Research On MicroRNA And Transcription Factor Co-regulatory Network In Acute Lymphoblastic Leukemia

Acute lymphoblastic leukemia (ALL) is an aggressive hematological malignancy arised from lymphatic system. This disease can affect people at any age, with a high incidence in2-5years old children. Although this neoplastic disorder mainly originates from the bone marrow, it will spread throughout all organs and will be fatal rapidly without therapy. Its clinical features include high white blood cell counts, lymph nodes enlargement and central nervous system involvement. Although the application of multi-agent combination chemotherapy and stem cell transplantation had made a great progress in the treatment, but the recurrence, central nervous system infiltrating and drug resistance are still big problems. Currently, understanding of the etiology of ALL has largely come from the studies of gene abnormalities. Although the oncogenicity of those genes was well established, understanding of the transformational programs and multi-step pathogenesis of ALL remains elusive. In this research, we hypothesized that miRNAs and TFs might play combinatory regulatory roles for the diseased related genes and, thus, explored miRNA-TF regulatory networks in acute lymphoblastic leukemia.First, we studied the strategy of miRNA-TF co-regulatory network. Aiming to explore the miRNA and TF co-regulatory network in ALL, we predicted all the regulatory relationships among miRNAs, TFs and protein-coding genes in the whole human genome. Based on bioinformatics analysis, we analyzed the genome location and evolutionary conservation of the1046miRNAs. Combined multiple miRNA target prediction methods and resources based on experimentally validated miRNA targets, we obtained672175miRNA and target pairs. By integrating transcription factor binding sites prediction and ChIP-seq data, we predicted the potential TF and their target pairs on miRNAs and protein-coding genes. Both the TFs and miRNAs are regulators of gene expression and they may mutual regulate each other to form feedback loops (FBL), or they regulate the same target gene to form a feed-forward loop (FFL). Then, we extracted all the two types of miRNA-TF regulatory modules in human genome.Second, we studied the miRNA-TF regulatory networks in ALL. Since there are two types of ALL:T-cell acute lymphoblastic leukemia (T-ALL) and B-cell acute lymphoblastic leukemia (B-ALL), we constructed two specific miRNA-TF co-regulatory networks, which were described in chapters III and IV, respectively. We obtained120feed-forward loops (FFLs) among T-ALL related genes, miRNAs and TFs by combining target prediction. Then, a miRNA and TF co-regulatory network specifically for T-ALL was constructed and its significance was tested by statistical methods. We found4miRNAs in the miR-17-92cluster and4important genes (CYLD, HOXA9, BCL2L11, and RUNX1) as hubs in the network. Next, we built a model to explain the carcinogenesis of miR-19and its targets in T-ALL. Similarly, for B-ALL, we obtained78feed-forward among B-ALL related genes, miRNAs and TFs, and constructed the miRNA-TF regulatory network for B-ALL. Six hub regulators (miR-19, miR-15a/16-1, MYC, NFKB1/2and USF1) and several hub genes (such as CCND1, CYLD, HOXA9and BCL2) were identified in the B-ALL regulatory network. Next, we also proposed a model to highlight the3miRNAs and its targets involved in signaling pathways in B-ALL. Interesting, the regulation between miR-19and CYLD existed in both T-ALL and B-ALL networks.Finally, we performed experiments to study the regulatory relationship between miR-19and CYLD. The results showed that miR-19was high expressed in T-ALL patients and tumor cell lines. WST assay revealed that miR-19also play an important role in cell proliferation. We confirmed that the hub miR-19indeed inhibited the hub gene CYLD in T-ALL and influence the NF-κB signaling pathway. Thus, CYLD, miR-19and NF-κB participated in a feed-forward loop, which may play a key role in the formation of acute lymphocytic leukemia. Taken together, this study enhanced the understanding of regulatory mechanism of ALL, and also shed light on combining bioinformatics and experiments in the research of complex diseases.