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Identification of P2RY13 as an immune-related prognostic biomarker in lung adenocarcinoma: A public database-based retrospective study

BACKGROUND: Lung adenocarcinoma (LUAD) is the leading histological subtype of non-small cell lung cancer (NSCLC). METHODS: In the present study, the gene matrixes of LUAD were downloaded from The Cancer Genome Atlas to infer immune and stromal scores with the ‘Estimation of Stromal and Immune cells...

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Autores principales: Lin, Jiang, Wu, Chunlei, Ma, Dehua, Hu, Quanteng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8106393/
https://www.ncbi.nlm.nih.gov/pubmed/33996281
http://dx.doi.org/10.7717/peerj.11319
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author Lin, Jiang
Wu, Chunlei
Ma, Dehua
Hu, Quanteng
author_facet Lin, Jiang
Wu, Chunlei
Ma, Dehua
Hu, Quanteng
author_sort Lin, Jiang
collection PubMed
description BACKGROUND: Lung adenocarcinoma (LUAD) is the leading histological subtype of non-small cell lung cancer (NSCLC). METHODS: In the present study, the gene matrixes of LUAD were downloaded from The Cancer Genome Atlas to infer immune and stromal scores with the ‘Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data’ (ESTIMATE) algorithm and identified immune-related differentially expressed genes (DEGs) between the high- and low-stromal/immune score groups. Next, all DEGs were subjected to univariate Cox regression and survival analyses to screen out prognostic biomarkers in the tumor microenvironment (TME), and were validated in the Gene Expression Omnibus database. Single-sample gene set enrichment analysis (ssGSEA) was performed to assess the level of tumor-infiltrating immune cells (TIICs) and immune functions, and GSEA was used to identified pathways altered by prognostic biomarkers. RESULTS: Survival analysis showed that LUAD in the high-immune and stromal score group had a better clinical prognosis. A total of 303 immune-related DEGs were detected. Univariate Cox regression and survival analyses revealed that P2Y purinoceptor 13 (P2RY13) was a favorable factor for the prognosis of LUAD. ssGSEA and Spearman correlation analysis demonstrated that P2RY13 was highly correlated with various TIICs and immune functions. Several immune-associated pathways were enriched between the high- and low-expression P2RY13 groups. CONCLUSION: P2RY13 may be a potential prognostic indicator and is highly associated with the TME in LUAD. However, further experimental studies are required to validate the present findings.
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spelling pubmed-81063932021-05-13 Identification of P2RY13 as an immune-related prognostic biomarker in lung adenocarcinoma: A public database-based retrospective study Lin, Jiang Wu, Chunlei Ma, Dehua Hu, Quanteng PeerJ Bioinformatics BACKGROUND: Lung adenocarcinoma (LUAD) is the leading histological subtype of non-small cell lung cancer (NSCLC). METHODS: In the present study, the gene matrixes of LUAD were downloaded from The Cancer Genome Atlas to infer immune and stromal scores with the ‘Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data’ (ESTIMATE) algorithm and identified immune-related differentially expressed genes (DEGs) between the high- and low-stromal/immune score groups. Next, all DEGs were subjected to univariate Cox regression and survival analyses to screen out prognostic biomarkers in the tumor microenvironment (TME), and were validated in the Gene Expression Omnibus database. Single-sample gene set enrichment analysis (ssGSEA) was performed to assess the level of tumor-infiltrating immune cells (TIICs) and immune functions, and GSEA was used to identified pathways altered by prognostic biomarkers. RESULTS: Survival analysis showed that LUAD in the high-immune and stromal score group had a better clinical prognosis. A total of 303 immune-related DEGs were detected. Univariate Cox regression and survival analyses revealed that P2Y purinoceptor 13 (P2RY13) was a favorable factor for the prognosis of LUAD. ssGSEA and Spearman correlation analysis demonstrated that P2RY13 was highly correlated with various TIICs and immune functions. Several immune-associated pathways were enriched between the high- and low-expression P2RY13 groups. CONCLUSION: P2RY13 may be a potential prognostic indicator and is highly associated with the TME in LUAD. However, further experimental studies are required to validate the present findings. PeerJ Inc. 2021-05-05 /pmc/articles/PMC8106393/ /pubmed/33996281 http://dx.doi.org/10.7717/peerj.11319 Text en ©2021 Lin et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Lin, Jiang
Wu, Chunlei
Ma, Dehua
Hu, Quanteng
Identification of P2RY13 as an immune-related prognostic biomarker in lung adenocarcinoma: A public database-based retrospective study
title Identification of P2RY13 as an immune-related prognostic biomarker in lung adenocarcinoma: A public database-based retrospective study
title_full Identification of P2RY13 as an immune-related prognostic biomarker in lung adenocarcinoma: A public database-based retrospective study
title_fullStr Identification of P2RY13 as an immune-related prognostic biomarker in lung adenocarcinoma: A public database-based retrospective study
title_full_unstemmed Identification of P2RY13 as an immune-related prognostic biomarker in lung adenocarcinoma: A public database-based retrospective study
title_short Identification of P2RY13 as an immune-related prognostic biomarker in lung adenocarcinoma: A public database-based retrospective study
title_sort identification of p2ry13 as an immune-related prognostic biomarker in lung adenocarcinoma: a public database-based retrospective study
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8106393/
https://www.ncbi.nlm.nih.gov/pubmed/33996281
http://dx.doi.org/10.7717/peerj.11319
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