Nucleic Acids Research

A cluster-based cell-type deconvolution of spatial transcriptomic data

Abstract Spatial transcriptomics (ST) has emerged as an efficient technology for mapping gene expression within tissue sections, offering informative spatial context for gene activities. However, most current ST techniques suffer from low spatial resolution, where each spatial location often contains cells of various types. Deconvolution methods are used to resolve the cell mixture within the spots, but conventional approaches rely on spot-by-spot analyses, which are limited by low gene expression levels and disregard spatial relationships between spots, ultimately reducing performance. Here, we introduce DECLUST, a cluster-based deconvolution method to accurately estimate the cell-type composition in ST data. The method identifies spatial clusters of spots using both gene expression and spatial coordinates, hence preserving the spatial structure of the tissue. Deconvolution is subsequently performed on the aggregated gene expression of individual clusters, mitigating the challenges associated with low expression levels in individual spots. We evaluate DECLUST on simulated ST datasets from a human breast cancer tissue and two real ST datasets from human ovarian cancer and mouse brain. We compare DECLUST to current methods including CARD, GraphST, Cell2location, and Tangram. The results indicate that DECLUST not only maintains the spatial integrity of tissues but also outperforms existing methods in terms of robustness and accuracy. In conclusion, DECLUST provides an effective and reliable approach for identifying cell-type compositions in ST data.

DirectHRD enables sensitive scar-based classification of homologous recombination deficiency

Abstract Homologous recombination deficiency (HRD) is a predictive biomarker for efficacy of PARP (poly ADP-ribose polymerase) inhibition and platinum chemotherapy for cancer patients but remains challenging to detect. The discovery of patients without pathogenic mutations in known HR genes but exhibiting genomic scars indicative of HRD led to the FDA approval of the first scar-based HRD test. Despite advancements in whole genome sequencing (WGS) and integration of large training datasets with machine learning models, current methods lack the sensitivity required for detecting HRD scars in low tumor purity samples, especially in liquid biopsies. Here, we describe DirectHRD, a genomic scar-based HRD classifier based on WGS. Compared to other WGS-based methods, DirectHRD exclusively utilizes a highly specific type of HRD scar—small deletions with microhomology—and its associated signatures in a probabilistic framework. We applied DirectHRD to 501 tumor and 90 cell-free DNA (cfDNA) samples from 4 cancer types: breast, ovarian, prostate, and pancreas. Among all 501 tumor biopsies, DirectHRD achieved 100% detection of HRD with high specificity (>90%). Across all 90 cfDNA samples, the method achieved an area under the curve of 0.87 and demonstrated the ability to detect HRD at tumor fractions as low as 1%, making it 10 times more sensitive than state-of-the-art methods.

From ArrayExpress to BioStudies.

ArrayExpress (https://www.ebi.ac.uk/arrayexpress) is an archive of functional genomics data at EMBL-EBI, established in 2002, initially as an archive for publication-related microarray data and was later extended to accept sequencing-based data. Over the last decade an increasing share of biological experiments involve multiple technologies assaying different biological modalities, such as epigenetics, and RNA and protein expression, and thus the BioStudies database (https://www.ebi.ac.uk/biostudies) was established to deal with such multimodal data. Its central concept is a study, which typically is associated with a publication. BioStudies stores metadata describing the study, provides links to the relevant databases, such as European Nucleotide Archive (ENA), as well as hosts the types of data for which specialized databases do not exist. With BioStudies now fully functional, we are able to further harmonize the archival data infrastructure at EMBL-EBI, and ArrayExpress is being migrated to BioStudies. In future, all functional genomics data will be archived at BioStudies. The process will be seamless for the users, who will continue to submit data using the online tool Annotare and will be able to query and download data largely in the same manner as before. Nevertheless, some technical aspects, particularly programmatic access, will change. This update guides the users through these changes.

CVCDAP: an integrated platform for molecular and clinical analysis of cancer virtual cohorts

Abstract Recent large-scale multi-omics studies resulted in quick accumulation of an overwhelming amount of cancer-related data, which provides an unprecedented resource to interrogate diverse questions. While certain existing web servers are valuable and widely used, analysis and visualization functions with regard to re-investigation of these data at cohort level are not adequately addressed. Here, we present CVCDAP, a web-based platform to deliver an interactive and customizable toolbox off the shelf for cohort-level analysis of TCGA and CPTAC public datasets, as well as user uploaded datasets. CVCDAP allows flexible selection of patients sharing common molecular and/or clinical characteristics across multiple studies as a virtual cohort, and provides dozens of built-in customizable tools for seamless genomic, transcriptomic, proteomic and clinical analysis of a single virtual cohort, as well as, to compare two virtual cohorts with relevance. The flexibility and analytic competence of CVCDAP empower experimental and clinical researchers to identify new molecular mechanisms and develop potential therapeutic approaches, by building and analyzing virtual cohorts for their subject of interests. We demonstrate that CVCDAP can conveniently reproduce published findings and reveal novel insights by two applications. The CVCDAP web server is freely available at https://omics.bjcancer.org/cvcdap/.

