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PubMed2026

Genomic and evolutionary analysis reveals dynamic variations of MKK3 gene, a key regulator for seed dormancy in barley.

Barley (Hordeum vulgare L.) is an important crop in the world, and its seed dormancy is primarily controlled by a mitogen-activated protein kinase kinase 3 (MKK3) gene. Although kinase activity of MKK3 and its roles in barley post-domestication have been widely studied, the pre-domestication evolution of MKK3 and the spread of nondormant alleles among global barley varieties remain largely unexplored. In this study, we analyzed MKK3 sequences in barley and its wild progenitor (Hordeum spontaneum K. Koch) and identified two polymorphic miniature inverted-repeat transposable elements (MITEs). Comparative analyses indicated that the insertions/excision of the MITEs predated the current estimates of barley domestication. Examination of the barley pangenomes coupled with droplet digital polymerase chain reaction revealed extensive copy number variation of MKK3 and suggested that transposons likely contributed to tandem amplification of the MKK3 gene on chromosome 5H. Additionally, approximately 1-Kb MKK3 sequences were found on chromosomes 1H and 6H. Further analysis indicated that these short MKK3 sequences were captured by a CACTA transposon that also contained fragments from four other expressed genes. The acquisition of MKK3 was estimated to be between 1.9 and 2.5 million years ago. Together, these findings illuminate the dynamic pre-domestication evolution of the MKK3 gene and identify three divergent MKK3 haplotype groups including a unique lineage predominant in Ethiopian germplasm. This study highlights the contribution of transposons to structural diversification and evolutionary differentiation of the MKK3 locus and provides helpful information for understanding the complex history of MKK3 gene in barley and also for improving preharvest sprouting tolerant varieties under distinct natural conditions.

Hordeum↗

PubMed2022

An Exosomal miRNA Biomarker for the Detection of Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) remains a difficult tumor to diagnose and treat. To date, PDAC lacks routine screening with no markers available for early detection. Exosomes are 40-150 nm-sized extracellular vesicles that contain DNA, RNA, and proteins. These exosomes are released by all cell types into circulation and thus can be harvested from patient body fluids, thereby facilitating a non-invasive method for PDAC detection. A bioinformatics analysis was conducted utilizing publicly available miRNA pancreatic cancer expression and genome databases. Through this analysis, we identified 18 miRNA with strong potential for PDAC detection. From this analysis, 10 (MIR31, MIR93, MIR133A1, MIR210, MIR330, MIR339, MIR425, MIR429, MIR1208, and MIR3620) were chosen due to high copy number variation as well as their potential to differentiate patients with chronic pancreatitis, neoplasms, and PDAC. These 10 were examined for their mature miRNA expression patterns, giving rise to 18 mature miRs for further analysis. Exosomal RNA from cell culture media was analyzed via RTqPCR and seven mature miRs exhibited statistical significance (miR-31-5p, miR-31-3p, miR-210-3p, miR-339-5p, miR-425-5p, miR-425-3p, and miR-429). These identified biomarkers can potentially be used for early detection of PDAC.

Humans↗

PubMed2026

Optical genome mapping enhanced by refined variant interpretation in pediatric acute lymphoblastic leukemia.

Reliable detection of structural variants (SVs) and copy number variations (CNVs) is crucial in the contemporary diagnostics of pediatric B-cell acute lymphoblastic leukemia (B-ALL). However, limitations of commonly used conventional and molecular cytogenetic methods may hinder the accurate genetic characterization of patients. Optical genome mapping (OGM) offers a reliable alternative by enabling high-resolution, genome-wide detection of CNVs and SVs. Chromosomal aberrations were screened using OGM in 51 children with B-ALL. The results were compared with those of karyotyping, fluorescence in situ hybridization (FISH), digital multiplex ligation-dependent probe amplification (digitalMLPA), and targeted RNA sequencing (RNA-seq). OGM data showed high congruency with karyotyping and FISH findings, detecting clinically relevant variants beyond G-banding results and unraveling a complex KMT2A fusion undetected by FISH. Gene fusions involved in complex ETV6::RUNX1 translocations, but not detected by RNA-seq, were confirmed using FISH. Normalization of OGM copy number values with DNA-index-improved concordance with FISH-derived copy numbers in near-tri/tetraploid cases. In the peripheral regions of OGM variants (fringe-zones), a novel evaluation strategy called 'FriZone' was applied, which significantly improved the concordance between OGM and digitalMLPA. In addition, a co-segregation analysis revealed strong associations between ETV6::RUNX1 fusion and deletions of ETV6, RAG2, and NR3C2. OGM uncovered complex rearrangements undetected by widely used methods in 15% of cases, improving genetic classification and risk stratification in 10% of the patients. The FriZone analysis and normalization by DNA-index provide a refined, more accurate approach to OGM variant interpretation, facilitating the efficient application of OGM in clinical diagnostics. © 2026 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Humans↗

