A single-cell atlas of the healthy breast tissues reveals clinically relevant clusters of breast epithelial cells.
Adult
Atlases as Topic
Breast Neoplasms
/ genetics
Cell Lineage
/ genetics
Epithelial Cells
/ classification
Estrogen Receptor alpha
/ genetics
Female
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
High-Throughput Nucleotide Sequencing
Humans
Mammary Glands, Human
/ cytology
Prognosis
Pyruvate Dehydrogenase Acetyl-Transferring Kinase
/ genetics
Receptor, ErbB-2
/ genetics
Signal Transduction
Single-Cell Analysis
/ methods
Stem Cells
/ cytology
Survival Analysis
T-Box Domain Proteins
/ genetics
Transcriptome
breast cancer
cell of origin
epithelial cell clusters
normal breasts
single-cell analyses
Journal
Cell reports. Medicine
ISSN: 2666-3791
Titre abrégé: Cell Rep Med
Pays: United States
ID NLM: 101766894
Informations de publication
Date de publication:
16 03 2021
16 03 2021
Historique:
received:
11
06
2020
revised:
10
11
2020
accepted:
18
02
2021
entrez:
25
3
2021
pubmed:
26
3
2021
medline:
26
3
2021
Statut:
epublish
Résumé
Single-cell RNA sequencing (scRNA-seq) is an evolving technology used to elucidate the cellular architecture of adult organs. Previous scRNA-seq on breast tissue utilized reduction mammoplasty samples, which are often histologically abnormal. We report a rapid tissue collection/processing protocol to perform scRNA-seq of breast biopsies of healthy women and identify 23 breast epithelial cell clusters. Putative cell-of-origin signatures derived from these clusters are applied to analyze transcriptomes of ~3,000 breast cancers. Gene signatures derived from mature luminal cell clusters are enriched in ~68% of breast cancers, whereas a signature from a luminal progenitor cluster is enriched in ~20% of breast cancers. Overexpression of luminal progenitor cluster-derived signatures in HER2+, but not in other subtypes, is associated with unfavorable outcome. We identify TBX3 and PDK4 as genes co-expressed with estrogen receptor (ER) in the normal breasts, and their expression analyses in >550 breast cancers enable prognostically relevant subclassification of ER+ breast cancers.
Identifiants
pubmed: 33763657
doi: 10.1016/j.xcrm.2021.100219
pii: S2666-3791(21)00035-5
pmc: PMC7974552
doi:
Substances chimiques
ESR1 protein, human
0
Estrogen Receptor alpha
0
PDK4 protein, human
0
Pyruvate Dehydrogenase Acetyl-Transferring Kinase
0
T-Box Domain Proteins
0
TBX3 protein, human
0
ERBB2 protein, human
EC 2.7.10.1
Receptor, ErbB-2
EC 2.7.10.1
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Pagination
100219Informations de copyright
© 2021 The Author(s).
Déclaration de conflit d'intérêts
The authors declare no competing interests.
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