Year: 2023
Type: dissertation
Study design: Observational Study
Abstract: The genomic architecture of blood is complex with germline polymorphisms, somatic point mutations, and mosaic chromosomal alterations (mCAs) shaping the fitness of immune cells. Many advances have been made in understanding how the age-associated acquisition of somatic mutations in blood, termed Age-Related Clonal Hematopoiesis (ARCH), predispose individuals to blood cancer. Yet, ARCH is commonly observed in healthy individuals and our ability to predict who is at risk of progressing to disease remains limited. In this thesis, I interrogate the mutational and selective pressures within blood to understand how the full spectrum of somatic changes within an individual impact clonal fitness and cancer outcomes. I integrate deep learning and population genetics to evaluate the interplay of positive and negative selection in deeply sequenced blood samples from 92 individuals who subsequently progressed to blood cancer and 385 controls. I discriminate amongst evolutionary classes with high accuracy (86%) and capture pervasive signatures of purifying selection in blood cells. The proportion of passenger-to-driver mutations in an individual appears to be critical in determining if the selective advantage conferred by a driver mutation can overwhelm purifying selection acting on passenger mutations thus allowing disease-predisposing clones to rise to dominance. Further, I evaluate how selection shapes the prevalence of mCAs among 14,000 individuals. I find that mCA-associated ARCH is three times higher than previously estimated with up to one in eight individuals harbouring a mCA. I find that mCAs accumulate preferentially across genes implicated in blood cancer development and observe a 136% increase in the rate of cancer development for each additional autosomal mCA. To determine the functional impact of mCAs, I investigate the relationship between mCAs and gene expression and find that different types of mCAs impact gene expression distinctly. Over 30% of eQTLs are impacted by mCAs, with loss events accounting for 9.1% of allele specific expression revealing a previously overlooked somatic contribution to blood expression profiles, regulatory mechanisms, and disease development. In summary, my work explores how different evolutionary models shape clonal dynamics in healthy and pre-cancerous blood and are critical when leveraging the predictive power of somatic events for early cancer detection.
Source: TSpace (University of Toronto)
Author: Skead, Kimberly Megan
Institution: University of Toronto
Language: English
Subfield: Hematology
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7133058093