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Expression profiles analysis identifies specific interferon-stimulated signatures as potential diagnostic and predictive indicators of JAK2V617F (+) myelofibrosis

Objective: This study aimed to identify specific dysregulated genes with potential diagnostic and predictive values for JAK2V617F (+) myelofibrosis. Methods: Two gene expression datasets of CD34(+) hematopoietic stem and progenitor cells (HSPCs) from patients with JAK2V617F (+) myeloproliferative ne...

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Detalles Bibliográficos
Autores principales: Zhao, Yanhong, Wang, Di, Liang, Yipeng, Xu, Changlu, Shi, Lihong, Tong, Jingyuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9434717/
https://www.ncbi.nlm.nih.gov/pubmed/36061178
http://dx.doi.org/10.3389/fgene.2022.927018
Descripción
Sumario:Objective: This study aimed to identify specific dysregulated genes with potential diagnostic and predictive values for JAK2V617F (+) myelofibrosis. Methods: Two gene expression datasets of CD34(+) hematopoietic stem and progenitor cells (HSPCs) from patients with JAK2V617F (+) myeloproliferative neoplasm (MPN) [n = 66, including polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF)] and healthy controls (HC) (n = 30) were acquired from the GEO (Gene Expression Omnibus) database. The differentially expressed genes (DEGs) were screened between each JAK2V617F (+) MPN entity and HC. Subsequently, functional enrichment analyses, including Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and Gene Set Enrichment Analysis (GSEA), were conducted to decipher the important biological effects of DEGs. Protein–protein interaction (PPI) networks of the DEGs were constructed to identify hub genes and significant modules. Another two gene expression profiles of patients with JAK2V617F (+) MPN [n = 23, including PV, ET, secondary myelofibrosis (SMF), and PMF] and HC (n = 6) from GEO were used as external validation datasets to prove the reliability of the identified signatures. Results: KEGG analysis revealed the upregulated genes in three JAK2V617F (+) MPN entities compared with HC were essentially enriched in inflammatory pathways and immune response signaling pathways, and the number of these pathways enriched in PMF was obviously more than that in PV and ET. Following the PPI analysis, 10 genes primarily related to inflammation and immune response were found upregulated in different JAK2V617F (+) MPN entities. In addition, Reactome enrichment analysis indicated that interferon signaling pathways were enriched specifically in PMF but not in PV or ET. Furthermore, several interferon (IFN)-stimulated genes were identified to be uniquely upregulated in JAK2V617F (+) PMF. The external datasets validated the upregulation of four interferon-related genes (OAS1, IFITM3, GBP1, and GBP2) in JAK2V617F (+) myelofibrosis. The receiver operating characteristic (ROC) curves indicate that the four genes have high area under the ROC curve (AUC) values when distinguishing JAK2V617F (+) myelofibrosis from PV or ET. Conclusion: Four interferon-stimulated genes (OAS1, IFITM3, GBP1, and GBP2) exclusively upregulated in JAK2V617F (+) myelofibrosis might have the potential to be the auxiliary molecular diagnostic and predictive indicators of myelofibrosis.