Copy Number Architectures Define Treatment-Mediated Selection of Lethal Prostate Cancer Clones

Prostate cancer is still the leading cause of male cancer-related mortality globally. While Androgen Deprivation Therapy (ADT) initially displays promise in patients, metastatic prostate cancer inevitably transforms into a lethal state due to treatment resistance, often within two years. Therefore, deciphering this conundrum is a major medical need.

In the paper, titled "Copy number architectures define treatment-mediated selection of lethal prostate cancer clones", we characterised the intra-patient relationships of metastases that evade treatment using genome-wide copy number profiling and bespoke approaches targeting the androgen receptor (AR) on 167 metastatic regions from 11 organs harvested post-mortem from 10 men who died from prostate cancer.

Our research unveiled diverse and patient-unique alterations clustering around the AR in metastatic lesions from each patient, signifying independent acquisition of related genomic changes within an individual. Intriguingly, we observed cases where both wild-type and aberrant AR gene clones coexisted in patients.

Using the genomic boundaries of pan-autosome copy number change (referred to as Transition points), we reaffirmed a common clone of origin across metastases and diagnostic biopsies. Fascinatingly, we identified in individual patients, limited number of clusters of metastases characterise by dominant clones featuring diverged autosomal copy number alterations. These autosome-defined clusters are characterised by cluster-specific AR gene architectures, and in two index cases are topologically more congruent than by chance. Moreover, in one case, we have found that the expression of an AR splice variant is influenced by the evolutionary-selected genomic background.

Here, we showed that copy number boundaries identified treatment-selected clones with putatively distinct lethal trajectories. This strategy proved effective on Formalin Fixed Paraffin Embedded samples and plasma DNA, which showed the opportunity to expand in the future to studies with multiple temporally-separated samples. Integration with anatomical sites suggests patterns of spread and points of genomic divergence. By defining treatment-selected clones through copy number boundaries, we offer insights into potential lethal trajectories, providing a foundation for enhanced understanding and targeted interventions.

Written by: A. M. Mahedi Hasan, Research Fellow, University College London Cancer Institute, London, UK

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