Identification of Potential Key Genes and Regulatory Markers in Essential Thrombocythemia Through Integrated Bioinformatics Analysis and Clinical Validation - Wang J; Wu Y; Uddin MN; Chen R; Hao JP (Dove Medical Press, 2021)
Jie Wang,1,2 Yun Wu,3 Md Nazim Uddin,2,4 Rong Chen,5 Jian-Ping Hao5 1Department of Pharmacy, First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830011, People's Republic of China; 2School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 211198, People's Republic of China; 3Department of General Medicine, First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830011, People's Republic of China; 4Bangladesh Council of Scientific and Industrial Research (BCSIR), Dhaka, 1205, Bangladesh; 5Department of Hematology, First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830011, People's Republic of ChinaCorrespondence: Jian-Ping Hao No. 137 Liyushan S. Road, Urumqi, Xinjiang, People's Republic of ChinaTel +86 13579876416Email 13579876416@163.comIntroduction: Essential thrombocytosis (ET) is a group of myeloproliferative neoplasms characterized by abnormal proliferation of platelet and megakaryocytes. Research on potential key genes and novel regulatory markers in essential thrombocythemia (ET) is still limited.Methods: Downloading array profiles from the Gene Expression Omnibus database, we identified the differentially expressed genes (DEGs) through comprehensive bioinformatic analysis. GO, and REACTOME pathway enrichment analysis was used to predict the potential functions of DEGs. Besides, constructing a protein-protein interaction (PPI) network through the STRING database, we validated the expression level of hub genes in an independent cohort of ET, and the transcription factors (TFs) were detected in the regulatory networks of TFs and DEGs. And the candidate drugs that are targeting hub genes were identified using the DGIdb database.Results: We identified 63 overlap DEGs that included 21 common up-regulated and 42 common down-regulated genes from two datasets. Functional enrichment analysis shows that the DEGs are mainly enriched in the immune system and inflammatory processes. Through PPI network analysis, ACTB, PTPRC, ACTR2, FYB, STAT1, ETS1, IL7R, IKZF1, FGL2, and CTSS were selected as hub genes. Interestingly, we found that the dysregulated hub genes are also aberrantly expressed in a bone marrow cohort of ET. Moreover, we found that the expression of CTSS, FGL2, IKZF1, STAT1, FYB, ACTR2, PTPRC, and ACTB genes were significantly under-expressed in ET (P< 0.05), which is consistent with our bioinformatics analysis. The ROC curve analysis also shows that these hub genes have good diagnostic value. Besides, we identified 4 TFs (SPI1, IRF4, SRF, and AR) as master transcriptional regulators that were associated with regulating the DEGs in ET. Cyclophosphamide, prednisone, fluorouracil, ruxolitinib, and lenalidomide were predicted as potential candidate drugs for the treatment of ET.Discussion: These dysregulated genes and predicted key regulators had a significant relationship with the occurrence of ET with affecting the immune system and inflammation of the processes. Some of the immunomodulatory drugs have potential value by targeting ACTB, PTPRC, IL7R, and IKZF1 genes in the treatment of ET.Keywords: essential thrombocythemia, hub genes, regulatory markers, candidate drugs, bioinformatics analysis