Identification of cell adhesion related signature for molecular subtyping and prognostic prediction in acute myeloid leukemia

Acute Myeloid Leukemia (AML) is a heterogeneous hematologic malignancy, characterized by complex molecular features that significantly impact prognosis and therapeutic responses. Despite considerable progress, effective risk stratification and predictive biomarkers for personalized therapies remain inadequate. The involvement of cell adhesion-related genes in the progression of AML has yet to be fully explored.

AML patients were grouped into distinct molecular subtypes based on the expression patterns of cell adhesion-related genes. Enrichment analyses were subsequently performed to identify associated biological pathways. Differentially expressed genes were identified, and through Lasso regression and multivariate Cox regression, eight prognostically significant genes were selected. These genes were then used to construct a prognostic model, which was validated using external datasets. Furthermore, analyses of immune cell infiltration and drug sensitivity were conducted to evaluate the practical applicability of the model.

Two AML molecular subtypes were identified, each linked to distinct biological pathways. A prognostic model comprising 8 genes was developed, showing strong predictive power for overall survival and significant correlations with immune cell infiltration patterns. Drug sensitivity analyses identified potential therapeutic targets and candidate drugs, offering new directions for AML treatment.

This study reveals novel AML subtypes driven by cell adhesion-related genes, providing insights into genetic heterogeneity, immune landscape, and therapeutic vulnerabilities. The developed prognostic model and identified therapeutic candidates offer valuable tools for prognosis prediction and personalized treatment strategies in AML.