Search Results (134)

Background: The molecular concordance between primary lung adenocarcinoma and metastatic lesions remains incompletely characterized despite its direct implications for precision oncology and biopsy-driven therapeutic decision-making. This prospective monocentric paired-sample study evaluated genomic concordance between primary lung adenocarcinoma and synchronous thoracic metastatic lesions using targeted next-generation sequencing (NGS). Methods: We identified 27 treatment-naïve patients with histologically confirmed lung adenocarcinoma who underwent paired molecular profiling of the primary tumor and a synchronous thoracic metastatic site (pleural or intrapulmonary). DNA and RNA were analyzed using validated institutional NGS platforms. Genomic alterations, including clinically actionable oncogenic drivers consistently covered by the sequencing panel used in each pair, were compared across matched samples. Concordance was assessed using exact binomial confidence intervals, Cohen’s κ statistics, McNemar tests, and paired Wilcoxon signed-rank tests. Results: Actionable driver alterations were identified in 17 of 27 patients (63.0%; 95% CI 42.4–80.6), including EGFR mutations (40.7%), KRAS alterations (18.5%), and one ALK gene rearrangement (3.7%). TP53 concurrent mutations were detected in 14 cases (51.9%). Across all 27 paired samples, driver-level concordance was 100% (95% CI 87.2–100), with perfect agreement for EGFR, KRAS, and ALK alterations (κ = 1.00). TP53 mutations showed high concordance (92.9%; κ = 0.85), while CNVs were concordant in 88.0% of evaluable pairs. Variant allele frequency (VAF) comparisons, adjusted for tumor cellularity, further supported the apparent clonal stability of driver alterations across paired samples. Conclusions: This study demonstrates very high molecular concordance between primary lung adenocarcinomas and their synchronous pleural or intrapulmonary metastases. The observed 100% concordance of actionable driver alterations across paired specimens supports the clinical reliability of thoracic metastatic biopsies for baseline molecular profiling in treatment-naïve disease. Although limited by sample size, these findings support the biological stability of actionable driver alterations during early thoracic metastatic dissemination. Full article

Birt–Hogg–Dubé syndrome (BHDS) is a hereditary cancer syndrome caused by pathogenic variants in the FLCN gene. BHDS is characterized by clinical heterogeneity and similarities with other non-hereditary diseases, which can complicate diagnosis. The aim of our study was to analyze FLCN variants in Russian patients and select the optimal diagnostic approach. We studied 121 unrelated patients suspected for BHDS and 29 of their relatives. Germline variants were analyzed using Sanger sequencing and Multiplex Ligation-dependent Probe Amplification (MLPA). Variant annotation was performed according to the ACMG and AMP recommendations. Pathogenic and likely pathogenic (P/LP) FLCN variants were identified in 20.7% of patients, including six new variants. The distribution of FLCN variants in our cohort was consistent with data obtained from other authors. The mean age of patients with P/LP variants was higher than of those without: 46.91 versus 33.8 years (p < 0.05), suggesting the necessity to apply diagnostic criteria in young patients more carefully. The most common clinical manifestation of BHDS was pulmonary cysts/pneumothorax, while the most informative were alterations involving at least two of three organ systems, which was present in all patients with the P/LP variants, but only in 54% without them (p = 0.001). BHDS diagnostics involves sequencing exons 4–14 of the FLCN gene in patients with proposed clinical criteria. If the result is negative, extensive FLCN deletions are excluded using MLPA, and, in the absence of CNV, WGS is performed. Full article

Background/Objectives: Genomic alterations play a central role in diagnosis, prognostication, and therapeutic planning for hematolymphoid malignancies. At our tertiary care center, frontline genomic testing relies on optical genome mapping, karyotyping, and fluorescence in situ hybridization, with targeted next-generation sequencing (NGS) performed externally. To provide more comprehensive genomic profiling, we evaluated two large-panel NGS platforms and subsequently performed a clinical validation of the selected assay. Methods: The Illumina PanHeme DNA panel and the SOPHiA Genetics Community Myeloid Solution were compared using 24 bone marrow aspirate specimens with previously characterized alterations, including single nucleotide variants (SNVs), insertions/deletions (indels), and copy number variants (CNVs). The selected panel underwent full analytical validation using 60 specimens. Results: Both panels demonstrated excellent concordance for SNVs and indels, with comparable analytical performance and workflow. CNV calling with SOPHiA was notably strong. Platform selection was influenced by practical considerations, including panel content and cost, leading to a preference for further evaluation of the Illumina assay. Clinical validation of the Illumina PanHeme DNA panel, along with a complementary RNA Exome panel, was subsequently performed. Sequence variant detection showed 100% concordance with orthogonal testing, while CNV detection was variable, reflecting known limitations of targeted NGS. The RNA panel detected all expected fusion transcripts. Conclusions: These findings demonstrate robust analytical performance of both evaluated DNA panels. Clinical validation of the Illumina PanHeme DNA and RNA Exome assays supports their use for comprehensive molecular profiling of hematologic malignancies. Full article

