Abstract 2663: Mapping clonal heterogeneity and stromal dynamics in prostate cancer
Authors: Sandy Figiel, Mengxiao He, Wencheng Yin, Emmanouela Perisynaki, Renuka Teague, Thineskrishna Anbarasan, Eleanor O’Roberts, Nithesh Ranasinha, Sophia M. Abusamra, Trishna Desai, Dimitrios Doultsinos, Andrew Erickson, Srinivasa Rao, Clare Verrill, Richard Colling, Pelvender Gill, Tuomas Mirtti, Ibrahim Kulac, Karl Smith-Byrne, Ruth Travis, Charlotte Stadler, Richard J. Bryant, Freddie C. Hamdy, Dan J. Woodcock, Ian G. Mills, Joakim Lundeberg, Alastair D. Lamb
Journal: Cancer Research (2025)

Abstract Introduction: Prostate cancer (PCa) exhibits significant intratumoral heterogeneity, driving a spectrum of phenotypes ranging from indolent disease to aggressive metastasis, challenging risk stratification and treatment. A key feature of this heterogeneity is clonal diversity, encompassing both cancer cells and their interactions with the surrounding stromal microenvironment. Understanding clonal dynamics and stromal influences on tumor progression is crucial for identifying factors that contribute to metastasis and disease lethality, ultimately improving risk stratification and therapeutic strategies. Methods: We performed organ-wide spatial transcriptomic analyses (VisiumTM v2, 10x Genomics) on formalin-fixed paraffin-embedded tissues from ten patients with primary, nodal metastatic PCa and biopsy samples, recruited to a local trial (ISRCTN10046036). Two pathologists meticulously annotated each spot, including benign, Gleason grade, stroma, and immune cells. Fastq data were processed using SpaceRangerTM, and inferred clonal genomic identities were analyzed with SpatialInferCNV (https://github.com/aerickso/SpatialInferCNV). We reconstructed clonal evolution using phylogenetic trees and analyzed stromal gene expression around distinct tumor clones using differential expression analyses. In addition, we performed multiplex imaging on consecutive sections to assess protein expression and correlate it with gene expression data, enabling the identification of key tumor-stroma interactions associated with metastatic progression. Results: We analyzed 122 spatial transcriptomics capture areas, collectively representing over 1, 000, 000 spots (55 µm diameter), or approximately 16, 000, 000 cells. We identified clonal subtypes across biopsy, primary and metastatic tissues, revealing distinct clonal relationships and polyclonal lymph node colonization at different evolutionary stages. Stromal cells around metastatic progenitor clones showed upregulation of antigen presentation and inflammatory pathway genes, contrasting with stromal profiles surrounding lethal clones (as defined by their ability to metastasize to lymph nodes). These findings suggest a dynamic interplay between tumor cells and their stroma, potentially influencing metastatic potential and immune evasion. Conclusion: This study provides a detailed cellular-level characterization of clonal heterogeneity in PCa and its relationship with stromal dynamics, offering insights into mechanisms driving metastatic progression. These insights could inform strategies for risk stratification and therapeutic intervention, including leveraging dual tumor-stromal profiles as biomarkers to distinguish lethal from indolent disease. Understanding the interplay between tumor clones and their stroma opens new avenues for targeted treatment approaches aimed at preventing metastasis and improving patient outcomes. Citation Format: Sandy Figiel, Mengxiao He, Wencheng Yin, Emmanouela Perisynaki, Renuka Teague, Thineskrishna Anbarasan, Eleanor O’Roberts, Nithesh Ranasinha, Sophia M. Abusamra, Trishna Desai, Dimitrios Doultsinos, Andrew Erickson, Srinivasa Rao, Clare Verrill, Richard Colling, Pelvender Gill, Tuomas Mirtti, Ibrahim Kulac, Karl Smith-Byrne, Ruth Travis, Charlotte Stadler, Richard J. Bryant, Freddie C. Hamdy, Dan J. Woodcock, Ian G. Mills, Joakim Lundeberg, Alastair D. Lamb. Mapping clonal heterogeneity and stromal dynamics in prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2663.