Single-cell transcriptomics reveals multi-step adaptations to endocrine therapy
File(s)
Author(s)
Type
Journal Article
Abstract
Resistant tumours are thought to arise from the action of Darwinian selection on genetically heterogenous cancer cell populations. However, simple clonal selection is inadequate to describe the late relapses often characterising luminal breast cancers treated with endocrine therapy (ET), suggesting a more complex interplay between genetic and non-genetic factors. Here, we dissect the contributions of clonal genetic diversity and transcriptional plasticity during the early and late phases of ET at single-cell resolution. Using single-cell RNA-sequencing and imaging we disentangle the transcriptional variability of plastic cells and define a rare sub population of pre-adapted (PA) cells which undergoes further transcriptomic reprogramming and copy number changes to acquire full resistance. We find evidence for sub-clonal expression of a PA signature in primary tumours and for dominant expression in clustered circulating tumour cells. We propose a multi-step model for ET resistance development and advocate the use of stage-specific biomarkers.
Date Issued
2019-09-02
Date Acceptance
2019-07-30
Citation
Nature Communications, 2019, 10 (1)
ISSN
2041-1723
Publisher
Nature Research (part of Springer Nature)
Journal / Book Title
Nature Communications
Volume
10
Issue
1
Copyright Statement
© 2019 The Author(s). This article is licensed under a Creative Commons
Attribution 4.0 International License, which permits use, sharing,
adaptation, distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to the Creative
Commons license, and indicate if changes were made. The images or other third party
material in this article are included in the article’s Creative Commons license, unless
indicated otherwise in a credit line to the material. If material is not included in the
article’s Creative Commons license and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from
the copyright holder. To view a copy of this license, visit http://creativecommons.org/
licenses/by/4.0/.
Attribution 4.0 International License, which permits use, sharing,
adaptation, distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to the Creative
Commons license, and indicate if changes were made. The images or other third party
material in this article are included in the article’s Creative Commons license, unless
indicated otherwise in a credit line to the material. If material is not included in the
article’s Creative Commons license and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from
the copyright holder. To view a copy of this license, visit http://creativecommons.org/
licenses/by/4.0/.
Sponsor
Cancer Research UK
Grant Number
23110
Subjects
Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
REGULATORY NETWORK INFERENCE
PATIENT-LEVEL METAANALYSIS
BREAST-CANCER
READ ALIGNMENT
HETEROGENEITY
RESISTANCE
RNA
EVOLUTION
RARE
HIGHLIGHTS
Publication Status
Published
Article Number
3840
Date Publish Online
2019-09-02