Header

UZH-Logo

Maintenance Infos

Dynamic prostate cancer transcriptome analysis delineates the trajectory to disease progression


Bolis, Marco; Bossi, Daniela; Vallerga, Arianna; Ceserani, Valentina; Cavalli, Manuela; et al; Schraml, Peter; Moch, Holger (2021). Dynamic prostate cancer transcriptome analysis delineates the trajectory to disease progression. Nature Communications, 12:7033.

Abstract

Comprehensive genomic studies have delineated key driver mutations linked to disease progression for most cancers. However, corresponding transcriptional changes remain largely elusive because of the bias associated with cross-study analysis. Here, we overcome these hurdles and generate a comprehensive prostate cancer transcriptome atlas that describes the roadmap to tumor progression in a qualitative and quantitative manner. Most cancers follow a uniform trajectory characterized by upregulation of polycomb-repressive-complex-2, G2-M checkpoints, and M2 macrophage polarization. Using patient-derived xenograft models, we functionally validate our observations and add single-cell resolution. Thereby, we show that tumor progression occurs through transcriptional adaption rather than a selection of pre-existing cancer cell clusters. Moreover, we determine at the single-cell level how inhibition of EZH2 - the top upregulated gene along the trajectory - reverts tumor progression and macrophage polarization. Finally, a user-friendly web-resource is provided enabling the investigation of dynamic transcriptional perturbations linked to disease progression.

Abstract

Comprehensive genomic studies have delineated key driver mutations linked to disease progression for most cancers. However, corresponding transcriptional changes remain largely elusive because of the bias associated with cross-study analysis. Here, we overcome these hurdles and generate a comprehensive prostate cancer transcriptome atlas that describes the roadmap to tumor progression in a qualitative and quantitative manner. Most cancers follow a uniform trajectory characterized by upregulation of polycomb-repressive-complex-2, G2-M checkpoints, and M2 macrophage polarization. Using patient-derived xenograft models, we functionally validate our observations and add single-cell resolution. Thereby, we show that tumor progression occurs through transcriptional adaption rather than a selection of pre-existing cancer cell clusters. Moreover, we determine at the single-cell level how inhibition of EZH2 - the top upregulated gene along the trajectory - reverts tumor progression and macrophage polarization. Finally, a user-friendly web-resource is provided enabling the investigation of dynamic transcriptional perturbations linked to disease progression.

Statistics

Citations

Dimensions.ai Metrics
16 citations in Web of Science®
13 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

43 downloads since deposited on 27 Dec 2021
9 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Institute of Pathology and Molecular Pathology
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Physical Sciences > General Chemistry
Life Sciences > General Biochemistry, Genetics and Molecular Biology
Physical Sciences > General Physics and Astronomy
Language:English
Date:2 December 2021
Deposited On:27 Dec 2021 04:14
Last Modified:28 Jan 2024 02:38
Publisher:Nature Publishing Group
ISSN:2041-1723
OA Status:Gold
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1038/s41467-021-26840-5
PubMed ID:34857732
  • Content: Published Version
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)