A tailored phosphorothioate coordinator enables CRISPR/Cas in-situ amplification

Abstract The CRISPR/Cas system is a powerful tool for molecular diagnostics, but its reliance on linear amplification constrains sensitivity, particularly for in situ imaging. Here, we discovered that phosphorothioate (PS)-modified activators can modulate Cas enzyme conformation via hydrophobic anchoring. By adjusting the PS modification sites, we achieved precise control over Cas activation and trans-cleavage resistance. Guided by this mechanism, we proposed a tailored design strategy featuring a “scattered” PS modification to engineer a linear “Coordinator” probe. This design effectively decouples Cas enzyme activation from substrate trans-cleavage resistance, enabling the construction of a Scattered PS Nucleic Acid-driven Cas Autocatalytic system (SACA). SACA achieves exponential amplification without external enzymes, enhancing Cas12a and Cas13a sensitivity by 50 000-fold and 10 000-fold, respectively. Furthermore, the superior biostability and structural simplicity of these linear probes endow SACA with excellent compatibility, facilitating precise in situ imaging of HPV16 and HPV18 mRNA in cervical cancer cells. This study not only advances the understanding of Cas enzyme regulation by chemically modified nucleic acids but also establishes a new paradigm for precise and efficient molecular diagnostics.

DOCK7 protects against replication stress by promoting RPA stability on chromatin

Abstract RPA is a critical factor for DNA replication and replication stress response. Surprisingly, we found that chromatin RPA stability is tightly regulated. We report that the GDP/GTP exchange factor DOCK7 acts as a critical replication stress regulator to promote RPA stability on chromatin. DOCK7 is phosphorylated by ATR and then recruited by MDC1 to the chromatin and replication fork during replication stress. DOCK7-mediated Rac1/Cdc42 activation leads to the activation of PAK1, which subsequently phosphorylates RPA1 at S135 and T180 to stabilize chromatin-loaded RPA1 and ensure proper replication stress response. Moreover, DOCK7 is overexpressed in ovarian cancer and depleting DOCK7 sensitizes cancer cells to camptothecin. Taken together, our results highlight a novel role for DOCK7 in regulation of the replication stress response and highlight potential therapeutic targets to overcome chemoresistance in cancer.

Whole-miRNome sequencing: a panel for the targeted sequencing of all human miRNA genes

Abstract Interest in the genetic variation of noncoding genomic elements, including microRNAs (miRNAs), is growing, and several mutations in miRNA genes implicated in human diseases, including cancer, have already been detected. However, the lack of dedicated analytical tools severely hampers progress in this area. In this study, we developed the first whole-miRNome sequencing (WMS) platform, which enables the targeted sequencing of all human miRNA genes (n ∼2000) and 28 miRNA biogenesis genes. By sequencing various types of DNA samples, including ∼300 tumor/normal pairs, from lung, colorectal, ovarian, renal, and basal cell carcinomas, we identified ∼2000 mutations, including 879 in miRNA genes. These mutations were located in all parts of the genes, including seed or cleavage sites essential for the functioning of miRNA genes. The high reliability of the mutations was confirmed through various approaches, including different sequencing methods. The analysis identified several miRNA genes with functional enrichment of cancer mutations, including MIR3928, which was specifically mutated in basal cell carcinoma, suggesting its potential role in this cancer. WMS also allowed the identification of multiple copy number alterations, which often encompassed miRNA genes. WMS provides highly effective, low-cost sequencing of all miRNA genes in different types of samples, including highly degraded ones.

mBodyMap: a curated database for microbes across human body and their associations with health and diseases

Abstract mBodyMap is a curated database for microbes across the human body and their associations with health and diseases. Its primary aim is to promote the reusability of human-associated metagenomic data and assist with the identification of disease-associated microbes by consistently annotating the microbial contents of collected samples using state-of-the-art toolsets and manually curating the meta-data of corresponding human hosts. mBodyMap organizes collected samples based on their association with human diseases and body sites to enable cross-dataset integration and comparison. To help users find microbes of interest and visualize and compare their distributions and abundances/prevalence within different body sites and various diseases, the mBodyMap database is equipped with an intuitive interface and extensive graphical representations of the collected data. So far, it contains a total of 63 148 runs, including 14 401 metagenomes and 48 747 amplicons related to health and 56 human diseases, from within 22 human body sites across 136 projects. Also available in the database are pre-computed abundances and prevalence of 6247 species (belonging to 1645 genera) stratified by body sites and diseases. mBodyMap can be accessed at: https://mbodymap.microbiome.cloud.

