Detection and analysis of complex structural variation in human genomes across populations and in brains of donors with psychiatric disorders.

Complex structural variations (cxSVs) are often overlooked in genome analyses due to detection challenges. We developed ARC-SV, a probabilistic and machine-learning-based method that enables accurate detection and reconstruction of cxSVs from standard datasets. By applying ARC-SV across 4,262 genomes representing all continental populations, we identified cxSVs as a significant source of natural human genetic variation. Rare cxSVs have a propensity to occur in neural genes and loci that underwent rapid human-specific evolution, including those regulating corticogenesis. By performing single-nucleus multiomics in postmortem brains, we discovered cxSVs associated with differential gene expression and chromatin accessibility across various brain regions and cell types. Additionally, cxSVs detected in brains of psychiatric cases are enriched for linkage with psychiatric GWAS risk alleles detected in the same brains. Furthermore, our analysis revealed significantly decreased brain-region- and cell-type-specific expression of cxSV genes, specifically for psychiatric cases, implicating cxSVs in the molecular etiology of major neuropsychiatric disorders.

Deterministic evolution and stringent selection during preneoplasia.

The earliest events during human tumour initiation, although poorly characterized, may hold clues to malignancy detection and prevention1. Here we model occult preneoplasia by biallelic inactivation of TP53, a common early event in gastric cancer, in human gastric organoids. Causal relationships between this initiating genetic lesion and resulting phenotypes were established using experimental evolution in multiple clonally derived cultures over 2 years. TP53 loss elicited progressive aneuploidy, including copy number alterations and structural variants prevalent in gastric cancers, with evident preferred orders. Longitudinal single-cell sequencing of TP53-deficient gastric organoids similarly indicates progression towards malignant transcriptional programmes. Moreover, high-throughput lineage tracing with expressed cellular barcodes demonstrates reproducible dynamics whereby initially rare subclones with shared transcriptional programmes repeatedly attain clonal dominance. This powerful platform for experimental evolution exposes stringent selection, clonal interference and a marked degree of phenotypic convergence in premalignant epithelial organoids. These data imply predictability in the earliest stages of tumorigenesis and show evolutionary constraints and barriers to malignant transformation, with implications for earlier detection and interception of aggressive, genome-instable tumours.

Data integration and inference of gene regulation using single-cell temporal multimodal data with scTIE.

Single-cell technologies offer unprecedented opportunities to dissect gene regulatory mechanisms in context-specific ways. Although there are computational methods for extracting gene regulatory relationships from scRNA-seq and scATAC-seq data, the data integration problem, essential for accurate cell type identification, has been mostly treated as a standalone challenge. Here we present scTIE, a unified method that integrates temporal multimodal data and infers regulatory relationships predictive of cellular state changes. scTIE uses an autoencoder to embed cells from all time points into a common space by using iterative optimal transport, followed by extracting interpretable information to predict cell trajectories. Using a variety of synthetic and real temporal multimodal data sets, we show scTIE achieves effective data integration while preserving more biological signals than existing methods, particularly in the presence of batch effects and noise. Furthermore, on the exemplar multiome data set we generated from differentiating mouse embryonic stem cells over time, we show scTIE captures regulatory elements highly predictive of cell transition probabilities, providing new potentials to understand the regulatory landscape driving developmental processes.

Activation of innate immunity is required for efficient nuclear reprogramming.

Retroviral overexpression of reprogramming factors (Oct4, Sox2, Klf4, c-Myc) generates induced pluripotent stem cells (iPSCs). However, the integration of foreign DNA could induce genomic dysregulation. Cell-permeant proteins (CPPs) could overcome this limitation. To date, this approach has proved exceedingly inefficient. We discovered a striking difference in the pattern of gene expression induced by viral versus CPP-based delivery of the reprogramming factors, suggesting that a signaling pathway required for efficient nuclear reprogramming was activated by the retroviral, but not CPP approach. In gain- and loss-of-function studies, we find that the toll-like receptor 3 (TLR3) pathway enables efficient induction of pluripotency by viral or mmRNA approaches. Stimulation of TLR3 causes rapid and global changes in the expression of epigenetic modifiers to enhance chromatin remodeling and nuclear reprogramming. Activation of inflammatory pathways are required for efficient nuclear reprogramming in the induction of pluripotency.

