Clonal deconvolution of transcriptomic signatures and their spatial organisation in a mouse model of breast cancer
type: CreativeWork
description: Intratumour heterogeneity is a phenomenon during cancer progression in which cancer cells diverge and form clonal populations with distinct phenotypic, genetic, or epigenetic states within the same tumour. This intrinsic heterogeneity provides a fuel for cancer evolution enabling tumour cell populations to adapt to selective pressures imposed by the tumour microenvironment or therapeutic interventions. Lineage-tracing approaches shed light into the clonal dynamics of complex populations, but generally lack the ability to directly associate clonal lineage with measurements that infer phenotype such as epigenetics and transcriptomics. In contrast, single-cell sequencing techniques can provide insight into the makeup of complex biological ecosystems, revealing the presence of rare cell populations that are typically masked in bulk analyses, but lack the ability to link these cell populations to clonal lineages. To address this challenge, we developed the WILDseq platform, a novel approach that allows clonal characterisation at the single-cell transcriptomic level while facilitating the prospective analysis of dynamic regulation of phenotypic heterogeneity under the selective pressure of therapeutic intervention. WILDseq relies on uniquely labelling individual cells with a heritable, expressed DNA barcode coupled with high-throughput single-cell RNA-sequencing. Importantly, this lentiviral-labelling approach can be deployed in any model system that is susceptible to viral transfection. Thus, this platform allows the comprehensive and systematic characterisation of clonal phenotypic di fferences within complex populations. Here we demonstrate how this technology can be used to determine clonal populations which are sensitive or resistant to a particular therapeutic intervention, identify transcriptomic signatures that correlate with these phenotypes and analyse how these cells adapt their transcriptomes to escape therapy. We have applied WILDseq to the study of di fferen…
abstract: Intratumour heterogeneity is a phenomenon during cancer progression in which cancer cells diverge and form clonal populations with distinct phenotypic, genetic, or epigenetic states within the same tumour. This intrinsic heterogeneity provides a fuel for cancer evolution enabling tumour cell populations to adapt to selective pressures imposed by the tumour microenvironment or therapeutic interventions. Lineage-tracing approaches shed light into the clonal dynamics of complex populations, but generally lack the ability to directly associate clonal lineage with measurements that infer phenotype such as epigenetics and transcriptomics. In contrast, single-cell sequencing techniques can provide insight into the makeup of complex biological ecosystems, revealing the presence of rare cell populations that are typically masked in bulk analyses, but lack the ability to link these cell populations to clonal lineages. To address this challenge, we developed the WILDseq platform, a novel approach that allows clonal characterisation at the single-cell transcriptomic level while facilitating the prospective analysis of dynamic regulation of phenotypic heterogeneity under the selective pressure of therapeutic intervention. WILDseq relies on uniquely labelling individual cells with a heritable, expressed DNA barcode coupled with high-throughput single-cell RNA-sequencing. Importantly, this lentiviral-labelling approach can be deployed in any model system that is susceptible to viral transfection. Thus, this platform allows the comprehensive and systematic characterisation of clonal phenotypic di fferences within complex populations. Here we demonstrate how this technology can be used to determine clonal populations which are sensitive or resistant to a particular therapeutic intervention, identify transcriptomic signatures that correlate with these phenotypes and analyse how these cells adapt their transcriptomes to escape therapy. We have applied WILDseq to the study of di fferen…
author: Wild, Sophia
language: eng
keywords: lentiviral barcoding, high-complexity libraries, breast cancer, single-cell RNA sequencing, drug resistance, clonal dyamics
license: https://www.repository.cam.ac.uk/bitstreams/caf8b76f-8b38-475d-be1e-7f83c89696a6/download
license: http://purl.org/NET/rdflicense/allrightsreserved
date published: 2021-10-20
date modified: 2026-07-24T01:33:15Z
provider: Cambridge University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Cambridge

PropertyValue
property ID: DOI
value: 10.17863/CAM.78611