PubMed2026

PScnv: personalized self-normalizing CNV detection with a hierarchical multi-phase framework.

MOTIVATION: Accurate detection of copy number variations (CNVs) from targeted panel sequencing remains challenging due to limited genomic coverage and pronounced sample-specific biases. Existing normalization strategies, including baseline-cohort, matched-control, and single-sample approaches, often struggle to balance noise suppression with adaptability, leading to inconsistent performance across heterogeneous samples. RESULTS: We present PScnv, a personalized self-normalizing framework for robust CNV detection from panel sequencing data. PScnv integrates a pre-built panel-of-normals (PoN) with sample-intrinsic stable chromosomes through ridge-regression normalization to generate individualized log2 ratio profiles with reduced systematic variation. CNVs are then identified using a hierarchical multi-phase segmentation pipeline incorporating z-score pre-partitioning, kernel-based correction, and circular binary segmentation. In 139 clinical tumor samples with orthogonal FISH validation at MET, ERBB2, and MTAP, PScnv showed improved accuracy and robustness over existing methods that do not require patient-matched normal samples, provided that a pre-built PoN cohort is available. AVAILABILITY: Source code is available for academic use at https://github.com/lvws/PScnv.

DNA Copy Number Variations↗

PubMed2025

The CAP/ACMG CYCGH proficiency testing program: 10 years in review.

PURPOSE: The College of American Pathologists has offered proficiency testing (PT) for the detection of copy-number variations (CNV) in the constitutional setting (CYCGH) since 2008. We review and summarize data from the CYCGH PT program, including participant performance over time, changes made to the program, and ungraded challenges. METHODS: The PT challenges from 2011 through 2021 (22 total mailings) and changes to the program over time were reviewed. Laboratory enrollment and performance were assessed. RESULTS: Overall participation has increased over time, and laboratories have maintained a high level of proficiency. The major changes to the program have occurred twice during the time span examined. Reasons for challenges not meeting consensus were varied. The use of ungraded challenges was also discussed. CONCLUSION: The CYCGH PT program is challenging because it assesses both analytical performance and interpretation as a single analyte. The program has evolved over time to address the changes in the field of CNV detection. During this time, additional technologies with the ability to detect CNVs have emerged, and the possibility of developing a platform-agnostic CNV PT program is being explored.

Humans↗

PubMed2024

Prenatal diagnosis and molecular cytogenetic analysis of pure chromosome 10p15.3 microdeletion using chromosomal microarray analysis.

BACKGROUND: The literature contains exceedingly limited reports on chromosome 10p15.3 microdeletions. In the present study, two cases of fetuses with pure terminal 10p15.3 microdeletion syndrome in a Chinese population were examined, with the objective of enhancing understanding of the genotype-phenotype correlation associated with 10p15.3 microdeletions. METHODS: Two fetuses with chromosome 10p15.3 microdeletion were identified from a cohort of 5,258 cases undergoing amniocentesis. Karyotyping and chromosomal microarray analysis (CMA) was conducted to assess chromosomal abnormalities and detect copy number variations (CNVs) within the families, respectively. RESULTS: In Family 1, the fetus exhibited a 556.2-Kb deletion in the 10p15.3 region, encompassing OMIM genes such as DIP2C and ZMYND11, and presented with increased nuchal translucency on prenatal ultrasound examination. Parental CMA analysis revealed that the 10p15.3 microdeletion was inherited from the father, who displayed mild language impairment. In Family 2, a comparable 10p15.3 microdeletion was identified in a fetus presenting with asymmetric butterfly vertebrae at T10 and T12, along with mild scoliosis of the spine. Family 1 elected to terminate the pregnancy, while Family 2 chose to continue. At a follow-up conducted at one year and eight months, the child demonstrated delays in both speech and motor development. CONCLUSION: The present study is the first to report two cases of pure terminal chromosome 10p15.3 microdeletion syndrome in fetuses, offering valuable insights for the prenatal diagnosis of 10p15.3 microdeletion syndrome. Further, it is the first to describe mild clinical features, specifically limited to language impairment, in a patient with 10p15.3 microdeletion syndrome.

