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PubMed2026

Structural complexity and mechanistic diversity of MECOM rearrangements in myeloid neoplasms.

Rearrangements involving MECOM at chromosome 3q26.2 are recurrent in myeloid neoplasms, classically represented by inv(3)(q21q26.2) and t(3;3)(q21;q26.2), which reposition the GATA2-distal haematopoietic enhancer and drive aberrant EVI1 overexpression. However, the full structural and mechanistic diversity of MECOM rearrangements (MECOM-r) is yet to be explored. We retrospectively analysed 97 cases with cytogenetically defined MECOM-r and identified 12 with complex rearrangements using GTG-banded karyotyping and tri-colour interphase/metaphase fluorescence in situ hybridisation analyses. These 12 cases demonstrated remarkable structural heterogeneity. The abnormalities encompassed translocations, inversions, insertions, duplications, and deletions, which often coexisted within the same specimen as multiple rearranged subclones. Insertional events emerged as a distinct mechanism of MECOM activation. These encompassed insertions of MYNN and/or MECOM into chromosomes 1 and 6, insertion of chromosome 8 segment into MECOM, and inverted insertions between homologous chromosome 3 segments. Recurrent breakpoints at 3q21 across multiple cases, together with localised copy number imbalances frequently involving the MYNN and GOLIM4 loci at 3q26.2, underscore the architectural fragility of these two regions. Co-occurring abnormalities such as -5/del(5q), -7/del(7q), and TP53 loss were common, reflecting a permissive genomic background for chromosomal reassembly. Our findings expand the mechanistic landscape of MECOM-r beyond canonical inv(3)/t(3;3), establishing 3q21 and 3q26.2 as structural 'hotspots' and genomic instability hubs. Distinct from fusion-driven oncogenes such as KMT2A, MECOM activation results from enhancer hijacking and regional structural remodelling, leading to EVI1 overexpression and clonal evolution in myeloid malignancies.

Humans↗

PubMed2026

Complex structural variation, phylogeny, and disease associations of the mucin pangenome.

Mucins are large glycoproteins that provide hydration and barrier function to epithelial tissues. Although genetically heterogeneous, all mucins harbor a large exon composed of variable number tandem repeats (VNTRs). Short-read sequencing has limited our understanding of mucin VNTR diversity and makes disease association studies challenging. We leverage 296 long-read phased genome assemblies to characterize 14 mucin family members, achieving ≥97% accuracy across 572 haplotypes. Phylogenetic haplogroup analysis reveals extraordinary structural heterozygosity, with MUC4 harboring the greatest allelic diversity (n=240 distinct lengths) and MUC12 the greatest size range (Δ = 55,233 bp; 23,080 amino acids). Ten mucins show significant population stratification (pFDR < 0.05). At the MUC4/MUC20 locus, we characterize higher-order structural variation, including a recurrent inversion, copy number variation, and interlocus gene conversion. Optimized genotyping achieves ≥95% haplogroup concordance across 10 loci. We apply this to 4,637 deeply phenotyped cystic fibrosis patients and identify a significant association between short MUC1 VNTRs and severe disease (p=0.0056), demonstrating the pangenome's utility for complex locus genotyping and disease discovery.

Journal Article↗

PubMed2026

The Charcot-Marie-Tooth Neuropathy (CMTX3) Complex Structural Variation Causes Differential SOX3 Spatiotemporal Expression.

