ArticleScientific reports2025
Signature of leukemia stem cell death pattern predicts prognosis and therapeutic response of acute myeloid leukemia patients.
Article in Scientific reports, 2025. 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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Who cites it
3 citing papers in PubMed.
- The LSC17 score: a prognostic biomarker now validated for real-world clinical application in acute myeloid leukemia.Haematologica · 2026Article
- Decoding the archipelago: single-cell biomarkers rechart the molecular geography of acute myeloid leukemia.Cell communication and signaling : CCS · 2026Review
- Numerical simulations and experimental analysis of high-speed turnout rails wear models.Scientific reports · 2025Article
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Authors and funding
6 authors.
Funding
Abstract
Acute Myeloid Leukemia (AML) is a highly heterogeneous malignant hematologic cancer with poor clinical outcome. The presence of leukemia stem cells (LSC) is a significant factor contributing to the failure of AML treatments and frequent relapses. The quiescent and plastic nature of LSC decreases cell death under conventional chemotherapy. Programmed cell death (PCD) plays a critical role in the development and progression of various cancers including AML. We hypothesized that the expression of PCD gene in LSCs may predict the therapeutic outcome of AML patients in the clinic. In this study, we comprehensively analyzed the expression of PCD gene and identified the unique expression patterns of cell death genes of LSC. By integrating PCD- and LSC-related genes, we identified eight LSC death genes with prognostic values: OAZ1, S100A4, MPG, IL2RA, MMRN1, CDK6, HOXA9, and XIRP2. Based on these genes, we developed a leukemia stem cell prognostic death score (LSCD) and a prognostic nomogram. Our findings revealed that LSC, particularly Quiescent LSPC, exhibits a high LSCD score. AML patients with high LSCD score group showed characteristics of significant immune dysfunction and worse prognosis. Additionally, predictions regarding FDA-approved drugs indicated that the high LSCD score group is less sensitive to Venetoclax but more sensitive to Crenolanib, Tandutinib, or Midostaurin. In summary, we developed an LSCD model that shows the predictive potential of clinical prognosis and drug sensitivity. This model provides meaningful insights for personalized treatment of AML patients.
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