ArticleAging2023
Comprehensive analysis of the role of a four-gene signature based on EMT in the prognosis, immunity, and treatment of lung squamous cell carcinoma.
Article in Aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Machine learning-based prognostic model of stemness and angiogenesis-related genes for predicting prognosis and immune infiltration in patients with HCC.Scientific reports · 2026Article
- A Novel Partial EMT-Associated Transcriptomic Signature for Prognostic Stratification in Ovarian Cancer.Oncology research · 2026Article
- Metabolic syndrome-related gene signature for prognosis and immune microenvironment prediction in hepatocellular carcinoma.Scientific reports · 2025Article
- Interpretable and integrative analysis of single-cell multiomics with scMKL.Communications biology · 2025Article
- Metastasis and basement membrane-related signature enhances hepatocellular carcinoma prognosis and diagnosis by integrating single-cell RNA sequencing analysis and immune microenvironment assessment.Journal of translational medicine · 2024Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Epithelial-mesenchymal transition (EMT), a biological process through which epithelial cells transform into mesenchymal cells, contributes to tumor progression and metastasis. However, a comprehensive analysis of the role of EMT-related genes in Lung squamous cell carcinoma (LUSC) is still lacking. In this study, data were downloaded from available databases, including The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. The association between differentially expressed EMT-related genes (EMT-RDGs) and LUSC prognosis, drug sensitivity, mutation, and immunity was analyzed using bioinformatics methods. In the results, Lasso and univariate Cox regression analyses identified four EMT-RDGs that were differentially expressed, and used to establish a prognostic model capable of distinguishing between high- and low-risk groups. Then, prognostic factors were identified by multivariate Cox regression analysis and used to construct a nomogram. The high-risk group had a significantly poorer prognosis than the low-risk group. The tumor immune environment was significantly different between the two groups, with the low-risk group exhibiting a better response to immunotherapy. In addition, the half-maximal inhibitory concentration prediction indicating that the constructed model could effectively predict sensitivity to chemotherapy. This study provides new reference for further exploration of new clinical therapeutic strategies for LUSC.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.