Bolis, Marco; Bossi, Daniela; Vallerga, Arianna; Ceserani, Valentina; Cavalli, Manuela; Impellizzieri, Daniela; Di Rito, Laura; Zoni, Eugenio; Mosole, Simone; Elia, Angela Rita; Rinaldi, Andrea; Pereira Mestre, Ricardo; D'Antonio, Eugenia; Ferrari, Matteo; Stoffel, Flavio; Jermini, Fernando; Gillessen, Silke; Bubendorf, Lukas; Schraml, Peter; Calcinotto, Arianna; ... (2021). Dynamic prostate cancer transcriptome analysis delineates the trajectory to disease progression. Nature Communications, 12(1), p. 7033. Springer Nature 10.1038/s41467-021-26840-5
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Tha_Dynamic_prostate_cancer_transcriptome_analysis_delineates_the_trajectory_to_disease_progression.pdf - Published Version Available under License Creative Commons: Attribution (CC-BY). Download (4MB) | Preview |
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.
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