Charcot-Marie-Tooth (CMT) neuropathy is a clinically and genetically heterogeneous group of diseases characterized by the length-dependent axonal degeneration of peripheral nerves. We previously mapped a rare form of X-linked CMT, CMTX3, to a 5.7-Mb interval on chromosome Xq26.3-q27.1 and excluded the coding region of all known genes in the linkage interval for mutations. Whole genome sequencing subsequently identified a 78-kb region of chromosome 8q24.3 that had been duplicated and inserted into the CMTX3 locus between the genes HAPSTR2 and SOX3. The 78-kb insertion, which contains a partial transcript of ARHGAP39, fully segregated in families with CMTX3 and was absent in neurologically normal controls. To retain the CMTX3 insertion and investigate its consequences in appropriate neuronal tissue, we generated induced pluripotent stem cells (iPSCs) from CMTX3 fibroblasts. Using bulk RNA sequencing of patient-derived spinal motor neurons, ARHGAP39 was deemed nonpathogenic by excluding both the formation of novel fusion transcripts and dosage effects from the partial duplication. Subsequent NanoString expression analyses of candidate genes within the CMTX3 locus, across different stages of neuronal differentiation, identified spatiotemporal dysregulation of SOX3. NanoString showed reduced SOX3 expression in patient iPSCs. RNA sequencing detected SOX3 downregulation in CMTX3 neuroepithelial progenitor cells, which was further confirmed by quantitative proteomics. Given the early onset and relatively rapid progression of CMTX3, these data prioritise SOX3 as a leading candidate gene, consistent with its role as one of the earliest transcription factors expressed in the developing nervous system and a key regulator of neuronal fate.

Humans↗

PubMed2025

SVbyEye: a visual tool to characterize structural variation among whole-genome assemblies.

MOTIVATION: We are now in the era of being able to routinely generate highly contiguous (near telomere-to-telomere) genome assemblies of human and nonhuman species. Complex structural variation and regions of rapid evolutionary turnover are being discovered for the first time. Thus, efficient and informative visualization tools are needed to evaluate and directly observe structural differences between two or more genomes. RESULTS: We developed SVbyEye, an open-source R package to visualize and annotate sequence-to-sequence alignments along with various functionalities to process these alignments. The tool facilitates the characterization of complex structural variants in the context of sequence homology helping resolve the mechanisms underlying their formation. AVAILABILITY AND IMPLEMENTATION: SVbyEye is available on GitHub (https://github.com/daewoooo/SVbyEye) and via Zenodo (https://doi.org/10.5281/zenodo.15303553).

Software↗

PubMed1976

Fine structure of complex ocelli of a cubomedusan, Tamoya bursaria Haeckel.

The retina of the distal and proximal lens-bearing complex ocelli are composed of pigmented sensory cells and long pigmented cells. A ciliary sheath from each sensory cell, together with the processes of long pigmented cells, extends through the vitreous layer as far as the capsule that envelops the lens. Each ciliary sheath has several ballon-like swellings and the ciliary microtubules, arranged in the 9+2 pattern in the proximal part, are markedly disorganized distally in the swollen parts, out of which extends most of the microvilli in the vitreous layer. It is suggested that some of the microvilli may originate in vesicles that are constricted off from the surface of the pigmented sensory cells. Closely packed microvilli run in parallel in short bundles. In addition to characteristic junctions between sensory cells, junctions that are presumably synaptic and, of a new type in coelenterates, are observed between sensory cells and nerve endings.

Animals↗

PubMed2026

Deletion of the MALAT1 RNA 3' end promotes transcript decay and inhibits proliferation in gastric and breast cancer cells.

The long non-coding RNA MALAT1 is a conserved oncogenic driver whose function relies on a 3' triple-helix motif. While its biochemistry is well-characterized in vitro, the endogenous requirement for this motif in regulating the stability of the transcript and other genes residing in its locus remains unclear. In this study, we employed a dual-sgRNA CRISPR-Cas9 approach to systematically excise triple-helix-forming sequences from the native MALAT1 locus in gastric (AGS) and breast (MCF7) cancer cells. Our findings demonstrate that the 3' end strongly contributes to MALAT1 stability. Perturbations ranging from genomic deletions to a single-base changes trigger transcript collapse and rapid exonucleolytic decay, while the biogenesis of the small RNA mascRNA (a byproduct of MALAT1, also involved in cancer) remains decoupled and unaffected. In cellulo, DMS probing reveals that edited transcripts retain structural complexity in the 3' region. Phenotypically, structural disruption of the 3' end significantly impairs proliferation of both cancer cellular models. These results identify the 3' triple-helix as a determinant of MALAT1 stability and provide endogenous validation for its role in the analyzed AGS and MCF7 cells.

