ArticleJournal of thoracic disease2021
DNA repair genes are associated with tumor tissue differentiation and immune environment in lung adenocarcinoma: a bioinformatics analysis based on big data.
Article in Journal of thoracic disease, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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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Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- Transcriptome‑wide excavation and expression pattern analysis of the NAC transcription factors in methyl jasmonate- and sodium chloride-induced Glycyrrhiza uralensis.Scientific reports · 2025Article
- Association between cancer stem cell gene expression signatures and prognosis in head and neck squamous cell carcinoma.BMC cancer · 2022Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLung adenocarcinoma (LUAD) is the most common type of lung cancer. DNA repair genes (DRGs) is important in lung cancer. The relationship between the immune environment and the expression levels of DRGs in LUAD remains unclear. The purpose of this study is to assess the relationship between DRGs and the immune environment and clinical characteristics of LUAD.
methodsData of 169 LUAD cases were obtained from cbioportal. The RNA-seq data came from the The Cancer Genome Atlas (TCGA) database. We collected DRGs from the Reactom database (KW0037, Reactom.org). The 302 genes expressed in each sample were analyzed by hierarchical clustering and grouped using the Gene Cluster 3.0 program. The Java Treeview program was used to generate heat maps of cluster indications and tumor staging patterns. GraphPad Prism 8 was used to draw survival curves and compare overall survival (OS). For single genes, an OS difference analysis between low and high expression populations was performed in GraphPad Prism 8.
resultsMatrix clustering showed no difference in the prognosis of the two clusters. The comparison of subgroups showed that Subcluster 1 (SC1) had the best prognosis, and Subcluster 2 (SC2) had the worst. There was a significant difference in tumor grades between Cluster 1 and Cluster 2 (P=0.01). There were significant differences in smoking status, histological grade and adenocarcinoma subtype among subgroups. In Subcluster 3 (SC3), the proportion of poorly differentiated cases was highest. Immunological index analysis showed that there were significant differences between Cluster 1 and Cluster 2 in interferon, macrophages, monocytes, neutrophils, natural killer (NK) cells, and T cells. Tumor purity, interferon, macrophages, monocytes, neutrophils, NK cells, T cells, translation, and proliferation all showed significant differences between subgroups. In SC2, the proliferation index increased (0.082
conclusionsThe differences of DRGs in LUAD are related to tissue differentiation and immune indicators but not to prognosis.
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