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PubMed2003

RIKEN Arabidopsis full-length (RAFL) cDNA and its applications for expression profiling under abiotic stress conditions.

Full-length cDNAs are essential for the correct annotation of genomic sequences and for the functional analysis of genes and their products. 155,144 RIKEN Arabidopsis full-length (RAFL) cDNA clones were isolated. The 3'-end expressed sequence tags (ESTs) of all 155,144 RAFL cDNAs were clustered into 14,668 non-redundant cDNA groups, about 60% of predicted genes. The sequence database of the RAFL cDNAs is useful for promoter analysis and the correct annotation of predicted transcription units and gene products. Recently, cDNA microarray analysis has been developed for quantitative analysis of global and simultaneous analysis of expression profiles. RAFL cDNA microarrays were prepared, containing independent full-length cDNA groups for analysing the expression profiles of genes under various stress- and hormone-treatment conditions and in various mutants and transgenic plants. In this review, recent progress on transcriptome analysis using the RAFL cDNA microarray is highlighted.

Arabidopsis↗
PubMed2026

Genomic characterization of aggressiveness in pituitary neuroendocrine tumors.

BACKGROUND: Aggressive evolution of PitNETs is rare; metastatic spread is even more. Defining aggressiveness and malignancy is challenging, subsequently hard to predict, and to understand. The aim was to provide a molecular definition of aggressiveness using genomic approaches. METHODS: PitNETs from 206 patients were included. Associations between 9 clinicopathological features of aggressiveness and PitNETs' omics were explored. Omics included transcriptome, DNA methylation, chromosomal alterations, and mutations. Clonal tumor evolution was monitored in 7 patients. RESULTS: Among the 9 clinicopathological features of aggressiveness, only rapid progression, progression after radiotherapy, Ki67/MIB1 proliferation index ≥10%, temozolomide treatment, metastases, and specific death were associated with specific omics signatures, while tumour maximal diameter ≥40 mm, cavernous, and sphenoid invasion were not. The omic signatures associated with these features of aggressiveness overlapped but remained distinct between corticotroph and mammo-somato-thyrotroph lineages. For each lineage, a common signature of aggressiveness was identified, associating a proliferative transcriptome signature and DNA hypermethylation. Alterations in specific genes were associated with aggressive features, including a novel PitNET gene, LRP1B, and known cancer genes (TP53, CDKN2A), while USP8 and GNAS alterations were not. Integration of gene alterations with methylome and transcriptome signatures isolated a subset of molecularly aggressive PitNETs. Molecular signatures were stable during the course of the disease, despite evolution toward aggressiveness and potential clonal divergence. CONCLUSION: This systematic analysis of clinicopathological features of aggressiveness using an integrated multiomic approach establishes a histomolecular definition of aggressiveness in PitNETs. Prospective cohort studies are needed to validate these molecular signatures and establish their prognostic value.

Humans↗
PubMed2026

Identifying JAK2 and ANXA5 as Key Genes Linking Obstructive Sleep Apnea and Oxidative Stress via Machine Learning and Multilayer Transcriptomic Integration With Functional Validation.

