ArticleAnnals of hematology2024
Investigation of fatty acid metabolism in chronic lymphocytic leukemia to guide clinical outcome and therapy.
Article in Annals of hematology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Comparative safety of different first-line treatments for chronic lymphocytic leukemia/small lymphocytic lymphoma: A systematic review and network meta-analysis.Annals of hematology · 2025Pooled it
- Darunavir analog precursors target mitochondrial metabolism in multiple myeloma and CLL.Cancer cell international · 2025Article
- The microbiome-cancer axis as a hidden contributor to early-onset tumorigenesis.Medical oncology (Northwood, London, England) · 2025Review
- Cholesterol homeostasis and lipid raft dynamics at the basis of tumor-induced immune dysfunction in chronic lymphocytic leukemia.Cellular & molecular immunology · 2025Article
- Artificial intelligence assisted diagnosis of chronic lymphocytic leukemia in a historic pediatric case using large language models.Annals of hematology · 2024Article
- Research progress of additional pathogenic mutations in chronic neutrophilic leukemia.Annals of hematology · 2024Review
Corrections and comments
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Authors and funding
13 authors at 2 institutions in 1 country.
Funding
Abstract
Chronic lymphocytic leukemia (CLL) is the most common leukemia in the West. With CLL's heterogeneity, some people still develop disease refractory and relapse despite advances in treatment. Thus, early diagnosis and treatment of high-risk CLL patients is critical. Fatty acid (FA) metabolism contributes to tumorigenesis, progression, and therapy resistance through enhanced lipid synthesis, storage, and catabolism. In this study, we aimed to construct a prognostic model to improve the risk stratification of CLL and reveal the link between FA metabolism and CLL. The differentially expressed FA metabolism-related genes (FMGs) in CLL were filtered through univariate Cox regression analysis based on public databases. Functional enrichment was examined using prognostic FA metabolism-related gene enrichment analysis. CIBERSORT and single-sample gene set enrichment analysis (ssGSEA) estimated immune infiltration score and immune-related pathways. Pearson's correlation analysis investigated FA metabolism-related genes and drug sensitivity. A novel prognostic model was built using least absolute shrinkage and selection operator (LASSO) Cox algorithms. This validation cohort included 36 CLL patients from our center. We obtained CLL RNA microarray profiles from public databases and identified 15 prognostic-related FMGs. CLL patients were divided into two molecular clusters based on the expression of FMGs. The Kaplan-Meier analysis revealed a significant difference in TFS (P < 0.001) and OS (P < 0.001) between the two clusters. KEGG functional analysis showed that several pathways were enriched, including the chemokine and immune-related signaling pathways. In the training and validation cohorts, patients with higher FA metabolism-related prognostic index (FAPI) levels had worse outcomes. Finally, a novel nomogram prognostic model including CLL international prognostic index (CLL-IPI) was constructed, exhibiting reliable effectiveness and accuracy. In conclusion, we established a reliable predictive signature based on FA metabolism-related genes and constructed a novel nomogram prognostic model, supporting the potential preclinical implications of FA metabolism in CLL research.
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