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Spatial deconvolution of HER2-positive breast cancer delineates tumor-associated cell type interactions

Andersson, Alma ; Larsson, Ludvig ; Stenbeck, Linnea ; Salmén, Fredrik ; Ehinger, Anna LU orcid ; Wu, Sunny Z. ; Al-Eryani, Ghamdan ; Roden, Daniel ; Swarbrick, Alex and Borg, Åke LU , et al. (2021) In Nature Communications 12.
Abstract
In the past decades, transcriptomic studies have revolutionized cancer treatment and diagnosis. However, tumor sequencing strategies typically result in loss of spatial information, critical to understand cell interactions and their functional relevance. To address this, we investigate spatial gene expression in HER2-positive breast tumors using Spatial Transcriptomics technology. We show that expression-based clustering enables data-driven tumor annotation and assessment of intra- and interpatient heterogeneity; from which we discover shared gene signatures for immune and tumor processes. By integration with single cell data, we spatially map tumor-associated cell types to find tertiary lymphoid-like structures, and a type I interferon... (More)
In the past decades, transcriptomic studies have revolutionized cancer treatment and diagnosis. However, tumor sequencing strategies typically result in loss of spatial information, critical to understand cell interactions and their functional relevance. To address this, we investigate spatial gene expression in HER2-positive breast tumors using Spatial Transcriptomics technology. We show that expression-based clustering enables data-driven tumor annotation and assessment of intra- and interpatient heterogeneity; from which we discover shared gene signatures for immune and tumor processes. By integration with single cell data, we spatially map tumor-associated cell types to find tertiary lymphoid-like structures, and a type I interferon response overlapping with regions of T-cell and macrophage subset colocalization. We construct a predictive model to infer presence of tertiary lymphoid-like structures, applicable across tissue types and technical platforms. Taken together, we combine different data modalities to define a high resolution map of cellular interactions in tumors and provide tools generalizing across tissues and diseases. (Less)
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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Nature Communications
volume
12
article number
6012
publisher
Nature Publishing Group
external identifiers
  • scopus:85117381388
  • pmid:34650042
ISSN
2041-1723
DOI
10.1038/s41467-021-26271-2
language
English
LU publication?
yes
id
20a11c23-3da2-4593-83ed-a7c51fb7d46c
date added to LUP
2021-10-14 18:03:01
date last changed
2024-02-20 14:03:30
@article{20a11c23-3da2-4593-83ed-a7c51fb7d46c,
  abstract     = {{In the past decades, transcriptomic studies have revolutionized cancer treatment and diagnosis. However, tumor sequencing strategies typically result in loss of spatial information, critical to understand cell interactions and their functional relevance. To address this, we investigate spatial gene expression in HER2-positive breast tumors using Spatial Transcriptomics technology. We show that expression-based clustering enables data-driven tumor annotation and assessment of intra- and interpatient heterogeneity; from which we discover shared gene signatures for immune and tumor processes. By integration with single cell data, we spatially map tumor-associated cell types to find tertiary lymphoid-like structures, and a type I interferon response overlapping with regions of T-cell and macrophage subset colocalization. We construct a predictive model to infer presence of tertiary lymphoid-like structures, applicable across tissue types and technical platforms. Taken together, we combine different data modalities to define a high resolution map of cellular interactions in tumors and provide tools generalizing across tissues and diseases.}},
  author       = {{Andersson, Alma and Larsson, Ludvig and Stenbeck, Linnea and Salmén, Fredrik and Ehinger, Anna and Wu, Sunny Z. and Al-Eryani, Ghamdan and Roden, Daniel and Swarbrick, Alex and Borg, Åke and Frisén, Jonas and Engblom, Camilla and Lundeberg, Joakim}},
  issn         = {{2041-1723}},
  language     = {{eng}},
  publisher    = {{Nature Publishing Group}},
  series       = {{Nature Communications}},
  title        = {{Spatial deconvolution of HER2-positive breast cancer delineates tumor-associated cell type interactions}},
  url          = {{http://dx.doi.org/10.1038/s41467-021-26271-2}},
  doi          = {{10.1038/s41467-021-26271-2}},
  volume       = {{12}},
  year         = {{2021}},
}