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PubMed2026

Colocalization and functional analyses identify GBE1 as a gene linking muscle strength and cardiometabolic fitness.

Handgrip strength is a proxy for muscular fitness, an indicator for general health status, and is associated with cardiometabolic health. The mechanisms connecting handgrip strength to skeletal muscle function are incompletely understood. We applied integrated linkage-disequilibrium-adjusted colocalization analysis of genome-wide association study summary statistics for handgrip strength, combined with expression and splicing quantitative trait loci from skeletal muscle, and identified glycogen branching enzyme 1 (GBE1) as a candidate gene for handgrip strength. CRISPR-interference knockdown of GBE1 in immortalized human skeletal muscle cells (HMCL-7304) demonstrated decreased glycogen content and accumulation of polyglucosan bodies. Knockdown of GBE1 led to increased oxygen consumption rate, oxidative stress, and changes in mitochondrial morphology. Transcriptomic profiling of GBE1 knockdown cells identified upregulation of the human superoxide dismutase 2 and enrichment of pathways related to muscle contraction and oxidative stress responses. These functional genomic analyses prioritize GBE1 as a muscle-relevant candidate gene for handgrip strength and provide mechanistic insights to muscle fitness.NEW & NOTEWORTHY Colocalization of genome-wide association study (GWAS) loci with quantitative trait loci (QTL) in skeletal muscle tissue identified GBE1 as a candidate for handgrip strength. Cellular phenotypes with GBE1 knockdown in immortalized human skeletal muscle cells include decreased glycogen content, accumulation of polyglucosan bodies, changes in mitochondrial function and morphology, and increased expression of reactive oxygen species (ROS) scavengers. Transcriptomic changes suggest a role for GBE1 in muscle contraction and oxidative stress-mediated responses.

Humans↗

PubMed2003

Gene expression analysis of plant host-pathogen interactions by SuperSAGE.

The type III restriction endonuclease EcoP15I was used in isolating fragments of 26 bp from defined positions of cDNAs. We call this substantially improved variant to the conventional serial analysis of gene expression (SAGE) procedure "SuperSAGE." By applying SuperSAGE to Magnaporthe grisea (blast)-infected rice leaves, gene expression profiles of both the rice host and blast fungus were simultaneously monitored by making use of the fully sequenced genomes of both organisms, revealing that the hydrophobin gene is the most actively transcribed M. grisea gene in blast-infected rice leaves. Moreover, SuperSAGE was applied to study gene expression changes before the so-called hypersensitive response in INF1 elicitor-treated Nicotiana benthamiana, a "nonmodel" organism for which no DNA database is available. Again, SuperSAGE allowed rapid identification of genes up- or down-regulated by the elicitor. Surprisingly, many of the down-regulated genes coded for proteins involved in photosynthesis. SuperSAGE will be especially useful for transcriptome profiling of two or more interacting organisms like hosts and pathogens, and of organisms, for which no DNA database is available.

Base Sequence↗

PubMed2005

Immunoreactivity and differential developmental expression of known and putative Chlamydia trachomatis membrane proteins for biologically variant serovars representing distinct disease groups.

Chlamydia trachomatis is an intracellular bacterium that causes ocular and urogenital diseases worldwide. Membrane proteins have only been partially characterized, and the discovery of a nine-member polymorphic membrane protein gene family has enhanced interest in defining their function. We previously reported two putative insertion sequence-like elements in pmpC for biovariant Ba and one each for G and L2, suggesting horizontal gene transfer. Because of this and the tissue tropism differences for these biovariants, we analyzed by quantitative real-time RT-PCR pmpC expression relative to immunogenic protein genes ompA, groEL and gseA throughout development. Sera from infected adolescents were reacted by immunoblot against recombinant (r)PmpC and rMOMP. ompA and groEL revealed different developmental transcriptome profiles among the biovariants. pmpC expression occurred at 2 h, peaked at 18 for L2 (at 24 for Ba and G), with the highest mRNA levels throughout development for L2. pmpC expression as a function of time paralleled ompA expression with higher mRNA levels compared with groEL later in development. Only sera from D-, E- and G-infected patients reacted to rPmpC; all infected patients reacted to rMOMP. pmpC expression during logarithmic growth suggests a role in membrane building and/or integrity, which is supported by the presence of a signal peptidase and C-terminal phenylalanine in PmpC. Because phylogenetic analyses of pmpC segregate serovars according to tissue tropism, we speculate that biovariant transcriptome differences may contribute to this tropism. The heterogeneous biovariant pmpC expression throughout development and differential PmpC immunoreactivity also suggest a role for pmpC in antigenic variation.