Obstructive sleep apnea (OSA) is a common and severe sleep disorder closely associated with oxidative stress (OS). This study aims to identify and validate potential OS-related genes associated with OSA through bioinformatics methods. We successfully identified OS-related differentially expressed genes (OS-DEGs) by combining the limma test, weighted correlation network analysis (WGCNA), and OS-related genes from the GeneCards database. Key genes and potential biological roles were further identified using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), enrichment analysis, protein-protein interaction (PPI) network analysis, Lasso regression analysis, random forest algorithm, and support vector machine recursive feature elimination (SVM-RFE) method. Evaluate and validate the accuracy of key genes through receiver operating characteristic (ROC) curve analysis. The human single-cell RNA sequencing (scRNA-seq) dataset is used for cell classification annotation, analysis of key gene single-cell expression profiles, and virtual gene knockout experiments based on the scTenifoldKnk algorithm. Integrating scRNA-seq sequencing, pseudotime trajectory inference, cell-cell communication analysis, and bulk immune infiltration deconvolution reveals monocyte subtype remodeling in OSA. Finally, the expression levels of key genes in clinical samples were validated using real-time quantitative PCR (RT-qPCR) and Western blotting. A total of 57 common DEGs, indicating significant enrichment in OS, inflammation, and tumor pathways, particularly prominent in the immunometabolism pathway. By integrating DEGs, WGCNA, PPI results, and machine learning methods, key genes Janus kinase 2 (JAK2) and ANXA5 were screened out. JAK2 was significantly upregulated under disease conditions, while ANXA5 was significantly downregulated. ROC curve exhibited high accuracy (area under the curve [AUC] > 0.85). Human scRNA-seq analysis revealed that key genes were predominantly highly expressed in monocytes. Virtual knockout experiments demonstrated that these key genes play a crucial role in regulating immune responses and inflammatory reactions. PPI networks and enrichment analysis verified that downstream genes S100P, ALOX5AP, PROK2, and PADI4 may collaboratively participate in immune response and inflammation regulation. Finally, clinical sample experiment further validated the results of bioinformatics analysis. This study provides new research insights for the diagnosis, mechanism research, and treatment development of OSA in the future by integrating multilayer transcriptomic and machine learning techniques.

Humans↗
PubMed2025

Immune landscape and novel therapeutic targets of epidermal growth factor receptor and anaplastic lymphoma kinase wild type never-smoker lung adenocarcinoma.

BACKGROUND: Never-smoker lung adenocarcinoma (NSLA) exhibits distinct immunosuppressive profiles and a lower tumor mutation burden compared with lung adenocarcinoma in smokers. These correlate with poor responses to immune checkpoint inhibitors. In this study, we aimed to elucidate the tumor-immune microenvironment of NSLA without epidermal growth factor receptor (EGFR) or anaplastic lymphoma kinase (ALK) alterations and identify novel therapeutic targets. METHODS: We analyzed genome, transcriptome, and proteomic data from 102 NSLA tumor samples and 16 normal adjacent tissues. We classified tumors into distinct immune clusters (IC) based on gene signatures by profiling the tumor-infiltrating immune cells. RESULTS: The tumors were stratified into three ICs: hot, intermediate, and cold. Notably, only 21 (20.6%) patients exhibited hot IC enriched in cytotoxic T cells, natural killer cells, and B-cell signatures, which correlated with improved recurrence-free survival. Cold ICs (37.3%) exhibited higher myeloid-derived suppressor cell (MDSC) levels and M2 macrophage signatures, with poor immune cell infiltration and relatively low stimulatory cytokines and chemokines expression. CEACAM1, and NECTIN2 were upregulated in intermediate and cold ICs and correlated with MDSC and M2 macrophage infiltration. High expression of these genes was associated with poor survival outcomes. Protein-protein network analysis of 20 upregulated molecules associated with cancer- and driver-related proteins in cold IC identified XPO 1 as a key component. CONCLUSION: Our proteogenomic analysis highlighted the immunosuppressive properties of NSLA without EGFR and ALK alterations and identified novel therapeutic targets. These findings may provide novel treatment strategies that could improve the clinical outcomes of patients with NSLA.

Humans↗
PubMed2004

Alterations in the ovarian transcriptome during primordial follicle assembly and development.

