A single-cell and spatially resolved atlas of human breast cancers

Sunny Z. Wu, Ghamdan Al-Eryani, Daniel Lee Roden, Simon Junankar, Kate Harvey, Alma Andersson, Aatish Thennavan, Chenfei Wang, James R. Torpy, Nenad Bartonicek, Taopeng Wang, Ludvig Larsson, Dominik Kaczorowski, Neil I. Weisenfeld, Cedric R. Uytingco, Jennifer G. Chew, Zachary W. Bent, Chia Ling Chan, Vikkitharan Gnanasambandapillai, Charles Antoine DutertreLaurence Gluch, Mun N. Hui, Jane Beith, Andrew Parker, Elizabeth Robbins, Davendra Segara, Caroline Cooper, Cindy Mak, Belinda Chan, Sanjay Warrier, Florent Ginhoux, Ewan Millar, Joseph E. Powell, Stephen R. Williams, X. Shirley Liu, Sandra O’Toole, Elgene Lim, Joakim Lundeberg, Charles M. Perou, Alexander Swarbrick

Research output: Contribution to journalArticlepeer-review

554 Citations (Scopus)

Abstract

Breast cancers are complex cellular ecosystems where heterotypic interactions play central roles in disease progression and response to therapy. However, our knowledge of their cellular composition and organization is limited. Here we present a single-cell and spatially resolved transcriptomics analysis of human breast cancers. We developed a single-cell method of intrinsic subtype classification (SCSubtype) to reveal recurrent neoplastic cell heterogeneity. Immunophenotyping using cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) provides high-resolution immune profiles, including new PD-L1/PD-L2+ macrophage populations associated with clinical outcome. Mesenchymal cells displayed diverse functions and cell-surface protein expression through differentiation within three major lineages. Stromal-immune niches were spatially organized in tumors, offering insights into antitumor immune regulation. Using single-cell signatures, we deconvoluted large breast cancer cohorts to stratify them into nine clusters, termed ‘ecotypes’, with unique cellular compositions and clinical outcomes. This study provides a comprehensive transcriptional atlas of the cellular architecture of breast cancer.

Original languageEnglish
Pages (from-to)1334-1347
Number of pages14
JournalNature Genetics
Volume53
Issue number9
DOIs
Publication statusPublished - 1 Sept 2021
Externally publishedYes

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