ArticleAmerican journal of translational research2022
A six-gene prognostic signature for both adult and pediatric acute myeloid leukemia identified with machine learning.
Article in American journal of translational research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 5 citations in OpenAlex.
- A m6A/m1A/m5C-related eight-gene signature predicts prognosis and correlates with immune microenvironment in pediatric acute myeloid leukemia.Translational pediatrics · 2026Article
- Leveraging diverse liquid-liquid phase separation patterns to predict the prognosis and immunotherapy of pediatric acute myeloid leukemia.BMC cancer · 2025Article
- A Five-Gene Signature for the Prediction of Event-Free Survival of Both Pediatric and Adult Acute Myeloid Leukemia.Diagnostics (Basel, Switzerland) · 2025Article
- Identification and analysis of methylation signature genes and association with immune infiltration in pediatric acute myeloid leukemia.Journal of cancer research and clinical oncology · 2023Article
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2 authors at 2 institutions in 1 country.
Funding
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Abstract
backgroundAlthough it is well-known that adult and pediatric acute myeloid leukemias (AMLs) are genetically distinct diseases, they still share certain gene expression profiles. The age-related genetic heterogeneities of AMLs have been well-studied, but the common prognostic signatures and molecular mechanisms of adult and pediatric AMLs are less investigated.
aimTo identify genes and pathways that are associated with both pediatric and adult AMLs and discover a gene signature for overall survival (OS) prediction.
methodsThrough mining the transcriptome profiles of The Cancer Genome Atlas (TCGA) data sets of adult cancers and The Therapeutically Applicable Research to Generate Effective Treatments (TARGET) data of pediatric cancers, we identified genes that are commonly dysregulated in both pediatric and adult AMLs, further discovered a common gene signature, and built two risk score models for TCGA and TARGET cohorts, respectively with
resultsWe identified 57 genes that are differentially expressed and prognostically significant in both adult and childhood AMLs. The top 4 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enriched with those 57 genes include transcriptional misregulation, focal adhesion, PI3K-Akt signaling pathway, and signaling pathways regulating pluripotency of stem cells. We further identified a 6-gene signature including genes of ADAMTS3, DNMT3B, NYNRIN, SORT1, ZFHX3, and ZG16B for risk prediction. We constructed a risk score model with one dataset (either TCGA or TARGET) and evaluated its performance with the other. The test AUCs for the risk prediction of TCGA data with a 2-year and 5-year OS cutoffs are 0.762 (P = 2.33e-13, 95% CI: 0.69-0.83) and 0.759 (P = 7.26e-08, 95% CI: 0.66-0.85), respectively, while the test AUCs of TARGET data with the same cutoffs are 0.71 (P = 3.3e-07, 95% CI: 0.62-0.79) and 0.72 (P= 5.25e-09, 95% CI: 0.65-0.80), respectively. We further stratified patients into 3 equal sized prognostic subtypes with the 6-gene risk scores. The
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