The assembly of the developmentally arrested primordial follicle and subsequent transition to the primary follicle are poorly understood processes critical to ovarian biology. Abnormal primordial follicle development can lead to pathologies such as premature ovarian failure. The current study used a genome-wide expression profile to investigate primordial follicle assembly and development. Rat ovaries with predominantly unassembled, primordial, or primary follicles were obtained. RNA from these ovaries was hybridized to rat microarray gene chips, and the gene expression (i.e., ovarian transcriptome) was compared between the developmental stages. Analysis of the ovarian transcriptome demonstrated 148 genes up-regulated and 50 genes down-regulated between the unassembled and primordial follicle stages. Observations demonstrate 80 genes up-regulated and 44 genes down-regulated between the primordial and primary follicle stages. The analysis demonstrated 2332 genes common among the three developmental stages, 146 genes specific for the unassembled follicles, 94 genes specific for the primordial follicles, and 151 genes specific for the primary follicles. Steroidogenic genes are up-regulated between unassembled and primordial follicles, and then many are again down-regulated between primordial and primary follicles. The hormones inhibin and Mullerian inhibitory substance (MIS) display a similar pattern of expression with the highest levels of mRNA in the primordial follicles. Several novel unknown genes that had dramatic changes in expression during primordial follicle development were also identified. Gene families/clusters identified that were up-regulated from unassembled to primordial follicles include growth factors and signal transduction gene clusters, whereas a down-regulated gene family was the synaptonemal complex genes associated with meiosis. Gene families/clusters that were up-regulated between primordial and primary follicles included immune response genes, metabolic enzymes, and proteases, whereas down-regulated gene families include the globulin genes and some steroidogenic genes. The expression of several growth factors changed during primordial follicle development, including vascular endothelial growth factor and insulin-like growth factor II. Elucidation of how these changes in gene expression coordinate primordial follicle assembly and the primordial to primary follicle transition provides a better understanding of these critical biological processes and allows selection of candidate regulatory factors for further investigation.

Animals↗
PubMed2005

The expression signature of in vitro senescence resembles mouse but not human aging.

BACKGROUND: The biological mechanisms that underlie aging have not yet been fully identified. Senescence, a phenomenon occurring in vitro, limits the number of cell divisions in mammalian cell cultures and has been suggested to contribute to aging. RESULTS: We investigated whether the changes in gene expression that occur during mammalian aging and induction of cellular senescence are similar. We compared changes of gene expression in seven microarray datasets from aging human, mouse and rat, as well as four microarray datasets from senescent cells of man and mouse. The datasets were publicly available or obtained from other laboratories. Correlation measures were used to establish similarities of the expression profiles and gene ontology analyses to identify functional groups of genes that are co-regulated. Robust similarities were established between aging in different species and tissues, indicating that there is an aging transcriptome. Although some cross-species comparisons displayed high correlation, intra-species similarities were more reliable. Similarly, a senescence transcriptome was demonstrated that is conserved across cell types. A similarity between the expression signatures of cellular senescence and aging could be established in mouse, but not in human. CONCLUSION: Our study is the first to use microarray data from several studies and laboratories for dissection of a complex biological phenotype. We demonstrate the presence of a mammalian aging transcriptome, and discuss why similarity between cellular senescence and aging is apparent in aging mice only.

Aging↗
PubMed2026

Unveiling m7G modification patterns and causal drivers governing intracranial aneurysm rupture risk through multi-omics validation and m7G-MeRIP-seq profiling.

Intracranial aneurysm (IA) rupture causes severe brain hemorrhage with high mortality, yet its molecular drivers remain unclear and better risk prediction is urgently needed. Using transcriptomics, single-cell analysis, and genetic data, we investigated the role of N7-methylguanosine (m7G) RNA modification in IA. We identified distinct m7G modification patterns, validated their methylation features in patient samples, and incorporated these patterns into a machine learning-based rupture prediction model. The presence and characteristics of m7G patterns significantly improved model performance, achieving high predictive accuracy across three independent cohorts (AUC 0.91-0.95). Genetic analyses further identified three causal m7G-related genes (NSUN2, IFIT5, SNUPN), and laboratory experiments confirmed their altered expression and methylation in ruptured aneurysms. Overall, our findings demonstrate that m7G modifications play a key role in IA rupture. The validated prediction model offers strong clinical potential for rupture risk assessment, and the identified genes represent promising therapeutic targets.

Humans↗
PubMed2005

Molecular signature analysis: using the myocardial transcriptome as a biomarker in cardiovascular disease.

