Background: Familial prostate cancer (PCa) accounts for nearly 20% of all PCa cases and is associated with increased genetic susceptibility and earlier disease onset. However, early detection and risk stratification in genetically predisposed individuals remain challenging. Circulating cell-free DNA (cfDNA) provides a minimally invasive source of tumor-derived genomic and epigenomic information. Integrating multi-omic cfDNA analyses may enhance the discovery of biomarkers relevant to familial PCa biology. Methods: We conducted a pilot feasibility study employing whole-genome, strand-specific sequencing of cfDNA from eight patients with familial PCa. A unified analytical pipeline was used to jointly profile genomic alterations and epigenomic features. Variant calling, methylation mapping, and allele-specific methylation (ASM) analysis were performed to identify somatic mutations, characterize epigenetic dysregulation, and explore potential interactions between genetic and epigenetic mechanisms. Results: Sequencing revealed 18,878 genetic variants, including 2276 potentially pathogenic alterations. We identified 26 recurrent high-impact mutations, such as stop-gain and start-loss variants, in genes including MUC4, MCM9, and SKA3. Epigenomic profiling demonstrated widespread gene-specific hypermethylation, consistent with transcriptional repression in these loci. ASM events were detected in TTC22, TEX51, WDR89, LAIR2, and SKA3, suggesting coordinated interactions between somatic variation and epigenetic regulation in familial PCa. Conclusions: This proof-of-concept study highlights the feasibility and potential of integrating whole-genome and epigenome profiling of cfDNA to decode the molecular architecture of familial prostate cancer. By jointly capturing genomic alterations and epigenetic signatures, including allele-specific methylation, this multi-omic liquid biopsy approach supports a high-resolution exploration of biologically relevant molecular features. Moreover, this integrated profiling strategy provides a minimally invasive and clinically scalable tool that may substantially improve risk assessment. These findings offer a promising foundation for future validation studies in larger cohorts, with the aim of advancing multi-omic cfDNA analysis as a next-generation technology in the field of precision oncologic epigenetics.
Truda et al. (Fri,) studied this question.