Excessive transcription-replication conflicts are a vulnerability of BRCA1-mutant cancers

Abstract BRCA1 mutations are associated with increased breast and ovarian cancer risk. BRCA1-mutant tumors are high-grade, recurrent, and often become resistant to standard therapies. Herein, we performed a targeted CRISPR-Cas9 screen and identified MEPCE, a methylphosphate capping enzyme, as a synthetic lethal interactor of BRCA1. Mechanistically, we demonstrate that depletion of MEPCE in a BRCA1-deficient setting led to dysregulated RNA polymerase II (RNAPII) promoter-proximal pausing, R-loop accumulation, and replication stress, contributing to transcription-replication collisions. These collisions compromise genomic integrity resulting in loss of viability of BRCA1-deficient cells. We also extend these findings to another RNAPII-regulating factor, PAF1. This study identifies a new class of synthetic lethal partners of BRCA1 that exploit the RNAPII pausing regulation and highlight the untapped potential of transcription-replication collision-inducing factors as unique potential therapeutic targets for treating cancers associated with BRCA1 mutations.

The deubiquitinase USP36 Regulates DNA replication stress and confers therapeutic resistance through PrimPol stabilization

Abstract PrimPol has been recently identified as a DNA damage tolerant polymerase that plays an important role in replication stress response. However, the regulatory mechanisms of PrimPol are not well defined. In this study, we identify that the deubiquitinase USP36 interferes with degradation of PrimPol to regulate the replication stress response. Mechanistically, USP36 is deubiquitinated following DNA replication stress, which in turn facilitates its upregulation and interaction with PrimPol. USP36 deubiquitinates K29-linked polyubiquitination of PrimPol and increases its protein stability. Depletion of USP36 results in replication stress-related defects and elevates cell sensitivity to DNA-damage agents, such as cisplatin and olaparib. Moreover, USP36 expression positively correlates with the level of PrimPol protein and poor prognosis in patient samples. These findings indicate that the regulation of PrimPol K29-linked ubiquitination by USP36 plays a critical role in DNA replication stress and chemotherapy response.

An engineered glutamic acid tRNA for efficient suppression of pathogenic nonsense mutations

Abstract Nonsense mutations that introduce premature termination codons (PTCs) into protein-coding genes are responsible for numerous genetic diseases; however, there are currently no effective treatment options for individuals affected by these mutations. One approach to combat nonsense-related diseases relies on the use of engineered suppressor transfer RNAs (sup-tRNAs) that facilitate translational stop codon readthrough, thereby restoring full-length protein synthesis. While several sup-tRNAs have shown promising results in preclinical models, many exhibit low PTC suppression efficiency, precluding their use as therapeutics. For example, glutamic acid (Glu) codons represent one of the most common sites for nonsense mutations, yet existing sup-tRNAs are ineffective at suppressing Glu-to-Stop mutations. To address this limitation, here we describe a rationally designed sup-tRNA (tRNAGluV13) with greatly improved ability to suppress PTCs occurring at Glu codons. We demonstrate that tRNAGluV13 efficiently restores protein synthesis from multiple nonsense-containing reporter genes, faithfully installing Glu in response to PTCs. Additionally, we demonstrate that tRNAGluV13 can functionally rescue pathogenic PTCs that cause hereditary breast and ovarian cancer syndrome and cystic fibrosis. The ability of tRNAGluV13 to effectively suppress one of the most common PTC mutations should greatly expand the potential of sup-tRNA-based therapeutics.

Cancer-causingBRCA2missense mutations disrupt an intracellular protein assembly mechanism to disable genome maintenance

AbstractCancer-causing missense mutations in the 3418 amino acid BRCA2 breast and ovarian cancer suppressor protein frequently affect a short (∼340 residue) segment in its carboxyl-terminal domain (DBD). Here, we identify a shared molecular mechanism underlying their pathogenicity. Pathogenic BRCA2 missense mutations cluster in the DBD’s helical domain (HD) and OB1-fold motifs, which engage the partner protein DSS1. Pathogenic - but not benign – DBD mutations weaken or abolish DSS1-BRCA2 assembly, provoking mutant BRCA2 oligomers that are excluded from the cell nucleus, and disable DNA repair by homologous DNA recombination (HDR). DSS1 inhibits the intracellular oligomerization of wildtype, but not mutant, forms of BRCA2. Remarkably, DSS1 expression corrects defective HDR in cells bearing pathogenic BRCA2 missense mutants with weakened, but not absent, DSS1 binding. Our findings identify a DSS1-mediated intracellular protein assembly mechanism that is disrupted by cancer-causing BRCA2 missense mutations, and suggest an approach for its therapeutic correction.