With the emergence of microarray technology, it is now possible to simultaneously assess the expression of tens of thousands of gene transcripts, providing a resolution and precision of phenotypic characterization not previously possible. In the field of cardiomyopathy, microarray studies have largely focused on gene discovery, identifying differentially expressed genes characteristic of diverse disease states, through which novel genetic pathways and potential therapeutic targets may be elucidated. However, gene expression profiling may also be used to identify a pattern of genes (a molecular signature) that serves as a biomarker for clinically relevant parameters. One study thus far does demonstrate that a molecular signature can accurately identify etiology in cardiovascular disease, supporting ongoing efforts to incorporate expression-profiling-based biomarkers in determining prognosis and response to therapy in heart failure. Microarray research in cardiomyopathy is still in its earliest stages. Nevertheless, the ultimate potential application of transcriptome-based molecular signature analysis is individualization of the management of patients with heart failure, whereby a patient with a newly diagnosed cardiomyopathy could, through molecular signature analysis, be offered an accurate assessment of prognosis and how individualized medical therapy could affect his or her outcome.

Biomarkers↗
PubMed2026

Expression patterns of potential targets for antibody-directed therapy in metastatic castration-resistant prostate cancer patients.

INTRODUCTION: Survival in metastatic castration-resistant prostate cancer (mCRPC) patients remains limited and treatment is complicated by tumor heterogeneity. As antibody-based therapeutics emerge, identifying actionable antigen targets and patient subgroups most likely to benefit is essential. MATERIALS & METHODS: Gene expression of 62 antibody-targetable proteins was analyzed in 296 mCRPC biopsies. These genes encode proteins targeted by approved or investigational antibody-based cancer therapeutics. Associations between target expression with genomic classifications and transcriptomic subtypes were evaluated. Target expression was also assessed in tumors with low expression of established mCRPC targets. Subgroup-specific targets were validated in an independent cohort and single-cell transcriptomics. RESULTS: Established targets KLK2, FOLH1 (PSMA) and STEAP1 showed the highest median expression across the cohort. Target expression did not correlate with genomic classifications, including homologous recombination deficiency, microsatellite instability, CDK12, TP53, PTEN or AR alterations Target expression did associate with transcriptomic subtypes: CRPC-AR (driven by androgen receptor-signaling) and CRPC-SCL (stem cell-like features, AP-1/YAP/TAZ-driven), displayed the highest expression of multiple targets, including KLK2, FOLH1, and SLC44A4. CRPC-NE (neuroendocrine phenotype) showed heterogeneous expression, with high CD46 expression, whereas CRPC-WNT (Wnt-signaling driven) generally showed low target expression. Notably, CD46 was highly expressed in tumors with low KLK2, FOLH1, and STEAP1 expression, a subgroup associated with poor prognosis. CONCLUSIONS: Although several antibody targets showed broad expression in mCRPC-tumors, expression varied by transcriptomic subtype. Subgroups such as CRPC-WNT expressed fewer targets, suggesting the need for alternative therapeutic strategies. CD46 emerged as a promising target, with wide expression across multiple subtypes, including clinically challenging CRPC-NE and mCRPC tumors lacking expression of established targets.

Humans↗
PubMed2026

Nested co-expression network analysis identifies compact gene clusters in a black box.

MOTIVATION: Digital analysis of biological systems requires methods capable of identifying both broad and nested gene modules reflecting complex biological processes. Existing transcriptomic methods often miss compact gene sets corresponding to subprocesses in specialized cell types, limiting insights into functional heterogeneity. RESULTS: We present Nested-WGCNA, a two-stage unsupervised network analysis algorithm designed to identify coarse-grained and fine-grained gene modules. Applied to bulk RNA-Seq data, Nested-WGCNA reveals stable modules reproducible across datasets. When validated against scRNA-Seq data, these modules correspond to both major and minor immune cell subtypes. Application to immunotherapy response datasets uncovers predictive and prognostic biomarkers, highlighting its utility in treatment stratification and biomarker discovery. AVAILABILITY: The NestedWGCNA source code and analysis pipeline are available on GitHub (https://github.com/ilyada/NestedWGCNA) and archived on Zenodo (https://doi.org/10.5281/zenodo.18959244).

Algorithms↗
PubMed2006

Inflammatory response of esophageal epithelium in combined-type esophagitis in rats: a transcriptome analysis.

