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PubMed2026

Novel epigenetic loci identified from an epigenome-wide association study underlying brain structural changes in bipolar disorder.

BACKGROUND: DNA methylation influences gene-environment interactions and brain development in bipolar disorder (BD). We aimed to identify BD-associated epigenetic loci and examine their associations with brain structural variation. METHODS: We conducted an epigenome-wide association study (BD group, n = 90; healthy controls group, n = 161) to identify BD-associated DNA methylation loci, and we additionally performed copy number alteration and functional enrichment analyses. The correlations between epigenetic loci and cortical thickness (CT) were assessed using Pearson's partial correlation analysis, and the co-methylation effect of the epigenetic loci identified in the neuroimaging-epigenetic analysis was investigated. FINDINGS: A total of 156 differentially methylated positions (DMPs) and 7 differentially methylated regions were identified, and the genes associated with them were observed to be enriched in biological processes related to muscle hypertrophy and neuronal activity. Significant correlations between the methylation levels of 13 DMPs associated with three genes (miR886, PLEC1, and ICAM5) and the CT of the right postcentral gyrus and inferior frontal gyrus were identified. Specifically, 10 DMPs associated with the CpG island in the upstream region of the miR886 gene showed negative correlations with the right postcentral gyrus CT, implicating miR886-associated CpG-island methylation in regional cortical thinning. CONCLUSION: Epigenetic changes might play an important role in brain structural changes in BD. These multimodal findings nominate miR886-related methylation as a candidate molecular correlate of cortical thinning and warrant replication and mechanistic follow-up in larger, state-diverse cohorts.

Humans↗

PubMed2025

CNV-Finder: Streamlining Copy Number Variation Discovery.

Copy Number Variations (CNVs) play pivotal roles in the etiology of complex diseases and are variable across diverse populations. Understanding the association between CNVs and disease susceptibility is significant in disease genetics research and often requires analysis of large sample sizes. One of the most cost-effective and scalable methods for detecting CNVs is based on normalized signal intensity values, such as Log R Ratio (LRR) and B Allele Frequency (BAF), from Illumina genotyping arrays. In this study, we present CNV-Finder, a novel pipeline integrating deep learning techniques on array data, specifically a Long Short-Term Memory (LSTM) network, to expedite the large-scale identification of CNVs within predefined genomic regions. This facilitates efficient prioritization of samples for time-consuming or costly subsequent analyses such as Multiplex Ligation-dependent Probe Amplification (MLPA), short-read, and long-read whole genome sequencing. We incorporate four genes to establish our methods-Parkin (PRKN), Leucine Rich Repeat And Ig Domain Containing 2 (LINGO2), Microtubule Associated Protein Tau (MAPT), and alpha-Synuclein (SNCA)-which may be relevant to neurological diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), Progressive Supranuclear Palsy (PSP), or related disorders such as essential tremor (ET). By training our models on expert-annotated samples and validating them across diverse cohorts, including those from the Global Parkinson's Genetics Program (GP2) and additional dementia-specific databases, we demonstrate the efficacy of CNV-Finder in accurately detecting deletions and duplications. Our pipeline outputs app-compatible files for visualization within CNV-Finder's interactive web application. This interface enables researchers to review predictions and filter displayed samples by model prediction values, LRR range, and variant count in order to explore or confirm results. Our pipeline integrates this human feedback to enhance model performance and reduce false positive rates. Through a series of comprehensive analyses and validations using visual inspection, MLPA, short-read, and long-read sequencing data, we demonstrate the robustness and adaptability of CNV-Finder in identifying CNVs with regions of varied size, probe density, and noise. Our findings highlight the significance of contextual understanding and human expertise in enhancing the precision of CNV identification, particularly in complex genomic regions like 17q21.31. The CNV-Finder pipeline is a scalable, publicly available resource for the scientific community, available on GitHub (https://github.com/GP2code/CNV-Finder; DOI 10.5281/zenodo.14182563). CNV-Finder not only expedites accurate candidate identification but also significantly reduces the manual workload for researchers, enabling future targeted validation and downstream analyses in regions or phenotypes of interest.

