ArticleTranslational cancer research2023
Identifying a prognostic model and screening of potential natural compounds for acute myeloid leukemia.
Article in Translational cancer research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 6 citations in OpenAlex.
- Profiling Ten RHO GTPases in Myeloid Malignancies Reveals Distinct Expression Patterns and Prognostic Associations.Cancer medicine · 2026Article
- Konjac petroleum ether extract inhibits triple-negative breast cancer cell migration and invasion by attenuatingFrontiers in pharmacology · 2026Article
- CSRP1 is a potential therapeutic targets for DLBCL: A computational analysis and in vitro experiments.Clinical and experimental medicine · 2025Article
- RHOBTB2 enhances cell proliferation of acute myeloid leukemia by modulating Hippo-YAP1 signaling and dependent of KLHL13.Scientific reports · 2025Article
- CSRP1 gene: a potential novel prognostic marker in acute myeloid leukemia with implications for immune response.Discover oncology · 2024Article
- Data mining in acute myeloid leukemia: identification of disease biomarkers, prognostic factors, novel targets, and potential drugs.Translational cancer research · 2023Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Acute myeloid leukemia (AML) is one of the most common hematologic malignancies with a poor prognosis and high recurrence rate. The discovery of new predictive models and therapeutic agents plays a crucial role. Methods: The differentially expressed gene that was explicitly highly expressed in The Cancer Genome Atlas (TCGA) and GSE9476 transcriptome databases were screened and included in the least absolute shrinkage and selection operator (LASSO) regression model to derive risk coefficients and build a risk score model. Functional enrichment analysis was conducted on the screened hub genes to explore the potential mechanisms. Subsequently, critical genes were incorporated into a nomogram model based on risk scores to analyze prognostic value. Finally, this study combined network pharmacology to find potential natural compounds for hub genes and used molecular docking to verify the binding ability of molecular structures to natural compounds to explore drug development for possible efficacy in AML. Results: A total of 33 highly expressed genes may be associated with poor prognosis of AML patients. After LASSO and multivariate Cox regression analysis of 33 critical genes, Rho-related BTB domain containing 2 ( Conclusions: The predictive model of
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.