Differentially expressed genes (DEGs) biomarkers can be used to help diagnose and monitor the disease, as well as to determine which treatments are most effective. So, given the complexity of Myelodysplastic neoplasm (MDS), it is difficult to determine the impact and disparities of DEGs between CD34+ HSC (hematopoietic stem cells) or primary bone marrow cells (PBMC) in MDS pathogenesis, and therefore it remains largely unknown. Here, we performed an in-silico transcriptome analysis on CD34+ HSC and PBMC from 1092 MDS patients analyzing the divergences between differential gene expression patterns in these two cell types as potential pathogenic biomarkers for MDS. Initially, we observed a difference of 7117 expressed transcripts between PBMC (n = 40,165) and CD34 +HSC (n = 33,048). Also, we identified that CD34+ HSC and PBMC samples showed 240 and 2948 DEGs, respectively. In summary, we identified DEGs disparities in CD34+ HSC and PBMC cell types. However, there was a certain similarity of the activated pathways in both cellular samples based on Gene Ontology and KEGG pathways enrichment analyses. Our results provide novel insights into novel DEGs biomarkers to MDS pathogenesis with clinical significance. AVAILABILITY OF DATA AND MATERIALS: All microarray databases were obtained from Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/). To evaluate the biological function of differentially expressed genes, the DAVID (Database for Annotation, Visualization and Integrated Discovery tool was used) (https://david.ncifcrf.gov/).
Keywords: CD34 + stem-cells; Gene expression; Microarray; Myelodysplastic neoplasm; Pathogenesis; Primary bone marrow cells.
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