Adolescent↗

PubMed2026

AI-Supported, Integrative Prediction of Postoperative Delirium: Protocol for the CONFUSED Study.

BACKGROUND: Postoperative delirium (POD) is a frequent and serious complication in older surgical patients, characterized by acute cognitive dysfunction and fluctuating levels of consciousness. POD is associated with prolonged hospitalization, long-term cognitive decline, reduced quality of life, and increased mortality. Despite its clinical relevance, the underlying pathophysiological mechanisms remain poorly understood, and reliable biomarkers for early prediction and prevention are lacking. OBJECTIVE: The CONFUSED study aims to identify molecular and clinical predictors of POD by integrating clinical data with proteomic, transcriptomic, and epigenetic analyses. The primary objective is to develop predictive models for POD using multimodal data. Secondary objectives include the identification of delirium-associated genes, proteins, and epigenetic signatures, as well as the exploration of patient subgroups at increased risk for POD. METHODS: CONFUSED is a prospective observational cohort study conducted at a German university hospital. Adult patients undergoing major surgery under general anesthesia will be enrolled until 100 cases of POD have been observed, which is expected to require a total sample size of approximately 200 to 300 patients. Blood samples are collected at 4 predefined time points: before premedication, immediately after surgery, and on postoperative days 2 and 5. Samples undergo comprehensive proteomic profiling, transcriptomic analysis using RNA microarrays, DNA methylation analysis, and genotyping of selected polymorphisms. Clinical data, including demographics, comorbidities, perioperative variables, medications, and delirium assessments using the Confusion Assessment Method (CAM) and CAM for the intensive care unit, are systematically recorded. Statistical analyses include univariate and multivariate methods, as well as machine learning approaches such as random forests and support vector machines, to identify relevant biomarkers and develop predictive models. The study protocol follows STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) and TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis) guidelines and was approved by the responsible ethics committees. RESULTS: The study was registered in the German Clinical Trials Register (DRKS00033854) on March 18, 2024. Recruitment started in January 2024 and is ongoing at the time of manuscript submission. As of now, 135 patients have been enrolled. Sample collection and laboratory analyses are ongoing. Data analysis began in January 2026, with first results anticipated in July 2026. Final data lock is anticipated after the completion of recruitment. CONCLUSIONS: By integrating multimodal molecular data with clinical parameters and applying advanced machine learning techniques, the CONFUSED study aims to improve the prediction and understanding of POD. The results are expected to support the development of personalized preventive strategies and contribute to improved perioperative care for patients at risk of POD.

Humans↗

PubMed2026

Deep learning-based multimodal pathogenomics integration for precision cancer prognosis.

BACKGROUND: Recent studies have revealed valuable prognostic insights in haematoxylin and eosin (H&E)-stained histological sections and transcriptomic profiles, suggesting potential applications in machine learning. However, existing methods lack sufficient intra- and inter-modal interactions, and face challenges in clinical validation due to incomplete multimodal data. METHODS: We proposed PathoGems (PathoGenomics-based integrative survival prediction), a weakly-supervised, interpretable multimodal learning framework that integrates histology and genomic profiles for precise cancer prognosis prediction. To evaluate the robustness of PathoGems, we initially curated a dataset of 1965 cases across four cohorts from The Cancer Genome Atlas (TCGA), including breast, colorectal, glioblastoma, and esophageal cancers. For external validation, PathoGems was further evaluated on four independent cohorts, consisting of 76 breast cancer and 41 esophageal squamous cell carcinoma cases from Zhejiang Cancer Hospital, as well as 102 colorectal cancer and 58 glioblastoma cases from the Clinical Proteomic Tumor Analysis Consortium (CPTAC). RESULTS: PathoGems effectively stratified patients into favorable and unfavorable risk groups, revealing significant differences in histological patterns, genomic features, and overall survival (log-rank test, p < 0.05). Moreover, the model’s predictions are further supported by visualization and transcriptomic analysis, enhancing interpretability and reliability. CONCLUSIONS: By fusing histological and clinicogenomic multimodal models, PathoGems will provide a solid foundation for developing an innovative tool that aids clinicians in making informed decisions and selection personalized treatment strategies for cancer patients.

