Kates, D. H. | Search bioRxiv

bioRxiv2026

Dependencies in heterogeneous, lineage plastic patient-derived prostate cancer organoids revealed through integrated single-cell multiomics and CRISPR screening

Lineage plasticity and tumor heterogeneity limit the effectiveness of targeted therapies, yet the functional dependencies used to nominate therapeutic targets are often derived from homogeneous systems that fail to capture this complexity. Here, we establish a framework to resolve state-specific genetic vulnerabilities by integrating single-cell multiomics (RNA and ATAC) with pooled CRISPR-Cas9 screening across a large panel of patient-derived organoids (PDOs) from castrate-resistant prostate cancer (CRPC) and neuroendocrine prostate cancer (NEPC). We generate a single-cell multiome atlas spanning >190,000 cells across 22 PDOs, defining seven lineage states--including intermediate and plastic populations not resolved by bulk profiling--and demonstrate that these lineage programs robustly classify independent transcriptomic datasets from prostate cancer patient tumors. By systematically coupling this atlas to subtype-resolved CRISPR screens, we construct a functional dependency map linking cell state in heterogeneous 3D human tumor models. We show that intratumoral heterogeneity fundamentally reshapes the interpretation of gene essentiality, whereby gene-level depletion reflects the composite behavior of co-existing subpopulations, and identify a general principle in which resistant "limiting" populations disproportionately determine aggregate fitness effects. This framework reveals both canonical and previously unrecognized lineage-restricted dependencies within highly plastic tumor and NEPC states, including a therapeutically targetable dependency on the aryl hydrocarbon receptor (AHR) in a novel hybrid stem-like/ASCL1 population. Together, these data establish an extensive multi-dimensional prostate cancer resource, identify novel lineage-resolved biology, and provide a generalizable strategy for interpreting functional genomics in heterogeneous human tumors.

cancer biology↗

bioRxiv2024

Single Cell Analysis of Treatment-Resistant Prostate Cancer: Implications of Cell State Changes for Cell Surface Antigen Targeted Therapies

Targeting cell surface molecules using radioligand and antibody-based therapies has yielded considerable success across cancers. However, it remains unclear how the expression of putative lineage markers, particularly cell surface molecules, varies in the process of lineage plasticity, wherein tumor cells alter their identity and acquire new oncogenic properties. A notable example of lineage plasticity is the transformation of prostate adenocarcinoma (PRAD) to neuroendocrine prostate cancer (NEPC)--a growing resistance mechanism that results in the loss of responsiveness to androgen blockade and portends dismal patient survival. To understand how lineage markers vary across the evolution of lineage plasticity in prostate cancer, we applied single cell analyses to 21 human prostate tumor biopsies and two genetically engineered mouse models, together with tissue microarray analysis (TMA) on 131 tumor samples. Not only did we observe a higher degree of phenotypic heterogeneity in castrate-resistant PRAD and NEPC than previously anticipated, but also found that the expression of molecules targeted therapeutically, namely PSMA, STEAP1, STEAP2, TROP2, CEACAM5, and DLL3, varied within a subset of gene-regulatory networks (GRNs). We also noted that NEPC and small cell lung cancer (SCLC) subtypes shared a set of GRNs, indicative of conserved biologic pathways that may be exploited therapeutically across tumor types. While this extreme level of transcriptional heterogeneity, particularly in cell surface marker expression, may mitigate the durability of clinical responses to novel antigen-directed therapies, its delineation may yield signatures for patient selection in clinical trials, potentially across distinct cancer types. SIGNIFICANCE STATEMENTTreatment of prostate cancer is rapidly evolving with several promising new drugs targeting different cell surface antigens. Selection of patients most likely to benefit from these therapies requires an understanding of how expression of these cell surface antigens varies across patients and how they change during disease progression, particularly in tumors that undergo lineage plasticity. Using immunohistochemistry and single cell mRNA sequencing, we reveal heterogeneity of cell states across a cohort of advanced disease prostate cancer patients; this heterogeneity is not captured by conventional histology-based designations of adenocarcinoma and neuroendocrine prostate cancer. We show these cell states can be identified by gene regulatory networks that could provide additional diagnostic precision based on their correlation with clinically relevant cell surface antigen expression.

cancer biology↗