Copy Number Variation (CNV)↗

PubMed2025

MPAC: a computational framework for inferring pathway activities from multi-omic data.

MOTIVATION: Fully capturing cellular state requires examining genomic, epigenomic, transcriptomic, proteomic, and other assays for a biological sample and comprehensive computational modeling to reason with the complex and sometimes conflicting measurements. Modeling these so-called multi-omic data is especially beneficial in disease analysis, where observations across omic data types may reveal unexpected patient groupings and inform clinical outcomes and treatments. RESULTS: We present Multi-omic Pathway Analysis of Cells (MPAC), a computational framework that interprets multi-omic data through prior knowledge from biological pathways. MPAC leverages network relationships encoded in pathways through a factor graph to infer consensus activity levels for proteins and associated pathway entities from multi-omic data, runs permutation testing to eliminate spurious activity predictions, and groups biological samples by pathway activities to allow identifying and prioritizing proteins with potential clinical relevance, e.g. associated with patient prognosis. Using DNA copy number alteration and RNA-seq data from head and neck squamous cell carcinoma patients from The Cancer Genome Atlas as an example, we demonstrate that MPAC predicts a patient subgroup related to immune responses not identified by analysis with either input omic data type alone. Key proteins identified via this subgroup have pathway activities related to clinical outcome as well as immune cell composition. Our MPAC R package enables similar multi-omic analyses on new datasets. AVAILABILITY AND IMPLEMENTATION: The MPAC package is available at Bioconductor https://bioconductor.org/packages/MPAC.

Humans↗

PubMed2025

Regulation of replication timing in Saccharomyces cerevisiae.

In order to maintain genomic integrity, DNA replication must be highly coordinated. Disruptions in this process can cause replication stress which is aberrant in many pathologies including cancer. Despite this, little is known about the mechanisms governing the temporal regulation of DNA replication initiation, thought to be related to the limited copy number of firing factors. Here, we present a high (1-kilobase) resolution stochastic model of Saccharomyces cerevisiae whole-genome replication in which origins compete to associate with limited firing factors. After developing an algorithm to fit this model to replication timing data, we validated the model by reproducing experimental inter-origin distances, origin efficiencies, and replication fork directionality. This suggests the model accurately simulates the aspects of DNA replication most important for determining its dynamics. We also use the model to predict measures of DNA replication dynamics which are yet to be determined experimentally and investigate the potential impacts of variations in firing factor concentrations on DNA replication.

Saccharomyces cerevisiae↗

PubMed2026

Mitochondrial Haplotype Shapes the Trajectory of Ovarian Aging in Genetically Heterogeneous Rats.

Ovarian aging leads to permanent reproductive senescence and systemic hormonal changes that predispose women to age-associated comorbidities. Despite these observations, the intrinsic mechanisms driving age-related ovarian decline are poorly defined. Mitochondrial DNA (mtDNA) mutations and instability are strongly associated with aging; however, it remains unknown if naturally occurring mitochondrial genetic variation influences the trajectory of ovarian aging. To address this, we compared two genetically heterogeneous rat cohorts (OKC-HETB and OKC-HETW) that differ in mitochondrial haplotype on a randomized but equivalently distributed nuclear background. The OKC-HETW haplotype was associated with accelerated loss of primordial follicles and pathological remodeling marked by fibrosis, macrophage infiltration, and multinucleated giant cells. These tissue-level pathologies were paralleled by mitochondrial dysfunction, characterized by decreased respiratory complex activity, ATP production, and mtDNA copy number. Mechanistically, we identified a haplotype-specific defect in mitochondrial genome maintenance. Although TFAM expression was normal, and total TFAM protein was elevated, OKC-HETW ovaries showed reduced mitochondrial TFAM abundance, TFAM-mtDNA binding, and TOMM20, suggesting that impaired TOMM20-mediated import is associated with compromised mitochondrial genomic stability. Longitudinal transcriptomic and proteomic analyses further indicate that mitochondrial haplotype influences the rate of ovarian aging, with OKC-HETW ovaries showing accelerated activation of inflammatory and fibrotic pathways alongside suppressed proteostasis and mitochondrial function. These defects corresponded to impairments in ovulation and a trend toward worsening oocyte quality. Collectively, our findings identify mitochondrial haplotype as a heritable modifier of ovarian aging rate that acts in concert with the nuclear genome, and a putative target for preserving ovarian function and female healthspan.