Humans↗

PubMed2006

Gene expression profiling using cDNA microarray analysis of the sexual reproduction stage of the unicellular charophycean alga Closterium peracerosum-strigosum-littorale complex.

The desmid Closterium peracerosum-strigosum-littorale complex, which is the closest unicellular sister to land plants, is the best characterized of the charophycean green algae with respect to the process of sexual reproduction. To elucidate the molecular mechanism of intercellular communication during sexual reproduction, we created a normalized cDNA library from mixed cells of the sexual and the vegetative phases and generated a cDNA microarray. In total, 3,236 expressed sequence tags, which were classified into 1,615 nonredundant groups, were generated for cDNA microarray construction. Candidate genes for key factors involved in fertilization, such as those that encode putative receptor-like protein kinase, leucine-rich-repeat receptor-like protein, and sex pheromone homologs, were up-regulated during sexual reproduction and/or by the addition of the purified sex pheromones, and the expression patterns of these genes were confirmed by quantitative real-time polymerase chain reaction analysis. This first transcriptome profile of Closterium will provide critical clues as to the mechanism and evolution of intercellular communication between the egg and sperm cells of land plants.

Algal Proteins↗

PubMed2026

Alternative End Joining Dependency Imposed by miR-21-5p Defines Radiation Resistance and a Targetable Vulnerability in Oral Squamous Cell Carcinoma.

PURPOSE: Clinical control of oral squamous cell carcinoma (OSCC) is constrained by heterogeneous radiosensitivity driven by divergent DNA damage response programs. The architecture and functional contribution of alternative end joining (Alt-EJ), an error-prone DNA double-strand break (DSB) repair pathway frequently upregulated in cancer, to radiation resistance remains poorly defined. METHODS AND MATERIALS: We profiled microRNAs in radioresistant OSCC clones and performed multiomic integration across an institutional OSCC cohort, an external OSCC cohort from the Gene Expression Omnibus, The Cancer Genome Atlas pan-cancer tumors, and cell lines characterized by Sanger Genomics of Drug Sensitivity in Cancer to infer DNA damage response characteristics, genomic scar features, drug sensitivity, and radiation therapy outcomes. DSB repair capacity and pathway usage were validated using functional assays, including Alt-EJ reporters and droplet digital PCR quantification of microhomology-mediated repair events. Core Alt-EJ effectors such as PARP1 and POLQ were perturbed genetically and pharmacologically. Therapeutic efficacy of PARP or POLQ inhibition with or without irradiation was tested in a syngeneic OSCC model, followed by bulk tumor transcriptomics to assess pathway engagement. RESULTS: Upregulation of miR-21-5p was not only selectively detected in radioresistant OSCC, but also modulated radiosensitivity in vitro and in vivo, and was associated with inferior postradiation therapy survival. A calibrated miR-21-5p target-gene signature tracked Alt-EJ activity across patient and mouse tumors and cancer cell lines, correlated with microhomology-mediated indels and broader genomic scarring, and predicted sensitivity to clinically available PARP inhibitors. Functionally, enforced miR-21-5p expression increased Alt-EJ usage and accelerated DSB repair, whereas inhibition or depletion of key Alt-EJ effectors reduced repair efficiency and restored radiosensitivity. In vivo, Alt-EJ targeting with PARP or POLQ inhibitor abrogated miR-21-5p-driven radiation resistance; transcriptomic profiling supported suppression of Alt-EJ programs as the operative mechanism. CONCLUSIONS: These findings establish a mechanistic link between miR-21-5p activity and Alt-EJ dependence, provide a clinically deployable signature to identify Alt-EJ-dependent OSCC, and support rational combinations of Alt-EJ targeting agents with radiation therapy to overcome treatment failure and advance precision radiation oncology.