Female↗

PubMed2025

Unraveling cellular dynamic changes in tumor evolution induced by long-term low dose-rate radiation.

BACKGROUND: In recent years, there has been a steady increase in professionals engaged in radioactive work. The biological impacts of long-term exposure to low dose-rate radiation remain elusive, as there is a dearth of systematic research in this field. METHODS: BEAS-2B cells were used to establish a cell model with continuous passaging after radiation exposure, which was subsequently subjected to in vivo tumorigenesis assays and in vitro malignant phenotype experiments. By scRNA-seq, we conducted copy number variation analysis, cell trajectory analysis, and cell communication analysis. Furthermore, we used FACS, molecular docking, multiplex immunohistochemistry, qRT-PCR, and co-immunoprecipitation to validate and further explore the molecular mechanisms driving tumor evolution. RESULTS: Long-term low dose-rate exposure is associated with a higher degree of malignancy, as evidenced by the induction of more CNV and EMT events, as well as the delayed activation of DNA repair pathways, which trigger increased genomic instability. The long-term low dose-rate specific ligand-receptor pair, ANGPTL4-SDC4, enhances cell malignancy by promoting angiogenesis in newly formed lung tumor cells. CONCLUSIONS: This study not only provides the first evidence and mechanistic explanation that long-term low dose-rate radiation leads to increased cellular malignancy but also offers valuable theoretical insights into the dynamic processes of early tumor evolution in lung cancer within the realm of tumor biology.

Humans↗

PubMed2026

Identification of novel HUWE1 variants in Turner-type X-linked intellectual disability.

OBJECTIVE: To characterize the clinical phenotypes and identify the genetic etiology in four unrelated families affected by Turner-type X-linked intellectual disability (XLID). METHODS: Peripheral blood samples were collected from four probands and their parents. Genomic DNA was extracted, and a comprehensive genetic analysis was performed using trio-based Whole Exome Sequencing (WES) combined with low-pass Copy Number Variation sequencing (CNV-seq). Candidate variants were subsequently validated via Sanger sequencing. RESULTS: Genetic analysis identified distinct variants in the HUWE1 across the four families. Specifically, four distinct HUWE1 variants were identified across the families: a hemizygous c.10034 > T (p.Lys3345Met) in Family 1; a heterozygous c.9209G > A (p.Arg3070His) in Family 2; a heterozygous c.12688T > C (p.Phe4230Leu) in Family 3; and a hemizygous c.9070G > A (p.Ala3024Thr) in Family 4. In accordance with ACMG guidelines, the novel variants in Families 1, 3, and 4 were classified as "Likely Pathogenic" (PS2 + PM2_Supporting + PP2 + PP3). In contrast, the previously reported variant in Family 2 was categorized as "Pathogenic" based on the criteria PS2 + PM2_Supporting + PM5 + PP2 + PP3_Moderate. All probands were clinically diagnosed with Turner-type XLID. CONCLUSIONS: This study expands the pathogenic variant spectrum of HUWE1 and provides novel molecular evidence for the clinical diagnosis of Turner-type XLID. These findings are of significant value for genetic counseling, carrier screening, and prenatal diagnosis for the affected families.

Humans↗

PubMed2020

Genomic Analysis of Circulating Tumor Cells at the Single-Cell Level.

