Overlapped differentially expressed genes between acute lymphoblastic leukemia and chronic lymphocytic leukemia revealed potential key genes and pathways involved in leukemia

• Published in: Journal of cellular biochemistry Vol. 120; no. 9; pp. 15980 - 15988
• Main Authors: Zhang, Suwei, Zhang, Qiaoxin, Yin, Jun, Wu, Xianheng
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 01.09.2019
• Subjects: Acute lymphoblastic leukemia; Agent Orange; Blood; CD19 antigen; CD1c antigen; Chronic lymphocytic leukemia; differentially expressed genes; Fibroblast growth factor receptor 1; Gene expression; Gene sequencing; Genes; Leukemia; Lymphatic leukemia; Lymphocytes B; Pathogenesis; Peripheral blood; Ribonucleic acid; RNA; Therapeutic applications; Thymus; leukemia; differentially expressed genes; chronic lymphocytic leukemia; acute lymphoblastic leukemia
• DOI: 10.1002/jcb.28876
• ISSN: 0730-2312; 1097-4644

Common differentially expressed genes (DEGs) in acute lymphoblastic leukemia (ALL) and chronic lymphocytic leukemia (CLL) might play critical roles in the pathogenesis and process of leukemia. We collected RNA sequencing (RNA‐seq) data of human CLL, ALL samples, and normal peripheral blood CD19+ B cells as well as thymus samples, and analyzed similarities and differences between their transcriptomes using Cuffdiff2, DESeq, and edgeR. Compared with the RNA‐seq data of normal peripheral blood CD19+ B cells and thymus samples, there were a large number of DEGs in ALL and CLL. DEGs in ALL and CLL not only have their distinguished features but also have a similar pattern. To figure out the common DEGs between CLL and ALL, we further identified 26 overlapped genes between CLL and ALL, among which 10 genes showed similar expression variation profiles whereas 16 genes showed opposite variation. The expression levels of 10 genes (SCML4, TNF‐α, CD1C, FGFR1, MYO7B, DUSP1, PAP1GAP, MAN1C1, SLFN5, and CD8A) among the 26 genes were further confirmed by experiments, which was consistent with the results obtained by analyzing the RNA‐seq data. The current study contributes to better understanding the pathophysiology of leukemia and unearthing novel potential prognostic markers and therapeutic targets of leukemia. The current study contributes to better understanding the pathophysiology of leukemia and unearthing novel potential prognostic markers and therapeutic targets of leukemia.