Karina Dalsgaard Sørensen

Abstract Prostate cancer (PCa) is heterogeneous, making risk stratification essential for clinical care. Although polygenic risk scores (PRSs) with main effects of single-nucleotide polymorphisms (SNPs) can help identify individuals at high risk before biological and clinical onset, a PRS for predicting PCa aggressiveness remains underdeveloped. The KLK3, which encodes prostate-specific antigen (PSA), is linked to PCa aggressiveness.

Abstract Tissue detection is a crucial first step in most digital pathology applications. By applying image segmentation algorithms, all tissue is delineated and background discarded from further analyses, improving both computational efficiency and analytical results. Details of the segmentation algorithm are rarely reported, and there is a lack of studies investigating the downstream effects of a poor segmentation algorithm.

Abstract Metastatic castration-resistant prostate cancer (mCRPC) remains a lethal disease with few biomarkers to inform treatment selection or patient prognosis. Methylation profiles of plasma circulating tumour DNA (ctDNA) accurately reflect tumour methylomes and may reveal novel biomarkers of mCRPC. To establish a novel mCRPC-associated methylation signature for detection of ctDNA, we performed plasma methylome profiling on 27 mCRPC patients and 10 controls (cohort 1).