ArticleFrontiers in genetics2020
Increased NFATC4 Correlates With Poor Prognosis of AML Through Recruiting Regulatory T Cells.
Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 13 citations in OpenAlex.
- Integrative single-cell and spatial transcriptomic analysis reveals a lactate-driven crosstalk between NFATc4⁺ tumor cells and SPP1⁺ macrophages in glioblastoma.Journal of translational medicine · 2026Article
- Nuclear Factor of Activated T Cells (NFAT) Proteins as Targeted Molecules in Diseases: A Narrative Review.Cureus · 2024Review
- Review
- The Role of Epithelial-to-Mesenchymal Transition Transcription Factors (EMT-TFs) in Acute Myeloid Leukemia Progression.Biomedicines · 2024Review
- Identification and validation of a prognostic model based on immune-related genes in ovarian carcinoma.PeerJ · 2024Article
- Enhanced annotation of CD45RA to distinguish T cell subsets in single-cell RNA-seq via machine learning.Bioinformatics advances · 2023Article
- Twist1 Promoter Methylation Regulates the Proliferation and Apoptosis of Acute Myeloid Leukemia Cells via PI3K/AKT Pathway.Indian journal of hematology & blood transfusion : an official journal of Indian Society of Hematology and Blood Transfusion · 2023Article
- A novel immune-related gene signature correlated with serum IL33 expression in acute myeloid leukemia prognosis.American journal of translational research · 2023Article
- Recent knowledge of NFATc4 in oncogenesis and cancer prognosis.Cancer cell international · 2022Review
- N6-Methyladenosine-Related lncRNAs Are Novel Prognostic Markers and Predict the Immune Landscape in Acute Myeloid Leukemia.Frontiers in genetics · 2022Article
- A Novel Prognostic Model for Acute Myeloid Leukemia Based on Gene Set Variation Analysis.Journal of oncology · 2022Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite that immune responses play important roles in acute myeloid leukemia (AML), immunotherapy is still not widely used in AML due to lack of an ideal target. Therefore, we identified key immune genes and cellular components in AML by an integrated bioinformatics analysis, trying to find potential targets for AML. Eighty-six differentially expressed immune genes (DEIGs) were identified from 751 differentially expressed genes (DEGs) between AML patients with fair prognosis and poor prognosis from the TCGA database. Among them, nine prognostic immune genes, including NCR2, NPDC1, KIR2DL4, KLC3, TWIST1, SNORD3B-1, NFATC4, XCR1, and LEFTY1, were identified by univariate Cox regression analysis. A multivariable prediction model was established based on prognostic immune genes. Kaplan-Meier survival curve analysis indicated that patients in the high-risk group had a shorter survival rate and higher mortality than those in the low-risk group (
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