Recent studies have shown that esophageal mucosal inflammatory response is involved in the pathophysiology of gastro-esophageal reflux disease. The aim of the present study was to identify specific gene expression profiles of the esophageal mucosa in a rat model of combined-type chronic reflux esophagitis. Esophagogastroduodenal anastomosis was carried out in male Wistar rats by anastomosing the jejunum to the gastroesophageal junction under diethyl-ether inhalation anesthesia. Esophageal epithelial cells were obtained from esophagi of rats by laser capture microdissection. Preparation of cRNA and target hybridization were performed according to the Affymetrix GeneChip eukaryotic small sample target labeling assay protocol. The gene expression profile was evaluated by the rat toxicology U34 GeneChip. Array data analysis was carried out using Affymetrix GeneChip operating software, ingenuity pathway analysis software, and Gene Springs software. A comparison between esophagitis and sham-operated rats 2 weeks after the operation revealed that 368 probes (36%) were significantly affected, i.e. 185 probes were up-regulated, and 183 probes were down-regulated, both at levels of at least 1.5-fold in the esophagitis rats. Ingenuity signal analysis of 207 affected probes revealed the interleukin-6 signaling pathway as the most significantly affected caronical pathway. In addition, the expression of many genes associated with cytokine and transcription factor was enhanced in the esophagitis rats. This transcriptome approach provided insight into genes and putative genetic pathways thought to be affected by stimulation with gastroduodenal refluxates.

Animals↗
PubMed2004

High-coverage profiling analysis of genes expressed during rice seed development, using an improved amplified fragment length polymorphism technique.

A novel method, based on quantitative PCR and amplified fragment length polymorphism was applied to the analysis of high-coverage gene expression profiles during the development of rice seeds. This represents the first report of the application of this method to plants, which permitted the detection and analysis of approximately 70% of all the genes that are expressed in rice. The method was used to compare gene expression at different developmental stages, subspecies or cultivars, and phyletic lines to identify genes of interest through differences in their level of expression. Using this approach, even novel anonymous genes could be detected. Examples of these include the soluble starch synthase (SS) II-I and the rice branching enzyme 4 (rbe4) genes in the starch synthesis pathway. A profiling database was compiled and the results compared with public data on full-length cDNA sequences of rice. The method enables candidate novel genes to be immediately identified among the large numbers of genes that are expressed during the development of rice seeds. Our results will contribute to a better understanding of comparative transcriptomics in all plant species.

Gene Expression Profiling↗
PubMed2006

Expression profiling of proteins in L-threonine biosynthetic pathway of Escherichia coli by using antibody microarray.

We demonstrate the use of an antibody (Ab) microarray for a comparative expression profiling of proteins in an L-threonine biosynthetic pathway of Escherichia coli between a parental strain (W3110) and L-threonine overproducing mutant (TF5015). On the basis of a global comparative transcriptome analysis between the two strains, 28 analytical target proteins were selected and subjected to a production of polyclonal Abs against them. An Ab microarray was constructed by spotting a set of produced antibodies on a glass slide, and was employed for a comparative expression profiling of the proteins between the two strains by a two-color fluorescence assay method. The performance of the Ab microarray was evaluated with respect to cross-reactivity of the antibodies, dye-labeling efficiency, and the nature of antigenic proteins. Of these, the cross-reactivity of the used antibodies was found to mainly cause the deviation of the observed expression ratios from the expected ones. To offset the deviations, correction factors were derived from a statistical analysis and introduced. As a result, ten proteins were categorized to be up-regulated, while one was down-regulated in TF5015. Expression profiling of proteins using the Ab microarray was further verified by comparison with Western blotting and 2-DE.

Antibodies, Bacterial↗
PubMed2006

Development of mussel mRNA profiling: Can gene expression trends reveal coastal water pollution?