Circulating tumor cells (CTCs) have a great potential for noninvasive diagnosis and real-time monitoring of cancer. A comprehensive evaluation of four whole genome amplification (WGA)/next-generation sequencing workflows for genomic analysis of single CTCs, including PCR-based (GenomePlex and Ampli1), multiple displacement amplification (Repli-g), and hybrid PCR- and multiple displacement amplification-based [multiple annealing and loop-based amplification cycling (MALBAC)] is reported herein. To demonstrate clinical utilities, copy number variations (CNVs) in single CTCs isolated from four patients with squamous non-small-cell lung cancer were profiled. Results indicate that MALBAC and Repli-g WGA have significantly broader genomic coverage compared with GenomePlex and Ampli1. Furthermore, MALBAC coupled with low-pass whole genome sequencing has better coverage breadth, uniformity, and reproducibility and is superior to Repli-g for genome-wide CNV profiling and detecting focal oncogenic amplifications. For mutation analysis, none of the WGA methods were found to achieve sufficient sensitivity and specificity by whole exome sequencing. Finally, profiling of single CTCs from patients with non-small-cell lung cancer revealed potentially clinically relevant CNVs. In conclusion, MALBAC WGA coupled with low-pass whole genome sequencing is a robust workflow for genome-wide CNV profiling at single-cell level and has great potential to be applied in clinical investigations. Nevertheless, data suggest that none of the evaluated single-cell sequencing workflows can reach sufficient sensitivity or specificity for mutation detection required for clinical applications.

Carcinoma, Non-Small-Cell Lung↗

PubMed2024

Whole exome sequencing analysis of 167 men with primary infertility.

BACKGROUND: Spermatogenic failure is one of the leading causes of male infertility and its genetic etiology has not yet been fully understood. METHODS: The study screened a cohort of patients (n = 167) with primary male infertility in contrast to 210 normally fertile men using whole exome sequencing (WES). The expression analysis of the candidate genes based on public single cell sequencing data was performed using the R language Seurat package. RESULTS: No pathogenic copy number variations (CNVs) related to male infertility were identified using the the GATK-gCNV tool. Accordingly, variants of 17 known causative (five X-linked and twelve autosomal) genes, including ACTRT1, ADAD2, AR, BCORL1, CFAP47, CFAP54, DNAH17, DNAH6, DNAH7, DNAH8, DNAH9, FSIP2, MSH4, SLC9C1, TDRD9, TTC21A, and WNK3, were identified in 23 patients. Variants of 12 candidate (seven X-linked and five autosomal) genes were identified, among which CHTF18, DDB1, DNAH12, FANCB, GALNT3, OPHN1, SCML2, UPF3A, and ZMYM3 had altered fertility and semen characteristics in previously described knockout mouse models, whereas MAGEC1,RBMXL3, and ZNF185 were recurrently detected in patients with male factor infertility. The human testis single cell-sequencing database reveals that CHTF18, DDB1 and MAGEC1 are preferentially expressed in spermatogonial stem cells. DNAH12 and GALNT3 are found primarily in spermatocytes and early spermatids. UPF3A is present at a high level throughout spermatogenesis except in elongating spermatids. The testicular expression profiles of these candidate genes underlie their potential roles in spermatogenesis and the pathogenesis of male infertility. CONCLUSION: WES is an effective tool in the genetic diagnosis of primary male infertility. Our findings provide useful information on precise treatment, genetic counseling, and birth defect prevention for male factor infertility.

Humans↗

PubMed2025

Anticancer drug response prediction integrating multi-omics pathway-based difference features and multiple deep learning techniques.

Individualized prediction of cancer drug sensitivity is of vital importance in precision medicine. While numerous predictive methodologies for cancer drug response have been proposed, the precise prediction of an individual patient's response to drug and a thorough understanding of differences in drug responses among individuals continue to pose significant challenges. This study introduced a deep learning model PASO, which integrated transformer encoder, multi-scale convolutional networks and attention mechanisms to predict the sensitivity of cell lines to anticancer drugs, based on the omics data of cell lines and the SMILES representations of drug molecules. First, we use statistical methods to compute the differences in gene expression, gene mutation, and gene copy number variations between within and outside biological pathways, and utilized these pathway difference values as cell line features, combined with the drugs' SMILES chemical structure information as inputs to the model. Then the model integrates various deep learning technologies multi-scale convolutional networks and transformer encoder to extract the properties of drug molecules from different perspectives, while an attention network is devoted to learning complex interactions between the omics features of cell lines and the aforementioned properties of drug molecules. Finally, a multilayer perceptron (MLP) outputs the final predictions of drug response. Our model exhibits higher accuracy in predicting the sensitivity to anticancer drugs comparing with other methods proposed recently. It is found that PARP inhibitors, and Topoisomerase I inhibitors were particularly sensitive to SCLC when analyzing the drug response predictions for lung cancer cell lines. Additionally, the model is capable of highlighting biological pathways related to cancer and accurately capturing critical parts of the drug's chemical structure. We also validated the model's clinical utility using clinical data from The Cancer Genome Atlas. In summary, the PASO model suggests potential as a robust support in individualized cancer treatment. Our methods are implemented in Python and are freely available from GitHub (https://github.com/queryang/PASO).