Prioritizing disease-related rare variants by integrating gene expression data.

Rare variants, comprising the vast majority of human genetic variations, are likely to have more deleterious impact in the context of human diseases compared to common variants. Here we present carrier statistic, a statistical framework to prioritize disease-related rare variants by integrating gene expression data. By quantifying the impact of rare variants on gene expression, carrier statistic can prioritize those rare variants that have large functional consequence in the patients. Through simulation studies and analyzing real multi-omics dataset, we demonstrated that carrier statistic is applicable in studies with limited sample size (a few hundreds) and achieves substantially higher sensitivity than existing rare variants association methods. Application to Alzheimer's disease reveals 16 rare variants within 15 genes with extreme carrier statistics. We also found strong excess of rare variants among the top prioritized genes in patients compared to that in healthy individuals. The carrier statistic method can be applied to various rare variant types and is adaptable to other omics data modalities, offering a powerful tool for investigating the molecular mechanisms underlying complex diseases.

An encoding generative modeling approach to dimension reduction and covariate adjustment in causal inference with observational studies.

In this article, we develop CausalEGM, a deep learning framework for nonlinear dimension reduction and generative modeling of the dependency among covariate features affecting treatment and response. CausalEGM can be used for estimating causal effects in both binary and continuous treatment settings. By learning a bidirectional transformation between the high-dimensional covariate space and a low-dimensional latent space and then modeling the dependencies of different subsets of the latent variables on the treatment and response, CausalEGM can extract the latent covariate features that affect both treatment and response. By conditioning on these features, one can mitigate the confounding effect of the high dimensional covariate on the estimation of the causal relation between treatment and response. In a series of experiments, the proposed method is shown to achieve superior performance over existing methods in both binary and continuous treatment settings. The improvement is substantial when the sample size is large and the covariate is of high dimension. Finally, we established excess risk bounds and consistency results for our method, and discuss how our approach is related to and improves upon other dimension reduction approaches in causal inference.

Resolving the 22q11.2 deletion using CTLR-Seq reveals chromosomal rearrangement mechanisms and individual variance in breakpoints.

We developed a generally applicable method, CRISPR/Cas9-targeted long-read sequencing (CTLR-Seq), to resolve, haplotype-specifically, the large and complex regions in the human genome that had been previously impenetrable to sequencing analysis, such as large segmental duplications (SegDups) and their associated genome rearrangements. CTLR-Seq combines in vitro Cas9-mediated cutting of the genome and pulse-field gel electrophoresis to isolate intact large (i.e., up to 2,000 kb) genomic regions that encompass previously unresolvable genomic sequences. These targets are then sequenced (amplification-free) at high on-target coverage using long-read sequencing, allowing for their complete sequence assembly. We applied CTLR-Seq to the SegDup-mediated rearrangements that constitute the boundaries of, and give rise to, the 22q11.2 Deletion Syndrome (22q11DS), the most common human microdeletion disorder. We then performed de novo assembly to resolve, at base-pair resolution, the full sequence rearrangements and exact chromosomal breakpoints of 22q11.2DS (including all common subtypes). Across multiple patients, we found a high degree of variability for both the rearranged SegDup sequences and the exact chromosomal breakpoint locations, which coincide with various transposons within the 22q11.2 SegDups, suggesting that 22q11DS can be driven by transposon-mediated genome recombination. Guided by CTLR-Seq results from two 22q11DS patients, we performed three-dimensional chromosomal folding analysis for the 22q11.2 SegDups from patient-derived neurons and astrocytes and found chromosome interactions anchored within the SegDups to be both cell type-specific and patient-specific. Lastly, we demonstrated that CTLR-Seq enables cell-type specific analysis of DNA methylation patterns within the deletion haplotype of 22q11DS.

