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PubMed2026

Targeting super-enhancer-driven SKIL transcription by CDK7 inhibitor THZ1 to suppress gastric cancer progression.

BACKGROUND: Gastric cancer (GC) is a lethal malignancy characterized by high incidence, mortality, and limited treatment options. Transcriptional addiction is a key cancer hallmark that drives tumor pathogenesis, making its inhibition a promising therapeutic strategy for GC. The study aims to investigate the roles and mechanisms of super-enhancer (SE)-driven oncogenic transcriptional addiction in GC progression and to identify novel targetable vulnerabilities. METHODS: We utilized cellular and animal models to assess the effects of THZ1 treatment and CDK7 knockdown on GC progression. RNA sequencing was employed to elucidate the potential molecular mechanism of THZ1 treatment. ChIP-seq was performed to establish SE landscape in GC. Integrative analysis of transcriptomic and SE profiling was used to identify THZ1-targeted oncogenic genes. Rescue experiments were conducted to confirm that THZ1 treatment suppresses GC malignant progression by targeting SE-driven SKIL transcription. RESULTS: GC cells exhibited pronounced sensitivity to THZ1 compared to normal gastric mucosa cells, and the treatment potently suppressed tumor growth and migration in both cellular and animal models. CDK7 was significantly upregulated in GC tissues, and its knockdown inhibited malignant progression in vitro and in vivo, whereas its overexpression accelerated tumor progression. Mechanistically, SE-driven oncogenic transcriptional amplification underlies GC cell susceptibility to THZ1, supported by the identification of novel oncogenic genes such as SKIL. SKIL, a key Hippo pathway regulator, was highly expressed in GC cells, and its elevated expression predicted poor patient prognosis. SKIL silencing attenuated malignant phenotypes, while its overexpression diminished THZ1’s suppression of GC cell proliferation and migration. CONCLUSION: Our findings demonstrate that THZ1 inhibits GC progression by disrupting SE-driven oncogenic transcription, thereby offering CDK7 inhibition as a promising therapeutic intervention for GC.

Stomach Neoplasms↗
PubMed2026

Epigenetic and metabolic reprogramming of innate immune cells establishes immunological memory in the Schistosomiasis vector snail Biomphalaria glabrata.

Innate immune memory enables non-vertebrates to mount faster and more effective immune responses upon re-exposure to a previously encountered pathogen, yet its cellular and molecular bases remain poorly understood. The freshwater snail Biomphalaria glabrata, intermediate host of the human parasite Schistosoma mansoni, provides a powerful model to investigate this phenomenon. Here, we show that innate immune memory in B. glabrata is carried by hemocytes and relies on profound metabolic and epigenetic reprogramming initiated during primary infection. Using an integrative multi-omics approach combining transcriptomics, chromatin accessibility profiling, whole-genome bisulfite sequencing and targeted metabolomics, we reveal that the first parasite encounter induces a stable rewiring of hemocyte metabolism and chromatin landscape. This reprogramming primes hemocytes for a massive and rapid transcriptional response upon secondary challenge, characterized by an immune shift toward highly specific humoral effector pathways. Metabolic analyses demonstrate an early switch toward aerobic glycolysis, altered tricarboxylic acid cycle activity and amino acid metabolism, consistent with a Warburg-like metabolic state previously described in vertebrate trained immunity. Notably, metabolic and epigenetic remodeling occurs primarily during the primary infection and remains stable upon secondary exposure, suggesting that immune memory is encoded prior to pathogen re-encounter. Together, our results identify conserved metabolic and epigenetic mechanisms underlying innate immune memory in a non-vertebrate host and provide direct evidence that hemocyte-mediated innate immune memory in B. glabrata shares core features with trained immunity described in vertebrates.

Animals↗
PubMed2026

Integrated Metabolomic and Transcriptomic Analysis Reveals Tissue-Specific Secondary Metabolic Differentiation and Indole Alkaloid Accumulation in Evodia rutaecarpa.

