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Updated: Dec 12, 2025

Assessing Autophagic Flux by Measuring LC3, p62, and LAMP1 Co-localization Using Multispectral Imaging Flow Cytometry
Published on: July 21, 2017
Systematic Analysis of Autophagy-Related Signature Uncovers Prognostic Predictor for Acute Myeloid Leukemia
Xue-Xing Chen1, Zi-Ping Li1, Jian-Hua Zhu2
1Institute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Abstract:
Autophagy, a highly conserved cellular protein degradation process, has been involved in acute myeloid leukemia (AML). The present study aims to establish a novel, autophagy-related prognostic signature for prediction of AML prognosis. Differentially expressed autophagy-related genes in AML and healthy samples were screened using GSE1159. Univariate Cox regression analysis was applied to determine survival-associated autophagy-related genes in The Cancer Genome Atlas (TCGA) AML cohort. Lasso regression was performed to develop multiple-gene prognostic signatures. A novel six-gene signature (including CASP3, CHAF1B, KLHL24, OPTN, VEGFA, and VPS37C) DC was established for AML prognosis prediction. The Kaplan-Meier survival analysis revealed that patients in the high-risk score group had poorer overall survival (OS). The receiver operating characteristic (ROC) curve validated its good performance in survival prediction in TCGA AML cohort, and the area under the curve value was 0.817. Moreover, our signature could independently predict OS. A nomogram was constructed, including the six-gene signature and other clinical parameters, and predictive efficiency was confirmed using the ROC curve and calibration curve. Furthermore, gene set enrichment analyses identified several tumor-associated pathways that may contribute to explain the potential molecular mechanisms of our signature. Overall, we developed a new autophagy-associated gene signature and nomogram to predict OS of AML patients, which may help in clinical decision-making for AML treatment.

