Nuovi metodi computazionali per lo studio degli RNA circolari e caratterizzazione del circRNAoma nella leucemia linfoblastica acuta a cellule T

Circular RNAs (circRNAs), a type of endogenous RNAs with covalently closed-loop structures generated by backsplicing, have become a new research hotspot in biomedicine. Their diversity, stability, evolutionary conservation, and cell type- or tissue-specific expression patterns indicated that circRNAs could play important biological functions, as is emerging from recent functional investigations. Growing evidence has shown that their dysregulation is implicated in the pathogenesis of diseases and cancer through diverse mechanisms, such as transcription and splicing regulation, microRNA (miRNA) sponging activity, coding potential, modulation of RNA translation efficiency and of protein activity. In the oncohematology field, the study of circRNAs can facilitate a deeper understanding of their biological functions, of their leukemogenic potential and provide new perspectives on circRNA-based clinical applications. When this thesis work started, data about circRNA expression and roles in Acute Lymphoblastic Leukemia (ALL) were scattered, and almost nothing was known in T-cell ALL (T-ALL). T-ALL is an aggressive, highly proliferative malignancy caused by the accumulation of genetic lesions that affect the development of T-cells. The still unsatisfactory cure rate of this malignancy incites studies to improve patient stratification, identify new disease mechanisms and potential targets for innovative therapies. The aim of this PhD project was to reveal new insight about T-ALL with the study of circRNA expression, of the biological features underlying their dysregulation and by elucidating their functional impact on the pathogenesis of the disease. Furthermore, novel computational and statistical approaches have been improved and developed, endowing the scientific community with useful and robust bioinformatics tools to study circRNAs. The first highlight of this thesis is the elucidation of the T-ALL circRNAome. Analysis of RNA-seq data of 25 pediatric patients representative of five T-ALL molecular subtypes, compared to normal thymocytes from healthy donors, disclosed a dramatic circRNAs dysregulation in T-ALL samples, with a majority of circRNAs overexpressed in malignant cells. Moreover, circRNA signatures of T-ALL molecular subgroups have been disclosed. Second, the first data about circRNA oncogenic roles in T-ALL have been provided, showing that circZNF609 overexpression can contribute to T-ALL cell viability in vitro. Moreover, we studied circFBXW7, which is expressed at heterogenous levels in T-ALL patients. Silencing experiments in T-ALL cell lines revealed a significant effect of the circFBXW7 depletion on cell proliferation and apoptosis, indicating a tumor suppressor role in T-ALL. Observation of a marked circRNA overexpression in T-ALL incited the study of the mechanisms underlying dysregulated circRNA biogenesis. Particularly, we focused on the RNA binding protein Quaking (QKI), depleted in T-ALL, whose link with back splicing regulation was reported in the literature. A study cohort of 85 T-ALL samples was classified according to QKI expression into three groups (low, normal, or high QKI level) whose comparative analysis revealed a striking effect of QKI depletion in the T-ALL circRNAome. The QKI knockdown in Jurkat cells defined that one-third of abundant circRNAs in T-ALL are dynamically regulated by QKI. In parallel, three new computational methods have been developed to improve the analysis of circRNAs from RNA-seq data. CircIMPACT is a bioinformatics tool to evaluate the implication of circRNAs in the gene expression changes observed upon circRNA expression variation. CirComPara2 is a cutting-edge pipeline for sensitive and robust circRNA identification and quantification. Finally, we devised DECMiMo, a novel statistical approach to improve circRNA differential expression analysis.