Evodia rutaecarpa is a valuable medicinal plant, yet its non-medicinal tissues remain largely underexplored. Here, we integrated ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS)-based widely targeted metabolomics and RNA sequencing (RNA-seq) transcriptomics to systematically profile the metabolic and transcriptional landscapes of roots, stems, leaves, and flowers of Evodia rutaecarpa (Juss.) Benth. Our aim was to characterize tissue-specific metabolic differentiation and its underlying transcriptional regulatory mechanisms. Metabolomic analysis, employing principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) with robust model parameters (R2Y > 0.9, Q2 > 0.5), identified 3090 differential metabolite features (variable importance in projection, VIP > 1.0; p < 0.05) across the four tissues, which exhibited distinct tissue-specific clustering patterns. Integrated Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and weighted gene co-expression network analysis (WGCNA) revealed that roots specifically accumulated quinolone alkaloids and flavonoid glycosides, accompanied by the coordinated upregulation of genes involved in flavonoid and phenylpropanoid biosynthetic pathways. In contrast, stems, leaves, and flowers were enriched in indole alkaloids (evodiamine and rutaecarpine) and volatile oil precursors, with concurrent upregulation of genes involved in tryptophan metabolism and indole alkaloid biosynthesis (e.g., tryptophan decarboxylase, TDC; s N-methyltransferase, NMT). Notably, leaves and flowers displayed particularly high accumulation levels of these bioactive alkaloids, suggesting their potential as alternative sources for industrial and pharmaceutical applications. WGCNA further identified multiple transcription factors and structural gene modules tightly correlated with evodiamine accumulation, offering promising candidate regulators for future biosynthetic pathway engineering. Collectively, this multi-omics integration study systematically elucidates the tissue-partitioned secondary metabolism of Evodia rutaecarpa (Juss.) Benth. and provides a solid scientific foundation for full-plant resource utilization, targeted development of non-medicinal tissues, and future metabolic engineering of indole alkaloid production.

Evodia rutaecarpa↗
PubMed2026

Genome-Wide Identification of the Soybean GH5 Gene Family and Functional Analysis of GmGH5-22 in Salt Tolerance.

Plant GH5 family genes function in both cell wall biosynthesis and stress responses. However, comprehensive studies on GH5 genes in the soybean remain limited. Here, we identified 28 GmGH5 genes from the soybean genome. Phylogenetic analysis assigned these genes to three subfamilies (I-III), with no representatives in subfamily IV. The GmGH5 family harbors 15 conserved motifs, which are largely similar within subfamilies but differ across subfamilies. Additionally, exon-intron structures (2-7 introns) exhibit clade-specific patterns, with members within the same clade sharing similar intron numbers and lengths, whereas distinct clades show some variation. The promoter regions of GmGH5 genes contained various cis-acting regulatory elements associated with stress responses and developmental processes. Transcriptome-based expression profiling revealed distinct tissue-specific expression patterns of GmGH5 genes. RT-qPCR further confirmed their differential expression under salt, alkaline, cold, and drought stresses, especially a significant increase in GmGH5-22 expression under salt stress (approximately 22-fold at 6 h, **** p < 0.0001). Furthermore, GmGH5-22 was highly expressed in roots, and transient expression in tobacco leaves showed its peripheral localization, which aligns with its predicted extracellular localization, suggesting that GmGH5-22 is highly likely localized to the cell wall. Overexpression of GmGH5-22 in soybean hairy roots significantly improved tolerance to salt stress. These findings establish a foundation for functional characterization of GmGH5 genes and provide viable targets for molecular breeding to enhance salt tolerance in soybeans.

GH5 family↗
PubMed2000

Identifying cytotoxic T cell epitopes from genomic and proteomic information: "The human MHC project.".

