biostudies-arrayexpressGenomix4Life Genomix4LifeHomo sapiensNextflow Duet pipeline version 1.3.0https://www.ebi.ac.uk/biostudies/studies/E-MTAB-15437Prostate cancer (PCa) is one of the most common malignancies in men, with familial forms accounting for nearly 20% of cases. Early detection and risk stratification remain challenging, especially in individuals with a genetic predisposition. In this pilot study, we evaluated the feasibility and clinical relevance of an integrated multi-omic approach by performing whole-genome, strand-specific sequencing of circulating cell-free DNA (cfDNA) from eight patients with confirmed familial PCa. Through an integrated analysis pipeline, we identified 18,878 genetic variants, of which 2,276 were potentially pathogenic. Among these, 26 recurrent high-impact mutations—such as stop-gain and start-loss variants—were found in genes including MUC4, MCM9, and SKA3. Epigenomic profiling revealed widespread hypermethylation in these genes, suggesting transcriptional repression, while allele-specific methylation (ASM) was detected in TTC22, TEX51, WDR89, LAIR2, and SKA3, indicating functional interplay between somatic mutations and local epigenetic regulation. These findings demonstrate the potential of combining genetic and epigenetic data from cfDNA to uncover novel markers for improved stratification and personalized management of familial prostate cancer.biostudies-arrayexpressLibrary Construction - Indexed libraries were prepared from 10 ng purified total cfDNA each using Biomodal duet evoC kit (Biomodal, Chesterford Research Park, Cambridge, United Kingdom) was carried out according to the manufacturer’s instructions.Nucleic Acid Extraction - Cell-Free DNA (cfDNA) was extracted using the QIAamp Circulating Nucleic Acid Kit (Qiagen, Hilden, Germany) according to the manufacturer's protocol.Sequencing - Illumina NovaSeq 6000 System was used to sequence the pooled samples in a 2 × 151 paired end format on a S4 300 Cycles flow cell (llumina, San Diego, CA, USA).Sample Collection - Peripheral whole blood samples were collected from eight patients with familial prostate cancer using Cell-Free DNA BCT tubes (Streck, La Vista, NJ, USA) according to the manufacturer's protocolOrganizationMINSEQE ScoreAssays and DataProcessed DataMAGE-TAB FilesSequence Alignment - Raw sequencing data were processed using Nextflow Duet pipeline version 1.3.0, which integrates genetic and epigenetic information by aligning and merging original and complementary DNA strand sequences.Data Transformation - Reads were aligned to the reference genome (GRCh38Decoy with Gencode v40 annotation) and spike-in controls using BWA-MEM; duplicates were removed with Picard MarkDuplicates. Methylation status at each CpG site was quantified, with accuracy assessed using spike-in controls. Germline variants were called with GATK HaplotypeCaller, somatic variants using Mutect2. Epigenetic calls were preserved from FASTQ to BAM files using MM tagsMetabolomicsUnknownTranscriptomicsGenomicsProteomicsIllumina NovaSeq 6000DNA-seqHomo sapiensGenomix4Life Genomix4LifefalseIntegrative Whole-Genome and Epigenome profiling of cfDNA in Familial Prostate Cancer: Insights from a Pilot StudyProstate cancer (PCa) is one of the most common malignancies in men, with familial forms accounting for nearly 20% of cases. Early detection and risk stratification remain challenging, especially in individuals with a genetic predisposition. In this pilot study, we evaluated the feasibility and clinical relevance of an integrated multi-omic approach by performing whole-genome, strand-specific sequencing of circulating cell-free DNA (cfDNA) from eight patients with confirmed familial PCa. Through an integrated analysis pipeline, we identified 18,878 genetic variants, of which 2,276 were potentially pathogenic. Among these, 26 recurrent high-impact mutations—such as stop-gain and start-loss variants—were found in genes including MUC4, MCM9, and SKA3. Epigenomic profiling revealed widespread hypermethylation in these genes, suggesting transcriptional repression, while allele-specific methylation (ASM) was detected in TTC22, TEX51, WDR89, LAIR2, and SKA3, indicating functional interplay between somatic mutations and local epigenetic regulation. These findings demonstrate the potential of combining genetic and epigenetic data from cfDNA to uncover novel markers for improved stratification and personalized management of familial prostate cancer.2026-06-15T00:00:00Z2026-06-15T01:00:40.105Z2025-08-04T10:58:48.993ZE-MTAB-15437ERP177719EFO_0002944EFO_0004170EFO_0002693EFO_0004917EFO_0005518EFO_0003816EFO_0004184