MicroRNAs↗

PubMed2025

Host-Associated Genetic Differentiation in the Face of Ongoing Gene Flow: Ecological Speciation in a Pathogenic Parasite of Freshwater Fish.

Adaptive evolution in response to varying environments, leading to population divergence, is among the most intriguing processes of speciation. However, the extent to which these adaptive processes effectively drive population divergence amidst ongoing gene flow remains controversial. Our study addresses this by analyzing population genetic structure, gene flow, and genomic divergence between lineages of a tapeworm parasite (Ligula intestinalis) isolated from sympatric fish hosts. This parasite, which must overcome host immunological defenses for successful infection, significantly impacts host health. Utilizing genome-wide Single Nucleotide Polymorphisms (SNPs) and transcriptome data, we investigated whether host species impose distinct selection pressures on parasite populations. Genetic clustering analyses revealed clear divergence, with parasites from bream (Abramis brama) forming a distinct genetic cluster separate from those infecting roach (Rutilus rutilus), rudd (Scardinius erythrophthalmus), and bleak (Alburnus alburnus). Demographic modeling indicated isolation with continuous gene flow as the most plausible scenario for this divergence. Selection analyses identified 896 SNPs under selection, displaying low to moderate nucleotide diversity and genetic divergence compared with neutral loci. Transcriptome profiling supported these findings, revealing distinct gene expression profiles between parasite populations. Examination of selected SNPs and differentially expressed genes identified candidate genes linked to immune evasion mechanisms, potentially driving ecological speciation. This research highlights the interplay of host specificity, population demography, and disruptive selection in ecological speciation. By dissecting genomic factors, our study improves the understanding of mechanisms facilitating population divergence despite ongoing gene flow.

Animals↗

PubMed2004

High-accuracy amplification of nanogram total RNA amounts for gene profiling.

Microarray-based gene profiling of laser-assisted microdissected tissues or clinical biopsies is still a challenge since the amount of total RNA in such samples is limited and amplification of RNA is mandatory. Representative amplification of mRNA is highly dependent on the reverse transcription reaction, which is error prone, and on the number of amplification cycles. To improve the accuracy of RNA amplification, we optimized, combined, and tested different amplification strategies for Affymetrix oligonucleotide array hybridization. We demonstrate that different protocols differ significantly in quality of mRNA amplification. To demonstrate the accuracy and reproducibility of our optimized protocol in a clinical setting, we analyzed total RNAs from laser-assisted, microdissected cells of human prostate tissues. On the basis of these results, we recommend a standard reverse transcription reaction for small-sample-transcriptome profiling experiments as part of the Minimal Information about a Microarray Experiment (MIAME) set of standards.

Animals↗

PubMed2026

Human IL-34 Deficiency Primes Microglia Toward Alzheimer's Disease-Associated States.