Cutaneous T-cell lymphoma (CTCL), primarily mycosis fungoides (MF) and Sézary syndrome (SS), has long been characterized as a neoplasm of mature memory T cells, based on monoclonal T-cell receptor (TCR) rearrangements and tissue-resident memory (TRM)/central memory (TCM) T-cell phenotypes. This review synthesizes converging population-genetic, multi-omic, and single-cell evidence to argue that this characterization is incomplete and that a progenitor-based model better accounts for the full spectrum of disease biology. We present evidence that initiating mutations arise in hematopoietic stem or early lymphoid progenitor survive thymic selection, and diversify after TCR assembly, resulting in branched evolution across both blood and skin. In SS, paired analyses reveal > 200 shared variants between CD34⁺ progenitors and Sézary cells, as well as signal-joint T-cell receptor excision circle (sjTREC) positivity, providing direct progenitor-level evidence. In MF, convergent signals, multiple malignant clonotypes per lesion, greater blood–skin than skin–skin clonotype overlap, and compartment-specific CNV subclones, implicate hematogenous seeding and reseeding. Population-scale lymphoid clonal hematopoiesis and lymphoid-pattern mosaic chromosomal alterations define a compatible antecedent state. Spatial single-cell atlases and trajectory analyses map site-conditioned programs in skin, including Th2-skewed cytokines, microbial responses, and UV signatures, that select and expand subclones and explain inter- and intra-patient heterogeneity. This framework reconciles mature immunophenotypes with upstream initiation and clarifies why compartment-focused therapies often reshape rather than eradicate disease. It yields testable predictions and actionable implications: trials should pair multicompartment cytoreduction with strategies that attenuate progenitor-derived reservoirs, restore immune balance, and repair skin barrier dysfunction. A progenitor-initiated, niche-adapted model provides a coherent scaffold for more durable control in CTCL. Full article

Background: Evaluation of chromosome aneuploidy and gene-level copy number alterations for diagnosis, prognosis, and therapeutic decision-making in solid tumors is the standard of care. Chromosomal microarray (CMA), next-generation sequencing (NGS), immunohistochemistry (IHC), and fluorescence in situ hybridization (FISH) are the gold standard for detecting these variants in tumor tissue. In contrast to most solid tumors, cancers of the central nervous system (CNS) pose a unique challenge for effective detection via plasma due to the blood–brain barrier (BBB), with the additional challenges of brain biopsy or surgery being highly invasive and posing a significant risk to the patient. The Belay Ascent™ liquid biopsy test uses low-pass whole-genome sequencing (LP-WGS) to report on chromosome arm-level aneuploidy and gene-level copy number variants (CNVs) in cerebrospinal fluid (CSF) to inform diagnosis, prognosis, and therapeutic decision-making in CNS tumors. Methods: This study presents the equivalence of Ascent™ in detecting chromosome arm-level aneuploidy and gene-level CNVs using 48 tissue specimens followed by a clinical validation using a cohort of 32 CSF specimens with matched tissue-based tumor profiling information. Results: Equivalence of Ascent™ in detecting chromosome arm-level aneuploidy and gene-level CNVs using 48 tissue specimens was shown to have 100% and 97% positive percent agreement (PPA), respectively, compared to the gold standard of CMA/NGS. The validation cohort of 32 CSF specimens demonstrated 78% and 90% PPA for aneuploidy and gene-level CNVs, respectively. Clinical impact of Ascent™ was demonstrated, with 243 production cases able to inform the diagnosis and management of CNS tumors with high accuracy. Conclusions: Given the paucity of cells in CSF, limiting the use of karyotyping, CMA, IHC, and FISH, the Belay Ascent™ test provides a highly sensitive novel minimally invasive method for the evaluation of chromosome aneuploidy and gene-level CNVs in CSF. Full article

