Proteomic analysis for identifying the differences in molecular profiling between fanconi anaemia and aplastic...

Treatment and prognosis of Fanconi anaemia (FA) and acquired aplastic anaemia (AA) differ. However, delayed and inappropriate treatments are administered in FA due to its similarities to AA in presentation. The objective of the current study was to elucidate differences between the molecular mechanisms underlying FA and AA as well as to identify biomarkers and pathways associated with FA via bioinformatics analyses. Proteomic data were obtained from bone marrow samples of patients with FA and AA. Gene ontology analysis was performed using a Database for Annotation, Visualization and Integrated Discovery. KEGG pathway enrichment analyses were conducted using the ClueGO plug-in in Cytoscape. A DEP-associated protein-protein interaction (PPI) network was constructed using STRING and visualized in Cytoscape. A total of 114 DEPs, including 71 upregulated proteins and 43 downregulated proteins, were present in the FA samples, compared with those in the AA samples. Upregulated proteins were enriched in the nucleosome assembly, canonical glycolysis, glycolytic process, and the glycolysis/gluconeogenesis pathway, whereas downregulated proteins were enriched in relation to immune response, negative regulation of apoptosis, proteolysis and CoA biosynthesis. Eight hub proteins with a high degree of connectivity were obtained as follows: alpha-enolase (ENO1), HSP90AA1, phosphoglycerate kinase 1 (PGK1), HSP90AB1, ACTC1, ACTBL2, EEF1A1 and CFL1. Upregulation of ENO1 and CFL1 in patients with FA was confirmed through a WB experiment, and substantiated by the results of data analyses. Bioinformatics analyses are useful for identification of biomarkers and pathways associated with FA and AA. Some crucial DEPs, such as ENO1, PGK1, ACTC1, ACTBL2, EEF1A1 and CFL1, may play an important role in FA and show potential as serological markers for its early diagnosis.