Abstract
Intratumor heterogeneity is a major obstacle to effective cancer treatment. Current methods to study intratumor heterogeneity using single-cell RNA sequencing (scRNA-seq) lack information on the spatial organization of cells. While state-of-the art spatial transcriptomics methods capture the spatial distribution, they either lack single cell resolution or have relatively low transcript counts. Here, we introduce spatially annotated single cell sequencing, based on the previously developed functional single cell sequencing (FUNseq) technique, to spatially profile tumor cells with deep scRNA-seq and single cell resolution. Using our approach, we profiled cells located at different distances from the center of a 2D epithelial cell mass. By profiling the cell patch in concentric bands of varying width, we showed that cells at the outermost edge of the patch responded strongest to their local microenvironment, behaved most invasively, and activated the process of epithelial-to-mesenchymal transition (EMT) to migrate to low-confluence areas. We inferred cell-cell communication networks and demonstrated that cells in the outermost ∼10 cell wide band, which we termed the invasive edge, induced similar phenotypic plasticity in neighboring regions. Applying FUNseq to spatially annotate and profile tumor cells enables deep characterization of tumor subpopulations, thereby unraveling the mechanistic basis for intratumor heterogeneity.
Original language | English |
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Article number | 829509 |
Journal | Frontiers in Bioengineering and Biotechnology |
Volume | 10 |
DOIs | |
Publication status | Published - 22 Feb 2022 |
Bibliographical note
ACKNOWLEDGEMENTSM-PC acknowledges support from the Oncode Institute, Cancer GenomiCs.nl (CGC), NWO (Netherlands Organization for
Scientific Research) Veni Grant, Stichting Ammodo and Erasmus MC grant. M-PC appreciates Josephine Nefkens
Stichting’s support on the UFO microscope. We thank Reuven Agami for the kind gift of the MCF10A-H2B-GFP cell line.
Publisher Copyright:
Copyright © 2022 Smit, Feller, You, Storteboom, Begce, Beerens and Chien.