Background and Objectives: Hepatoblastoma (HB) is a rare pediatric liver cancer. Complete resection and chemotherapy are standard treatments, but many patients in developing countries present with unresectable tumors and show poor responses to conventional chemotherapy. Identifying somatic alterations in HB may help develop targeted molecular therapies. Materials and Methods: Exome sequencing was conducted on 34 HB patient samples to identify somatic mutations and copy number variations (CNVs) and to evaluate their relationships with clinical outcomes, including survival. Results: HB tumors showed a low mutational burden but a high rate of CNVs, averaging 181.5 CNVs compared to 3.6 somatic mutations per tumor. CNVs were enriched in pathways involved in transcription, differentiation, and development. The most common alterations were missense mutations in KMT2D (18%), CTNNB1 (12%), and MUC16 (3%). KMT2D mutations occurred more frequently than CTNNB1 mutations in this cohort. Patients with KMT2D or CTNNB1 mutations generally had better overall survival and longer disease-free intervals. Deletions of ZNF429 or FGD4 were linked to shorter survival in the cohort. Validation with an external dataset confirmed significant downregulation of FGD4 expression in HB samples, correlating with poorer survival. Conclusions: This study broadens the understanding of somatic alterations in HB patients, offering insights into the molecular mechanisms behind HB development and highlighting the potential of CNV profiling and FGD4 deletions as prognostic factors in HB. Full article

Background: Comprehensive genomic profiling (CGP) is increasingly used in precision oncology to identify actionable genomic alterations and guide targeted therapies in solid tumors. However, the clinical implementation of CGP assays requires rigorous analytical validation to ensure accurate and reproducible detection of diverse genomic alterations across heterogeneous tumor samples. Despite rapid advancements in next-generation sequencing technologies, there remains a need for validated CGP platforms that demonstrate reliable performance and readiness for routine clinical use. Methods: This study evaluated the analytical and clinical performance of a CGP assay capable of detecting multiple genomic alteration types, including single nucleotide variants (SNVs), insertions/deletions (Indels), copy number variations (CNVs), gene fusions, and tumor mutational burden (TMB). Validation was conducted using patient-derived 117 FFPE tumor samples, external proficiency testing materials, and reference standards. Assay performance was assessed through comparison with orthogonal methods and through evaluation of reproducibility, limit of detection, and TMB concordance. Results: The assay demonstrated excellent analytical performance, achieving 100% sensitivity, specificity, and accuracy for variant detection across evaluated samples. Strong concordance was observed for TMB estimation (R² = 0.9925), with consistent classification of TMB-high cases. The assay showed robust inter- and intra-run reproducibility and reliable detection of low-frequency variants. Limit-of-detection (LOD) analysis confirmed accurate SNV detection at approximately 1% variant allele frequency and reliable RNA fusion detection at low input levels. Conclusions: The validated CGP assay provides accurate, reproducible, and comprehensive detection of clinically relevant genomic alterations in solid tumors. These results support its suitability for routine clinical deployment, enabling reliable genomic profiling to inform precision oncology treatment decisions. Full article

Copy number variants (CNVs) are large-scale genomic alterations that contribute substantially to genetic diversity and may influence phenotypic variation in livestock. This study investigated the genome-wide CNV landscape of three Vietnamese indigenous chicken breeds. Whole-genome sequencing on the Illumina platform (3–5× coverage) was performed on 24 individuals from Dong Tao (DT), Cay Cum (CC), and Ri (RI) breeds. A total of 1743 CNVs were detected, clustering into 315 copy number variation regions (CNVRs). Most CNVRs were rare, with 31.7% present in only one animal among breeds. Across the genome, 122 unique CNVRs were distributed over 28 chromosomes, predominantly the first five. Losses were the most frequent type (45.9%), followed by gains (39.3%), and mixed events (14.8%). Within these CNVRs, 3633 genes were identified. In DT and RI, CNVR-embedded genes included several candidates, potentially related to adaptability, development, and phenotypic diversification. Notably, DT harbored genes such as EGLN1, OASL, GPX1, DUOX1/DUOXA2 (adaptation, stress/immune response) and LRP4, ZIC1, ZIC4, JARID2, KMT2C, OGN, OMD, and PLOD2 (developmental and skeletal traits), whereas in RI they included genes such as CACNA1S, CALCR, CAPN3, and MAPK13/MAPK14, which may contribute to muscle, bone, and physiological regulation. Functional enrichment analysis revealed numerous genes and Quantitative Trait Loci (QTLs) associated with metabolic, developmental, and immune-related pathways. This study provides the first comprehensive genome-wide CNV profile of Vietnamese indigenous chickens and offers a valuable genomic resource for investigating the genetic basis of breed-specific and adaptive phenotypes. Full article

