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Identification of CDT1 as a prognostic marker in human lung adenocarcinoma using bioinformatics approaches
BACKGROUND: Lung cancer has the highest cancer-related mortality worldwide. Lung adenocarcinoma (LUAD) is the most common histological subtype of non-small cell lung cancer (NSCLC). Chromatin licensing and DNA replication factor 1 (CDT1), a key regulator of cell cycle control and replication in euka...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10542661/ https://www.ncbi.nlm.nih.gov/pubmed/37790630 http://dx.doi.org/10.7717/peerj.16166 |
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author | Jiang, Jing Zhang, Yu Wang, Jun Yang, Xuefei Ren, Xingchang Huang, Hai Wang, Jue Lu, Jinhua Zhong, Yazhen Lin, Zechen Lin, Xianlei Jia, Yewei Lin, Shengyou |
author_facet | Jiang, Jing Zhang, Yu Wang, Jun Yang, Xuefei Ren, Xingchang Huang, Hai Wang, Jue Lu, Jinhua Zhong, Yazhen Lin, Zechen Lin, Xianlei Jia, Yewei Lin, Shengyou |
author_sort | Jiang, Jing |
collection | PubMed |
description | BACKGROUND: Lung cancer has the highest cancer-related mortality worldwide. Lung adenocarcinoma (LUAD) is the most common histological subtype of non-small cell lung cancer (NSCLC). Chromatin licensing and DNA replication factor 1 (CDT1), a key regulator of cell cycle control and replication in eukaryotic cells, has been implicated in various cancer-related processes. Given its significant role in cancer, the focus on CDT1 in this study is justified as it holds promise as a potential biomarker or therapeutic target for cancer treatment. However, its prognostic value in lung adenocarcinoma (LUAD) remains unclear. METHODS: Bioinformatics analysis was conducted using data obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were utilized to predict biological processes and signaling pathways, respectively. The LinkedOmics database was employed to identify differentially expressed genes (DEGs) associated with CDT1. Nomograms and Kaplan-Meier plots were generated to assess the survival rates of patients with lung adenocarcinoma (LUAD). To determine the RNA and protein expression levels of CDT1 in LUAD and adjacent normal tissues, quantitative polymerase chain reaction (qPCR) and immunohistochemistry techniques were employed, respectively. RESULTS: CDT1 was upregulated in the vast majority of cancer tissues, based on pan-cancer analysis in TCGA and GEO datasets, as to lung cancer, the level of CDT1 expression was much higher in LUAD tissue than in healthy lung tissue. Our clinical data supported these findings. In our study, we used a specific cutoff value to dichotomize the patient samples into high and low CDT1 expression groups. The Kaplan–Meier survival curve revealed poor survival rates in CDT1 high expression group than the low expression group. To determine if CDT1 expression was an independent risk factor in LUAD patients, univariate and multivariate Cox regression analyses were performed. The result showed that CDT1 was a potential novel prognosis factor for LUAD patients, whose prognosis was poorer when CDT1 expression was higher. Based on functional enrichment analysis, highly expressed DEGs of CDT1-high patients were predicted to be involved in the cell cycle. According to our analysis of immune infiltration, CDT1 exhibited a strong correlation with specific immune cell subsets and was found to be a significant predictor of poor survival in patients with LUAD. CONCLUSIONS: Our research found that CDT1 was upregulated in LUAD and that high CDT1 expression predicted poor prognosis. We comprehensively and systematically analyzed the expression level in the datasets as well as in our own clinical samples, we also evaluated the prognostic and diagnostic value of CDT1, and finally, the potential mechanisms of CDT1 in the progression of LUAD. These results suggested that CDT1 may be a prognostic marker and therapeutic target for LUAD. |
format | Online Article Text |