Deep Learning↗

PubMed2026

Urinary Small Extracellular Vesicle DNA as a Biomarker for the Non-Invasive Diagnosis of Bladder Cancer.

Existing diagnostic technologies for bladder cancer (BC) suffer from low sensitivity, low specificity, or a lack of validation. Therefore, validated, non-invasive diagnostic biomarkers with high sensitivity and specificity for early detection of BC are needed to complement and improve upon the limitations of existing diagnostic methods. We used low-pass whole genome sequencing (LP-WGS) technology to detect copy number variations (CNVs) in small extracellular vesicle (sEV) DNA isolated from urine samples of patients. Based on these results, we constructed and validated a diagnostic model to differentiate between benign and malignant bladder lesions. We conducted a receiver operating characteristic analysis and calculated the area under the curve (AUC) to evaluate the performance of the diagnostic model. The urine sEV-DNA LP-WGS data revealed CNV differences between benign and malignant samples. The diagnostic model achieved an AUC of 0.953, a sensitivity of 86.7%, and a specificity of 100% in the training cohort and an AUC of 0.985, a sensitivity of 90%, and a specificity of 100% in the validation cohort. Even at the lowest coverage depth of 0.01X, the performance of the diagnostic model remained relatively robust. Notably, the performance of this diagnostic model surpassed that of the biomarker neuron-specific enolase (sensitivity: 85.7% vs. 64.3%; specificity: 100% vs. 87.5%) and urinary cytology (sensitivity: 100% vs. 66.7%; specificity: 100% vs. 94.1%). Our study demonstrates that urine sEV-DNA exhibits high discriminatory power in distinguishing between benign and malignant bladder lesions, making it a promising tool for auxiliary diagnosis of BC.

Humans↗

PubMed2026

A cfDNA fragmentomics classifier for noninvasive differentiation of benign and malignant renal masses.

Noninvasive differentiation of malignant and benign renal masses remains a major clinical challenge, particularly for radiologically indeterminate lesions. Here, we developed and validated a plasma cell-free DNA (cfDNA) fragmentomics-based machine learning classifier for renal mass characterization. The model was trained on 331 participants (171 cancer, 160 benign) and independently validated on 144 participants (73 cancer, 71 benign). Three cfDNA fragmentation features, including copy number variation (CNV), fragmentation-based methylation (FRAGMA), and nucleosome footprint (NF), derived from low-pass whole-genome sequencing, were integrated into an ensemble framework. The model achieved strong discriminative performance, with area under the curve (AUC) values of 0.956 in the training cohort and 0.946 in the validation cohort, outperforming individual feature-based models. At a predefined operating threshold corresponding to 90% sensitivity, specificity reached 0.90 and 0.87, respectively. Notably, most cancer samples exhibited low tumor fraction (TF < 3%), yet the model maintained robust performance in low-TF samples (AUCs: 0.952 and 0.941, respectively). Performance remained consistent across tumor stage, grade, and histological subtypes. The classifier also demonstrated potential clinical utility in diagnostically challenging settings, including lipid-poor angiomyolipoma and oncocytoma, with 12 of 13 oncocytoma samples correctly classified in an independent cohort. In addition, the model correctly identified 85.3% of benign masses > 4 cm, for which surgical intervention is more commonly considered, and 84.6% of malignant tumors ≤ 4 cm, for which management can be challenging. Collectively, these findings support cfDNA fragmentomics as a promising noninvasive liquid biopsy approach for renal mass evaluation and clinical decision-making.

Humans↗

PubMed2025

The MTORC1 signaling pathway related gene POLR3G serves as a potential prognostic biomarker in Hepatocellular Carcinoma.

