Improving prostate cancer risk stratification using spatial single-cell tumor profiling.
Authors: William S. Chen, Mikhail Dias, Chien-Kuang Cornelia Ding, Stefanie Engler, Sophie Déglise, Aishwarya Subramanian, Haolong Li, Andrea Jacobs, Martin Sjöström, Jonathan Chou, Julian C. Hong, Shuang Zhao, Jeffry Simko, Eric J. Small, Alan Ashworth, David Alan Quigley, Peter Carroll, Matthew R. Cooperberg, Bernd Bodenmiller, Felix Y Feng
Journal: Journal of Clinical Oncology (2025)

413 Background: Effective prostate cancer (PCa) risk stratification is paramount to guide treatment considerations across all stages of PCa. Serum PSA, Gleason score (GS), and bulk-profiling tests (e.g. Decipher) form the cornerstone of risk stratification in clinical practice. New techniques such as Imaging Mass Cytometry (IMC) now enable tumor profiling with unprecedented resolution. We developed a novel IMC assay with the goal of identifying single cell subtypes prognostic of clinical outcomes in localized PCa. Methods: Spatial single-cell expression profiling with IMC was performed on primary PCa tumor biopsies and paired benign prostate samples obtained from patients with localized PCa who subsequently underwent radical prostatectomy. Cell subtypes were defined using the Phenograph cell-clustering approach. Per-sample “cell fraction” (percent abundance) of each cell subtype was defined as cell count of that subtype divided by total number of cells in the sample. Association between cell fraction of each cell subtype and both GS and Canary risk score was assessed using one-way analysis of variance (ANOVA) with Tukey's multiple comparison test. Biochemical progression-free survival (bPFS) and cancer-specific survival (CSS) were prespecified clinical endpoints. Analyses stratified by cell fraction tertiles were performed using the Kaplan-Meier method with Cox proportional hazards testing for significance. All hypothesis tests were performed using a two-tailed significance level of 0.05. Results: Co-expression patterns of 40 selected proteins in 3,429,844 cells comprising 604 biopsy samples obtained from 393 patients were measured. 28 of 393 patients (7%) were assigned a GS of 4+3 or higher. Single-cell clustering analysis revealed 16 distinct prostate, stromal, and immune cell subtypes including androgen-driven (AR+ PSMA+ KLK2+ CD46+) luminal prostate cancer cells (Subtypes 1, 8, 10), basal epithelial cells (Subtype 9), CD8+ T-cells (Subtype 14), CD4+ T-cells (Subtype 15), and antigen-presenting cells (Subtype 12). Subtypes 2, 7, and 9 were enriched in benign and low-risk samples; Subtypes 1, 6 and 12 were enriched in samples with GS of 4+3 or higher (P&lt;0.001) and Canary high-risk ( P &lt;0.01) samples. Patients with tumors enriched for Subtypes 6 and 12 demonstrated shorter bPFS ( P =0.008 and P =0.001 respectively) and shorter CSS ( P =0.02 and P =0.002 respectively) than those with tumors not enriched for these cell subtypes. Multivariable analysis including GS and Canary risk score revealed that Subtype 6 and Subtype 12 cell fraction were both independently prognostic of bPFS and CSS ( P &lt;0.05). Conclusions: In our cohort of men with localized PCa, we identified single-cell features associated with biochemical recurrence and CSS that complement existing risk stratification approaches. Future work includes validation in independent cohorts and further investigation of spatial co-localization patterns between these prognostic cell types and neighboring cells of the tumor microenvironment.