ArticlePeerJ2023
Identification of CDT1 as a prognostic marker in human lung adenocarcinoma using bioinformatics approaches.
Article in PeerJ, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 5 citations in OpenAlex.
- Prognostic and immunotherapeutic implications of histamine-related biomarkers in lung adenocarcinoma.PeerJ · 2026Article
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- RNA analysis of patients with benign and malignant pulmonary nodules.Oncology letters · 2025Article
- Identification of KRT80 as a Novel Prognostic and Predictive Biomarker of Human Lung Adenocarcinoma via Bioinformatics Approaches.Combinatorial chemistry & high throughput screening · 2025Article
- MEF2C is a Potential Prognostic Biomarker and is Correlated with Immune Infiltrates in Lung Adenocarcinoma.Current medicinal chemistry · 2025Article
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Authors and funding
13 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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