.png){kind=icon}
Return
Decoding the tumor microenvironment with spatial technologies
.png){kind=icon}
PRE
AI
DOI：10.1038/s41590-023-01678-9.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Visualization of the cellular heterogeneity and spatial architecture of the tumor microenvironment (TME) is becoming increasingly important to understand mechanisms of disease progression and therapeutic response. This is particularly relevant in the era of cancer immunotherapy, in which the contexture of immune cell positioning within the tumor landscape has been proven to affect efficacy. Although single-cell technologies have mostly replaced conventional approaches to analyze specific cellular subsets within tumors, those that integrate a spatial dimension are now on the rise. In this Review, we assess the strengths and limitations of emerging spatial technologies with a focus on their applications in tumor immunology, as well as forthcoming opportunities for artificial intelligence (AI) and the value of integrating multiomics datasets to achieve a holistic picture of the TME. We are in the midst of an explosion of multiomics and spatial data along with constant innovation of the tools used to study these data. In this Review article, as part of our Cancer Immunology and Immunotherapy series, the authors discuss these innovations and their application to study the tumor microenvironment.
Keywords:
SINGLE-CELL
BREAST-CANCER
GENE-EXPRESSION
INTACT-TISSUE
IMMUNE NICHES
B-CELLS
RNA
RESOLUTION
MULTIPLEX
ATLAS
Journal
IF:
27.6
Papers:
6.4K
Citations:
5.6W
Organization
Cited Papers
Nitrogen-doped p-type ZnO films prepared from nitrogen gas radio-frequency magnetron sputtering
PREAI
ShareSaveEndogenous opioid actions and effects of environmental disturbance on parturition and oxytocin secretion in rats.png)
Reproduction
OAAI
ReproductionIF0
OAAIShareSaveShareSaveThe Single-Cell Immunogenomic Landscape of B and Plasma Cells in Early-Stage Lung AdenocarcinomaCANCER DISCOVERY
OAAI
CANCER DISCOVERYIF33.3
OAAIShareSave
View more