%0 Thesis
%9 Doctoral
%A Pawlik, Piotr
%B UCL Cancer Institute
%D 2025
%F discovery:10203239
%I UCL (University College London)
%P 207
%T Inference of clone-specific copy numbers from bulk tumour DNA
%U https://discovery.ucl.ac.uk/id/eprint/10203239/
%X Cancer is an evolutionary process. During this process, single nucleotide variants (SNVs) and somatic copy-number alterations (SCNAs) accumulate, contributing to clonal evolution. Nevertheless, making accurate inferences about  their co-evolution and clone-specific copy numbers from bulk DNA sequencing poses a significant challenge. In this thesis, I present ALPACA (ALlelespecific Phylogenetic Analysis of clone Copy-number Alterations), a computational method which allows inference of clone-specific copy-numbers from bulk  DNA by leveraging phylogenetic trees and SNV cellular frequencies obtained  from multi-sample sequencing experiments. I validate this approach with two  simulated tumour cohorts and with single-cell data, comparing the ALPACA  output both with the ground truth and with the outputs of two previously  published methods. I then apply ALPACA to the TRACERx421 (TRAcking  non-small cell lung Cancer Evolution through therapy Frankell et al. 2023; Al  Bakir et al. 2023) cohort and demonstrate that ALPACA can identify loss-ofheterozygosity events and amplifications in minor metastasis seeding clones,  not detectable on bulk-sample copy-number level. By comparing seeding and  non-seeding clones within the primary-metastatic matched cohort I observe evidence of increased chromosomal instability in metastasis seeding clones. Using  ALPACA’s clone-specific copy-numbers I develop a novel method to quantify  intra-tumour copy-number heterogeneity: clone copy-number diversity (CCD).  Using this metric I show that patients who later develop a metastatic disease  harbour a higher intra-tumour clone copy number diversity within their primary tumours compared to patients who do not relapse. Lastly, I show an  association between CCD and patient survival.
%Z Copyright © The Author 2025.   Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/).  Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms.  Access may initially be restricted at the author’s request.