Complete genomes of many species including pathogenic microorganisms are rapidly becoming available and with them the encoded proteins, or proteomes. Proteomes are extremely diverse and constitute unique imprints of the originating organisms allowing positive identification and accurate discrimination, even at the peptide level. It is not surprising that peptides are key targets of the immune system. It follows that proteomes can be translated into immunogens once it is known how the immune system generates and handles peptides. Recent advances have identified many of the basic principles involved. The single most selective event is that of peptide binding to MHC, making it particularly important to establish accurate descriptions and predictions of peptide binding for the most common MHC variants. These predictions should be integrated with those of other steps involved in antigen processing, as these become available. The ability to translate the accumulating primary sequence databases in terms of immune recognition should enable scientists and clinicians to analyze any protein of interest for the presence of potentially immunogenic epitopes. The computational tools to scan entire proteomes should also be developed, as this would enable a rational approach to vaccine development and immunotherapy. Thus, candidate vaccine epitopes might be predicted from the various microbial genome projects, tumor vaccine candidates from mRNA expression profiling of tumors ("transcriptomes") and auto-antigens from the human genome.

Antigen Presentation↗
PubMed2026

Integrated metabolomic, transcriptomic, and proteomic analyses reveal changes in the non-volatile metabolite profile of LED light-withered oolong tea.

LED light withering is a crucial method for overcoming weather limitations and enhancing the quality of oolong tea. To elucidate the underlying molecular mechanisms, this study simulated solar spectra using multiwavelength LED light and compared the resulting metabolic, transcriptomic, and proteomic profiles during the enzymatic-catalysis process (ECP) in oolong tea processing. Results indicated that LED light withering altered gene expression and protein regulation of secondary metabolism, particularly in the flavonoid biosynthesis pathway. These shifts encompassed key quality-related compounds, including flavonoids (quercetin-3-O-rhamnoside, dihydroquercetin), amino acids (L-asparagine, L-histidine), guanosine 5'-monophosphate (GMP), and carbohydrates. Furthermore, LED light withering accelerated tea leaf water loss, influenced gene expression involved in photosynthetic cellular components (chloroplasts, thylakoids), increased ascorbate peroxidase regulation under stress, and subsequently modulated energy metabolism and signal transduction in tea leaves. This study offers molecular theoretical framework for the controlled light-withering of oolong tea under bad weather and the associated improvements in its quality.

Camellia sinensis↗
PubMed2025

Coalescing single-cell genomes and transcriptomes to decode breast cancer progression.

Understanding epithelial lineages of breast cancer and genotype-phenotype relationships requires direct measurements of the genome and transcriptome of the same single cells at scale. To achieve this, we developed wellDR-seq, a high-genomic-resolution, high-throughput method to simultaneously profile the genome and transcriptome of thousands of single cells. We profiled 33,646 single cells from 12 estrogen-receptor-positive breast cancers and identified ancestral subclones in multiple patients that showed a luminal hormone-responsive lineage, indicating a potential cell of origin. In contrast to bulk studies, wellDR-seq enabled the study of subclone-level gene-dosage relationships, which showed near-linear correlations in large chromosomal segments and extensive variation at the single-gene level. We identified dosage-sensitive and dosage-insensitive genes, including many breast cancer genes as well as sporadic copy-number aberrations in non-cancer cells. Overall, these data reveal complex relationships between copy number and gene expression in single cells, improving our understanding of breast cancer progression.

Breast Neoplasms↗
PubMed2025

Human-specific features of the cerebellum and ZP2-regulated synapse development.

Understanding the unique features of the human brain compared to non-human primates has long intrigued humankind. The cerebellum refines motor coordination and cognitive functions, contributing to the evolutionary development of human adaptability and dexterity. To identify shared and divergent features across primates, we conducted single-nucleus transcriptomic and chromatin accessibility profiling of the adult cerebellar cortex in humans, chimpanzees, macaques, and marmosets. We revealed human-specific transcriptomic and regulatory features, particularly those involved in synaptogenesis. Notably, we identified an enrichment of the sperm receptor zona pellucida glycoprotein 2 (ZP2) and its potential interactors, known for their roles in gamete interaction, in human granule cells. Experimental data show that ZP2 expression in human granule cells is induced by pontine mossy fibers, reducing synaptic proteins at pontocerebellar glomerular synapses, and decreasing cerebellar neuron electrophysiological activity. This unexpected co-option of ZP2 in human-specific synapse regulation provides insights into the evolutionary specialization of the human cerebellum.

