A comprehensive assessment of the prognostic role of cell adhesion molecules in acute myeloid leukemia

Background: The outcomes for patients with acute myeloid leukemia (AML) have been shown to vastly differ, predominantly due to genetic heterogeneity. Cell adhesion molecules (CAMs) concluding numerous genes play an important role in AML. We aimed to systematically assess the expression characteristics of adhesion molecules and their correlation to the outcomes of AML. Method: A total of 173 patients with AML were enrolled in this study. The genetic expressional information and clinical data sourced in previous studies were collected from the Cancer Genome Atlas (TCGA) database. The expression profiles of 141 CAMs were assessed, and the AML subgroups with specific patterns of expression were identified. The outcomes and clinical features of each AML subgroup were compared to detect the factors associated with prognosis. The differentially expressed genes (DEGs) between each subgroup were identified and the prognostic roles of those molecules were evaluated. Results: According to subgroup clustering, both the primary cluster_1 and subcluster_1 showed a favorable prognosis compared to that of the other patients (26.3 vs. 17.0 months of overall survival (OS) and 46.5 vs. 15.8 months of OS, respectively). Both of the two subgroups were characterized by depressed human leukocyte antigen (HLA) genes. Assessment of the expression of prognosis-associated CAMs revealed that the expressions of SELE, NRCAM, ITGA4. and SDC1 were positively correlated with AML prognosis, while the expression of L1CAM, PDCD1, CD276, SELPLG, and CLDN14 were negatively correlated with AML. Among the abovementioned genes, we detected that the individual gene expressions of NRCAM and VCAM1 were capable of independently predicting OS, and the OS was correlated with CAMs closely enough to enable the construction of models for prognosis prediction [area under the curve (AUC) =0.78 and AUC=0.77, respectively]. Conclusions: This study showed a landscape of the expression of CAMs in AML and identified a distinct subgroup with a significantly favorable prognosis. We detected that CAMs can assist in distinguishing the cohort with long term survival and constructed two models to predict the prognosis. Those CAMs have the potential to be developed as therapy targets in the treatment of AML.