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September 10, 2025Discover OncologyOpen Access

Lysosome-derived biomarkers for predicting survival outcome in acute myeloid leukemia

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Authors

GLG. LiYMYangyang MiaoYFYuan Fang

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Overview

Machine learning identifies a six-LRGs signature predicting prognosis and treatment response in AML, suggesting improved outcomes.

Key Points

  • The six-LRGs-related signature significantly predicts survival outcomes in acute myeloid leukemia patients.
  • Using machine learning methods, including random forest and XGBoost, the study identified crucial biomarkers linked to prognosis.
  • Data from ICGC and TARGET cohorts validated the effectiveness of the prognostic lysosome-related gene signature.
  • Implications for therapeutic approaches reveal the potential of targeting lysosome-related genes to improve AML treatment.

Cite This Study

Li et al. (2025) studied this question.

synapsesocial.com/papers/68c23fc3b210217d6479780ehttps://doi.org/10.1007/s12672-025-03302-8
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