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Construction and validation of a two-gene signature based on SUMOylation regulatory genes in non-small cell lung cancer patients

BACKGROUND: Post-translational modification plays an important role in the occurrence and development of various tumors. However, few researches were focusing on the SUMOylation regulatory genes as tumor biomarkers to predict the survival for specific patients. Here, we constructed and validated a t...

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Autores principales: Sheng, Hongxu, Hao, Zhexue, Zhu, Linhai, Zeng, Yuan, He, Jianxing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9125860/
https://www.ncbi.nlm.nih.gov/pubmed/35606717
http://dx.doi.org/10.1186/s12885-022-09575-4
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author Sheng, Hongxu
Hao, Zhexue
Zhu, Linhai
Zeng, Yuan
He, Jianxing
author_facet Sheng, Hongxu
Hao, Zhexue
Zhu, Linhai
Zeng, Yuan
He, Jianxing
author_sort Sheng, Hongxu
collection PubMed
description BACKGROUND: Post-translational modification plays an important role in the occurrence and development of various tumors. However, few researches were focusing on the SUMOylation regulatory genes as tumor biomarkers to predict the survival for specific patients. Here, we constructed and validated a two-gene signature to predict the overall survival (OS) of non-small cell lung cancer (NSCLC) patients. METHODS: The datasets analyzed in this study were downloaded from TCGA and GEO databases. The least absolute shrinkage and selection operator (LASSO) Cox regression was used to construct the two-gene signature. Gene set enrichment analysis (GSEA) and Gene Ontology (GO) was used to identify hub pathways associated with risk genes. The CCK-8 assay, cell cycle analysis, and transwell assay was used to validate the function of risk genes in NSCLC cell lines. RESULTS: Firstly, most of the SUMOylation regulatory genes were highly expressed in various tumors through the R package ‘limma’ in the TCGA database. Secondly, our study found that the two gene signature constructed by LASSO regression analysis, as an independent prognostic factor, could predict the OS in both the TCGA training cohort and GEO validation cohorts (GSE68465, GSE37745, and GSE30219). Furthermore, functional enrichment analysis suggests that high-risk patients defined by the risk score system were associated with the malignant phenomenon, such as DNA replication, cell cycle regulation, p53 signaling pathway. Finally, the results of the CCK-8 assay, cell cycle analysis, and transwell assay demonstrated that the two risk genes, SAE1 and UBA2, could promote proliferation and migration in non-small cell lung cancer cells. CONCLUSIONS: The two-gene signature constructed in our study could predict the OS and may provide valuable clinical guidance for the treatment of NSCLC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-09575-4.
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spelling pubmed-91258602022-05-24 Construction and validation of a two-gene signature based on SUMOylation regulatory genes in non-small cell lung cancer patients Sheng, Hongxu Hao, Zhexue Zhu, Linhai Zeng, Yuan He, Jianxing BMC Cancer Research BACKGROUND: Post-translational modification plays an important role in the occurrence and development of various tumors. However, few researches were focusing on the SUMOylation regulatory genes as tumor biomarkers to predict the survival for specific patients. Here, we constructed and validated a two-gene signature to predict the overall survival (OS) of non-small cell lung cancer (NSCLC) patients. METHODS: The datasets analyzed in this study were downloaded from TCGA and GEO databases. The least absolute shrinkage and selection operator (LASSO) Cox regression was used to construct the two-gene signature. Gene set enrichment analysis (GSEA) and Gene Ontology (GO) was used to identify hub pathways associated with risk genes. The CCK-8 assay, cell cycle analysis, and transwell assay was used to validate the function of risk genes in NSCLC cell lines. RESULTS: Firstly, most of the SUMOylation regulatory genes were highly expressed in various tumors through the R package ‘limma’ in the TCGA database. Secondly, our study found that the two gene signature constructed by LASSO regression analysis, as an independent prognostic factor, could predict the OS in both the TCGA training cohort and GEO validation cohorts (GSE68465, GSE37745, and GSE30219). Furthermore, functional enrichment analysis suggests that high-risk patients defined by the risk score system were associated with the malignant phenomenon, such as DNA replication, cell cycle regulation, p53 signaling pathway. Finally, the results of the CCK-8 assay, cell cycle analysis, and transwell assay demonstrated that the two risk genes, SAE1 and UBA2, could promote proliferation and migration in non-small cell lung cancer cells. CONCLUSIONS: The two-gene signature constructed in our study could predict the OS and may provide valuable clinical guidance for the treatment of NSCLC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-09575-4. BioMed Central 2022-05-23 /pmc/articles/PMC9125860/ /pubmed/35606717 http://dx.doi.org/10.1186/s12885-022-09575-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Sheng, Hongxu
Hao, Zhexue
Zhu, Linhai
Zeng, Yuan
He, Jianxing
Construction and validation of a two-gene signature based on SUMOylation regulatory genes in non-small cell lung cancer patients
title Construction and validation of a two-gene signature based on SUMOylation regulatory genes in non-small cell lung cancer patients
title_full Construction and validation of a two-gene signature based on SUMOylation regulatory genes in non-small cell lung cancer patients
title_fullStr Construction and validation of a two-gene signature based on SUMOylation regulatory genes in non-small cell lung cancer patients
title_full_unstemmed Construction and validation of a two-gene signature based on SUMOylation regulatory genes in non-small cell lung cancer patients
title_short Construction and validation of a two-gene signature based on SUMOylation regulatory genes in non-small cell lung cancer patients
title_sort construction and validation of a two-gene signature based on sumoylation regulatory genes in non-small cell lung cancer patients
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9125860/
https://www.ncbi.nlm.nih.gov/pubmed/35606717
http://dx.doi.org/10.1186/s12885-022-09575-4
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