The m6A reader YTHDF1 promotes ovarian cancer progression via augmenting EIF3C translation

Abstract N 6-Methyladenosine (m6A) is the most abundant RNA modification in mammal mRNAs and increasing evidence suggests the key roles of m6A in human tumorigenesis. However, whether m6A, especially its ‘reader’ YTHDF1, targets a gene involving in protein translation and thus affects overall protein production in cancer cells is largely unexplored. Here, using multi-omics analysis for ovarian cancer, we identified a novel mechanism involving EIF3C, a subunit of the protein translation initiation factor EIF3, as the direct target of the YTHDF1. YTHDF1 augments the translation of EIF3C in an m6A-dependent manner by binding to m6A-modified EIF3C mRNA and concomitantly promotes the overall translational output, thereby facilitating tumorigenesis and metastasis of ovarian cancer. YTHDF1 is frequently amplified in ovarian cancer and up-regulation of YTHDF1 is associated with the adverse prognosis of ovarian cancer patients. Furthermore, the protein but not the RNA abundance of EIF3C is increased in ovarian cancer and positively correlates with the protein expression of YTHDF1 in ovarian cancer patients, suggesting modification of EIF3C mRNA is more relevant to its role in cancer. Collectively, we identify the novel YTHDF1-EIF3C axis critical for ovarian cancer progression which can serve as a target to develop therapeutics for cancer treatment.

mirnaQC: a webserver for comparative quality control of miRNA-seq data

Abstract Although miRNA-seq is extensively used in many different fields, its quality control is frequently restricted to a PhredScore-based filter. Other important quality related aspects like microRNA yield, the fraction of putative degradation products (such as rRNA fragments) or the percentage of adapter-dimers are hard to assess using absolute thresholds. Here we present mirnaQC, a webserver that relies on 34 quality parameters to assist in miRNA-seq quality control. To improve their interpretability, quality attributes are ranked using a reference distribution obtained from over 36 000 publicly available miRNA-seq datasets. Accepted input formats include FASTQ and SRA accessions. The results page contains several sections that deal with putative technical artefacts related to library preparation, sequencing, contamination or yield. Different visualisations, including PCA and heatmaps, are available to help users identify underlying issues. Finally, we show the usefulness of this approach by analysing two publicly available datasets and discussing the different quality issues that can be detected using mirnaQC.

HnRNP D activates production of HPV16 E1 and E6 mRNAs by promoting intron retention

Abstract Human papillomavirus type 16 (HPV16) E1 and E6 proteins are produced from mRNAs with retained introns, but it has been unclear how these mRNAs are generated. Here, we report that hnRNP D act as a splicing inhibitor of HPV16 E1/E2- and E6/E7-mRNAs thereby generating intron-containing E1- and E6-mRNAs, respectively. N- and C-termini of hnRNP D contributed to HPV16 mRNA splicing control differently. HnRNP D interacted with the components of splicing machinery and with HPV16 RNA to exert its inhibitory function. As a result, the cytoplasmic levels of intron-retained HPV16 mRNAs were increased in the presence of hnRNP D. Association of hnRNP D with HPV16 mRNAs in the cytoplasm was observed, and this may correlate with unexpected inhibition of HPV16 E1- and E6-mRNA translation. Notably, hnRNP D40 interacted with HPV16 mRNAs in an HPV16-driven tonsillar cancer cell line and in HPV16-immortalized human keratinocytes. Furthermore, knockdown of hnRNP D in HPV16-driven cervical cancer cells enhanced production of the HPV16 E7 oncoprotein. Our results suggest that hnRNP D plays significant roles in the regulation of HPV gene expression and HPV-associated cancer development.

CZ CELLxGENE Discover: a single-cell data platform for scalable exploration, analysis and modeling of aggregated data.

Hundreds of millions of single cells have been analyzed using high-throughput transcriptomic methods. The cumulative knowledge within these datasets provides an exciting opportunity for unlocking insights into health and disease at the level of single cells. Meta-analyses that span diverse datasets building on recent advances in large language models and other machine-learning approaches pose exciting new directions to model and extract insight from single-cell data. Despite the promise of these and emerging analytical tools for analyzing large amounts of data, the sheer number of datasets, data models and accessibility remains a challenge. Here, we present CZ CELLxGENE Discover (cellxgene.cziscience.com), a data platform that provides curated and interoperable single-cell data. Available via a free-to-use online data portal, CZ CELLxGENE hosts a growing corpus of community-contributed data of over 93 million unique cells. Curated, standardized and associated with consistent cell-level metadata, this collection of single-cell transcriptomic data is the largest of its kind and growing rapidly via community contributions. A suite of tools and features enables accessibility and reusability of the data via both computational and visual interfaces to allow researchers to explore individual datasets, perform cross-corpus analysis, and run meta-analyses of tens of millions of cells across studies and tissues at the resolution of single cells.