Cancer↗

PubMed2025

Complex de novo structural variants are an underestimated cause of rare disorders.

Complex de novo structural variants (dnSVs) are crucial genetic factors in rare disorders, yet their prevalence and characteristics in rare disorders remain poorly understood. Here, we conduct a comprehensive analysis of whole-genome sequencing data of 12,568 families, including 13,698 offspring with rare diseases, obtained as part of the UK 100,000 Genomes Project. We identify 1,870 dnSVs, constituting the largest dnSV dataset reported to date. Complex dnSVs (n = 158; 8.4%) emerge as the third most common type of SV, following simple deletions and duplications. We classify 65% of these complex dnSVs into 11 subtypes. Among probands with dnSVs (n = 1,696), 9% exhibit exon-disrupting pathogenic dnSVs associated with the probands' phenotype. Notably, 12% of exon-disrupting pathogenic dnSVs and 22% of de novo deletions or duplications previously identified by array-based or whole-exome sequencing methods are found to be complex dnSVs. We also find distinct genomic properties of de novo deletions depending on the parent of origin. This study highlights the importance of complex dnSVs in the cause of rare disorders and demonstrates the necessity of specific genomic analysis to avoid overlooking these variants.

Humans↗

PubMed2025

Recurrent structural variation and recent turnover at the 17q21.31 locus in humans and great apes.

The 17q21.31 locus in humans harbors several complex structural haplotypes including a ~970kb inversion. Different inversion haplotypes have been associated with susceptibility to microdeletions causing Koolen-de Vries syndrome and variation in fecundity and recombination rates. Here, using 210 haplotype-resolved human genome assemblies and pangenome graph-based approaches we characterize 11 distinct structural haplotypes, several of which have not been previously described. Extending our analyses to a set of haplotype-resolved great-ape genomes, we characterize the structure of an independent inversion in chimpanzees which extends an additional 650kb, encompasses 5 additional genes, and is ~2 million years younger than the human inversion. We further determine that gorillas exhibit an independent duplication of the KANSL1 gene which may predispose them to Koolen-de Vries syndrome causing microdeletions. Using short read sequencing data we characterize 17q21.31 haplotype diversity worldwide in ~5174 individuals from 107 populations finding increased frequencies of KANSL1 duplication-containing haplotypes in both European and South Asian populations as well as 8 double recombination events between inverted and non-inverted haplotypes ranging in size from 20-180kb. Finally, using 626 ancient Eurasian human genomes we show the frequency of haplotypes containing KANSL1 duplications has increased ~6-fold over the past 12 thousand years in Europe. Together, our results highlight the dynamics, complexity, and recurrent, independent evolution of a medically relevant locus across humans and great apes.

Journal Article↗

PubMed2025

A small cationic probe for accurate, punctate discovery of RNA tertiary structure.

RNA molecules fold into intricate three-dimensional tertiary structures that are central to their biological functions. Yet reliably discovering new motifs that form true tertiary interactions remains a major challenge. Here we show that RNA tertiary folding occasionally generates electronegative motifs that react selectively with the small, positively-charged probe trimethyloxonium (TMO). Sites with enhanced reactivity to TMO, compared with the neutral reagent dimethyl sulfate (DMS), are indicative of tertiary structure and define T-sites. These positions share a structural signature in which a reactive nucleobase is adjacent to non-bridging phosphate oxygens, creating localized regions of negative charge. T-sites consistently map to the cores of higher-order structural interactions and functional centers across diverse RNAs, including distinct states in conformational ensembles. In the 10,723-nt dengue virus genome, three strong T-sites were detected, each within a complex structure required for viral replication. Cation-based covalent chemistry enables high-confidence discovery and analysis of functional RNA tertiary motifs across long and complex RNAs, opening new opportunities for transcriptome-wide structural analysis.