This study aims to investigate the prognostic significance and potential biological functions of the MTORC1 signaling pathway-associated gene POLR3G in Hepatocellular carcinoma (HCC). A prognostic risk model for HCC was developed by integrating HCC-related datasets and associated clinical data obtained from The Cancer Genome Atlas (TCGA) database. The GSVA website was employed to analyze the model genes across pan-cancer datasets, focusing on copy number variations (CNV), single nucleotide variations (SNV), methylation differences, drug sensitivity and immune cell infiltration profiles. Subsequently, we examined the expression levels and prognostic significance of POLR3G in HCC. Utilizing Spearman correlation analysis, we identified genes associated with POLR3G. Furthermore, Gene Set Enrichment Analysis (GSEA) was employed to elucidate the potential signaling pathways in which POLR3G may be involved. The relationship between POLR3G expression and immune cell abundance in HCC samples was assessed using the ssGSEA algorithm. Finally, the impact of POLR3G on HCC cell proliferation was validated through CCK-8 and EDU cell proliferation assays. Through univariate Cox regression analysis and LASSO regression analysis, we established a prognostic risk model for HCC comprising 13 genes. The analysis revealed that individuals categorized in the low-risk group had a markedly improved overall survival probability relative to those in the high-risk group. POLR3G exhibited a markedly elevated expression in HCC tissues when compared to adjacent normal tissues. The expression of POLR3G was correlated with tumor grade, and elevated POLR3G expression was associated with poor prognosis in HCC patients. Furthermore, the expression level of POLR3G was found to be correlated with the level of immune cell infiltration. Knockdown of POLR3G significantly inhibited the proliferative capacity of hepatocellular carcinoma cells. The findings suggest that POLR3G may serve as a potential biomarker influencing the prognosis of hepatocellular carcinoma patients by modulating the tumor immune microenvironment.

Humans↗

PubMed2025

Comprehensive chromosomal abnormality detection: integrating CNV-Seq with traditional karyotyping in prenatal diagnostics.

BACKGROUND: This study aimed to evaluate the efficacy of copy number variation sequencing (CNV-Seq) in detecting chromosomal abnormalities in prenatal diagnosis, comparing its performance with traditional karyotype analysis. METHODS: A retrospective analysis was conducted on 1001 prenatal samples collected between April 2021 and December 2023. Samples were analyzed using both CNV-Seq and karyotype analysis. The detection rates of chromosomal abnormalities were compared between the two methods across various prenatal diagnostic indications. Clinical follow-up was performed to assess pregnancy outcomes. RESULTS: CNV-Seq detected chromosomal abnormalities in 89 of 1,001 cases (8.9%), compared to 50 cases (5.0%) identified by traditional karyotyping. CNV-Seq not only detected all abnormalities identified by karyotyping, including common aneuploidies such as trisomy 21 and sex chromosome abnormalities, but also uncovered 53 additional pathogenic submicroscopic CNVs associated with 33 known syndromes. The detection rates of CNV-Seq were significantly higher in high-risk groups, such as those identified by non-invasive prenatal testing (HR-NIPT) and maternal serum screening (HR-MSS), demonstrating superior sensitivity and accuracy in prenatal diagnostics. CONCLUSION: CNV-Seq demonstrated superior sensitivity in detecting chromosomal abnormalities, particularly submicroscopic alterations, compared to traditional karyotyping. The study highlights the potential of CNV-Seq as a valuable tool in prenatal diagnostics, offering improved detection of genetic abnormalities and guiding clinical decision-making. However, a combined approach using both CNV-Seq and karyotype analysis is recommended for comprehensive prenatal genetic screening.

Humans↗

PubMed2025

Identification of maternal Gγ(Aγδβ)0 thalassemia through retrospective reanalysis of prenatal cfDNA sequencing data.

OBJECTIVE: Non-invasive prenatal screening (NIPS) is widely used to detect chromosomal abnormalities such as trisomies 21, 13, and 18 and is also effective in screening for copy number variations (CNVs). However, the routine application of NIPS to detect smaller CNVs within the HBB gene, specifically Gγ(Aγδβ)0 thalassemia, has yet to be well documented. This study aims to evaluate the efficacy of cfDNA-based maternal carrier screening in routine screening for Gγ(Aγδβ)0 thalassemia. METHODS: We performed a retrospective analysis of 107,300 pregnant women who underwent NIPS at Longgang Maternal and Child Healthcare Hospital in Shenzhen from December 2017 to May 2022. Using an improved algorithm, we reanalyzed NIPS data to identify maternal Gγ(Aγδβ)0 thalassemia. Positive cases were confirmed by multiplex ligation-dependent probe amplification (MLPA) using peripheral blood leukocytes. RESULTS: Among the 107,300 NIPS analyses, 38 maternal deletion CNVs within the HBB gene were identified using the improved algorithm, with a prevalence of 0.035% (38/107,300). MLPA confirmed that all detected deletions were consistent with Gγ(Aγδβ)0 thalassemia. The positive predictive value (PPV) for detecting Gγ(Aγδβ)0 thalassemia by cfDNA-based maternal carrier screening was 100%. Among the 38 Gγ(Aγδβ)0 cases, 9 were also associated with α-thalassemia deletions, including 4 cases with -SEA/αα, 4 with -α3.7/αα, and 1 with -α4.2/αα. No cases of homozygosity or compound HBB gene variants were observed. CONCLUSIONS: Gγ(Aγδβ)0 thalassemia is not uncommon in China, and repurposed NIPS methodology for maternal genomic analysis in detecting HBB gene deletions is a reliable method for identifying maternal carriers of this disease.