Animals↗

PubMed2024

Effects of particulate air pollution on BPDE-DNA adducts, telomere length, and mitochondrial DNA copy number in human exhaled breath condensate and BEAS-2B cells.

Traffic-related particulate matter (PM) and polycyclic aromatic hydrocarbons (PAHs) have been linked to respiratory diseases and cancer risk in humans. Genomic damage, including benzo[a]pyrene diolepoxide (BPDE)-DNA adducts as well as alterations in telomere length (TL) and mitochondrial DNA copy number (mtDNA-CN) are associated with respiratory diseases. This study aimed to investigate the association between exposure to traffic-related particulate pollutants and genomic damage in exhaled breath condensate (EBC) in human subjects and a bronchial epithelial cell line (BEAS-2B). Among the 60 healthy recruited subjects, residents living in high-traffic-congested areas were exposed to higher concentrations of PM2.5 (1.66-fold, p < 0.01), UFPs (1.79-fold, p < 0.01), PM2.5-PAHs (1.50-fold, p < 0.01), and UFPs-PAHs (1.35-fold, p < 0.05), than those in low-traffic-congested areas. In line with increased exposure to particulate air pollution, the high-traffic-exposed group had significantly increased BPDE-DNA adducts (1.40-fold, p < 0.05), TL shortening (1.24-fold, p < 0.05), and lower mtDNA-CN (1.38-fold, p < 0.05) in EBC. The observations in the human study linking exposure to PM2.5, UFPs, PM2.5-PAHs, and UFPs-PAHs with the aforementioned biological effects were confirmed by an in vitro cell-based study, in which BEAS-2B cells were treated with diesel exhaust particulate matter (DEP) containing fine and ultrafine PM and PAHs. Increased BPDE-DNA adducts levels, shortened TL, and decreased mtDNA-CN were also found in treated BEAS-2B cells. The shortened TL and decreased mtDNA-CN were in part mediated by decreased transcript levels of hTERT, and SIRT1, which are involved in telomerase activity and mitochondrial biogenesis, respectively. These results suggest that exposure to traffic-related particulate pollutants can cause genomic instability in respiratory cells, which may increase the health risk of respiratory diseases and the development of cancer.

Humans↗

PubMed2024

Genome-wide copy number variation association study in anorexia nervosa.

This study represents the first large-scale investigation of rare (<1% population frequency) copy number variants (CNVs) in anorexia nervosa (AN). Large, rare CNVs are reported to be causally associated with anthropometric traits, neurodevelopmental disorders, and schizophrenia, yet their role in the genetic basis of AN is unclear. Using genome-wide association study (GWAS) array data from the Anorexia Nervosa Genetics Initiative (ANGI), which included 7414 AN case and 5044 controls, we investigated the association of 67 well-established syndromic CNVs and 178 pleiotropic disease-risk dosage-sensitive CNVs with AN. To identify novel CNV regions (CNVRs) that increase the risk of AN, we conducted genome-wide association studies with a focus on rare CNV-breakpoints (CNV-GWAS). We found no net enrichment of rare CNVs, either deletions or duplications, in AN, and none of the well-established syndromic or pleiotropic CNVs had a significant association with AN status. However, the CNV-GWAS found 21 nominally associated CNVRs that contribute to AN risk, covering protein-coding genes implicated in synaptic function, metabolic/mitochondrial factors, and lipid characteristics, like the CD36 (7q21.11) gene, which transports long-chain fatty acids into cells. CNVRs intersecting genes previously related to neurodevelopmental traits include deletions of NRXN1 intron 5 (2p16.3), IMMP2L (7q31.1), and PTPRD (9p23). Overall, given that our study is well powered to detect the CNV burden level reported for schizophrenia, we can conclude that rare CNVs have a limited role in the etiology of AN, as reported for bipolar disorder. Our nominal associations for the 21 discovered CNVRs are consistent with AN being a metabo-psychiatric trait, as demonstrated by the common genetic architecture of AN, and we provide association results to allow for replication in future research.