Two-Year Outcomes of Valoctocogene Roxaparvovec Therapy for Hemophilia A.

BACKGROUND: Valoctocogene roxaparvovec delivers a B-domain-deleted factor VIII coding sequence with an adeno-associated virus vector to prevent bleeding in persons with severe hemophilia A. The findings of a phase 3 study of the efficacy and safety of valoctocogene roxaparvovec therapy evaluated after 52 weeks in men with severe hemophilia A have been published previously. METHODS: We conducted an open-label, single-group, multicenter, phase 3 trial in which 134 men with severe hemophilia A who were receiving factor VIII prophylaxis received a single infusion of 6×1013 vector genomes of valoctocogene roxaparvovec per kilogram of body weight. The primary end point was the change from baseline in the annualized rate of treated bleeding events at week 104 after receipt of the infusion. The pharmacokinetics of valoctocogene roxaparvovec were modeled to estimate the bleeding risk relative to the activity of transgene-derived factor VIII. RESULTS: At week 104, a total of 132 participants, including 112 with data that were prospectively collected at baseline, remained in the study. The mean annualized treated bleeding rate decreased by 84.5% from baseline (P<0.001) among the participants. From week 76 onward, the trajectory of the transgene-derived factor VIII activity showed first-order elimination kinetics; the model-estimated typical half-life of the transgene-derived factor VIII production system was 123 weeks (95% confidence interval, 84 to 232). The risk of joint bleeding was estimated among the trial participants; at a transgene-derived factor VIII level of 5 IU per deciliter measured with chromogenic assay, we expected that participants would have 1.0 episode of joint bleeding per year. At 2 years postinfusion, no new safety signals had emerged and no new serious adverse events related to treatment had occurred. CONCLUSIONS: The study data show the durability of factor VIII activity and bleeding reduction and the safety profile of valoctocogene roxaparvovec at least 2 years after the gene transfer. Models of the risk of joint bleeding suggest that the relationship between transgene-derived factor VIII activity and bleeding episodes is similar to that reported with the use of epidemiologic data for persons with mild-to-moderate hemophilia A. (Funded by BioMarin Pharmaceutical; GENEr8-1 ClinicalTrials.gov number, NCT03370913.).

The Patent and Literature Antibody Database (PLAbDab): an evolving reference set of functionally diverse, literature-annotated antibody sequences and structures.

Antibodies are key proteins of the adaptive immune system, and there exists a large body of academic literature and patents dedicated to their study and concomitant conversion into therapeutics, diagnostics, or reagents. These documents often contain extensive functional characterisations of the sets of antibodies they describe. However, leveraging these heterogeneous reports, for example to offer insights into the properties of query antibodies of interest, is currently challenging as there is no central repository through which this wide corpus can be mined by sequence or structure. Here, we present PLAbDab (the Patent and Literature Antibody Database), a self-updating repository containing over 150,000 paired antibody sequences and 3D structural models, of which over 65 000 are unique. We describe the methods used to extract, filter, pair, and model the antibodies in PLAbDab, and showcase how PLAbDab can be searched by sequence, structure, or keyword. PLAbDab uses include annotating query antibodies with potential antigen information from similar entries, analysing structural models of existing antibodies to identify modifications that could improve their properties, and facilitating the compilation of bespoke datasets of antibody sequences/structures that bind to a specific antigen. PLAbDab is freely available via Github (https://github.com/oxpig/PLAbDab) and as a searchable webserver (https://opig.stats.ox.ac.uk/webapps/plabdab/).

NeuronMotif: Deciphering cis-regulatory codes by layer-wise demixing of deep neural networks.

