ArticleFrontiers in immunology2024
Single-cell transcriptomics reveals heterogeneity and prognostic markers of myeloid precursor cells in acute myeloid leukemia.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- SPINK2 silencing suppresses leukemic proliferation and restores myeloid commitment via MECOM downregulation in acute myeloid leukaemia.Cell death discovery · 2026Article
- Glutaredoxin 2 is essential for AML survival through mitochondrial permeability transition pore regulation.Blood · 2026Article
- Decoding the archipelago: single-cell biomarkers rechart the molecular geography of acute myeloid leukemia.Cell communication and signaling : CCS · 2026Review
- DUSP5 contributes to platinum resistance in ovarian cancer: single-cell discovery and functional validation.Frontiers in pharmacology · 2026Article
- SLPI is associated with AR-regulated epithelial adaptation and enzalutamide sensitivity in castration-resistant prostate cancer.Frontiers in pharmacology · 2026Article
- Defining the role of natural killer cells in acute myeloid leukemia through the lens of single-cell omics.Frontiers in immunology · 2026Review
- UBE2S emerges as a key driver in an NK cell-based prognostic model for clear cell renal cell carcinoma.PloS one · 2026Article
- Charting the growth of programmed cell death studies in uveal melanoma: a bibliometric evidence.Discover oncology · 2025Article
- The Key Role of COA6 in Pancreatic Ductal Adenocarcinoma: Metabolic Reprogramming and Regulation of the Immune Microenvironment.Journal of cellular and molecular medicine · 2025Article
- Global research trends on Chinese patent drugs inducing programmed cell death in cancer: a bibliometric analysis (1998-2024).Discover oncology · 2025Article
- Unraveling the significance of cuproptosis in hepatocellular carcinoma heterogeneity and tumor microenvironment through integrated single-cell sequencing and machine learning approaches.Discover oncology · 2025Article
- Exploring novel biomarkers and immunotherapeutic targets for biofeedback therapies to reveal the tumor-associated immune microenvironment through a multimetric analysis of kidney renal clear cell carcinoma.Discover oncology · 2025Article
- Multi-omics characterization of RNF157 expression patterns in hepatocellular carcinoma and development of an RNF157-associated prognostic signature.Frontiers in pharmacology · 2025Article
- Joint exposure to PMFrontiers in public health · 2025Article
- Revolutionizing cervical cancer treatment: single-cell sequencing ofFrontiers in immunology · 2025Article
- Integrating multi-omics and experimental techniques to decode ubiquitinated protein modifications in hepatocellular carcinoma.Frontiers in pharmacology · 2025Article
- Single-cell technologies and spatial transcriptomics: decoding immune low - response states in endometrial cancer.Frontiers in immunology · 2025Review
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Acute myeloid leukemia (AML) is a hematologic tumor with poor prognosis and significant clinical heterogeneity. By integrating transcriptomic data, single-cell RNA sequencing data and independently collected RNA sequencing data this study aims to identify key genes in AML and establish a prognostic assessment model to improve the accuracy of prognostic prediction. Materials and methods: We analyzed RNA-seq data from AML patients and combined it with single-cell RNA sequencing data to identify genes associated with AML prognosis. Key genes were screened by bioinformatics methods, and a prognostic assessment model was established based on these genes to validate their accuracy. Results: The study identified eight key genes significantly associated with AML prognosis: SPATS2L, SPINK2, AREG, CLEC11A, HGF, IRF8, ARHGAP5, and CD34. The prognostic model constructed on the basis of these genes effectively differentiated between high-risk and low-risk patients and revealed differences in immune function and metabolic pathways of AML cells. Conclusion: This study provides a new approach to AML prognostic assessment and reveals the role of key genes in AML. These genes may become new biomarkers and therapeutic targets that can help improve prognostic prediction and personalized treatment of AML.
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