Humans↗

PubMed2025

Genetic insight into lung neuroendocrine tumors: Notch and Wnt signaling pathways as potential targets.

BACKGROUND: The molecular landscape of lung neuroendocrine neoplasms is still poorly characterized, making it difficult to develop a molecular classification and personalized therapeutic approaches. Significant clinical heterogeneity of these malignancies has been highlighted among poorly differentiated histotypes and within the subgroup of well-differentiated neuroendocrine tumors (NET). Currently, the main prognostic factors of lung NET include stage, histotype, grade, peripheral location, and demographic parameters. To gain deeper insights into the genomic underpinnings of lung NETs, we conducted a pilot investigation to uncover potential genetic mutations and copy number variations (CNVs) implicated in their pathogenesis. METHODS: Formalin-fixed, paraffin-embedded intraoperative tumor biopsies and matched peripheral blood mononuclear cell samples were collected from six consecutive patients with lung NETs. The whole exome sequencing (WES) was performed to profile germline and somatic mutations, identify novel genetic alterations, and detect CNVs. Clinical and pathological data were systematically documented at diagnosis and during follow-up. RESULTS: The WES analysis identified a subset of mutations shared between germline and somatic; some were of particular clinical interest as they were associated with tumor proliferation and potential therapeutic targets such as the genes KDM5C, ATR, COL7A1, NOTCH4, PTPRS, SMO, SPEN, SPTA1, TAF1. These mutations were predominantly linked to chromatin remodeling and were involved in critical oncogenic pathways such as Notch and Wnt signaling. CONCLUSIONS: This pilot study highlights the potential role of NGS analysis on solid biopsy in the assessment of the mutational profile of lung NET. A comparison of germline and somatic mutations is critical to identifying putative tumor driver mutations. In perspective, the enrichment of a subpopulation of cancer cells in the blood, with one or more specific mutations, is information of enormous clinical relevance, either for prognosis or therapeutic decisions. Translational studies on large prospective series are required to establish the role of liquid biopsy in lung NET.

Humans↗

PubMed2025

Mapping Cerebellar Morphology in 15q11.2 CNV Carriers Using Normative Modeling.

Copy number variations (CNVs) at the 15q11.2 locus of the human genome have been associated with altered brain structure and increased risk for neurodevelopmental and neuropsychiatric disorders. The cerebellum is increasingly seen as a crucial brain region for neurodevelopmental conditions, yet the effects of 15q11.2 CNVs on cerebellar morphology remain largely unclear. Importantly, 15q11.2 CNVs shows reduced or incomplete penetrance (meaning that not all CNV carriers are affected) and variable expressivity (meaning that symptoms may differ between individuals with the same genetic alteration). Thus, there is a need to not only assess group differences, but also to quantify anatomical variability at the individual level. Here, we address these issues using normative models of brain anatomy trained on large datasets (n > 52k, age range: 3-85) to assess both group and individual-level deviations in cerebellar anatomy in carriers of 15q11.2 deletions (n = 120, mean [SD] age= 64.95 [7.58]) and duplications (n = 149, mean [SD] age=64.31 [7.21]), compared to non-carriers (n = 19,028, mean [SD] age=64.31 [7.58]). Group-level case-control analyses revealed significantly smaller total and regional cerebellar volumes in both deletion and duplication carriers, though with small effect sizes. Individual-level deviation analyses, capturing pronounced alterations in specific individuals, revealed a heterogeneous pattern among carriers. Overall, our findings suggest that CNVs at the 15q11.2 locus exert modest and highly individualized effects on cerebellar morphology.

15q11.2↗