Abstract

Metastatic prostate cancer (PCa) poses a significant therapeutic challenge with high mortality rates. Utilizing CRISPR-Cas9 in vivo, we target five potential tumor suppressor genes (Pten, Trp53, Rb1, Stk11, and RnaseL) in the mouse prostate, reaching humane endpoint after eight weeks without metastasis. By further depleting three epigenetic factors (Kmt2c, Kmt2d, and Zbtb16), lung metastases are present in all mice. While whole genome sequencing reveals few mutations in coding sequence, RNA sequencing shows significant dysregulation, especially in a conserved genomic region at chr5qE1 regulated by KMT2C. Depleting Odam and Cabs1 in this region prevents metastasis. Notably, the gene expression signatures, resulting from our study, predict progression-free and overall survival and distinguish primary and metastatic human prostate cancer. This study emphasizes positive genetic interactions between classical tumor suppressor genes and epigenetic modulators in metastatic PCa progression, offering insights into potential treatments.

The molecular basis of the metastatic disease in prostate cancer remains poorly characterised. Here, the authors investigate the interaction of tumor suppressor and epigenetic factor genes and highlight the role of Kmt2c deficiency in facilitating lung metastasis.

Details

Title
CRISPR/Cas9 model of prostate cancer identifies Kmt2c deficiency as a metastatic driver by Odam/Cabs1 gene cluster expression
Author
Cai, Huiqiang 1 ; Zhang, Bin 2   VIAFID ORCID Logo  ; Ahrenfeldt, Johanne 3 ; Joseph, Justin V. 1 ; Riedel, Maria 1 ; Gao, Zongliang 1 ; Thomsen, Sofie K. 1 ; Christensen, Ditte S. 3 ; Bak, Rasmus O. 1   VIAFID ORCID Logo  ; Hager, Henrik 4 ; Vendelbo, Mikkel H. 5 ; Gao, Xin 2   VIAFID ORCID Logo  ; Birkbak, Nicolai 3   VIAFID ORCID Logo  ; Thomsen, Martin K. 6   VIAFID ORCID Logo 

 Aarhus University, Department of Biomedicine, Aarhus, Denmark (GRID:grid.7048.b) (ISNI:0000 0001 1956 2722) 
 King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center, Thuwal, Saudi Arabia (GRID:grid.45672.32) (ISNI:0000 0001 1926 5090); King Abdullah University of Science and Technology (KAUST), Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering Division, Thuwal, Saudi Arabia (GRID:grid.45672.32) (ISNI:0000 0001 1926 5090) 
 Aarhus University, Department of Clinical Medicine, Aarhus, Denmark (GRID:grid.7048.b) (ISNI:0000 0001 1956 2722); Aarhus University Hospital, Department of Molecular Medicine, Aarhus, Denmark (GRID:grid.154185.c) (ISNI:0000 0004 0512 597X) 
 Aarhus University Hospital, Department of Pathology, Aarhus, Denmark (GRID:grid.154185.c) (ISNI:0000 0004 0512 597X) 
 Aarhus University Hospital, Department of Nuclear Medicine & PET Centre, Aarhus, Denmark (GRID:grid.154185.c) (ISNI:0000 0004 0512 597X) 
 Aarhus University, Department of Biomedicine, Aarhus, Denmark (GRID:grid.7048.b) (ISNI:0000 0001 1956 2722); Aarhus University, Aarhus Institute of Advanced Studies (AIAS), Aarhus, Denmark (GRID:grid.7048.b) (ISNI:0000 0001 1956 2722) 
Pages
2088
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2941712805
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.