Background: Predicting genomic alterations from routine hematoxylin and eosin (H&E) whole-slide images (WSIs) may help triage molecular testing. Methods: We retrospectively enrolled 437 patients at Osaka Metropolitan University Hospital across 26 cancers, matched with clinical gene-panel data. We curated 1023 binary endpoints across SNV, CNV, and SV categories. We extracted slide embeddings from five pathology foundation models (Prism, GigaPath, Feather, Chief, and Titan) using a unified feature extraction pipeline and benchmarked them using a lightweight downstream Multi-Layer Perceptron (MLP) classifier. Using the best-performing patch feature system, we trained a multi-instance learning model to assess incremental benefit. Results: Titan achieved the highest and most stable transfer performance, with a median endpoint-wise Area Under the Receiver Operating Characteristic curve (AUROC) of 0.77 in the slide benchmarking; at the patch-level, prediction of APC_SNV reached an AUROC of 0.916, and prediction of KRAS_SNV reached an AUROC of 0.811 on the held-out test set. Conclusions: In a heterogeneous clinical gene-panel setting, pathology foundation models can provide strong baseline genomic-prediction signals without additional fine-tuning. We propose a practical, deployment-oriented two-stage workflow: rapid slide-embedding screening to prioritize robust representations and candidate endpoints, followed by patch-level training for high-value tasks where additional performance gains and interpretable regions are clinically worthwhile. Full article

Background: Hepatocellular carcinoma (HCC) stands as a prevalent global health issue with increasing incidence and mortality rates. Hepatocellular carcinoma (HCC) exhibits profound molecular and clinical heterogeneity, which limits the effectiveness of current therapeutic strategies. Circadian rhythm disruption has been implicated in metabolic reprogramming, proliferation, and immune modulation in cancer, but its role in shaping HCC heterogeneity remains poorly defined. Methods: Four public HCC transcriptomic cohorts (TCGA-LIHC, CHCC, LIRI, LICA) were integrated using RMA normalization and ComBat for batch correction. Consensus clustering based on 31 core circadian clock genes (CCGs) identified robust molecular subtypes. Multi-omics characterization—including genomic alterations, pathway activity (GSEA/GSVA), immune microenvironment profiling (CIBERSORT, EPIC, MCP-counter, xCell), and drug-sensitivity prediction (pRRophetic/oncoPredict)—was performed to delineate subtype-specific biological properties. A nine-gene CCG-based RiskScore model was constructed using LASSO Cox regression to internally validate subtype robustness and intra-subtype risk stratification. Results: Using consensus clustering of 31 core CCGs in TCGA-LIHC and three independent validation cohorts (CHCC, LIRI, LICA), we identified three reproducible subtypes—Cluster-1 (metabolic–quiescent), Cluster-2 (transition–intermediate), and Cluster-3 (proliferation–inflammatory)—which were recapitulated across cohorts and showed distinct overall survival (Cluster-3 worst; log-rank p values significant across datasets). Multi-omic characterization revealed that Cluster-3 exhibits the highest tumor mutational burden and CNV burden with enrichment of TP53/AXIN1/TERT alterations, strong activation of cell-cycle, E2F, and G2M programs, and an immune-hot yet immunosuppressed microenvironment enriched for TAMs, Tregs and MDSCs. By contrast, Cluster-1 shows relative genomic stability, dominant hepatic metabolic signatures (fatty-acid oxidation, bile-acid and xenobiotic metabolism) and an immune-cold phenotype. Single-cell mapping linked ALAS1 expression to malignant hepatocytes predominating in Cluster-1, whereas NONO and CSNK1D localized to stromal (CAFs/TECs) and both malignant/immune compartments respectively in Cluster-3, providing a cellular mechanism for subtype-specific metabolism, angiogenesis and immune modulation. Finally, a nine-gene CCG-based RiskScore validated prognostic stratification and drug-sensitivity predictions indicated subtype-specific therapeutic vulnerabilities (notably increased predicted TKI sensitivity in Cluster-3). Conclusion: In conclusion, this study proposes a robust circadian rhythm-based molecular classification of hepatocellular carcinoma, revealing three biologically and clinically distinct subtypes characterized by divergent genomic alterations, metabolic programs, immune microenvironment states, and prognostic patterns. By integrating bulk and single-cell transcriptomic data, we identify subtype-specific roles of key circadian regulators—including ALAS1, NONO, and CSNK1D—in shaping tumor metabolism, proliferation, stromal remodeling, and immune suppression. These findings highlight circadian dysregulation as a potential upstream factor associated with HCC heterogeneity and provide a conceptual framework for developing subtype-tailored mechanistic studies and circadian-informed therapeutic strategies. Full article