BACKGROUND: Genome-wide association studies (GWAS), with independent replication in large European consortia, have identified a common nonsense variant in IL-34 (Y213X) as a genetic risk factor for late-onset Alzheimer's disease (AD). However, the biological consequences of this IL-34 mutation in humans, its prevalence in the population, and the mechanisms by which IL-34-Y213X alters microglial homeostasis, cerebrospinal fluid (CSF) proteomic networks, and amyloid pathology remain poorly understood. METHODS: We combined human genetics, cerebrospinal fluid (CSF) and serum proteomics, transcriptomics, large-scale phenome-wide association analyses, and preclinical experimental models to define the impact of human IL-34 deficiency. IL-34 concentrations were first quantified in CSF and serum from deeply phenotyped AD cohorts stratified by the common IL-34-Y213X nonsense variant. IL-34 levels and IL-34-Y213X status were then integrated with unbiased CSF proteomic networks and AD biomarkers. Transcriptomic profiling of purified microglia from IL-34 knockout mice was performed to assess disease-associated microglial programs. Using APP/PS1 mice lacking IL-34, we examined the effects of IL-34 deficiency on microglial survival, tiling, and plaque encapsulation. Finally, we performed postmortem analyses of temporal cortex from AD patients carrying IL-34-Y213X to assess microglial density, spatial organization, and plaque-associated responses. FINDINGS: IL-34-Y213X was a strong, dose-dependent loss-of-function (LOF) allele that reduced IL-34 levels by up to 2.5 standard deviations in CSF and serum and was common in multiple populations. IL-34 deficiency reshaped CSF proteomic networks, downregulating axon guidance and microglial support modules while upregulating inflammatory and extracellular matrix signatures, and showed pleiotropic associations with neurological, inflammatory, and metabolic traits. Transcriptomic analysis of sorted microglia from healthy 9-month-old IL-34KO compare to wild-type mice revealed a profound pro-inflammatory and disease-associated microglial transcriptional program enriched for disease-associated microglia (DAM) signatures, inflammatory pathways, and AD risk genes including APOE, CLU, and CASS4. In APP/PS1 mice, genetic IL-34 deletion selectively depleted homeostatic gray-matter microglia, disrupted microglial tiling, and impaired plaque encapsulation, resulting in altered amyloid structure and enhancing neuritic injury. Concordantly, AD patients homozygous for IL-34-Y213X displayed markedly reduced cortical microglial density and increased microglial spatial dispersion, indicating a breakdown of the microglial network organization in the human brain. INTERPRETATION: A common human IL-34 LOF variant creates a naturally occurring model of IL-34 deficiency that links microglial survival, CSF network signatures, and amyloid pathology in both mice and humans. Importantly, IL-34 deficiency alone is sufficient to induce inflammatory, AD-associated microglial states beyond simply reducing microglial number. These findings identify IL-34/CSF1R signaling as a critical determinant of microglial resilience and a potential upstream pathway linking human genetic variation to AD susceptibility, highlighting IL-34-dependent pathways as promising targets for disease modification. FUNDING: This work was supported by grants from the Spanish Ministerio de Ciencia, Innovación y Universidades/FEDER/UE (PID2024-157400OB-I00) and FORTALECE program (FORT23/00008; Instituto de Salud Carlos III, Spain) to RRL and JLV, ISCIII of Spain co-financed by FEDER funds (European Union) through grants PI24/00308 (JV) and CIBERNED collaborative grant 2022/01 to JV, PID2023-147125OB-I00 and CEX2023-001386-S (Severo Ochoa Programme) to SMTBC. A.R. is supported by STAR Award. University of Texas System. Tx, United States, The South Texas ADRC. National Institute of Aging. National Institutes of Health. USA. (P30AG066546), the Keith M. Orme and Pat Vigeon Orme Endowed Chair in Alzheimer's and Neurodegenerative Diseases (2024-2025) and Patricia Ruth Frederick Distinguished Chair for Precision Therapeutics in Alzheimer's and Neurodegenerative Diseases (2025-2028). AR is also supported by the Agency for Innovation and Entrepreneurship (VLAIO) grant N° PR067/21 for the HARPONE project and the ADAPTED project the EU/EFPIA Innovative Medicines Initiative Joint Undertaking Grant N° 115975 and CIBERNED (ISCIII).

Journal Article↗

PubMed2005

Human side population keratinocytes exhibit long-term proliferative potential and a specific gene expression profile and can form a pluristratified epidermis.