Brain evolution↗
PubMed2003

Aging-associated changes in cardiac gene expression: large scale transcriptome analysis.

Aging and aging-related diseases are associated with altered patterns of gene expression, involving quantitative and qualitative changes in the abundance of specific transcripts. A complete and simultaneous analysis of gene expression should therefore lead to important insights into the transcriptional mechanisms underlying the aging process. Recently, we have employed high-throughput gene expression profiling to study transcriptional activity in heart. Two technologies, serial analysis of gene expression (SAGE) and gene expression arrays, allow rapid, large-scale expression profiling, which provides information about the dynamics of total gene expression with age and which can be employed to identify candidate genes that may serve as diagnostic and prognostic markers in age-associated cardiac diseases. The accompanying gene predictions from high-throughput gene expression profiling provide a starting point for understanding the function, the complexity of interactions, and the role of genes in promoting cellular/organismal phenotypes during senescence and disease. In this review we describe the current state of transcriptome profiling by SAGE and microarrays and discuss how results generated with these approaches in heart can be applied to the study of aging and the treatment of cardiovascular diseases.

Aging↗
PubMed2000

Transcriptome analysis of channel catfish (Ictalurus punctatus): genes and expression profile from the brain.

Expressed sequence tag (EST) analysis was conducted using a complementary DNA (cDNA) library made from the brain mRNA of channel catfish (Ictalurus punctatus). As part of our transcriptome analysis in catfish to develop molecular reagents for comparative functional genomics, here we report analysis of 1201 brain cDNA clones. Of the 1201 clones, 595 clones (49.5%) were identified as known genes by BLAST searches and 606 clones (50.5%) as unknown genes. The 595 clones of known gene products represent transcripts of 251 genes. These known genes were categorized into 15 groups according to their biological functions. The largest group of known genes was the genes involved in translational machinery (21.4%) followed by mitochondrial genes (6.2%), structural genes (3.1%), genes homologous to sequences of unknown functions (2.3%), enzymes (2.7%), hormone and regulatory proteins (2.5%), genes involved in immune systems (2.1%), genes involved in sorting, transport, and metal metabolism (1.8%), transcriptional factors and DNA repair proteins (1.6%), proto-oncogenes (1.2%), lipid binding proteins (1.2%), stress-induced genes (0.7%), genes homologous to human genes involved in mental diseases (0.6%), and development or differentiation-related genes (0.3%). The number of genes represented by the 606 clones of unknown genes is not known at present, but the high percentage of clones showing no homology to any known genes in the GenBank databases may indicate that a great number of novel genes exist in teleost brain.

Animals↗
PubMed2002

Analysis of altered genomic expression profiles in the senescent and diseased myocardium using cDNA microarrays.

Cardiac function deteriorates with aging or disease. Short term, any changes in heart function may be beneficial, but long term the alterations are often detrimental. At a molecular level, functional adaptations involve quantitative and qualitative changes in gene expression. Analysis of all the RNA transcripts present in a cell's population (transcriptome) offers unprecedented opportunities to map these transitions. Microarrays (chips), capable of evaluating thousands of transcripts in one assay, are ideal for transcriptome analyses. Gene expression profiling provides information about the dynamics of total genome expression in response to environmental changes and may point to candidate genes responsible for the cascade of events that result in disease or are a consequence of aging. The aim of this review is to describe how comparisons of cellular transcriptomes by cDNA array based techniques provide information about the dynamics of total gene expression, and how the results can be applied to the study of cardiovascular disease and aging.

Cardiovascular Diseases↗
PubMed2001

Transcriptome of channel catfish (Ictalurus punctatus): initial analysis of genes and expression profiles of the head kidney.