Marine bivalves of the genus Mytilus are intertidal filter-feeders commonly used as biosensors of coastal pollution. Mussels adjust their functions to ordinary environmental changes, e.g. temperature fluctuations and emersion-related hypoxia, and react to various contaminants, accumulated from the surrounding water and defining a potential health risk for sea-food consumers. Despite the increasing use of mussels in environmental monitoring, their genome and gene functions are largely unexplored. Hence, we started the systematic identification of expressed sequence tags and prepared a cDNA microarray of Mytilus galloprovincialis including 1714 mussel probes (76% singletons, approximately 50% putatively identified transcripts) plus unrelated controls. To assess the potential use of the gene set represented in MytArray 1.0, we tested different tissues and groups of mussels. The resulting data highlighted the transcriptional specificity of the mussel tissues. Further testing of the most responsive digestive gland allowed correct classification of mussels treated with mixtures of heavy metals or organic contaminants (expression changes of specific genes discriminated the two pollutant cocktails). Similar analyses made a distinction possible between mussels living in the Venice lagoon (Italy) at the petrochemical district and mussels close to the open sea. The suggestive presence of gene markers tracing organic contaminants more than heavy metals in mussels from the industrial district is consistent with reported trends of chemical contamination. Further study is necessary in order to understand how much gene expression profiles can disclose the signatures of pollutants in mussel cells and tissues. Nevertheless, the gene expression patterns described in this paper support a wider characterization of the mussel transcriptome and point to the development of novel environmental metrics.

Animals↗
PubMed2004

Monitoring gene expression changes in bovine oviduct epithelial cells during the oestrous cycle.

The oviduct epithelium undergoes marked morphological and functional changes during the oestrous cycle. To study these changes at the level of the transcriptome we did a systematic gene expression analysis of bovine oviduct epithelial cells at oestrus and dioestrus using a combination of subtracted cDNA libraries and cDNA array hybridisation. A total of 3072 cDNA clones of two subtracted libraries were analysed by array hybridisation with cDNA probes derived from six cyclic heifers, three of them slaughtered at oestrus and three at dioestrus. Sequencing of cDNAs showing significant differences in their expression levels revealed 77 different cDNAs. Thirty-seven were expressed at a higher level at oestrus, for the other 40 genes expression levels were higher at dioestrus. The identified genes represented a variety of functional classes. During oestrus especially genes involved in the regulation of protein secretion and protein modification, and mRNAs of secreted proteins, were up-regulated, whereas during dioestrus particularly transcripts of genes involved in transcription regulation showed a slight up-regulation. The concentrations of seven selected transcripts were quantified by real-time RT-PCR to validate the cDNA array hybridisation data. For all seven transcripts, RT-PCR results were in excellent correlation (r>0.92) with the results obtained by array hybridisation. Our study is the first to analyse changes in gene expression profiles of bovine oviduct epithelial cells during different stages of the oestrous cycle, providing a starting point for the clarification of the key transcriptome changes in these cells.

Animals↗
PubMed2026

Hyperlactate-Associated Lysine Lactylome Remodeling in Laryngeal Squamous Cell Carcinoma.

Laryngeal squamous cell carcinoma (LSCC) lacks reliable biomarkers, and the roles of lactate metabolism and lysine lactylation (Kla) remain largely unknown. We profiled the lysine lactylome of LSCC, paired it with adjacent normal tissues, and integrated the data with quantitative proteomic and transcriptomic analyses. LSCC exhibited a hyperlactate-associated phenotype characterized by dysregulated lactate-related genes (LRGs), altered protein abundance, increased tissue lactate, and globally increased Kla levels. Data-independent acquisition mass spectrometry (DIA-MS) identified 1616 Kla sites on 1468 peptides from 688 proteins, with most differential sites being upregulated in tumors. Differentially lactylated proteins were enriched in cell-matrix adhesion, cell migration, chromatin remodeling, and gene-regulatory processes and were clustered into cytoskeletal and nuclear regulatory modules. Multiple Kla sites were also detected on the core histones. Immunoblotting and tissue microarray analyses confirmed increased pan-Kla expression in the LSCC. Pan-Kla levels were independent of sex and age but positively correlated with the tumor stage and lymph-node metastasis. These findings provide a systematic resource for hyperlactate-associated lactylome remodeling in LSCCs and identify candidate Kla-related molecular features associated with clinicopathological progression for future functional and clinical evaluation.

Humans↗