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Inference of tissue relative proportions of the breast epithelial cell types luminal progenitor, basal, and luminal mature

Bartlett, T; Chandna, S; Roy, S; (2021) Inference of tissue relative proportions of the breast epithelial cell types luminal progenitor, basal, and luminal mature. BioRxiv: Cold Spring Harbor, Long Island, NY, USA. Green open access

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Abstract

Hormone receptor negative breast cancers are highly aggressive, and are thought to originate from a subtype of epithelial cells called the luminal progenitor. In this paper, we show how to quantify the number of luminal progenitor cells as well as other epithelial subtypes in breast tissue samples using DNA and RNA based measurements. We find elevated levels of these hormone receptor negative luminal progenitor cells in breast tumour biopsies of hormone receptor negative cancers, as well as in healthy breast tissue samples from BRCA1 (FANCS) mutation carriers. We also find that breast tumours from carriers of heterozygous mutations in non-BRCA Fanconi Anaemia pathway genes are much more likely to be hormone receptor negative. These findings have implications for understanding hormone receptor negative breast cancers, and for breast cancer screening in carriers of heterozygous mutations of Fanconi Anaemia pathway genes.

Type: Working / discussion paper
Title: Inference of tissue relative proportions of the breast epithelial cell types luminal progenitor, basal, and luminal mature
Open access status: An open access version is available from UCL Discovery
DOI: 10.1101/2021.05.17.444493
Language: English
Additional information: The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/10139290
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