Discovering DNA regulatory sequence motifs and their relative positions is vital to understanding the mechanisms of gene expression regulation. Although deep convolutional neural networks (CNNs) have achieved great success in predicting cis-regulatory elements, the discovery of motifs and their combinatorial patterns from these CNN models has remained difficult. We show that the main difficulty is due to the problem of multifaceted neurons which respond to multiple types of sequence patterns. Since existing interpretation methods were mainly designed to visualize the class of sequences that can activate the neuron, the resulting visualization will correspond to a mixture of patterns. Such a mixture is usually difficult to interpret without resolving the mixed patterns. We propose the NeuronMotif algorithm to interpret such neurons. Given any convolutional neuron (CN) in the network, NeuronMotif first generates a large sample of sequences capable of activating the CN, which typically consists of a mixture of patterns. Then, the sequences are "demixed" in a layer-wise manner by backward clustering of the feature maps of the involved convolutional layers. NeuronMotif can output the sequence motifs, and the syntax rules governing their combinations are depicted by position weight matrices organized in tree structures. Compared to existing methods, the motifs found by NeuronMotif have more matches to known motifs in the JASPAR database. The higher-order patterns uncovered for deep CNs are supported by the literature and ATAC-seq footprinting. Overall, NeuronMotif enables the deciphering of cis-regulatory codes from deep CNs and enhances the utility of CNN in genome interpretation.

Comprehensive tissue deconvolution of cell-free DNA by deep learning for disease diagnosis and monitoring.

Plasma cell-free DNA (cfDNA) is a noninvasive biomarker for cell death of all organs. Deciphering the tissue origin of cfDNA can reveal abnormal cell death because of diseases, which has great clinical potential in disease detection and monitoring. Despite the great promise, the sensitive and accurate quantification of tissue-derived cfDNA remains challenging to existing methods due to the limited characterization of tissue methylation and the reliance on unsupervised methods. To fully exploit the clinical potential of tissue-derived cfDNA, here we present one of the largest comprehensive and high-resolution methylation atlas based on 521 noncancer tissue samples spanning 29 major types of human tissues. We systematically identified fragment-level tissue-specific methylation patterns and extensively validated them in orthogonal datasets. Based on the rich tissue methylation atlas, we develop the first supervised tissue deconvolution approach, a deep-learning-powered model, cfSort, for sensitive and accurate tissue deconvolution in cfDNA. On the benchmarking data, cfSort showed superior sensitivity and accuracy compared to the existing methods. We further demonstrated the clinical utilities of cfSort with two potential applications: aiding disease diagnosis and monitoring treatment side effects. The tissue-derived cfDNA fraction estimated from cfSort reflected the clinical outcomes of the patients. In summary, the tissue methylation atlas and cfSort enhanced the performance of tissue deconvolution in cfDNA, thus facilitating cfDNA-based disease detection and longitudinal treatment monitoring.

Mutations in human DNA methyltransferase DNMT1 induce specific genome-wide epigenomic and transcriptomic changes in neurodevelopment.

DNA methyltransferase type 1 (DNMT1) is a major enzyme involved in maintaining the methylation pattern after DNA replication. Mutations in DNMT1 have been associated with autosomal dominant cerebellar ataxia, deafness and narcolepsy (ADCA-DN). We used fibroblasts, induced pluripotent stem cells (iPSCs) and induced neurons (iNs) generated from patients with ADCA-DN and controls, to explore the epigenomic and transcriptomic effects of mutations in DNMT1. We show cell type-specific changes in gene expression and DNA methylation patterns. DNA methylation and gene expression changes were negatively correlated in iPSCs and iNs. In addition, we identified a group of genes associated with clinical phenotypes of ADCA-DN, including PDGFB and PRDM8 for cerebellar ataxia, psychosis and dementia and NR2F1 for deafness and optic atrophy. Furthermore, ZFP57, which is required to maintain gene imprinting through DNA methylation during early development, was hypomethylated in promoters and exhibited upregulated expression in patients with ADCA-DN in both iPSC and iNs. Our results provide insight into the functions of DNMT1 and the molecular changes associated with ADCA-DN, with potential implications for genes associated with related phenotypes.

Valoctocogene Roxaparvovec Gene Therapy for Hemophilia A.

