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Updated: Jan 13, 2026

Visualization of DNA Repair Proteins Interaction by Immunofluorescence
Published on: June 26, 2020
Functional footprints of homologous recombination deficiency in prostate cancer revealed by ctDNA fragmentation and
Georgios Vlachos1,2, Tina Moser1, Isaac Lazzeri1,2
1Institute of Human Genetics, Diagnostic & Research Center for Molecular BioMedicine, Medical University of Graz, Graz, Austria.
Background:
Homologous recombination deficiency (HRD) is a predictive biomarker for response to PARP inhibitors and platinum-based therapies in prostate cancer (PCa). However, current diagnostic approaches, often limited to BRCA1/2 mutation testing or genomic scars, fail to capture the full spectrum of HRD. Tissue-based testing is further hampered by tumour heterogeneity and biopsy limitations in patients with metastatic bone disease. This study aimed to develop a noninvasive, multimodal ctDNA-based strategy for comprehensive HRD profiling in advanced PCa.
Methods:
We analysed plasma-derived ctDNA from 106 patients with metastatic PCa. The approach integrated targeted sequencing of homologous recombination repair (HRR) genes, low-pass whole genome sequencing for genomic instability scores (GIS), whole-exome sequencing for mutational signature analysis, and cfDNA fragmentomics, including chromatin accessibility profiling.
Results:
BRCA2 was the most frequently altered HRR gene, frequently co-occurring with PTEN loss. High GIS was associated with BRCA2/RB1 loss, increased somatic copy number alterations, and poor overall survival. HRD tumours were enriched for mutational signatures SBS3 and ID6, displayed increased dinucleosome-length fragments, and showed reduced accessibility at zinc finger transcription factor binding sites. A fragmentomics-based classifier identified HRD-positive cases with high accuracy.
Conclusions:
Our findings support the use of multimodal ctDNA profiling as a non-invasive approach to identify HRD in prostate cancer. The integration of mutation, genomic instability, and fragmentomic features provides a broader functional view of HRD and may enhance patient stratification for targeted therapies.
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