Background/Objectives: Head and neck cancer (HNC) represents the seventh most common cancer diagnosis globally, yet current treatments, including surgery, radiation, and immunotherapy, have shown limited improvement in outcomes. Drug repurposing offers a cost-effective strategy to identify new therapeutic options by leveraging existing medications with known safety profiles. Within this study, we developed the GARD pipeline (Genomic Alteration-based Repurposing for Drugs), designed to uncover repurposing candidates for HNC using genomic and network-based approaches. Methods: GARD integrates multi-omics data from The Cancer Genome Atlas (TCGA), including copy number variation (CNV) and somatic mutations (SOM). The cohort was stratified by human papillomavirus (HPV) status. Risk-associated genes were identified and then expanded via high-confidence protein–protein interaction (PPI) networks. Top candidate genes were filtered through comprehensive analysis of publicly available literature data in PubMed using LLMs to validate the relationship between the identified genes and HNC. The top risk genes and their network-expanded neighbors were mapped against DrugBank, and through statistical significance testing and literature validation, established significant drug–gene associations. Results: Significant genes associated with HNC, inferred by genomics alteration, were identified across HPV-positive and HPV-negative subgroups, such as PIK3CA, SOX2, TP53, EIF4G1, TLR7, CLDN1, PRKCI, and EPHA2. Further expansion through the PPI network identified other targetable genes such as EGFR, ERBB2, and the FGFRs. Literature-based validation efforts ensured confidence in the gene–disease association. Drug–gene mapping revealed candidates spanning those already in clinical trials for HNC (e.g., Afatinib, Cabozantinib, Dasatinib, Brigatinib, Lenvatinib, Capivasertib, and Erdafitinib) and emerging or repurposing candidates (Amuvatinib, XL765 (Voxtalisib), Golotimod, Artenimol, Quercetin, and Acetylsalicylic Acid), offering opportunities for precision repurposing. Conclusions: The GARD pipeline demonstrates a genomics-driven, network-informed framework for systematic drug repurposing in HNC. HPV stratification enhances precision, literature-based validation strengthens confidence, and integrated drug mapping enables refinement of existing therapies and discovery of novel candidates for personalized treatment strategies. Code Availability: The full implementation of the GARD pipeline, including preprocessing scripts, statistical analysis modules, and visualization tools, is publicly available on GitHub. Full article

Background: Neurodevelopmental disorders (NDDs) are a heterogeneous group of conditions characterized by cognitive, behavioral, and developmental impairments, frequently linked to structural genomic alterations. Copy number variants (CNVs) involving chromosome 16, particularly the short arm 16p, are recognized contributors to neurodevelopmental variability. Despite increasing international evidence, data from Italian clinical cohorts are still limited. Methods: We investigated 1200 patients referred for genetic evaluation due to suspected NDDs, including autism spectrum disorder (ASD), intellectual disability (ID), global developmental delay, and language impairment. All individuals underwent array comparative genomic hybridization (a-CGH) analysis, and identified variants were correlated with detailed clinical, cognitive, and behavioral assessments. The analysis focused on recurrent CNVs at 16p11.2, 16p13.3, and 16p13.11, regions containing dosage-sensitive genes relevant to neurodevelopment. Results: CNVs involving the 16p region were identified in 96 patients (8% of the cohort), encompassing both deletions and duplications. Deletions were mainly associated with developmental delay, language deficits, and ASD-related features, whereas duplications were more frequently linked to behavioral dysregulation, attentional deficits, and variable cognitive impairment. Marked phenotypic variability was observed among individuals carrying similar CNVs, suggesting the contribution of modifying genetic or environmental factors. In a subset of patients, additional CNVs were identified, potentially exacerbating clinical severity, consistent with the two-hit model. Conclusions: This study confirms a strong association between recurrent 16p CNVs and a wide spectrum of neurodevelopmental phenotypes in an Italian clinical cohort. The findings emphasize the diagnostic utility of systematic genomic screening and the importance of an integrated genotype–phenotype approach to improve clinical interpretation, management, and genetic counseling in NDDs. Full article