BACKGROUND: Valoctocogene roxaparvovec (AAV5-hFVIII-SQ) is an adeno-associated virus 5 (AAV5)-based gene-therapy vector containing a coagulation factor VIII complementary DNA driven by a liver-selective promoter. The efficacy and safety of the therapy were previously evaluated in men with severe hemophilia A in a phase 1-2 dose-escalation study. METHODS: We conducted an open-label, single-group, multicenter, phase 3 study to evaluate the efficacy and safety of valoctocogene roxaparvovec in men with severe hemophilia A, defined as a factor VIII level of 1 IU per deciliter or lower. Participants who were at least 18 years of age and did not have preexisting anti-AAV5 antibodies or a history of development of factor VIII inhibitors and who had been receiving prophylaxis with factor VIII concentrate received a single infusion of 6×1013 vector genomes of valoctocogene roxaparvovec per kilogram of body weight. The primary end point was the change from baseline in factor VIII activity (measured with a chromogenic substrate assay) during weeks 49 through 52 after infusion. Secondary end points included the change in annualized factor VIII concentrate use and bleeding rates. Safety was assessed as adverse events and laboratory test results. RESULTS: Overall, 134 participants received an infusion and completed more than 51 weeks of follow-up. Among the 132 human immunodeficiency virus-negative participants, the mean factor VIII activity level at weeks 49 through 52 had increased by 41.9 IU per deciliter (95% confidence interval [CI], 34.1 to 49.7; P<0.001; median change, 22.9 IU per deciliter; interquartile range, 10.9 to 61.3). Among the 112 participants enrolled from a prospective noninterventional study, the mean annualized rates of factor VIII concentrate use and treated bleeding after week 4 had decreased after infusion by 98.6% and 83.8%, respectively (P<0.001 for both comparisons). All the participants had at least one adverse event; 22 of 134 (16.4%) reported serious adverse events. Elevations in alanine aminotransferase levels occurred in 115 of 134 participants (85.8%) and were managed with immune suppressants. The other most common adverse events were headache (38.1%), nausea (37.3%), and elevations in aspartate aminotransferase levels (35.1%). No development of factor VIII inhibitors or thrombosis occurred in any of the participants. CONCLUSIONS: In patients with severe hemophilia A, valoctocogene roxaparvovec treatment provided endogenous factor VIII production and significantly reduced bleeding and factor VIII concentrate use relative to factor VIII prophylaxis. (Funded by BioMarin Pharmaceutical; GENEr8-1 ClinicalTrials.gov number, NCT03370913.).

HiChIPdb: a comprehensive database of HiChIP regulatory interactions.

Elucidating the role of 3D architecture of DNA in gene regulation is crucial for understanding cell differentiation, tissue homeostasis and disease development. Among various chromatin conformation capture methods, HiChIP has received increasing attention for its significant improvement over other methods in profiling of regulatory (e.g. H3K27ac) and structural (e.g. cohesin) interactions. To facilitate the studies of 3D regulatory interactions, we developed a HiChIP interactions database, HiChIPdb (http://health.tsinghua.edu.cn/hichipdb/). The current version of HiChIPdb contains ∼262M annotated HiChIP interactions from 200 high-throughput HiChIP samples across 108 cell types. The functionalities of HiChIPdb include: (i) standardized categorization of HiChIP interactions in a hierarchical structure based on organ, tissue and cell line and (ii) comprehensive annotations of HiChIP interactions with regulatory genes and GWAS Catalog SNPs. To the best of our knowledge, HiChIPdb is the first comprehensive database that utilizes a unified pipeline to map the functional interactions across diverse cell types and tissues in different resolutions. We believe this database has the potential to advance cutting-edge research in regulatory mechanisms in development and disease by removing the barrier in data aggregation, preprocessing, and analysis.

Leveraging cell-type-specific regulatory networks to interpret genetic variants in abdominal aortic aneurysm.

