Metastasis Related Epithelial-Mesenchymal Transition Signature Predicts Prognosis and Response to Chemotherapy in Acute Myeloid Leukemia

BACKGROUND: Acute myeloid leukemia (AML) is a highly heterogenous disease with varying clinical outcomes among patients. Epithelial-mesenchymal transition (EMT) is an important mechanism underlying cancer metastasis and chemotherapy resistance. However, few EMT-based signatures have been established to predict AML prognosis and treatment efficacy. METHODS: By conducting comparative RNA-seq analysis, we discovered the differential expression of EMT genes between AML patients with relapse and those without relapse. Based on the prognostic analysis of the differentially expressed EMT genes, a metastasis-related EMT signature (MEMTs) was constructed. An analysis was conducted on both TARGET and TCGA cohorts to explore the possible association between MEMTs and prognosis in AML. Three separate chemotherapy treatment cohorts were utilized to assess the predictive efficacy of MEMTs for chemotherapy response. In addition, the potential correlation between MEMTs and the tumor microenvironment was also investigated. Finally, random forest analysis and functional experiments were conducted to verify the key MEMTs gene associated with AML metastasis. RESULTS: Based on expression and prognostic analysis, we constructed MEMTs that include three EMT genes (CDH2, LOX, and COL3A1). Our findings suggested that the MEMTs could act as a prognostic factor for AML patients, and furthermore, it proved to be a predictor of their response to chemotherapy. Specifically, high MEMTs was associated with worse prognosis and poor response to chemotherapy, while low MEMTs was linked to better prognosis and higher response rates. Random forest and functional experiments demonstrate that CDH2 is a key gene promoting leukemia cell metastasis among the three MEMTs genes. CONCLUSION: The identification of MEMTs could potentially act as a predictor for the prognosis and the response to chemotherapy in AML patients. Individual tumor evaluation based on MEMTs could provide personalized treatment options for AML patients in the future.