Modelling timing in blood cancers
University of Cambridge
Doctor of Philosophy (PhD)
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Talarmain, L. (2020). Modelling timing in blood cancers (Doctoral thesis). https://doi.org/10.17863/CAM.66147
Dysregulation of biological processes in normal cells can lead to the abnormal growth of tumours. Oncogenesis requires the acquisition of advantageous mutations to expand in a fluctuating environment. Cancer cells gain these genetic and epigenetic alterations at different timing in their development, resulting in the formation of heterogeneous cell populations which interact and compete with each others inside tumours. At later stages, by escaping the immune system and acquiring malignant properties, some cancer cells manage to evade the primary tumour and spread in different organs to form metastases. Hence, tumour development in healthy tissues endure several biological changes whilst progressing and the order between these molecular and cellular events may modify prognosis. This thesis addresses the influence of biological event timing on blood cancer progression and clinical outcomes. It first investigates the therapeutic efficacy of p53 restoration in a lymphoma mouse model. While several therapy schedules are tested, all fail due to resistance emergence. Computational modelling establishes the cell dynamics in these tumours and how to use it to propose alternative treatment strategies. Data availability leads this work to explore the impact of molecular evolution in myeloid malignancies. Notably, one study has found that Myeloproliferative Neoplasms patients with both JAK2 and TET2 mutations have different disease characteristics with distinct mutation order. My analyses identify HOXA9 as a potential prognosis marker and biological switch responsible for patient stratification in these patients and in Acute Myeloid Leukemia. Additionally, a molecular network identifies the hematopoietic regulators involved in the branching evolution of Myeloproliferative Neoplasms. Further investigations of the Acute Myeloid Leukemia data show the possible involvement of APP, a gene associated to Alzheimer disease, in early cell fate commitment in hematopoiesis and in poor survival prognosis in undifferentiated leukemia when lowly expressed. Finally, this thesis examines the regulatory dynamics behind three clusters of Acute Myeloid Leukemia patients with distinct levels of HOXA9 and APP expression. By building a program inferring molecular motifs from biological observations, genes which may interact with HOXA9 and APP are identified.
Acute Myeloid Leukemia, Myeloproliferative Neoplasms, HOXA9, Molecular network, computational model, Cancer evolution
Microsoft Research and the MRC Cancer Unit.
This record's DOI: https://doi.org/10.17863/CAM.66147
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