ArticleAnnals of translational medicine2022
Identification of ATP1B1, a key copy number driver gene in diffuse large B-cell lymphoma and potential target for drugs.
Article in Annals of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 7 citations in OpenAlex.
- A palmitoylation-related signature predicts prognosis and immune microenvironment features in diffuse large B-cell lymphoma.Frontiers in immunology · 2026Article
- Systems pharmacology approaches decipher the anti-cancer efficacy of ethnopharmacological agents in hepatocellular carcinoma.Scientific reports · 2025Article
- Single-cell and spatial transcriptomics reveal a high glycolysis B cell and tumor-associated macrophages cluster correlated with poor prognosis and exhausted immune microenvironment in diffuse large B-cell lymphoma.Biomarker research · 2024Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Copy number variations (CNVs) participate in the development and progression of cancer by altering the expression levels of genes. However, it is unclear whether this correlation exists in diffuse large B-cell lymphoma (DLBCL). Methods: Differentially expressed genes (DEGs) were identified from the GSE25638 and GSE56315 datasets. Modules that were highly related to DLBCL prognosis were obtained by Weighted Gene Co-expression Network Analysis (WGCNA). We performed an integrated analysis between CNV and differential gene expression in The Cancer Genome Atlas (TCGA) DLBCL. The DEGs were then overlapped with the module genes and expression-copy number variations-related (Exp-CNV-related) genes to obtain the common key genes. Time-dependent receiver operating characteristic (ROC) analysis was utilized to evaluate the accuracy of the key gene in predicting the prognosis of DLBCL. Next, we conducted a Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to explore the key gene. The potential molecule drugs of the key gene were identified by Connectivity Map (Cmap) analysis. Results: A turquoise module with 160 genes was identified as the signature module. ATP1B1 is overexpressed in DLBCL cell lines, compared to Cluster of Differentiation 19+B (CD19+B) cells. The ROC curve indicated that ATP1B1 could be a biomarker for diagnosing DLBCL, and the forest map suggested that Conclusions: ATP1B1 is a copy number driver gene that could potentially be adopted as a diagnostic biomarker and therapeutic target of DLBCL.
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