Analysis of expressed sequence tags (ESTs) is an efficient approach for gene discovery, expression profiling, and development of resources useful for functional genomics studies. As part of the transcriptome analysis in channel catfish (Ictalurus punctatus), we have conducted EST analysis using a cDNA library made from the head kidney. We analysed 2228 EST clones. Orthologues were established for 1495 (67.1%) clones representing 748 genes, of which 545 (36.5%) clones were singletons. The remaining 733 (32.9%) clones represent unknown gene clones, for which the number of genes has not yet been determined.

Animals↗
PubMed2002

The yeast transcriptome in aerobic and hypoxic conditions: effects of hap1, rox1, rox3 and srb10 deletions.

The transcriptome of Saccharomyces cerevisiae was screened using the high-density membrane hybridization method, under aerobic and hypoxic conditions, in wild-type and mutant backgrounds obtained by the disruption of the genes encoding the regulatory proteins Hap1, Rox1 and the Srb10 and Rox3 subunits of RNA polymerase II holoenzyme. None of the mutations studied was able to fully overcome the wild-type hypoxic response. Deletion of the hap1 gene changed the expression profiles of individual open reading frames (ORFs) under both aerobic and hypoxic conditions. Major changes associated with rox3 deletion were related to the hypoxic activation. Rox3 also caused a repressor effect (oxygen-independent) on a subset of genes related to subtelomeric proteins. With regard to the effect brought about by the deletion of rox1 and srb10, correspondence cluster analysis revealed that the transcriptome profile in aerobic conditions is very similar in the wild-type and both deletion strains. In contrast, however, differences were found during hypoxia between the subgroup formed by wild-type and the Deltarox1 deletant compared with the Deltasrb10 deletant. An analysis of selected ORFs responding to hypoxia, in association with a dependence on the regulatory factors studied, made it possible to identify the clusters that are related to different regulatory circuits.

Aerobiosis↗
PubMed2026

The molecular similarity landscape of preclinical cancer models to patient tumors.

Selecting appropriate preclinical models is fundamental for translational oncology, yet a large-scale, multi-omic quantitative comparison of their similarity to primary human tumors is lacking. To address this, we integrated transcriptomic, proteomic, and genomic profiles from over 10,000 primary tumors from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC), alongside 4,000 preclinical models. Using a robust computational framework, we revealed a clear hierarchy of transcriptomic and proteomic similarity to patient tumors: with patient-dervied xenografts (PDXs) having greater transcriptomic and proteomic similarity to patient tumors (>) compared with patient-derived organoids (PDOs), which are equal in hierarchy to that of PDX-dervied organoids (PDXOs) > cell lines. We also quantified high molecular conservation (Pearson correlation coefficient = 0.96) across paired in vitro to in vivo platform (organoids to PDX) transitions. Furthermore, genomic analysis demonstrated that whole-exome sequencing (WES) outperforms RNA-seq in detecting DNA variants, and it identified a clonal complexity hierarchy (cell lines > PDXOs > PDXs > PDOs) reflecting the effect of passaging history on intratumor heterogeneity. Ultimately, this study delivers a comprehensive quantitative benchmark, establishing a population-level hierarchy of molecular similarity between preclinical models and primary tumors and providing a data-driven reference for model selection. These findings offer a data-driven framework for selecting models that balance biological representativeness with experimental practicality.

Humans↗
PubMed2026

Advances in the diagnosis and classification of B-ALL: comparative insights from updated guidelines.