Background: idiopathic pulmonary fibrosis (IPF) causes progressive and irreversible changes in the lung parenchyma, leading to respiratory failure. Its pathogenesis involves several damage/repair mechanisms leading to fibrosis, whilst alterations of genes implicated in these processes contribute to the development of the disease. At present, next-generation sequencing (NGS) analyses investigate single-nucleotide or small indel variants, and no evaluation of genomic rearrangements has been so far reported. Methods: In order to identify predisposing variants, we analyzed—both by NGS and by comparative genomic hybridization/single-nucleotide polymorphism (CGH-SNP array) array—37 patients with a diagnosis of familial pulmonary fibrosis. Results: a total of 17 patients (46%) harbored copy number variations (CNVs), 10 (27%) did not harbor any CNVs, 5 (13.5%) showed a mosaic deletion of the Y chromosome, and 5 (13.5%) showed a run of homozygosity (ROH). NGS identified causative variants (including a novel one) in five patients (5/37, 13.5%) and confirmed the high prevalence of MUC5B promoter polymorphism rs35705950, including the detection of a previously unreported form in IPF SNP (indicated as “novel” in the main text), rs141420125 (23/37; 62%). Conclusions: CGH-SNP array identified CNVs containing genes involved in mechanisms (i.e., oxidative stress, mitophagy, NF-Kb pathway) that have been shown to play a role in the pathogenesis of IPF. Therefore, the application of CGH-SNP array or other quantitative tests should be considered in the diagnostic setup of these patients Full article

Neurofibromatosis type 1 (NF1) predisposes to a spectrum of peripheral nerve sheath tumors, ranging from benign plexiform neurofibromas (PN) to atypical neurofibromatous neoplasms of uncertain biological potential (ANNUBP) and malignant peripheral nerve sheath tumors (MPNST). Tumorigenesis follows a multistep molecular cascade initiated by biallelic NF1 inactivation, followed by CDKN2A loss and disruption of the Polycomb Repressive Complex 2 (PRC2). These events guide chromatin remodeling, widespread epigenetic dysregulation, and activation of oncogenic pathways such as RAS/MAPK and PI3K/AKT. Here, we integrate genomic, transcriptomic, and epigenomic studies to delineate the molecular trajectories underlying tumor progression and to define promising biomarkers for the early detection of malignant transformation. Emerging liquid biopsy approaches, based on circulating tumor DNA (ctDNA) analyses, reveal distinctive copy number variations (CNVs) and methylation patterns that mirror tissue-derived profiles, enabling the detection of malignant transformation. Together, these findings support a model in which cumulative genetic and epigenetic alterations drive the PN–ANNUBP–MPNST continuum. They also underscore the value of multi-omics and liquid biopsy-based strategies to improve early diagnosis, patient risk stratification, and personalized management of NF1-associated tumors, thereby advancing precision medicine in this complex disease spectrum. Full article

Homologous recombination deficiency (HRD) resulting from inactivation of BRCA1/2 genes promotes chromosomal instability and renders tumor cells susceptible to platinum derivatives and PARP inhibitors (PARPi). The contribution of alterations in other homologous recombination repair (HRR) genes to HRD remains understudied. This investigation aimed to analyze the spectrum of mutations in 34 HRR genes in prostate carcinomas (PCs) and study the relationship between HRR status and HRD. HRR mutations and HRD scores were examined by NGS in 1131 and 680 PCs, respectively. Pathogenic or likely pathogenic variants in HRR genes were detected in 216/1131 cases (19.1%). HRD, defined by an HRD score cut-off of ≥42, was observed more frequently in HRR-mutated than in wild-type tumors (23/120 (19.2%) vs. 29/560 (5.2%), p < 0.0001). The highest HRD scores were detected in PCs with biallelic inactivation of the BRCA2 or PALB2 genes, as well as in tumors with BRIP1 mutations. HRD was also occasionally seen in PCs with ATM, NBN, FANCM, BRCA1 and CDK12 alterations, but never in cases with CHEK2 mutations. HRD was significantly more associated with aggressive PC features than HRR mutations. The majority of CDK12-mutated tumors exhibited a distinct type of copy number variations (CNV)–a tandem duplication phenotype. Our study suggests that the selection of PC patients for PARPi treatment requires a significant revision of existing attitudes towards tumor genetic profiling. Full article