Humans↗

PubMed2026

Identification and characterization of ectopic chromosomal amplifications in acute myeloid leukemia cell limes using high-throughput chromosome conformation capture screening.

Despite advanced molecular diagnostics, improving outcomes for refractory acute myeloid leukemia (AML) remains challenging. Although many cancer-related genes are identified, their molecular mechanisms are not fully elucidated. Amplification is a mechanism of cancer-associated gene activation, and ectopic gene amplification may have particularly high pathological significance. However, research on ectopically amplified cancer-associated genes in leukemia remains limited. Here, we evaluated the usefulness of high-throughput chromosomal conformation capture (Hi-C) as a screening method for ectopic gene amplification and assessed whether ectopic amplification of cancer-associated genes may represent a general phenomenon in AML. We screened the U-937 and NB-4 cell lines using in situ Hi-C. Regions appearing as "high-intensity bands" in Hi-C contact maps were identified and validated using fluorescence in situ hybridization (FISH). Additionally, copy number variation analysis was performed using whole-genome sequencing (WGS) to extract cancer-associated genes with ectopic amplification. In the U-937, three genomic regions showing "high-intensity bands" were identified and confirmed as ectopic amplifications-including PDCD1LG2 (PD-L2), CD274 (PD-L1), and JAK2; that is, four copies were detected by WGS, and amplification signals were observed by FISH. In the NB-4, four such regions were detected, including MYC and KRAS, with expression level of 498 transcripts per million (TPM) and 34 TPM, respectively. Copy number variation analysis further identified multiple cancer-associated genes with ectopic amplification. Overall, these findings demonstrate the presence of ectopic amplification of cancer-associated genes in AML cell lines and support the usefulness of Hi-C as a screening method for detecting such genomic alterations.

Acute myeloid leukemia↗

PubMed2019

Unique genetic basis of the distinct antibiotic potency of high acetic acid production in the probiotic yeast Saccharomyces cerevisiae var. boulardii.

The yeast Saccharomyces boulardii has been used worldwide as a popular, commercial probiotic, but the basis of its probiotic action remains obscure. It is considered conspecific with budding yeast Saccharomyces cerevisiae, which is generally used in classical food applications. They have an almost identical genome sequence, making the genetic basis of probiotic potency in S. boulardii puzzling. We now show that S. boulardii produces at 37°C unusually high levels of acetic acid, which is strongly inhibitory to bacterial growth in agar-well diffusion assays and could be vital for its unique application as a probiotic among yeasts. Using pooled-segregant whole-genome sequence analysis with S. boulardii and S. cerevisiae parent strains, we succeeded in mapping the underlying QTLs and identified mutant alleles of SDH1 and WHI2 as the causative alleles. Both genes contain a SNP unique to S. boulardii (sdh1 F317Y and whi2 S287*) and are fully responsible for its high acetic acid production. S. boulardii strains show different levels of acetic acid production, depending on the copy number of the whi2 S287* allele. Our results offer the first molecular explanation as to why S. boulardii could exert probiotic action as opposed to S. cerevisiae They reveal for the first time the molecular-genetic basis of a probiotic action-related trait in S. boulardii and show that antibacterial potency of a probiotic microorganism can be due to strain-specific mutations within the same species. We suggest that acquisition of antibacterial activity through medium acidification offered a selective advantage to S. boulardii in its ecological niche and for its application as a probiotic.

Acetic Acid↗

PubMed2025

Genome-wide association study of copy number variations in Parkinson's disease.

