Abstract A006: Cancer origin tracing and timing in two high risk prostate cancers using multisample whole genome analysis: Potential clinical value

Abstract

Prostate cancer (PrCa) genomic heterogeneity causes resistance to therapies such as androgen deprivation. Such heterogeneity can be deciphered in the context of evolutionary principles, but current clinical trials do not include evolution as an essential feature. Understanding the evolution of an individual PrCa through serial analysis in space and time may be more important than identifying actionable targets for therapy from single samples as in current practice. The most prominent recent example of this is our recent evolution-based discovery of subclone eradication in a metastatic PrCa, with subsequent identification of a novel method to compare eradicated and resistant subclones to better resolve actionable targets for therapy. Whether or not analysis of genomic data in an evolutionary context in primary prostate cancer can provide unique added value in the research and clinical domains remains an open question. We used novel processing techniques to obtain whole genome data together with 3D anatomic and histomorphologic analysis in two men (GP5 and GP12) with high risk PrCa undergoing radical prostatectomy. A total of 22 whole genome-sequenced sites (16 primary cancer foci and 6 lymph node metastatic) were analyzed using evolutionary reconstruction tools and spatio-evolutionary models. Probability models were used to trace spatial and chronological origins of the primary tumor and metastases, chart their genetic drivers, and distinguish metastatic and non-metastatic subclones. In patient GP5, CDK12 inactivation was among the first mutations, leading to a PrCa tandem duplicator phenotype and initiating the cancer around age 50, followed by rapid cancer evolution after age 57, and metastasis around age 59, five years prior to prostatectomy. In patient GP12, accelerated cancer progression was detected after age 54, and metastasis occurred around age 56, three years prior to prostatectomy. Multiple metastasis-originating events were identified in each patient and tracked anatomically. Metastasis from prostate to lymph nodes occurred strictly ipsilaterally in all 12 detected events. In this pilot, metastatic subclone content analysis appears to substantially enhance identification of key drivers. Evolutionary analysis’ potential impact on therapy selection appears positive in these pilot cases. Taken together with our recent discovery that solid tumor subclones can be eradicated, and that comparison of eradicated and resistant subclones could guide therapy, we believe the case for embarking on clinical trials testing evolutionary-analysis informed PrCa care is compelling. PrCa evolutionary analysis allows tracking of anatomic site of origin, timing of cancer origin and spread, and distinction of metastatic-capable from non-metastatic subclones. This enables better identification of actionable targets for therapy. If extended to larger cohorts, it appears likely that similar analyses could add substantial biological insight and clinically relevant value.

Citation Format: Anssi Nurminen, Serafiina Jaatinen, Sinja Taavitsainen, Gunilla Högnäs, Tom Lesluyes, Naser Ansari-Pour, Teemu Tolonen, Kerstin Haase, Antti Koskenalho, Matti Kankainen, Juho Jasu, Hanna Rauhala, Jenni Kesäniemi, Tiia Nikupaavola, Paula Kujala, Irina Rinta-Kiikka, Jarno Riikonen, Antti Kaipia, Teemu Murtola, Teuvo L. Tammela, Tapio Visakorpi, Matti Nykter, David C. Wedge, Peter Van Loo, G. Steven Bova. Cancer origin tracing and timing in two high risk prostate cancers using multisample whole genome analysis: Potential clinical value [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr A006.