by The Cancer Genome Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort), differential gene expression analysis, survival analysis, Lasso regression analysis, and univariate and multivariate Cox regression analyses were performed to generate a novel risk score model. LUAD cohort in International Cancer Genome Consortium (ICGC), GSE68465 cohort in Gene Expression Omnibus (GEO) and an immunohistochemical assay were used to validate the key genes constructed risk score. The LUAD-related prognosis, clinical indicators, immune infiltrate characteristics, response to immunotherapy, and response to chemotherapeutic agents in different risk groups were evaluated by CIBERSORT, ImmuCellAI, pRRophetic and other tools. RESULTS: The risk score model was constructed using CD79a molecule (CD79A), Dickkopf WNT signaling pathway inhibitor 1 (DKK1), and vascular endothelial growth factor C (VEGFC). High risk score was identified as a negative predictor for overall survival (OS) in subgroup analyses with tumor stage, TNM classification, therapy outcome, and ESTIMATE scores (P < 0.05). Low risk score was positively associated with plasma cells, memory B cells, CD8 T cells, regulatory T cells and γδT cells (P < 0.05). In low-risk group, programmed cell death 1 receptor (PD1), cytotoxic T-lymphocyte associated protein 4 (CTLA4), and lymphocyte activating 3 (LAG3) and indoleamine 2,3-dioxygenase (IDO) were more robustly expressed (P < 0.05). The treatment responses of immune checkpoint blockade (ICB) therapy and chemotherapy were likewise superior in low-risk group (P < 0.05). In immunohistochemical analysis, the tumor group had significantly higher levels of CD79A, DKK1, and VEGFC than the adjacent normal group (P < 0.01). CONCLUSIONS: CD79A, DKK1 and VEGFC are important differential genes related to LUAD, risk score could reliably predict prognosis, composition of TIME and immunotherapy responses in LUAD patients. The excellent performance of the risk model shows its strong and broad application potential.
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spelling pubmed-103921022023-08-02 Prediction of prognosis and immunotherapy response in lung adenocarcinoma based on CD79A, DKK1 and VEGFC Zhang, Qilong Zhao, Mingyuan Lin, Shuangyan Han, Qi Ye, He Peng, Fang Li, Li Heliyon Research Article BACKGROUND: Tumor immune microenvironment (TIME) is crucial for tumor initiation, progression, and metastasis; however, its relationship with lung adenocarcinoma (LUAD) is unknown. Traditional predictive models screen for biomarkers that are too general and infrequently associated with immune genes. METHODS: RNA sequencing data of LUAD patients and immune-related gene sets were retrieved from public databases. Using the common genes shared by The Cancer Genome Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort), differential gene expression analysis, survival analysis, Lasso regression analysis, and univariate and multivariate Cox regression analyses were performed to generate a novel risk score model. LUAD cohort in International Cancer Genome Consortium (ICGC), GSE68465 cohort in Gene Expression Omnibus (GEO) and an immunohistochemical assay were used to validate the key genes constructed risk score. The LUAD-related prognosis, clinical indicators, immune infiltrate characteristics, response to immunotherapy, and response to chemotherapeutic agents in different risk groups were evaluated by CIBERSORT, ImmuCellAI, pRRophetic and other tools. RESULTS: The risk score model was constructed using CD79a molecule (CD79A), Dickkopf WNT signaling pathway inhibitor 1 (DKK1), and vascular endothelial growth factor C (VEGFC). High risk score was identified as a negative predictor for overall survival (OS) in subgroup analyses with tumor stage, TNM classification, therapy outcome, and ESTIMATE scores (P < 0.05). Low risk score was positively associated with plasma cells, memory B cells, CD8 T cells, regulatory T cells and γδT cells (P < 0.05). In low-risk group, programmed cell death 1 receptor (PD1), cytotoxic T-lymphocyte associated protein 4 (CTLA4), and lymphocyte activating 3 (LAG3) and indoleamine 2,3-dioxygenase (IDO) were more robustly expressed (P < 0.05). The treatment responses of immune checkpoint blockade (ICB) therapy and chemotherapy were likewise superior in low-risk group (P < 0.05). In immunohistochemical analysis, the tumor group had significantly higher levels of CD79A, DKK1, and VEGFC than the adjacent normal group (P < 0.01). CONCLUSIONS: CD79A, DKK1 and VEGFC are important differential genes related to LUAD, risk score could reliably predict prognosis, composition of TIME and immunotherapy responses in LUAD patients. The excellent performance of the risk model shows its strong and broad application potential. Elsevier 2023-07-20 /pmc/articles/PMC10392102/ /pubmed/37534013 http://dx.doi.org/10.1016/j.heliyon.2023.e18503 Text en © 2023 The Authors 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 Research Article
Zhang, Qilong
Zhao, Mingyuan
Lin, Shuangyan
Han, Qi
Ye, He
Peng, Fang
Li, Li
Prediction of prognosis and immunotherapy response in lung adenocarcinoma based on CD79A, DKK1 and VEGFC
title Prediction of prognosis and immunotherapy response in lung adenocarcinoma based on CD79A, DKK1 and VEGFC
title_full Prediction of prognosis and immunotherapy response in lung adenocarcinoma based on CD79A, DKK1 and VEGFC
title_fullStr Prediction of prognosis and immunotherapy response in lung adenocarcinoma based on CD79A, DKK1 and VEGFC
title_full_unstemmed Prediction of prognosis and immunotherapy response in lung adenocarcinoma based on CD79A, DKK1 and VEGFC
title_short Prediction of prognosis and immunotherapy response in lung adenocarcinoma based on CD79A, DKK1 and VEGFC
title_sort prediction of prognosis and immunotherapy response in lung adenocarcinoma based on cd79a, dkk1 and vegfc
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10392102/
https://www.ncbi.nlm.nih.gov/pubmed/37534013
http://dx.doi.org/10.1016/j.heliyon.2023.e18503
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