Project description:Single-nuclear RNA-sequencing of murine organoid transplant-derived prostate tumors. Purpose: To identify differences in cell composition in murine prostatic tumors and to generate a reference dataset of all major cell types present in mouse prostate tumors Results: We recovered 4,872 cells with a median of 7055.5 UMIs per cell. Conclusions: snRNASeq reveals heterogeneity within neuroendocrine prostate cancer compartment, dominated by an Ascl1+ expression profile with mixed luminal lineage marker genes. snRNASeq recovers all the major epithelial, immune, and stromal cell types in prostate tumors. Spatial transcriptomic profiling of murine prostate tumors. Purpose: To spatially map the major cell types in the mouse prostatic tumors and identify spatially distinct neuroendocrine tumor compartments. Distinct tumor microenvironments were also used for identification of cell:cell signaling axes distributed between the histological subtypes. Conclusions: Spatial transcriptomic profiling of the mouse prostate reveals all major cell types and allows for cell:cell signaling analyses upon integration with our matching snRNA-Seq data
Project description:Single-nuclear RNA-sequencing of murine organoid transplant-derived prostate tumors. Purpose: To identify differences in cell composition in murine prostatic tumors and to generate a reference dataset of all major cell types present in mouse prostate tumors Results: We recovered 4,872 cells with a median of 7055.5 UMIs per cell. Conclusions: snRNASeq reveals heterogeneity within neuroendocrine prostate cancer compartment, dominated by an Ascl1+ expression profile with mixed luminal lineage marker genes. snRNASeq recovers all the major epithelial, immune, and stromal cell types in prostate tumors. Spatial transcriptomic profiling of murine prostate tumors. Purpose: To spatially map the major cell types in the mouse prostatic tumors and identify spatially distinct neuroendocrine tumor compartments. Distinct tumor microenvironments were also used for identification of cell:cell signaling axes distributed between the histological subtypes. Conclusions: Spatial transcriptomic profiling of the mouse prostate reveals all major cell types and allows for cell:cell signaling analyses upon integration with our matching snRNA-Seq data
Project description:RNA was extracted from the frozen prostate tumours or tissues of P1 prostate tumours (n=3), CP1 prostate tumours (n=3) and CP2 prostate tumours (n=4). RNA quality of RNA extracted was evaluated by RNA integrity number (RIN>7.3), calculated using an Agilent 2100 Bioanalyzer (Agilent Technologies) with the Agilent RNA 6000 Nano Kit.
Project description:RNA sequencing was performed on wildtype prostate tissues and tumours from mice with prostate-specific deletion of Pten (Ptenpc-/-) and oncogenic activation of ß-catenin (Ctnnb1pcex3(Δ)/+ Ptenpc-/+ , Ctnnb1pcex3(Δ)/+, Mock and ADT treated Ctnnb1Nkx3-1CreERT2(ex3)Δ/+ Pten Nkx3-1CreERT2(ex3)Δ+/-).