OBJECTIVE: To investigate the impact of copy number variations (CNVs) on Parkinson's disease (PD) pathogenesis using genome-wide data and explore their role in sporadic PD. METHODS: We analyzed CNV data from 11,035 PD patients (including 2,731 early-onset PD (EOPD)) and 8,901 controls from the COURAGE-PD consortium using a sliding window CNV-GWAS and genome-wide burden analysis. The independent dataset from the Global Parkinson Genetics Program (GP2) consisted of 23,089 cases and 18,824 controls were used to validate our initial findings. RESULTS: The exploratory dataset identifies multiple CNV regions associated with PD risk. The nominated CNV loci were not confirmed in an independent dataset, except that only a deletion in the PRKN gene, a well-established EOPD locus, remained genome-wide significant and robustly supported. CNV burden analysis showed a higher prevalence of CNVs in PD-related genes in patients compared to controls (OR=1.56 [1.18-2.09], p=0.0013), with PRKN showing the highest burden (OR=1.47 [1.10-1.98], p=0.026). Patients with CNVs in PRKN had an earlier disease onset. Burden analysis with controls and EOPD patients showed similar results. INTERPRETATION: The largest CNV-based GWAS on PD highlights both the promise and pitfalls of array-based CNV detection in PD and underscores the relevance of whole-genome sequencing approaches in resolving the role of CNV in PD. The array-based findings are prone towards false positive findings that might arise either from platform limitations and/or cohort biases. Future studies require improved genotyping resolution and rigorous cross-cohort validation to reliably assess CNV contributions to PD risk.

Journal Article↗

PubMed2025

Temperature and Pressure Shaped the Evolution of Antifreeze Proteins in Polar and Deep Sea Zoarcoid Fishes.

Antifreeze proteins (AFPs) have enabled teleost fishes to repeatedly colonize polar seas. Four AFP types have convergently evolved in several fish lineages. AFPs inhibit ice crystal growth and lower tissue freezing point. In lineages with AFPs, species inhabiting colder environments may possess more AFP copies. Elucidating how differences in AFP copy number evolve is challenging due to the genes' tandem array structure and consequently poor resolution of these repetitive regions. Here, we explore the evolution of type III AFPs (AFP III) in the globally distributed suborder Zoarcoidei, leveraging six new long-read genome assemblies. Zoarcoidei has fewer genomic resources relative to other polar fish clades while it is one of the few groups of fishes adapted to both the Arctic and Southern Oceans. Combining these new assemblies with additional long-read genomes available for Zoarcoidei, we conducted a comprehensive phylogenetic test of AFP III evolution and modeled the effects of thermal habitat and depth on AFP III gene family evolution. We confirm a single origin of AFP III via neofunctionalization of the enzyme sialic acid synthase B. We also show that AFP copy number increased under low temperature but decreased with depth, potentially because pressure lowers freezing point. Associations between the environment and AFP III copy number were driven by duplications of paralogs that were translocated out of the ancestral locus at which AFP III arose. Our results reveal novel environmental effects on AFP evolution and demonstrate the value of high-quality genomic resources for studying how structural genomic variation shapes convergent adaptation.

Animals↗

PubMed1976

Synethesis and integration of viral DNA in chicken cells at different time after infection with various multiplicities of avian oncornavirus.

To see if integration of the provirus resulting from RNA tumor virus infection is limited to specific sites in the cell DNA, the variation in the number of copies of virus-specific DNA produced and integrated in chicken embryo fibroblasts after RAV-2 infection with different multiplicities has been determined at short times, long times, and several transfers after infection. The number of copies of viral DNA in cells was determined by initial hybridization kinetics of single-stranded viral complementary DNA with a moderate excess of cell DNA. The approach took into account the different sizes of cell DNA and complementary DNA in the hybridization mixture. It was found that uninfected chicken embryo fibroblasts have approximately seven copies, part haploid genome of DNA sequences homologous to part of the Rous-association virus 2 (RAV-2) genome. Infection with RAV-2 adds additional copies, and different sequences, of RAV -2- specific DNA. By 13 h postinfection, there are 3 to 10 additional copies per haploid genome. This number can not be increased by increasing the multiplicity of infection, and stays relatively constant up to 20 h postinfection, when some of the additional viral DNA is integrated. Between 20 and 40 h postinfection, the cells accumulated up to 100 copies per haploid genome of viral DNA. Most of these are unintegrated. This number decreases with cell transfer, until cells are left with one to three copies of additional viral DNA sequences per haploid genome, of which most are integrated. The finding that viral infection causes the permanent addition of one to three copies of integrated viral DNA, despite the cells being confronted with up to 100 copies per haploid genome after infection, is consistent with a hypothesis that chicken cells contain a limited number of specific integration sites for the oncornavirus genome.