The aim of the present study was to characterize human side population (SP) epidermal keratinocytes isolated from primary cell cultures. For that purpose, keratinocytes were isolated from normal adult breast skin samples and the Hoechst 33342 exclusion assay described for hematopoietic cells was adapted to keratinocytes. Three types of keratinocytes were studied: the SP, the main population (MP), and the unsorted initial population. SP keratinocytes represented 0.16% of the total population. In short-term cultures, they exhibited an increased colony-forming efficiency and produced more actively growing colonies than did unsorted and MP keratinocytes. In long-term cultures, SP cells exhibited an extensive expansion potential, performing a mean of 44 population doublings for up to 12 successive passages after cell sorting. Moreover, even in long-term cultures, SP keratinocytes were able to form a pluristratified epidermis when seeded on a dermal substrate. Unsorted and MP keratinocytes promoted a reduced expansion: mean values of 14 population doublings for five passages and 12 population doublings for four successive passages, respectively. To further characterize SP cells, cDNA microarrays were used to identify their molecular signature. Transcriptome profiling showed that 41 genes were differentially expressed in SP (vs. MP) cells, with 37 upregulated genes and only four downregulated genes in SP cells. The majority of these genes were functionally related to the regulation of transcription and cell signaling. In conclusion, SP human keratinocytes isolated from primary cultures exhibited both short- and long-term high proliferative potential, formed a pluristratified epidermis, and were characterized by a specific gene expression profile.

Adult↗

PubMed2024

Nonlethal deleterious mutation-induced stress accelerates bacterial aging.

Random mutagenesis, including when it leads to loss of gene function, is a key mechanism enabling microorganisms' long-term adaptation to new environments. However, loss-of-function mutations are often deleterious, triggering, in turn, cellular stress and complex homeostatic stress responses, called "allostasis," to promote cell survival. Here, we characterize the differential impacts of 65 nonlethal, deleterious single-gene deletions on Escherichia coli growth in three different growth environments. Further assessments of select mutants, namely, those bearing single adenosine triphosphate (ATP) synthase subunit deletions, reveal that mutants display reorganized transcriptome profiles that reflect both the environment and the specific gene deletion. We also find that ATP synthase α-subunit deleted (ΔatpA) cells exhibit elevated metabolic rates while having slower growth compared to wild-type (wt) E. coli cells. At the single-cell level, compared to wt cells, individual ΔatpA cells display near normal proliferation profiles but enter a postreplicative state earlier and exhibit a distinct senescence phenotype. These results highlight the complex interplay between genomic diversity, adaptation, and stress response and uncover an "aging cost" to individual bacterial cells for maintaining population-level resilience to environmental and genetic stress; they also suggest potential bacteriostatic antibiotic targets and -as select human genetic diseases display highly similar phenotypes, - a bacterial origin of some human diseases.

Escherichia coli↗

PubMed2005

Profiling neurotransmitter receptor expression in mouse gonadotropin-releasing hormone neurons using green fluorescent protein-promoter transgenics and microarrays.

The definition of neurotransmitter receptors expressed by individual neuronal phenotypes is essential for our understanding of integrated neural regulation. We report here a single-neuron strategy using green fluorescent protein (GFP)-promoter transgenic mice and oligonucleotide microarrays that has enabled us to provide a qualitative profile of the neurotransmitter receptors expressed by the gonadotropin- releasing hormone (GnRH) neurons, critical for the neural regulation of fertility. Acute brain slices were prepared from adult female GnRH-GFP transgenic mice and single GnRH neurons identified and patched. The contents of GnRH neurons underwent reverse transcription and cDNA amplification using the switch mechanism at the 5' end of RNA templates system, and hybridization to mouse gene oligonucleotide arrays. Fifty different neurotransmitter receptor subunit mRNAs were detected in GnRH neurons. Many of the classical amino acid and aminergic receptors were present in addition to 14 distinct, and in most cases novel, neuropeptidergic receptor signaling families. Four of the latter were selected for functional validation with gramicidin-perforated patch-clamp electrophysiology. Galanin, GnRH and neuromedin B were all found to exert direct depolarizing actions upon GnRH neurons whereas somatostatin induced a potent hyperpolarizing response. These studies demonstrate a relatively straightforward approach for transcriptome profiling of specific neuronal phenotypes. The stimulatory actions of GnRH and galanin upon GnRH neurons found here indicate that positive ultrashort feedback loops exist among the GnRH neuronal population.

