Journal article
C. Ruiz-Moreno, Sergio Marco Salas, Erik R Samuelsson, S. Brandner, M. Kranendonk, M. Nilsson, H. Stunnenberg
bioRxiv, 2022
bioRxiv, 2022
Semantic Scholar
DOI
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APA
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Ruiz-Moreno, C., Salas, S. M., Samuelsson, E. R., Brandner, S., Kranendonk, M., Nilsson, M., & Stunnenberg, H. (2022). Harmonized single-cell landscape, intercellular crosstalk and tumor architecture of glioblastoma. BioRxiv.
Chicago/Turabian
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Ruiz-Moreno, C., Sergio Marco Salas, Erik R Samuelsson, S. Brandner, M. Kranendonk, M. Nilsson, and H. Stunnenberg. “Harmonized Single-Cell Landscape, Intercellular Crosstalk and Tumor Architecture of Glioblastoma.” bioRxiv (2022).
MLA
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Ruiz-Moreno, C., et al. “Harmonized Single-Cell Landscape, Intercellular Crosstalk and Tumor Architecture of Glioblastoma.” BioRxiv, 2022.
BibTeX Click to copy
@article{c2022a,
title = {Harmonized single-cell landscape, intercellular crosstalk and tumor architecture of glioblastoma},
year = {2022},
journal = {bioRxiv},
author = {Ruiz-Moreno, C. and Salas, Sergio Marco and Samuelsson, Erik R and Brandner, S. and Kranendonk, M. and Nilsson, M. and Stunnenberg, H.}
}
Abstract
Glioblastoma, isocitrate dehydrogenase (IDH)-wildtype (hereafter, GB), is an aggressive brain malignancy associated with a dismal prognosis and poor quality of life. Single-cell RNA sequencing has helped to grasp the complexity of the cell states and dynamic changes in GB. Large-scale data integration can help to uncover unexplored tumor pathobiology. Here, we resolved the composition of the tumor milieu and created a cellular map of GB (‘GBmap’), a curated resource that harmonizes 26 datasets gathering 240 patients and spanning over 1.1 million cells. We showcase the applications of our resource for reference mapping, transfer learning, and biological discoveries. Our results uncover the sources of pro-angiogenic signaling and the multifaceted role of mesenchymal-like cancer cells. Reconstructing the tumor architecture using spatially resolved transcriptomics unveiled a high level of well-structured neoplastic niches. The GBmap represents a framework that allows the streamlined integration and interpretation of new data and provides a platform for exploratory analysis, hypothesis generation and testing.