Animals↗

PubMed2026

A pan-cancer multi-omic SuperLearner for regulated cell death survival topologies.

INTRODUCTION: Regulated cell death (RCD) pathways influence tumor progression and immune modulation. We previously constructed a signature database mapping 25 RCD forms across seven multi-omic layers and 33 tumor types (CancerRCDShiny). Despite their ability to identify risk populations, translating these signatures into personalized clinical workflows requires a shift from cohort stratification to individualized risk mapping by modeling patient risk (survival topologies) to capture the non-linear dynamics of RCD signatures. METHODS: We engineered a pan-cancer multi-omic SuperLearner pipeline across 33 cancer types. Phase I performed zero-leakage harmonization and groupwise imputation to prevent cross-cohort amalgamation. Phase II deployed Elastic Net-regularized Cox regression as a CANARY diagnostic to map proportional hazards failures. Strata with a 35% missingness barrier entered Phase III, deploying a Quadripartite ensemble: Random Survival Forests, XGBoost, Survival-Boruta, and Multi-Task Logistic Regression, fused within an Elastic Net Multi-View Meta-Learner (MVL), with post-hoc TreeSHAP and LIME interpretability. RESULTS: The CANARY diagnostic demonstrated the structural invalidity of pan-cancer geometric proportional hazards. Across 96 admissible strata, Phase III executed algorithmic displacement: continuous multi-omic topologies suppressed static genomic mutations and copy number variations (85.7% vs. 0.0% apex retention). The MVL stabilized predictions against extreme variance; LIME surrogate validations (R 2 < 0.10) confirmed the systematic failure of linear interpretative proxies. N-dimensional TreeSHAP interaction mapping exposed synergistic and antagonistic rescue trajectories defining individualized Survival Topologies, which were invisible to additive models. The architecture was deployed as CancerRCDPredictor, a digital molecular tumor board with integrated LLM capabilities. The MVL SuperLearner achieved a median C-index of 0.749 (IQR: 0.722-0.836) across 96 modelable strata, with 95% bootstrap confidence intervals confirming precision (median width: 0.052) and permutation significance in 93.8% of strata (p < 0.001). External CPTAC validation across ten cancer types demonstrated significant cross-cohort generalizability in clear cell renal carcinoma (KIRC; C-index 0.675, p = 0.017) and modest performance across the remaining adequately powered cancers (median 0.582), underscoring the need for larger multi-institutional validation cohorts. CONCLUSION: This pan-cancer multi-omic SuperLearner bypasses linear topological failures, advancing beyond generalized stratification to establish a deterministically mapped architecture for predicting RCD-related survival topologies. Through the CancerRCDPredictor interface, multi-omic insights translate into individualized survival topology exploration, providing a foundation for future precision oncology validation.

SuperLearner↗

PubMed2025

Extrachromosomal DNA-Driven Oncogene Dosage Heterogeneity Promotes Rapid Adaptation to Therapy in MYCN-Amplified Cancers.

UNLABELLED: Extrachromosomal DNA (ecDNA) amplification enhances intercellular oncogene dosage variability and accelerates tumor evolution by violating foundational principles of genetic inheritance through its asymmetric mitotic segregation. Spotlighting high-risk neuroblastoma, we demonstrate how ecDNA amplification undermines the clinical efficacy of current therapies in cancers with extrachromosomal MYCN amplification. Integrating theoretical models of oncogene copy number-dependent fitness with single-cell ecDNA quantification and phenotype analyses, we reveal that ecDNA copy-number heterogeneity drives phenotypic diversity and determines treatment sensitivity through mechanisms unattainable by chromosomal oncogene amplification. We demonstrate that ecDNA copy number directly influences cell fate decisions in cancer cell lines, patient-derived xenografts, and primary neuroblastomas, illustrating how extrachromosomal oncogene dosage-driven phenotypic diversity offers a strong evolutionary advantage under therapeutic pressure. Furthermore, we identify senescent cells with reduced ecDNA copy numbers as a source of treatment resistance in neuroblastomas and outline a strategy for their targeted elimination to improve the treatment of MYCN-amplified cancers. SIGNIFICANCE: ecDNA-driven tumor genome evolution provides a major challenge to curative cancer therapies. We demonstrate that ecDNA copy-number dynamics drives treatment resistance by promoting oncogene dosage-dependent phenotypic heterogeneity in MYCN-amplified cancers. Exploiting phenotype-specific vulnerabilities of ecDNA cells, therefore, presents a powerful strategy to overcome treatment resistance. See related commentary by Korsah, p. 1979.