Animals↗

PubMed2026

SYT8 Drives Colorectal Cancer Progression and Immune Evasion via the SETD1A-H3K4me3 Axis.

By integrating transcriptomic data from The Cancer Genome Atlas, Gene Expression Omnibus, and a self-established colorectal cancer (CRC) cohort, it was identified that synaptotagmin 8 (SYT8) is significantly up-regulated in tumors and is predictive of poor prognosis. Single-cell RNA sequencing, immunohistochemistry, and immunofluorescence experiments demonstrate that SYT8 expression is largely confined to tumor cells, predominantly in the nucleus. Functional assays reveal that depletion of SYT8 impairs, whereas its overexpression enhances, CRC cell proliferation and invasion. Transcriptomic profiling indicates an enrichment of cell cycle and epithelial-mesenchymal transition signatures. Mechanistically, co-immunoprecipitation/mass spectrometry identifies SET domain containing 1A (SETD1A) as a direct SYT8-interacting partner. The SYT8-SETD1A axis forms a positive-feedback loop that increases histone H3 lysine 4 trimethylation (H3K4me3) levels and drives the transcription of protumorigenic genes. Immune profiling further indicates that high SYT8 expression correlates with increased regulatory T-cell infiltration, suggesting an immunosuppressive microenvironment and potential resistance to immunotherapy. Collectively, SYT8 promotes CRC progression through the SETD1A/H3K4me3-mediated activation of the cell cycle, induction of epithelial-mesenchymal transition, and remodeling of the immune microenvironment. Therefore, SYT8 is established as a prognostic biomarker and serves as a therapeutic target in colorectal cancer.

Humans↗

PubMed2026

GBFN: A gated bimodal fusion network leveraging foundation model embeddings for cancer drug sensitivity prediction.

Despite recent progress in deep learning for cancer drug sensitivity prediction, many existing models still rely on task-specific representation learning or relatively simple multimodal fusion, which may limit their ability to capture complex drug-cell interactions. To address this issue, we developed GBFN, a gated bimodal fusion network for continuous IC50 prediction that integrates pretrained drug and cell-line representations. Specifically, drug embeddings were obtained from SMI-TED, whereas cell-line embeddings were derived from transcriptomic profiles using BulkFormer. These two modalities were then combined through a dimension-wise gated fusion module and used to predict IC50 values in matched drug-cell line pairs. On the CCLE-based benchmark, GBFN outperformed representative neural baselines, including GraphDRP, TGSA, and TransEDRP, and achieved the best overall performance, with an R² of 0.8714 and an RMSE of 0.8938. Moreover, ablation analysis showed that the model using drug features and cell-line expression data with gated fusion performed better than the corresponding model using direct concatenation, indicating that the improvement was associated with the fusion strategy rather than with the input modalities alone. In addition, cell-line expression data were more informative than mutation data in the present setting, and adding mutation data to the model using drug features and expression data did not further improve performance. Across major cancer types, GBFN maintained generally high cell-line-level predictive performance, and perturbation-based attribution identified biologically relevant transcriptomic programs in selected drug-cell line settings. Together, these findings support GBFN as a compact and effective framework for continuous drug response prediction.

Humans↗

PubMed2026

Essence: A benchmarking-validated transformer framework for early diagnosis of Parkinson's disease using cerebrospinal fluid protein biomarkers.

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by motor and non-motor symptoms. The lack of objective molecular biomarkers limits early diagnosis and personalized treatment. Here, we propose Essence, a benchmarking-validated framework integrating cerebrospinal fluid (CSF) proteomics with traditional and deep learning models to identify robust protein signatures for PD. Using data from two independent cohorts, 1266 high-confidence proteins are quantified, among which 178 exhibit differential abundance between PD and healthy controls (HC). Through systematic benchmarking of ten machine learning algorithms and four neural architectures, the Transformer model consistently outperforms alternatives across multiple feature selection strategies, achieving an area under the receiver operating characteristic curve (AUC) of 1.0000 with only 35 features. Functional analyses of the top-ranked 35 proteins reveal enrichment in neuroinflammatory, synaptic, and oxidative stress-related pathways. Importantly, spatial transcriptomic profiling based on the Allen Brain Atlas shows region-specific expression of these biomarkers in PD-relevant brain structures, including the striatum, subthalamic nucleus, hippocampus, and white matter tracts. This anatomical alignment supports the functional relevance of the identified markers and highlights their potential utility in early-stage diagnosis and mechanistic understanding of PD.