RNA electrostatics↗

PubMed2003

Inhibition of the protein kinase PKR by the internal ribosome entry site of hepatitis C virus genomic RNA.

Translation of the hepatitis C genome is mediated by internal ribosome entry on the structurally complex 5' untranslated region of the large viral RNA. Initiation of protein synthesis by this mechanism is independent of the cap-binding factor eIF4E, but activity of the initiator Met-tRNA(f)-binding factor eIF2 is still required. HCV protein synthesis is thus potentially sensitive to the inhibition of eIF2 activity that can result from the phosphorylation of the latter by the interferon-inducible, double-stranded RNA-activated protein kinase PKR. Two virally encoded proteins, NS5A and E2, have been shown to reduce this inhibitory effect of PKR by impairing the activation of the kinase. Here we present evidence for a third viral strategy for PKR inhibition. A region of the viral RNA comprising part of the internal ribosome entry site (IRES) is able to bind to PKR in competition with double-stranded RNA and can prevent autophosphorylation and activation of the kinase in vitro. The HCV IRES itself has no PKR-activating ability. Consistent with these findings, cotransfection experiments employing a bicistronic reporter construct and wild-type PKR indicate that expression of the protein kinase is less inhibitory towards HCV IRES-driven protein synthesis than towards cap-dependent protein synthesis. These data suggest a dual function for the viral IRES, with both a structural role in promoting initiation complex formation and a regulatory role in preventing inhibition of initiation by PKR.

Animals↗

PubMed2025

In silico prediction method for plant Nucleotide-binding leucine-rich repeat- and pathogen effector interactions.

Plant Nucleotide-binding leucine-rich repeat (NLR) proteins play a crucial role in effector recognition and activation of Effector triggered immunity following pathogen infection. Genome sequencing advancements have led to the identification of a myriad of NLRs in numerous agriculturally important plant species. However, deciphering which NLRs recognize specific pathogen effectors remains challenging. Predicting NLR-effector interactions in silico will provide a more targeted approach for experimental validation, critical for elucidating function, and advancing our understanding of NLR-triggered immunity. In this study, NLR-effector protein complex structures were predicted using AlphaFold2-Multimer for all experimentally validated NLR-effector interactions reported in literature. Binding affinities- and energies were predicted using 97 machine learning models from Area-Affinity. We show that AlphaFold2-Multimer predicted structures have acceptable accuracy and can be used to investigate NLR-effector interactions in silico. Binding affinities for 58 NLR-effector complexes ranged between -8.5 and -10.6 log(K), and binding energies between -11.8 and -14.4 kcal/mol-1, depending on the Area-Affinity model used. For 2427 "forced" NLR-effector complexes, these estimates showed larger variability, enabling identification of novel NLR-effector interactions with 99% accuracy using an Ensemble machine learning model. The narrow range of binding energies- and affinities for "true" interactions suggest a specific change in Gibbs free energy, and thus conformational change, is required for NLR activation. This is the first study to provide a method for predicting NLR-effector interactions, applicable to all pathosystems. Finally, the NLR-Effector Interaction Classification (NEIC) resource can streamline research efforts by identifying NLRs important for plant-pathogen resistance, advancing our understanding of plant immunity.

Plant Proteins↗

PubMed2026

Artificial Intelligence for Natural Products Discovery and Development.

