AUTHOR=Zhang Jing , Wang Ying-Jun , Han Yan-Qiu TITLE=Identification of autophagy-associated genes and prognostic implications in adults with acute myeloid leukemia by integrated bioinformatics analysis JOURNAL=Frontiers in Oncology VOLUME=12 YEAR=2023 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.1074057 DOI=10.3389/fonc.2022.1074057 ISSN=2234-943X ABSTRACT=

Acute myeloid leukemia (AML) is one of the most common malignant blood neoplasma in adults. The prominent disease heterogeneity makes it challenging to foresee patient survival. Autophagy, a highly conserved degradative process, played indispensable and context-dependent roles in AML. However, it remains elusive whether autophagy-associated stratification could accurately predict prognosis of AML patients. Here, we developed a prognostic model based on autophagy-associated genes, and constructed scoring systems that help to predicte the survival of AML patients in both TCGA data and independent AML cohorts. The Nomogram model also confirmed the autophagy-associated model by showing the high concordance between observed and predicted survivals. Additionally, pathway enrichment analysis and protein-protein interaction network unveiled functional signaling pathways that were associated with autophagy. Altogether, we constructed the autophagy-associated prognostic model that might be likely to predict outcome for AML patients, providing insights into the biological risk stratification strategies and potential therapeutic targets.