Search PubMedSearch

PubMed · 42265755

The 'Prostate Cancer Screening for People at Genetic Risk of Aggressive Disease' (PATROL) study.

Abstract

BACKGROUND: Inherited (germline) pathogenic and likely pathogenic variants (gPVs) in key genes associated with increased risk of prostate cancer (PCa) now warrant more attentive PCa screening per National Comprehensive Cancer Network (NCCN) guidelines-e.g., BRCA2, HOXB13, ATM, BRCA1, MSH2, MSH6, CHEK2 and TP53. However, the optimal early detection strategy for gPV carriers, including use of age-adjusted PSA thresholds and prostate imaging may be refined. and as a means to investigate novel biomarkers. STUDY DESIGN: 'Prostate Cancer Screening for People at Genetic Risk of Aggressive Disease' (PATROL) is a multicentre, prospective early detection study for individuals at increased risk for PCa due to carrying a gPV in a PCa risk gene. ENDPOINTS: The primary endpoint is to determine the positive predictive value of pre-defined age-directed prostate-specific antigen (PSA) level thresholds and prostate-specific imaging, e.g., multiparametric magnetic resonance imaging (MRI) for clinically significant PCa on biopsy for individuals at risk of PCa due to a gPV. Exploratory endpoints include characterising clinicopathological characteristics of PCa and patient-reported outcomes. Biospecimens will be collected to evaluate emerging clinical and research biomarkers. PATIENTS AND METHODS: Key eligibility includes: individuals aged &#x2265;40&#x2009;years who carry a gPV in an eligible gene, who have no prior diagnosis of PCa, do not have another active malignancy, and provide informed consent. Study procedures include annual physical examination and PSA. Imaging with MRI is optional at baseline and recommended if the PSA level is above the protocol-recommended PSA level threshold. Participants will be offered prostate biopsy for any clinical concern, PSA level >1.0&#x2009;ng/mL if aged <50&#x2009;years; PSA level >1.5&#x2009;ng/mL if aged 50-59&#x2009;years; PSA level >2.0&#x2009;ng/mL if aged &#x2265;60&#x2009;years. If PCa is diagnosed, clinical care is determined by the participant and treating physician. If opting for active surveillance, study procedures will be collected annually for 10&#x2009;years or until definitive treatment. If definitive treatment, study procedures will be collected for an additional 1&#x2009;year. Long-term clinical outcomes will be collected annually until the study closes.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Heather H Cheng, Kara N Maxwell, Keyan Salari, Matthew R Cooperberg, Kristin Follmer, Joanne M Jeter, Grace Jun, Daniel J Lee, Hiten D Patel, Edward M Schaeffer, Alexandra O Sokolova, Erika M Wolff, Daniel W Lin. 2026-06-09. The 'Prostate Cancer Screening for People at Genetic Risk of Aggressive Disease' (PATROL) study.. https://doi.org/10.1111/bju.70334

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans