Homologous recombination deficiency (HRD) is a key biomarker associated with increased sensitivity to PARP inhibitors (PARPi) in advanced epithelial ovarian cancer. Accurate identification of HRD status is essential for selecting patients most likely to benefit from these therapies. Current diagnostic approaches combine sequencing to detect mutations in homologous recombination repair genes—particularly BRCA1 and BRCA2—with genome-wide analysis of structural genomic alterations indicative of HRD. This review briefly outlines the biological basis of HRD and its clinical significance and then focuses on currently available assays for HRD assessment. We compare their molecular strategies, including the use of targeted gene panels and genomic instability metrics such as loss of heterozygosity, telomeric allelic imbalance, and large-scale state transitions. The review also highlights the strengths and limitations of each platform and discusses their role in guiding clinical decision-making. Challenges related to dynamic tumor evolution and the interpretation of HRD status in recurrent disease settings are also addressed.

Background/Objectives: Despite advances in hepatocellular carcinoma (HCC) management, prognosis remains poor. Advanced-stage diagnosis often excludes curative treatments, and current biomarkers (e.g., alpha-fetoprotein [AFP]) have limited utility in early detection. Liquid biopsy has emerged as a promising cancer detection tool, with circulating cell-free DNA (ccfDNA) showing significant diagnostic potential. This proof-of-concept study aimed to investigate the potential role of tumor fraction (TF) within ccfDNA as a biomarker in HCC patients. Methods: A total of sixty patients were recruited, including thirteen with chronic liver disease (CLD), twenty-four with cirrhosis, and twenty-three with HCC. Plasma samples were collected, and ccfDNA was extracted for shallow whole genome sequencing (sWGS) analysis. The TF was calculated by focusing on somatic copy number alterations (SCNAs) within the ccfDNA. Results: Among patients with CLD and cirrhosis (n = 37), ctDNA was undetectable in all but one cirrhotic patient who exhibited a significant tumor fraction (TF) of 17% and subsequently developed HCC. Conversely, five out of twenty-three HCC patients (21.7%) displayed detectable ctDNA with TF levels ranging from 3.0% to 32.6%. Patients with detectable ctDNA were characterized by more aggressive oncological features, including a higher number of nodules (p = 0.005), advanced-stage disease (60% BCLC C, p = 0.010), and poorer response to therapy (80% PD, p = 0.001). Moreover, the overall survival (OS) was significantly reduced in patients with detectable ctDNA (median OS: 17 months; CI 95% 4.5–26.5) compared to those without (median OS: 24.0 months; CI 95% 7.0–66.0; log-rank p = 0.002). Conclusions: Our results suggest that the analysis of TF by sWGS is a promising non-invasive tool for the identification of HCC with aggressive clinical behavior, whereas it is not sensitive enough for early HCC detection. This molecular assay can improve prognostic stratification in HCC patients.

Shallow whole-genome sequencing (sWGS) offers a cost-effective approach to detect copy number alterations (CNAs). However, there remains a gap for a standardized workflow specifically designed for sWGS analysis. To address this need, in this work we present SAMURAI, a bioinformatics pipeline specifically designed for analyzing CNAs from sWGS data in a standardized and reproducible manner. SAMURAI is built using established community standards, ensuring portability, scalability, and reproducibility. The pipeline features a modular design with independent blocks for data preprocessing, copy number analysis, and customized reporting. Users can select workflows tailored for either solid or liquid biopsy analysis (e.g. circulating tumor DNA), with specific tools integrated for each sample type. The final report generated by SAMURAI provides detailed results to facilitate data interpretation and potential downstream analyses. To demonstrate its robustness, SAMURAI was validated using simulated and real-world data sets. The pipeline achieved high concordance with ground truth data and maintained consistent performance across various scenarios. By promoting standardization and offering a versatile workflow, SAMURAI empowers researchers in diverse environments to reliably analyze CNAs from sWGS data. This, in turn, holds promise for advancements in precision medicine.

Background: Bioinformatics pipelines for variant calling have undergone significant advancements due to the decreasing costs of next-generation sequencing. Accurate mutation detection is crucial for personalised medicine in cancer, particularly in assignment of therapy. Somatic variant calling, however, remains challenging due to diverse cancer types, heterogeneity, complex mutational profiles, and unpredictable sequencing errors. A dataset of fully characterised tumoral genomes and sequencing reads, large enough to represent the variability inherent in different cancer types, is still lacking, even considering synthetic data. The lack of such datasets hampers rigorous evaluation, benchmarking and optimization of variant callers for specific cancer types. Results: The contribution of this work is twofold. First, we conducted a comprehensive analysis of nine somatic sample simulators (Synggen, BAMSurgeon, SVEngine, VarSim, Xome-Blender, tHapMix, Pysim-sv, SCNVSim, HeteroGenesis) assessing their ability to control biological parameters , including variants characteristics (type, number, position, length, content, zygosity), and sample characteristics (clonality, contamination); and technical parameters , including reads characteristics (sequencing errors, coverage, base qualities). No single simulator provided complete control over both biological and technical parameters, nor guidance on tuning biological parameters for cancer-specific simulations. Consequently, we developed MOV&RSim, a novel simulator that leverages data-driven information to set variants and reads characteristics, producing realistic tumoral samples, and providing full control on biological and technical parameters. Additionally, we leveraged well-annotated variant databases to create cancer-specific presets that inform the simulator’s parameters for 21 cancer types. Conclusion: This new simulator, containerised with Docker and freely available for academic use, empowers users to define each biological parameter of a tumoral genome and faithfully replicates the variability of technical noise observed in real sequencing reads. The proposed simulator and presets represent the most adaptable and comprehensive framework currently available for generating tumor samples, enabling comprehensive benchmarking and, ultimately, the optimization of somatic variant callers across diverse cancer types.

Background/Objectives: Lyme disease diagnosis remains challenging due to the limitations of current methods. While PCR-based assays are widely used, their sensitivity can be affected by sample type and the inhibition of host DNA. This study aimed to evaluate the feasibility and sensitivity of a CRISPR/Cas12-based detection system for Borrelia burgdorferi sensu lato, comparing its performance with real-time PCR. Methods: DNA from three Borrelia genospecies (B. burgdorferi, B. garinii, and B. afzelii) was amplified targeting the OspA gene. Detection was performed using a Cas12/crRNA system with a fluorescent ssDNA reporter. Sensitivity assays were conducted on serial dilutions of Borrelia DNA, with and without human genomic DNA, and results were compared with qPCR. Results: Direct detection of Borrelia DNA without amplification was not feasible. However, when combined with PCR, the Cas12/crRNA system reliably detected as few as 5 genome copies per reaction. End-point PCR extended to 60 cycles improved detection robustness for B. garinii and B. afzelii, although sensitivity decreased in the presence of human genomic DNA. Conclusions: The Cas12/crRNA-based system offers a sensitive and accessible alternative to qPCR, especially in settings lacking real-time PCR instrumentation. Future developments may include integration with isothermal amplification and microfluidic platforms to enhance direct detection capabilities.