Abdominal aortic aneurysm (AAA) is a common degenerative cardiovascular disease whose pathobiology is not clearly understood. The cellular heterogeneity and cell-type-specific gene regulation of vascular cells in human AAA have not been well-characterized. Here, we performed analysis of whole-genome sequencing data in AAA patients versus controls with the aim of detecting disease-associated variants that may affect gene regulation in human aortic smooth muscle cells (AoSMC) and human aortic endothelial cells (HAEC), two cell types of high relevance to AAA disease. To support this analysis, we generated H3K27ac HiChIP data for these cell types and inferred cell-type-specific gene regulatory networks. We observed that AAA-associated variants were most enriched in regulatory regions in AoSMC, compared with HAEC and CD4+ cells. The cell-type-specific regulation defined by this HiChIP data supported the importance of ERG and the KLF family of transcription factors in AAA disease. The analysis of regulatory elements that contain noncoding variants and also are differentially open between AAA patients and controls revealed the significance of the interleukin-6-mediated signaling pathway. This finding was further validated by including information from the deleteriousness effect of nonsynonymous single-nucleotide variants in AAA patients and additional control data from the Medical Genome Reference Bank dataset. These results shed important insights into AAA pathogenesis and provide a model for cell-type-specific analysis of disease-associated variants.

Ligand-Receptor Interaction-Induced Intracellular Phase Separation: A Global Disruption Strategy for Resistance-Free Lethality of Pathogenic Bacteria.

Addressing the global challenge of bacterial resistance demands innovative approaches, among which multitargeting is a widely used strategy. Current strategies of multitargeting, typically achieved through drug combinations or single agents inherently aiming at multiple targets, face challenges such as stringent pharmacokinetic and pharmacodynamic requirements and cytotoxicity concerns. In this report, we propose a bacterial-specific global disruption approach as a vastly expanded multitargeting strategy that effectively disrupts bacterial subcellular organization. This effect is achieved through a pioneering chemical design of ligand-receptor interaction-induced aggregation of small molecules, i.e., DNA-induced aggregation of a diarginine peptidomimetic within bacterial cells. These intracellular aggregates display affinity toward various proteins and thus substantially interfere with essential bacterial functions and rupture bacterial cell membranes in an "inside-out" manner, leading to robust antibacterial activities and suppression of drug resistance. Additionally, biochemical analysis of macromolecule binding affinity, cytoplasmic localization patterns, and bacterial stress responses suggests that this bacterial-specific intracellular aggregation mechanism is fundamentally different from nonselective classic DNA or membrane binding mechanisms. These mechanistic distinctions, along with the peptidomimetic's selective permeation of bacterial membranes, contribute to its favorable biocompatibility and pharmacokinetic properties, enabling its in vivo antimicrobial efficacy in several animal models, including mice-based superficial wound models, subcutaneous abscess models, and septicemia infection models. These results highlight the great promise of ligand-receptor interaction-induced intracellular aggregation in achieving a globally disruptive multitargeting effect, thereby offering potential applications in the treatment of malignant cells, including pathogens, tumor cells, and infected tissues.

Gene Doping Control Analysis of Human Erythropoietin Transgene in Equine Plasma by PCR-Liquid Chromatography High-Resolution Tandem Mass Spectrometry.

Gene doping involves the misuse of genetic materials to alter an athlete's performance, which is banned at all times in both human and equine sports. Quantitative polymerase chain reaction (qPCR) assays have been used to control the misuse of transgenes in equine sports. Our laboratory recently developed and implemented duplex as well as multiplex qPCR assays for transgenes detection. To further advance gene doping control, we have developed for the first time a sensitive and definitive PCR-liquid chromatography high-resolution tandem mass spectrometry (PCR-LC-HRMS/MS) method for transgene detection with an estimated limit of detection of below 100 copies/mL for the human erythropoietin (hEPO) transgene in equine plasma. The method involved magnetic-glass-particle-based extraction of DNA from equine plasma prior to PCR amplification with 2'-deoxyuridine 5'-triphosphate (dUTP) followed by treatments with uracil DNA glycosylase and hot piperidine for selective cleavage to give small oligonucleotide fragments. The resulting DNA fragments were then analyzed by LC-HRMS/MS. The applicability of this method has been demonstrated by the successful detection of hEPO transgene in a blood sample collected from a gelding (castrated male horse) that had been administered the transgene. This novel approach not only serves as a complementary method for transgene detection but also paves the way for developing a generic PCR-LC-HRMS/MS method for the detection of multiple transgenes.