Humans↗

PubMed2026

Prognostic value of circulating tumor DNA and copy-number alterations in patients receiving tandem [225Ac]Ac-/[177Lu]Lu-PSMA-617 therapy for metastatic castration-resistant prostate cancer: a prospective observational study.

BACKGROUND: Prostate-specific membrane antigen-targeted radioligand therapy (PSMA-RLT) demonstrates clinical efficacy in metastatic castration-resistant prostate cancer (mCRPC), yet robust biomarkers for dynamic treatment monitoring and resistance remain lacking. We investigated circulating tumor DNA (ctDNA)-derived tumor fraction (TFx) and genome-wide copy-number alterations (CNAs) as non-invasive biomarkers of treatment response and resistance biology. METHODS: Seventy-eight patients with advanced mCRPC receiving tandem [225Ac]Ac-/[177Lu]Lu-PSMA-617 were prospectively enrolled. Plasma samples collected longitudinally (n = 172) underwent ultra-low-pass whole-genome sequencing. TFx was estimated using ichorCNA, and recurrent CNAs were identified using GISTIC2.0. Associations with progression and overall survival (OS) were assessed using Cox proportional hazards models, including time-dependent analyses. RESULTS: Baseline TFx differed across metastatic disease stages (p = 0.027) and dynamic TFx changes paralleled PSA kinetics during early treatment. Modelled as a time-dependent variable, TFx was associated with a significantly increased risk of progression (HR 4.9, 95% CI 1.2-20.1, p = 0.026). Unsupervised clustering identified distinct high- and low-CNA burden groups strongly correlated with TFx (p = 8.09 × 10⁻8). High CNA burden was associated with shorter median OS (8.3 vs 13.8 months). Multivariable analysis identified baseline logPSA and logALP as independent predictors of OS. Recurrent CNAs affected key tumor suppressors (PTEN, RB1, BRCA2, ATM) and were enriched in pathways related to TP53 signalling, homologous recombination repair, and oncogenic signaling. Longitudinal analyses demonstrated persistence and expansion of specific amplifications at progression. CONCLUSIONS: ctDNA-derived TFx represents a dynamic biomarker of treatment response and progression risk, while CNA profiling provides insight into resistance mechanisms in mCRPC treated with PSMA-RLT. These findings support the integration of ctDNA-based biomarkers into clinical stratification and real-time monitoring strategies.

Humans↗

PubMed2025

MarkerMatch: A Proximity-Based Probe-Matching Algorithm for Joint Analysis of Copy-Number Variants from Different Genotyping Arrays.

MOTIVATION: Copy-number variants (CNVs) are a form of genetic structural variation with increasing importance in complex human disorders. Both DNA sequencing and microarray data can be used to call CNVs, which can be used in association tests, such as association between CNV number and disease status. Unlike genotypes, CNV detection in microarrays requires the use of observed intensity signals at each probe, which limits the imputability for analyses that span multiple array types. Thus far, a consensus set of probes (the intersection encompassing the probes that occur in common on all arrays) has been used to circumvent the problem of differing array-specific sensitivities. This has, however, led to excessive reduction in overall sensitivity of CNV calls as arrays can have an undesirably low overlap of probe sets. To overcome this limitation, we developed MarkerMatch, a proximity-based algorithm that matches probes across different genotyping microarrays to maximize the number of probes considered in the CNV calling algorithm, thereby increasing the resolution and sensitivity while preserving precision. RESULTS: By analyzing CNV calls from 4,906 individuals genotyped across three different arrays (Global Screening Array, Omni2.5 array, and Omni Express Exome array), we show that the MarkerMatch approach improves sensitivity by increasing the density of probes available for CNV calling while maintaining precision or improving it relative to the current practice (e.g., use of consensus probes only). We further demonstrate that MarkerMatch exceeds the output from current practice in terms of F1 score, Fowlkes-Mallows index, and Jaccard index. We also optimize MarkerMatch parameters, D MAX and Method, and find an optimal D MAX setting at 10kb, with no clear optimal candidate based on Method, indicating that parameters for this metric should be determined on a use case basis.