Natural products (NPs) remain a cornerstone of modern drug discovery, offering stereochemical complexity and diverse bioactivities that precisely modulate therapeutic targets, refined through billions of years of evolution. However, their research has long been hindered by inefficient, empirical workflows, high resource consumption, structural complexity, and the "multicomponent, multi-target" nature of their mechanisms. The exponential growth of genomic, metabolomic, and spectral data has overwhelmed conventional analytical methods, exposing critical bottlenecks in handling high-dimensional, heterogeneous datasets that exceed human interpretive capacity. Artificial intelligence (AI) is emerging as a transformative paradigm to address these challenges, integrating multi-omics and chemical data to shift NP research from fragmented empiricism toward mechanism-driven, precision-oriented development. By leveraging deep learning architectures- including graph neural networks, Transformers, and diffusion-based generative models-AI enables systematic decoding of NP biosynthesis, automated structure elucidation, rational target identification, knowledge extraction from vast unstructured scientific literature, and de novo molecular design. This review comprehensively surveys recent advances in AI applications across the full NP discovery and development pipeline, encompassing genome mining, structure-based and ligand-based virtual screening, multimodal structural characterization, lead optimization, and biosynthetic pathway engineering. We further examine the emerging roles of protein-centric, molecule- centric, and multimodal foundation models, as well as large language models, in bridging genotype-to-chemotype gaps and unlocking unstructured scientific knowledge. Finally, we discuss critical challenges including data scarcity, representational limitations for complex stereochemistry, physical plausibility in generative models, and the urgent need for experimental validation, while outlining future directions toward autonomous experimentation, closed-loop optimization, and human-AI collaborative discovery.

Artificial intelligence↗

PubMed2025

Unsupervised multiscale clustering of single-cell transcriptomes to identify hierarchical structures of cell subtypes.

BACKGROUND: Cell clustering is an essential step in uncovering cellular architectures in single-cell RNA sequencing (scRNA-seq) data. However, the existing cell clustering approaches are not well designed to dissect complex structures of cellular landscapes at a finer resolution. RESULTS: Here, we develop a multiscale clustering (MSC) approach to construct a sparse cell-cell correlation network for unsupervised identification of de novo cell types and subtypes across multiple resolutions. Based upon simulated silver- and gold-standard data as well as real scRNA-seq data in diseases, MSC demonstrates significantly improved performance compared to established benchmark methods and reveals a biologically meaningful cell hierarchy to facilitate the discovery of novel disease-associated cell subtypes and mechanisms. CONCLUSIONS: We present MSC as a new single-cell multiscale clustering framework as a powerful tool for advancing discoveries in disease-associated cell populations using single-cell sequencing data.

Single-Cell Analysis↗

PubMed2026

Marine-derived Bioactive Compounds: A Promising Frontier against Multidrug-resistant Microbial Infections.

The global escalation of Multidrug-Resistant (MDR) bacterial infections poses a serious and growing threat to public health, contributing to increased morbidity, mortality, and substantial economic burden worldwide. The widespread and often indiscriminate use of antibiotics in clinical and agricultural settings has accelerated the emergence of resistance, significantly diminishing the efficacy of conventional antimicrobial therapies. This pressing challenge necessitates the exploration of alternative sources for novel antibiotics. Marine ecosystems-renowned for their immense biodiversity and ecological complexity-have gained attention as a rich and largely untapped reservoir of bioactive natural products with potent antimicrobial activity. Marine organisms, such as sponges, tunicates, algae, and bacteria and fungi derived from marine sources, produce structurally diverse and pharmacologically active metabolites, including peptides, polyketides, alkaloids, terpenoids, sterols, lactones, and halogenated compounds. Many of these marine-derived molecules possess unique chemical scaffolds and novel mechanisms of action, offering the potential to circumvent existing resistance pathways. Some compounds have shown promising activity against MDR pathogens, including Staphylococcus aureus, Pseudomonas aeruginosa, and Acinetobacter baumannii. However, challenges such as low natural abundance, difficulty in cultivation, and structural complexity have limited their clinical translation. Recent advancements in marine biotechnology, genomics, metagenomics, and synthetic biology have opened new avenues for the discovery, biosynthesis, and structural optimization of these compounds. These innovative approaches not only facilitate sustainable production but also enhance the pharmacological properties.

Humans↗

PubMed2024

Putative rhamnogalacturonan-II glycosyltransferase identified through callus gene editing which bypasses embryo lethality.

