A bioinformatics analysis and experimental validation of PDGFD as a promising diagnostic biomarker for acute myeloid leukemia.

Acute myeloid leukemia (AML) is a malignant blood cancer resulting from leukemia stem cells (LSCs) supplanting normal stem cells. Platelet-derived growth factors (PDGFs) are important for LSCs but have not been studied in the development of AML. In this study, transcriptome data of PDGFs were sourced from The Cancer Genome Atlas (TCGA) and GTEx databases, and relevant differential expression and prognosis analysis were performed using R software packages and online tools (UCSC-Xena Shiny tools, GEPIA2, Kaplan-Meier Plotter databases, etc.). Then, we focused on PDGFD expression in AML, along with its clinical and diagnostic importance, drug resistance studies, and association with immunotherapy. The real-time quantitative polymerase chain reaction (RT-qPCR) was performed to verify the expression and clinical characteristics of PDGFD. Analyses of public data and clinical samples revealed that PDGFD expression was upregulated compared with other PDGF genes, and only this upregulation was associated with poor prognosis in AML. High expression of PDGFD showed a significant positive correlation with intermediate-high cytogenetic risk, NPM1 mutation, FLT3-ITD mutation, and unfavorable prognosis. ROC curve analysis indicated that PDGFD holds substantial diagnostic potential for AML patients. Functional enrichment analysis revealed the role of PDGFD in calcium and Rap1 signaling pathways. Additionally, PDGFD expression exhibited a significant positive correlation with natural killer cells and dendritic cells. Furthermore, we propose that MiR-203-3p targeting PDGFD has potential anti-leukemic effects in AML. In conclusion, PDGFD serves as a possible diagnostic and prognostic biomarker, as well as a target for cellular immunotherapy in AML.