PRO-DEPEND: Functional Genomics of Prostate Cancer Vulnerabilities

We are developing a collaborative project to identify functional dependencies and actionable therapeutic vulnerabilities associated with prostate cancer progression, recurrence, and treatment resistance. We are seeking partners who can complement our clinical, molecular, computational and experimental resources with CRISPR screening, high-throughput drug screening, spatial transcriptomics and in vivo models.

Project concept: Prostate cancer is highly heterogeneous, and patients with similar clinicopathological features may experience markedly different disease courses. Our aim is to identify molecular cell states associated with aggressive behaviour and determine which genetic dependencies create selective therapeutic vulnerabilities, especially in an age-dependent manner.

The proposed workflow will integrate patient-derived transcriptomic and single-cell data with public functional-genomics and drug-response resources, including DepMap. We will then experimentally validate candidate dependencies and link them to spatial tumour organisation and drug sensitivity.

Our existing research foundations: We have established collaboration with clinical urology teams and access to patient-derived prostate cancer material, particularly radical prostatectomy specimens linked with clinical data. Our ongoing research focuses on clonal heterogeneity and the evolution of prostate cancer cells in relation to disease course, recurrence, and progression, using single-cell transcriptomic and genomic approaches. We also developed an RNAlater-compatible workflow to isolate nuclei from radical prostatectomy specimens for single-nucleus RNA sequencing, enabling high-resolution molecular profiling directly from clinical material (PMID: 42297938).

Our previous studies provide a strong biological basis for the project. We demonstrated that differential Notch signalling is associated with age- and stage-dependent prostate cancer aggressiveness (PMID: 36613607) and identified ESR1/MMP3 transcriptomic profiles that stratify biochemical recurrence risk beyond conventional clinical characteristics (PMID: 37176106). Our research has also addressed EMT-related phenotypes and molecular heterogeneity in prostate cancer (PMID: 29206234).

Available capabilities: Our local environment combines clinical access with wet-lab, bioinformatics and biostatistical expertise. We provide:

• processing of patient-derived material;

• bulk RNA-seq and sn/scRNA-seq workflows;

• established and primary 2D cultures;

• 3D cultures and patient-derived organoids;

• cell-based functional assays;

• gene-expression analysis and core molecular biology techniques;

• CAGE-seq;

• differential expression, GSEA and WGCNA;

• pathway and co-expression network analysis;

• tumour-cell state identification;

• dimensionality reduction, clustering and trajectory/pseudotime analyses;

• multi-omics and clinical data integration;

• survival and predictive modelling;

• machine learning and AI/XAI-supported interpretation;

• biostatistics and clinical study methodology.

This allows us to move from clinically derived samples through molecular discovery and computational target prioritisation to experimental validation.

Partnership sought: We are looking for partners with expertise in:

• genome-wide or targeted CRISPR/CRISPRi screening;

• high-throughput drug and combination screening;

• spatial transcriptomics/spatial multi-omics;

• advanced prostate cancer in vivo, orthotopic or PDX models;

• advanced, metastatic or treatment-resistant prostate cancer cohorts;

• therapeutic target validation and drug development.

Spatial-omics partners would localise dependency-associated cell states within tumour architecture; CRISPR and drug-screening partners would establish whether prioritised vulnerabilities are functionally essential and therapeutically actionable; in vivo partners would provide final validation of the most promising targets and treatment combinations.

Expected outcome: Together, we aim to move beyond descriptive molecular profiling towards a functional precision-oncology framework linking aggressive prostate cancer states with experimentally validated dependencies and actionable treatment strategies. We already provide clinical access, patient-derived material, single-cell and transcriptomic expertise, organoid models, systems biology, biomarker research, AI/XAI modelling, and a biostatistical framework, and we are seeking complementary partners to complete the functional-genomics validation pathway.