Understanding the effect of mutations on cell behaviour in blood disorders through mathematical modelling and computational analysis

This interdisciplinary project will involve computational and mathematical work at the Schumacher group in Edinburgh and in vitro experimental work and data analysis in the Hellström-Lindberg group at the Karolinska Institutet in Stockholm.

The student will be working with data from patient cohorts, develop and apply mathematical models, and generate in vitro data to study the effects of mutations on the growth and differentiation of blood stem cells.

Background

An important factor in the development of age-related diseases is the accumulation of somatic mutations. Human cells continually acquire mutations over the course of a lifetime. Some mutations can upset the balance of cell division and differentiation, and lead to the expansion of clones — an overrepresented subpopulation of cells all harbouring the same mutation. 

Clonal expansion is particularly well studied in haematopoiesis, the production of blood cells. Clonal haematopoiesis (CH) is the expansion of mutations in haematopoietic stem cells (HSCs) that become detectable in blood or bone marrow of healthy aged individuals. More than 10% of the population over 65 years of age are affected by CH. CH is associated with increased risk for all-cause mortality, heart disease and ischaemic stroke. In 2022, CH has been recognised by the World Health Organization as a precursor myeloid disease state.

CH constitutes a known risk factor for myelodysplastic syndromes (MDS), a group of blood cancers in which the maturation of blood stem cells in the bone marrow and their downstream production of differentiated blood cells is impaired. Various subtypes of MDS have been defined based on clinical/molecular characteristics and their risk of transformation to leukaemia or death. Mutations in spliceosome components, with SF3B1 as one of the most common events, play a significant role in driving clonal expansion and disease progression. Additionally, SF3B1 is a particularly interesting genetic driver due to its dual risk profile, constituting a protective event in MDS with ring sideroblasts (MDS-RS) and yet having a dismal prognosis when co-occurring in MDS with 5q deletion. The reasoning for these distinct effects and the role of different SF3B1 mutations in MDS expansion and progression are currently unknown.

Risk prognosis is currently calculated as part of a diagnostic sequencing approach, with few studies centred on what factors drive clonal expansion over time. Being able to predict the clonal expansion of different mutations and understanding how co-mutations interact to modify disease risk could facilitate monitoring of MDS in individuals for the stratification of risk. Before we can realise the potential of such monitoring, more research is required to determine the mechanisms by which certain clones can outcompete others in the bone marrow and blood production.

The Schumacher group has recently shown [1] that mutations in different genes can have different expansion rates. This insight was enabled by the availability of longitudinal sequencing data from healthy aged individuals in combination with mathematical models of clonal expansion to make sense of such data. We now plan to apply this approach to quantify and understand the clonal expansion of SF3B1 mutations in MDS. As MDS with SF3B1 mutations are typically lower risk they are closer to the pre-malignant status of CH than other blood malignancies and therefore our methods may be applicable with only small modifications.

The Hellström Lindberg group has established a well-annotated biobank of >1200 consecutive patients with MDS and related disorders. One focus of the group lies on MDS with mutations in the gene SF3B1, for which they do serial sampling over time. These data provide the ideal test-bed for extending the applicability of recent mathematical models [1], guided by the clinical expertise of the Hellström Lindberg group. The group has also established a 3D culture system [2,3] to study the clonal expansion of patient-derived cells with known mutations in vitro. We will systematically quantify the kinetics and variability of expansion of selected SF3B1 mutations. This will serve as validation of the in vivo findings and enable the further development of mathematical models to include different potential mechanisms of clonal expansion, the predictions of which can in turn be tested experimentally.

Aims

1.    Adapt mathematical models of clonal haematopoiesis to make them applicable to data from low risk MDS patients

2.    Test whether rate of clonal expansion of SF3B1 mutations is specific to the mutational variant, hotspot location within the gene, or other factors (e.g., from clinical metadata)

3.    Verify differences in clonal expansion using 3D culture system and quantify variability of kinetics

4.    Adapt mathematical models to make them applicable to in vitro data from 3D culture system

5.    Determine the mechanism of how SF3B1 mutations cause clonal expansion using a combination of in vitro experiments and mathematical models

Training Outcomes

• Developing so called T-shaped skills combining depth in mathematical modelling and computational data analysis with the skill to collaborate and communicate across disciplines in biomedical and clinical science
• Mathematical modelling using differential equations, stochastic processes, and Bayesian statistics for parameter inference.
• Bioinformatics of targeted and ddPCR sequencing data, working medical cohort data whilst maintaining patient anonymity.
• 3D culturing of patient-derived cells to study clonal expansion
• Scientific communication: Communicate complex ideas orally and in writing to both a specialist and lay audience across disciplines.

References

[1] Robertson, Neil, Latorre-Crespo, et al. ‘Longitudinal Dynamics of Clonal Hematopoiesis Identifies Gene-Specific Fitness Effects’. Nature Medicine 28, no. 7 (July 2022): 1439–46. https://doi.org/10.1038/s41591-022-01883-3.

[2] Mortera-Blanco et al. ‘Long-Term Cytokine-Free Expansion of Cord Blood Mononuclear Cells in Three-Dimensional Scaffolds’. Biomaterials 32, no. 35 (December 2011): 9263–70. https://doi.org/10.1016/j.biomaterials.2011.08.051.

[3] Elvarsdóttir et al. ‘A Three-Dimensional in Vitro Model of Erythropoiesis Recapitulates Erythroid Failure in Myelodysplastic Syndromes’. Leukemia 34, no. 1 (January 2020): 271–82. https://doi.org/10.1038/s41375-019-0532-7.