Benchmarking↗

PubMed2003

Global phenotypic analysis and transcriptional profiling defines the weak acid stress response regulon in Saccharomyces cerevisiae.

Weak organic acids such as sorbate are potent fungistatic agents used in food preservation, but their intracellular targets are poorly understood. We thus searched for potential target genes and signaling components in the yeast genome using contemporary genome-wide functional assays as well as DNA microarray profiling. Phenotypic screening of the EUROSCARF collection revealed the existence of numerous sorbate-sensitive strains. Sorbate hypersensitivity was detected in mutants of the shikimate biosynthesis pathway, strains lacking the PDR12 efflux pump or WAR1, a transcription factor mediating stress induction of PDR12. Using DNA microarrays, we also analyzed the genome-wide response to acute sorbate stress, allowing for the identification of more than 100 genes rapidly induced by weak acid stress. Moreover, a novel War1p- and Msn2p/4p-independent regulon that includes HSP30 was identified. Although induction of the majority of sorbate-induced genes required Msn2p/4p, weak acid tolerance was unaffected by a lack of Msn2p/4p. Ectopic expression of PDR12 from the GAL1-10 promoter fully restored sorbate resistance in a strain lacking War1p, demonstrating that PDR12 is the major target of War1p under sorbic acid stress. Interestingly, comparison of microarray data with results from the phenotypic screening revealed that PDR12 remained as the only gene, which is both stress inducible and required for weak acid resistance. Our results suggest that combining functional assays with transcriptome profiling allows for the identification of key components in large datasets such as those generated by global microarray analysis.

ATP-Binding Cassette Transporters↗

PubMed2026

Characterization of the genomic and transcriptomic landscape of invasive non-mucinous lung adenocarcinoma based on IASLC grading.

BACKGROUND: The IASLC grading system has prognostic utility and potential therapeutic implications in invasive non-mucinous lung adenocarcinoma (LUAD), but the molecular basis underlying the grading spectrum remains unclear. METHODS: We performed whole-genome sequencing in 138 Chinese patients with invasive non-mucinous LUAD and RNA sequencing of 96 matched tumor-normal tissue pairs to systematically characterize the molecular features across grades, including coding driver events, mutational signatures, non-coding regulatory disruptions, and transcriptional programs. RESULTS: Compared with Grade 1-2 tumors, Grade 3 LUADs exhibited heightened invasive potential, manifested by more advanced stage, more frequent spread through air spaces, and independently worse survival. Grade 3 tumors had elevated tumor mutational burden and were enriched for alterations in genome maintenance and cell-cycle genes, including TP53, as well as genes implicated in DNA damage response, including ZFHX4. APOBEC-associated mutagenesis was selectively enriched in Grade 3 tumors independent of smoking status, consistent with an instability-associated phenotype. Recurrent non-coding regulatory disruptions affected lung lineage-defining genes, particularly surfactant-associated genes, and were correlated with reduced expression. Transcriptomic profiling revealed epithelial dedifferentiation, loss of pulmonary homeostatic programs, and activation of proliferative and stress-related pathways. Notably, MUC16 emerged as a convergent event linking genomic and transcriptional dysregulation, with coding mutations associated with higher expression and increased expression in Grade 3 tumors correlating with the proportion of high-grade histologic patterns. CONCLUSIONS: These findings provide a molecular framework for the IASLC grading spectrum and identify Grade 3 LUAD as a distinct instability-associated and dedifferentiated biological state.

IASLC grading↗