id | pubmed-10542661 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-105426612023-10-03 Identification of CDT1 as a prognostic marker in human lung adenocarcinoma using bioinformatics approaches Jiang, Jing Zhang, Yu Wang, Jun Yang, Xuefei Ren, Xingchang Huang, Hai Wang, Jue Lu, Jinhua Zhong, Yazhen Lin, Zechen Lin, Xianlei Jia, Yewei Lin, Shengyou PeerJ Bioinformatics BACKGROUND: Lung cancer has the highest cancer-related mortality worldwide. Lung adenocarcinoma (LUAD) is the most common histological subtype of non-small cell lung cancer (NSCLC). Chromatin licensing and DNA replication factor 1 (CDT1), a key regulator of cell cycle control and replication in eukaryotic cells, has been implicated in various cancer-related processes. Given its significant role in cancer, the focus on CDT1 in this study is justified as it holds promise as a potential biomarker or therapeutic target for cancer treatment. However, its prognostic value in lung adenocarcinoma (LUAD) remains unclear. METHODS: Bioinformatics analysis was conducted using data obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were utilized to predict biological processes and signaling pathways, respectively. The LinkedOmics database was employed to identify differentially expressed genes (DEGs) associated with CDT1. Nomograms and Kaplan-Meier plots were generated to assess the survival rates of patients with lung adenocarcinoma (LUAD). To determine the RNA and protein expression levels of CDT1 in LUAD and adjacent normal tissues, quantitative polymerase chain reaction (qPCR) and immunohistochemistry techniques were employed, respectively. RESULTS: CDT1 was upregulated in the vast majority of cancer tissues, based on pan-cancer analysis in TCGA and GEO datasets, as to lung cancer, the level of CDT1 expression was much higher in LUAD tissue than in healthy lung tissue. Our clinical data supported these findings. In our study, we used a specific cutoff value to dichotomize the patient samples into high and low CDT1 expression groups. The Kaplan–Meier survival curve revealed poor survival rates in CDT1 high expression group than the low expression group. To determine if CDT1 expression was an independent risk factor in LUAD patients, univariate and multivariate Cox regression analyses were performed. The result showed that CDT1 was a potential novel prognosis factor for LUAD patients, whose prognosis was poorer when CDT1 expression was higher. Based on functional enrichment analysis, highly expressed DEGs of CDT1-high patients were predicted to be involved in the cell cycle. According to our analysis of immune infiltration, CDT1 exhibited a strong correlation with specific immune cell subsets and was found to be a significant predictor of poor survival in patients with LUAD. CONCLUSIONS: Our research found that CDT1 was upregulated in LUAD and that high CDT1 expression predicted poor prognosis. We comprehensively and systematically analyzed the expression level in the datasets as well as in our own clinical samples, we also evaluated the prognostic and diagnostic value of CDT1, and finally, the potential mechanisms of CDT1 in the progression of LUAD. These results suggested that CDT1 may be a prognostic marker and therapeutic target for LUAD. PeerJ Inc. 2023-09-28 /pmc/articles/PMC10542661/ /pubmed/37790630 http://dx.doi.org/10.7717/peerj.16166 Text en © 2023 Jiang 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 Jiang, Jing Zhang, Yu Wang, Jun Yang, Xuefei Ren, Xingchang Huang, Hai Wang, Jue Lu, Jinhua Zhong, Yazhen Lin, Zechen Lin, Xianlei Jia, Yewei Lin, Shengyou Identification of CDT1 as a prognostic marker in human lung adenocarcinoma using bioinformatics approaches |
title | Identification of CDT1 as a prognostic marker in human lung adenocarcinoma using bioinformatics approaches |
title_full | Identification of CDT1 as a prognostic marker in human lung adenocarcinoma using bioinformatics approaches |
title_fullStr | Identification of CDT1 as a prognostic marker in human lung adenocarcinoma using bioinformatics approaches |
title_full_unstemmed | Identification of CDT1 as a prognostic marker in human lung adenocarcinoma using bioinformatics approaches |
title_short | Identification of CDT1 as a prognostic marker in human lung adenocarcinoma using bioinformatics approaches |
title_sort | identification of cdt1 as a prognostic marker in human lung adenocarcinoma using bioinformatics approaches |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10542661/ https://www.ncbi.nlm.nih.gov/pubmed/37790630 http://dx.doi.org/10.7717/peerj.16166 |
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