ArticleScientific reports2024
Disulfidptosis-related lncRNA signature to assess the immune microenvironment and drug sensitivity in acute myeloid leukemia.
Article in Scientific reports, 2024. 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.
- Epigenetics and In Silico Transcriptome Analysis of Pediatric Acute Myeloid Leukemia.European journal of haematology · 2026Review
- Article
- Development of a senescence-related lncRNA signature in endometrial cancer based on multiple machine learning models.Frontiers in genetics · 2025Article
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7 authors.
Funding
Abstract
Acute myeloid leukemia (AML) represents a hematological malignancy that arises from the abnormal proliferation of progenitor cells or myeloid hematopoietic stem. The current standard treatments for AML include chemotherapy and hematopoietic stem cell transplantation. However, chemotherapy suffers from high toxicity and a shortage of hematopoietic stem cell donors, which significantly shortens patient survival. A new type of cell death, disulfidptosis, has shown potential in medicine. However, its specific biological mechanism of action in AML is currently unclear. This research developed a prognostic model of disulfidptosis-related long non-coding RNAs (DRLs) based on 132 AML patients with GDC TCGA Acute myeloid leukemia (LAML). In this model, eight DRLs: AL049835.1, EXOC3-AS1, AC009237.14, LINC00944, AP002761.4, LINC00926, AC010247.2, and AC099811.5 were included. Patients with high-risk AML evaluated based on the model had shorter survival, significant infiltration of monocytes and M2 macrophages, and elevated transcriptional levels of immune checkpoint genes. In addition, AML was classified into three subtypes according to the model, and patients in different subtypes showed different overall survival (OS) and drug sensitivity. Overall, we formulated a pioneering prognostic model utilizing DRLs, achieving precise AML outcome predictions. The correlations between the DRL prognostic models and the AML immune microenvironment, drug sensitivity, and tumor subtype were explored. In addition, further studies on the molecular mechanisms of key biomarkers, such as LINC00944 and LINC00926, will greatly contribute to our understanding of AML pathogenesis and drug resistance mechanisms in the future.
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