Project description:Background Metastatic hormone-naïve prostate cancer (mHNPC) is an infrequent form of this tumour type that is characterized by metastasis at the time of diagnosis and accounts for 50% of prostate cancer-related deaths. Despite the extensive characterization of localized and metastatic castration resistant prostate cancer (mCRPC), the molecular characteristics of mHNPC remain largely unexplored. Results Here we provide the first extensive transcriptomics characterization of mHNPC. We generated discovery and validation bulk and single-cell RNA-Seq datasets and performed integrative computational analysis in combination with experimental studies. Our results provide unprecedented evidence of the distinctive transcriptional profile of mHNPC and identify stroma remodelling as a predominant feature of these tumours. Importantly, we discover a central role for the transcription factor SOX11 in triggering a heterotypic communication that is associated to the acquisition of metastatic properties. Conclusions Our study will constitute an invaluable resource for a profound understanding of mHNPC that can influence patient management.
Project description:We report the generation and characterization of tumor organoids and PDOX derived from needle biopsies of metastatic lesions from neuroendocrine prostate cancer patients.
Project description:Here we performed a detailed characterization of prostate cancer (PCa) tumor endothelial cells (TEC) in order to delineate intercellular crosstalk between TEC and the TME.
Project description:This study delves into the proteomic intricacies of drug-resistant cells (DRCs) within prostate cancer, which are known for their pivotal roles in therapeutic resistance, relapse, and metastasis. Utilizing single-cell proteomics (SCP) with an optimized high-throughput Data Independent Acquisition (DIA) approach with the throughput of 60 sample per day, we characterized the proteomic landscape of DRCs in comparison to parental PC3 cells. This optimized DIA method allowed for robust and reproducible protein quantification at the single-cell level, enabling the identification and quantification of over 1,300 proteins per cell on average. Distinct proteomic sub-clusters within the DRC population were identified, closely linked to variations in cell size. The study uncovered novel protein signatures, including the regulation of proteins critical for cell adhesion and metabolic processes, as well as the upregulation of surface proteins and transcription factors pivotal for cancer progression. Furthermore, by integrating SCP and single-cell RNA-seq (scRNA-seq) data, we identified six upregulated and ten downregulated genes consistently altered in drug-treated cells across both SCP and scRNA-seq platforms. These findings underscore the heterogeneity of DRCs and their unique molecular signatures, providing valuable insights into their biological behavior and potential therapeutic targets.