Rhamnogalacturonan II (RG-II) is a structurally complex and conserved domain of the pectin present in the primary cell walls of vascular plants. Borate cross-linking of RG-II is required for plants to grow and develop normally. Mutations that alter RG-II structure also affect cross-linking and are lethal or severely impair growth. Thus, few genes involved in RG-II synthesis have been identified. Here, we developed a method to generate viable loss-of-function Arabidopsis (Arabidopsis thaliana) mutants in callus tissue via CRISPR/Cas9-mediated gene editing. We combined this with a candidate gene approach to characterize the male gametophyte defective 2 (MGP2) gene that encodes a putative family GT29 glycosyltransferase. Plants homozygous for this mutation do not survive. We showed that in the callus mutant cell walls, RG-II does not cross-link normally because it lacks 3-deoxy-D-manno-octulosonic acid (Kdo) and thus cannot form the α-L-Rhap-(1→5)-α-D-kdop-(1→sidechain). We suggest that MGP2 encodes an inverting RG-II CMP-β-Kdo transferase (RCKT1). Our discovery provides further insight into the role of sidechains in RG-II dimerization. Our method also provides a viable strategy for further identifying proteins involved in the biosynthesis of RG-II.

Arabidopsis↗

PubMed2026

From glycosylation to inflammation: insights from NMR-Derived GlycA and GlycB.

Post-translational modifications (PTMs) play a crucial role in increasing proteomic diversity. N-linked glycosylation acts as a key regulatory layer that influences protein stability, trafficking, circulation, and immune responses. Unlike conventional inflammatory biomarkers that measure individual proteins, nuclear magnetic resonance (NMR) spectroscopy identifies the combined signals GlycA and GlycB from glycoproteins, offering an overall view of systemic glycoprotein changes. These signals represent the N-glycosylation patterns of several abundant acute-phase proteins (APPs), giving detailed molecular insights. This review offers a detailed assessment of GlycA and GlycB as mechanistically grounded indicators of liver glycoprotein remodeling and systemic inflammation. GlycA mainly indicates the levels and structural complexity of N-acetylglucosamine (GlcNAc) and N-acetylgalactosamine (GalNAc) residues linked to acute-phase glycoproteins and glycan branching. In contrast, GlycB reflects changes in terminal sialylation, which influences glycoprotein half-life, immune recognition via lectins, and inflammatory signaling. Collectively, these biomarkers combine measurements of hepatic APP production with variations in glycan structure, offering mechanistically anchored reporters of hepatic glycoprotein remodeling. We explore the enzymatic pathways responsible for N-glycan branching, fucosylation, and sialylation, as well as the roles of major APP scaffolds in the GlycA and GlycB resonances. We also highlight the emerging clinical significance of these signals across infectious, autoimmune, cardiovascular, metabolic, neurodegenerative, and cancer-related diseases. Rather than serving simply as markers of inflammation, GlycA and GlycB provide mechanistically interpretable readouts of cytokine-driven hepatic glycoprotein remodeling and systemic immune activation, supporting their application in disease risk stratification, longitudinal monitoring, therapeutic response assessment, and precision medicine.

GlycA↗

PubMed2025

CS Ratio is an immune-related prognostic biomarker for cervical cancer.