Journal Article↗

PubMed2026

Copy number variants in BRCA1 and BRCA2 genes in Polish patients with breast and ovarian cancer.

PURPOSE: BRCA1 and BRCA2 are key susceptibility genes in hereditary breast and ovarian cancer (HBOC), with mutational status guiding PARP inhibitor therapy. While single-nucleotide variants (SNVs) predominate, the prevalence of copy number variants (CNVs) varies significantly across different populations. This study aims to determine the incidence of BRCA1/2 CNVs in the Polish population, where data remain scarce due to non-mandatory CNV testing. METHODS: We retrospectively analysed the results of genetic tests assessing the presence of BRCA1/2 CNVs performed in 2720 individuals tested at the Lower Silesian Oncology Centre (2021-2024), including 2702 breast/ovarian cancer patients and 18 unaffected relatives. The mean age was 54.7 ± 15.15 years. Genetic testing involved DNA extraction, NGS, and MLPA for CNV confirmation. Variants were classified according to ACMG-AMP guidelines and verified through independent testing. RESULTS: In this study, no BRCA2 CNVs were identified, consistent with previous Central European findings. Pathogenic BRCA1 CNVs were detected in 0.85% of the analyzed cohort and in 0.52% of the cancer patient subgroup, affecting 23 individuals from 13 families. Eight distinct BRCA1 CNVs were detected, the most common being exon 21 deletion. Affected families exhibited a high incidence of HBOC-related cancers, with early-onset breast cancer and a notable proportion of triple-negative breast cancer cases. CONCLUSIONS: This study highlights the clinical significance of BRCA1 CNVs in Polish patients with HBOC-spectrum cancers and their families. Although rare, these variants were associated with aggressive cancer phenotypes and early onset. Given their diagnostic and therapeutic implications, BRCA1 CNVs should be routinely analysed in high-risk families to ensure accurate detection and personalised treatment planning.

Humans↗

PubMed2026

Identification of rare maternal copy number variants by genome-wide analysis of noninvasive prenatal screening data in 113,017 pregnant women.

OBJECTIVES: Knowledge of copy number variants (CNVs) is relevant to maternal and fetal health and can be obtained from noninvasive prenatal screening (NIPS) of pregnancy. However, genome-wide analysis of maternal CNVs using NIPS data has not been conducted in large populations. METHODS: For CNV analysis, the human genome was segmented into 10 kilobase pairs (Kb) bins, and the relative sequencing depth of each bin was calculated. The circular binary segmentation algorithm was used to estimate CNVs. Detected CNVs from two pregnancies of the same participant were compared to validate the reproducibility. All CNVs were merged into CNV regions (CNVRs) to evaluate their frequency, distributions, and relationship with disease-related genes and regions. RESULTS: In this study, 113,017 pregnant women were recruited. A total of 363,886 CNVs larger than 50 Kb were detected in 101,779 individuals and merged into 43,005 CNVRs. For evaluating the reproducibility of CNVs, 90.18% of deletions and 88.07% of duplications were consistent. In general, 78.13% of individuals carried CNVRs that overlapped protein-coding genes, while 14.76% overlapped OMIM genes. We detected 246 novel CNVRs, 134 (54.47%) involving protein-coding genes. For the perspective of maternal-fetal health, we identified 4,984 (4.41%) individuals as carriers of 5,243 CNVs containing known pathogenic or likely pathogenic regions, including 22q11.2 region and DMD gene.. CONCLUSIONS: NIPS sequencing data is a reliable source for maternal CNV detection. These CNVs constitute an integrate component in maternal-fetal health management.

Humans↗