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基于生物信息学数据探究PKIG与肺鳞癌的相关性及其在肿瘤微环境中的作用

Background and objective Lung cancer is the leading cause of cancer-related death worldwide, and patients have limited survival benefits from traditional treatments such as surgery, radiotherapy and chemotherapy. As a new treatment for lung cancer, immunotherapy has significantly prolonged the overa...

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Autores principales: LIU, Qing, LI, Haitian, LI, Bin, REN, Meiyu, LI, Zhenqing, CHEN, Yuzhen, ZHENG, Zhizhong, MENG, Yuqi, FENG, Haiming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Editorial board of Chinese Journal of Lung Cancer 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10476207/
https://www.ncbi.nlm.nih.gov/pubmed/37653016
http://dx.doi.org/10.3779/j.issn.1009-3419.2023.102.24
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author LIU, Qing
LI, Haitian
LI, Bin
REN, Meiyu
LI, Zhenqing
CHEN, Yuzhen
ZHENG, Zhizhong
MENG, Yuqi
FENG, Haiming
author_facet LIU, Qing
LI, Haitian
LI, Bin
REN, Meiyu
LI, Zhenqing
CHEN, Yuzhen
ZHENG, Zhizhong
MENG, Yuqi
FENG, Haiming
author_sort LIU, Qing
collection PubMed
description Background and objective Lung cancer is the leading cause of cancer-related death worldwide, and patients have limited survival benefits from traditional treatments such as surgery, radiotherapy and chemotherapy. As a new treatment for lung cancer, immunotherapy has significantly prolonged the overall survival (OS) of patients. However, only some patients can benefit from it. We need to explore immunotherapy biomarkers more deeply to screen for advantages. Methods The original data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, and the immunological and prognostic genes of lung squamous cell carcinoma (LUSC) were screened using R software and TIMER database. The expression of target genes was studied in TCGA and GEO databases, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and correlation analysis with tumor immune characteristics were performed by R software and TISIDB database. Results We screened out a gene related to immunity and prognosis, cAMP dependent protein kinase inhibitor γ (PKIG), which is significantly differentially expressed in LUSC and normal tissues, and has important reference value for the diagnosis and prognosis assessment of LUSC. PKIG differential genes are mainly concentrated in the regulation of humoral immune response and other processes. The expression of PKIG was positively correlated with the infiltration level of regulatory T cells (Tregs) (r=0.340, P<0.001). In addition, the expression level of PKIG was positively correlated with the expression of chemokines/chemokine receptors such as chemokine C-C motif ligand 2 (CCL2) (r=0.503, P<0.001), CXC chemokine ligand 12 (CXCL12) (r=0.386, P<0.001) and CXC-chemokine receptor 4 (CXCR4) (r=0.492, P<0.001), and immunoinhibitors such as programmed cell death protein 1 (PDCD1) (r=0.359,P<0.001), cytotoxic T-lymphocyte associated antigen 4 (CTLA4) (r=0.375, P<0.001) and T cell immunoglobulin and ITIM domains (TIGIT) (r=0.305, P<0.001) in LUSC. Conclusion The immunological and prognostic gene PKIG in lung squamous cell carcinoma was screened through bioinformatics analysis. PKIG is highly correlated with LUSC prognosis and immune microenvironment, and is expected to be a potential biomolecular marker for LUSC immunotherapy.
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spelling pubmed-104762072023-09-05 基于生物信息学数据探究PKIG与肺鳞癌的相关性及其在肿瘤微环境中的作用 LIU, Qing LI, Haitian LI, Bin REN, Meiyu LI, Zhenqing CHEN, Yuzhen ZHENG, Zhizhong MENG, Yuqi FENG, Haiming Zhongguo Fei Ai Za Zhi Clinical Research Background and objective Lung cancer is the leading cause of cancer-related death worldwide, and patients have limited survival benefits from traditional treatments such as surgery, radiotherapy and chemotherapy. As a new treatment for lung cancer, immunotherapy has significantly prolonged the overall survival (OS) of patients. However, only some patients can benefit from it. We need to explore immunotherapy biomarkers more deeply to screen for advantages. Methods The original data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, and the immunological and prognostic genes of lung squamous cell carcinoma (LUSC) were screened using R software and TIMER database. The expression of target genes was studied in TCGA and GEO databases, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and correlation analysis with tumor immune characteristics were performed by R software and TISIDB database. Results We screened out a gene related to immunity and prognosis, cAMP dependent protein kinase inhibitor γ (PKIG), which is significantly differentially expressed in LUSC and normal tissues, and has important reference value for the diagnosis and prognosis assessment of LUSC. PKIG differential genes are mainly concentrated in the regulation of humoral immune response and other processes. The expression of PKIG was positively correlated with the infiltration level of regulatory T cells (Tregs) (r=0.340, P<0.001). In addition, the expression level of PKIG was positively correlated with the expression of chemokines/chemokine receptors such as chemokine C-C motif ligand 2 (CCL2) (r=0.503, P<0.001), CXC chemokine ligand 12 (CXCL12) (r=0.386, P<0.001) and CXC-chemokine receptor 4 (CXCR4) (r=0.492, P<0.001), and immunoinhibitors such as programmed cell death protein 1 (PDCD1) (r=0.359,P<0.001), cytotoxic T-lymphocyte associated antigen 4 (CTLA4) (r=0.375, P<0.001) and T cell immunoglobulin and ITIM domains (TIGIT) (r=0.305, P<0.001) in LUSC. Conclusion The immunological and prognostic gene PKIG in lung squamous cell carcinoma was screened through bioinformatics analysis. PKIG is highly correlated with LUSC prognosis and immune microenvironment, and is expected to be a potential biomolecular marker for LUSC immunotherapy. Editorial board of Chinese Journal of Lung Cancer 2023-07-20 /pmc/articles/PMC10476207/ /pubmed/37653016 http://dx.doi.org/10.3779/j.issn.1009-3419.2023.102.24 Text en 版权所有 © 2023《中国肺癌杂志》编辑部 https://creativecommons.org/licenses/by/3.0/This is an open access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 3.0) License. See: https://creativecommons.org/licenses/by/3.0/.
spellingShingle Clinical Research
LIU, Qing
LI, Haitian
LI, Bin
REN, Meiyu
LI, Zhenqing
CHEN, Yuzhen
ZHENG, Zhizhong
MENG, Yuqi
FENG, Haiming
基于生物信息学数据探究PKIG与肺鳞癌的相关性及其在肿瘤微环境中的作用
title 基于生物信息学数据探究PKIG与肺鳞癌的相关性及其在肿瘤微环境中的作用
title_full 基于生物信息学数据探究PKIG与肺鳞癌的相关性及其在肿瘤微环境中的作用
title_fullStr 基于生物信息学数据探究PKIG与肺鳞癌的相关性及其在肿瘤微环境中的作用
title_full_unstemmed 基于生物信息学数据探究PKIG与肺鳞癌的相关性及其在肿瘤微环境中的作用
title_short 基于生物信息学数据探究PKIG与肺鳞癌的相关性及其在肿瘤微环境中的作用
title_sort 基于生物信息学数据探究pkig与肺鳞癌的相关性及其在肿瘤微环境中的作用
topic Clinical Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10476207/
https://www.ncbi.nlm.nih.gov/pubmed/37653016
http://dx.doi.org/10.3779/j.issn.1009-3419.2023.102.24
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