BACKGROUND: The tumor microenvironment (TME) plays a crucial role in cancer progression but its complex structure significant variability among patients present considerable challenges for research. Recent studies have demonstrated that macrophage polarization states defined by the expression levels of CXCL9 SPP1 (CS Ratio) are more prognostically relevant than traditional M1/M2 markers. The CS polarization state reflects a highly coordinated network of pro-tumor anti-tumor variables offering a simplified yet effective immune response indicator for the complex TME. The CS Ratio has been shown to correlate with the abundance of anti-tumor immune cells the gene expression programs of tumor-infiltrating cells responses to immunotherapy. Cervical cancer, one of the most common gynecological malignancies, still faces limited therapeutic options. CXCL9, a member of the CXC chemokine family, plays a critical role in immune regulation, inflammation, tumor growth, angiogenesis, and metastasis. Similarly, SPP1, a cytokine, influences immune-related pathways by regulating molecules such as interferon-γ and interleukin-12. However, no studies have systematically investigated the role of the CS Ratio in cervical cancer or its relationship with immunotherapy characteristics. Research in this area could provide critical insights into the role and clinical potential of the CS Ratio in cervical cancer and related tumors. METHODS: The expression ratio of CXCL9 to SPP1 was analyzed in cervical cancer patients using data from the Gene Expression Omnibus (GEO) database, which revealed significant differences. Data for cervical cancer patients were obtained from The Cancer Genome Atlas (TCGA) database. The optimal cutoff value for the CS Ratio was determined using the maxstat package in R, and Kaplan-Meier (KM) survival curves were constructed. Patients were categorized into High and Low groups based on the median CS Ratio. Immune scores were analyzed, and immune cell infiltration was assessed using CIBERSORT. Differences in the CS Ratio were evaluated across patients with varying pathological T stages and FIGO stages. Additionally, receiver operating characteristic (ROC) analysis was performed using the pROC package in R to calculate the area under the curve (AUC). Univariate and multivariate Cox regression analyses were performed to evaluate the potential of the CS Ratio as an independent prognostic factor in cervical cancer. A Cox regression-based nomogram integrating four key features was subsequently developed for the TCGA-CESC cohort. Nomogram performance was assessed using calibration curves and ROC analysis. RESULTS: The CS Ratio was significantly lower in cervical cancer patients compared to normal controls (P < 0.05). KM survival curves indicated that patients in the CS High group exhibited better prognoses. Immune score analysis revealed significantly higher immune scores (P < 0.05) and lower tumor purity (P < 0.05)in the CS High group compared to the Low group. CIBERSORT analysis revealed significantly higher proportions of CD8+ T cells (P < 0.05) and M1 macrophages (P < 0.05), and a significantly lower proportion of M2 macrophages (P < 0.05), in the CS High group compared to the Low group. The CS Ratio significantly decreased with advancing FIGO stage (P < 0.05). Both univariate (P < 0.05) and multivariate Cox regression analyses (P < 0.05) confirmed the CS Ratio as an independent prognostic factor. ROC analysis demonstrated that the CS Ratio had higher AUC values for predicting 1-year (AUC=0.69), 3-year (AUC=0.66), and 5-year OS (AUC=0.68) than CXCL9 or SPP1 alone. The Cox regression-based nomogram integrating four key features demonstrated predictive capability for 1-, 3-, and 5-year OS in CESC patients (Concordance Index = 0.751; 95% CI: 0.678-0.824; p = 1.50Í10-11). Significant survival differences were observed between the high-risk and low-risk groups based on the nomogram score. ROC analysis yielded high AUC values for survival prediction: 0.85 (95% CI: 0.94-0.75) at 1-year, 0.74 (95% CI:0.84-0.64) at 3-year, and 0.72 (95% CI:0.84-0.61) at 5-year. CONCLUSION: The CS Ratio may serve as a more effective prognostic biomarker for cervical cancer patients.

CXCL9↗

PubMed2026

PangyPlot: multi-scale interactive visualization of pangenome variation graphs.

SUMMARY: Pangenome variation graphs integrate multiple samples into a unified representation, mitigating the reference bias inherent to linear genomes. However, these graphs can be large and structurally complex. Existing visualization tools are each confined to a fixed scale of resolution, requiring researchers to switch between multiple tools to examine variation at different levels of detail. PangyPlot is an interactive pangenome browser designed for multi-scale exploration of reference variation graphs from full chromosome to nucleotide-level sequence segments. PangyPlot anchors navigation to linear reference coordinates, organizes variation into hierarchical bubble structures, and uses a force-directed layout engine for automatic node arrangement. AVAILABILITY AND IMPLEMENTATION: An instance preloaded with data is available at https://pangyplot.research.sickkids.ca. Source code and documentation are openly available at https://github.com/strug-hub/pangyplot under the MIT License.

Software↗