TRPV2 calcium channel promotes breast cancer progression potential by activating autophagy.

Breast cancer, the most prevalent and aggressive tumor affecting women, requires identification of disease determinants to facilitate the development of effective therapeutic strategies. Transient receptor potential vanilloid 2 (TRPV2), an ion channel highly permeable for calcium (Ca2+), is implicated in physiological and pathological processes. Nevertheless, the role of TRPV2 in breast cancer remains poorly elucidated. In this study, we found high levels of TRPV2 expression associated with advanced malignancy, thereby suggesting its potential as a biomarker for breast cancer staging. We demonstrated that TRPV2 activation promotes breast cancer cell proliferation, migration, and invasion, while silencing of TRPV2 suppresses breast cancer progression, highlighting the oncogenic role of TRPV2. Moreover, we reveal that TRPV2 facilitates cancer progression by modulating the CaMKKß/AMPK/ULK1-autophagic axis through mediating calcium influx, providing new insights into TRPV2 as a novel therapeutic target for breast cancer treatment.

Long-term safety and efficacy outcomes of valoctocogene roxaparvovec gene transfer up to 6 years post-treatment.

INTRODUCTION: Valoctocogene roxaparvovec uses an adeno-associated virus serotype 5 (AAV5) vector to transfer a factor VIII (FVIII) coding sequence to individuals with severe haemophilia A, providing bleeding protection. AIM: To assess safety and efficacy of valoctocogene roxaparvovec 5-6 years post-treatment. METHODS: In a phase 1/2 trial, adult male participants with severe haemophilia A (FVIII ≤1 IU/dL) without FVIII inhibitors or anti-AAV5 antibodies received valoctocogene roxaparvovec and were followed for 6 (6 × 1013 vg/kg; n = 7) and 5 (4 × 1013 vg/kg; n = 6) years. Safety, including investigation of potential associations between a malignancy and gene therapy, and efficacy are reported. RESULTS: No new treatment-related safety signals emerged. During year 6, a participant in the 6 × 1013  vg/kg cohort was diagnosed with grade 2 parotid gland acinar cell carcinoma; definitive treatment was uncomplicated parotidectomy with lymph node dissection. Target enrichment sequencing of tumour and adjacent healthy tissue revealed low vector integration (8.25 × 10-5 per diploid cell). Integrations were not elevated in tumour samples, no insertions appeared to drive tumorigenesis, and no clonal expansion of integration-containing cells occurred. During all follow-ups, >90% decreases from baseline in annualised treated bleeds and FVIII infusion rates were maintained. At the end of years 6 and 5, mean FVIII activity (chromogenic assay) was 9.8 IU/dL (median, 5.6 IU/dL) and 7.6 IU/dL (median, 7.1 IU/dL) for the 6 × 1013 and 4 × 1013 vg/kg cohorts, respectively, representing proportionally smaller year-over-year declines than earlier timepoints. CONCLUSIONS: Valoctocogene roxaparvovec safety and efficacy profiles remain largely unchanged; genomic investigations showed no association with a parotid tumour.

One-pot sequential synthesis of unsymmetrical diarylmethanes using methylene chloride as a C1-synthon.

Bisindolylmethane (BIM) and its derivatives are widely used in the pharmaceutical industry due to their significant biological activities. However, most reported synthetic methods are focused on the synthesis of symmetric BIMs, while the synthesis of unsymmetrical BIMs remains a challenge. Herein, an unprecedented two-step one-pot method to afford unsymmetrically substituted 3,3'-BIM frameworks, using methylene chloride (DCM) as the C1-synthon is reported. In this protocol, the formation of two C-C bonds can be achieved via a one-pot reaction. The utility of commercially available phenols and anilines was also demonstrated in the construction of unsymmetrical diarylmethanes. This protocol provides a straightforward approach to access diverse unsymmetrical diarylmethane derivatives under simple and mild conditions. The broad substrate compatibility and good functional group tolerance of the protocol support its practical application potential.