Accurate molecular classification is essential for diagnosis, risk stratification, and treatment selection in B-cell lymphoblastic leukemia (B-ALL). In this study, we performed a comprehensive, real-world reclassification of 1015 consecutively diagnosed B-ALL patients using the fifth edition of the World Health Organization Classification of Haematolymphoid Tumours (WHO-HAEM5) and the International Consensus Classification (ICC). An integrative genomic strategy that combined whole transcriptome sequencing, fusion detection, mutational analysis, and cytogenetics enabled reclassification according to both the WHO-HAEM5 and ICC frameworks, thereby substantially reducing the proportion of unclassifiable B-ALL from 41.9% (2016 WHO revision [WHO-HAEM4R]) to 15.9% (WHO-HAEM5) and 11.9% (ICC). Distinct clinical and prognostic features were identified across newly defined subtypes. Multivariable analysis confirmed that this genomic classification is a robust, independent predictor of survival after adjusting for age, minimal residual disease status, and transplant intervention. Specifically, HLF-rearranged and MEF2D-rearranged B-ALL conferred a persistently poor prognosis across all age groups despite allogeneic hematopoietic stem cell transplantation, highlighting an urgent need for novel therapeutic strategies. Gene expression profiling resolved cryptic subtypes, including ETV6::RUNX1-like, ZNF384-rearranged-like, and BCR::ABL1-like B-ALL, and uncovered diagnostic ambiguity in patients with concurrent lesions. In addition, we report emerging high-risk groups, including IDH1/2- and ZEB2 Q1072-mutated B-ALL, that may warrant recognition as distinct molecular entities. Our findings demonstrate the clinical use of integrative transcriptomic profiling in refining B-ALL taxonomy in guiding risk-adapted therapies and informing future revisions of diagnostic standards. This study supports the incorporation of high-throughput molecular diagnostics into routine leukemia classification and precision treatment planning.

Humans↗
PubMed2026

Divergent evolutionary strategies in spider venoms: A comparative proteomic profiling of four sympatric species from Yunnan.

Spider venoms comprise complex cocktails of bioactive molecules evolved for predation and defense, representing a valuable resource for biological research and pharmaceutical discovery. In this study, we performed a systematic analysis of venom gland extracts from four common spider species indigenous to Yunnan, China: Agelena limbata, Hippasa lycosina, Lycosa grahami, and Sinopoda pengi. Using an integrated transcriptomic and proteomic targeted profiling approach, we successfully annotated 141 distinct toxins. Comparative analysis revealed significant interspecific heterogeneity, suggesting distinct evolutionary trajectories and "weapon system economics." Both A. limbata and L. grahami exhibited a "peptide-dominant" profile anchored by neurotoxic peptides and isomerases, optimized for rapid chemical paralysis. In contrast, S. pengi displayed a distinct "protein-dominant" signature enriched with high-molecular-weight enzymes and CAP superfamily proteins, likely functioning to facilitate tissue degradation and toxin diffusion. Occupying an intermediate position, H. lycosina demonstrated a hybrid composition. These findings suggest that although these species share the same geographical range, their venom systems have undergone divergent evolutionary adaptations driven by specific ecological niches and hunting strategies. This study represents the first systematic proteomic characterization of these venom components, providing a valuable reservoir of molecular candidates while highlighting the bioinformatic nuances of analyzing whole-gland homogenates.

Animals↗
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↗
PubMed2026

Multi-omics approaches in idiopathic pulmonary fibrosis: from molecular mechanisms to therapeutic targets and precision medicine.

Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease with limited therapeutic options and marked molecular heterogeneity. Despite available antifibrotic therapies, disease progression remains poorly predictable, highlighting the need for improved mechanistic understanding and therapeutic targeting. This review summarizes recent advances in multi-omics research to elucidate the molecular mechanisms underlying IPF and to identify potential biomarkers and pharmacological targets. Multi-omics studies, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiome profiling, and single-cell sequencing, have revealed key pathogenic mechanisms in IPF. Genetic susceptibility factors such as MUC5B promoter variants and telomere-related genes contribute to disease risk. Epigenetic regulation, including DNA methylation, histone modifications, and non-coding RNAs, plays a central role in fibrotic remodeling. Transcriptomic and proteomic analyses have identified dysregulated signaling pathways, including TGF-&#x3b2;, mTOR, cellular senescence, and extracellular matrix remodeling. Metabolomic alterations indicate disrupted lipid and amino acid metabolism. Importantly, integration of multi-omics datasets enables the identification of molecular endotypes, candidate biomarkers, and potential therapeutic targets. However, challenges including data integration, tissue heterogeneity, limited cohort size, and the need for functional validation remain important barriers to clinical translation. Continued development of multi-omics approaches may facilitate more accurate disease classification and support the development of personalized therapeutic strategies for IPF.

biomarkers↗