Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “transcriptomic profiling”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,153 records · Page 64Linked to original sources
PubMed2006

Expression profiling of Botrytis cinerea genes identifies three patterns of up-regulation in planta and an FKBP12 protein affecting pathogenicity.

The ascomycete Botrytis cinerea is a broad-spectrum plant pathogen. Here, we describe the first macroarray transcriptomic study of the fungus in real-time infection conditions. Infection of Arabidopsis thaliana leaves by B.cinerea was monitored using macroarrays, containing 3032 genes. Variance analysis revealed that 7% of B.cinerea genes are differentially expressed during infection and allowed us to identify 27 genes significantly up-regulated in planta. Among them, two genes have already been associated with fungal pathogenicity, while eight genes have unidentified functions. The 27 genes were separated into three groups according to their expression profile. The first group showed maximal expression at the early stage following fungal penetration, the second one showed maximal expression at the outset of the colonization of plant leaves and the third group showed maximal expression when the colonization of plant leaves was completed. A gene of the last group (BcPIC5), which is homologous to FKBP12 proteins, was disrupted in order to determine its role in pathogenicity. At seven days post-inoculation, the lesions caused by the DeltaBcPIC5 mutant on bean leaves were reduced by 69% and did not further expand compared to the wild-type. These results confirm that transcriptomic analysis under infection conditions can be very valuable for the identification of fungal genes related to pathogenicity.

Arabidopsis↗
PubMed2006

Massively parallel signature sequencing.

Massively parallel signature sequencing is an ultra-high throughput sequencing technology. It can simultaneously sequence millions of sequence tags, and, therefore, is ideal for whole genome analysis. When applied to expression profiling, it reveals almost every transcript in the sample and provides its accurate expression level. This chapter describes the technology and its application in establishing stem cell transcriptome databases.

Cell Culture Techniques↗
PubMed2004

Transcriptome analysis of haploid male gametophyte development in Arabidopsis.

BACKGROUND: The haploid male gametophyte generation of flowering plants consists of two- or three-celled pollen grains. This functional specialization is thought to be a key factor in the evolutionary success of flowering plants. Moreover, pollen ontogeny is also an attractive model in which to dissect cellular networks that control cell growth, asymmetric cell division and cellular differentiation. Our objective, and an essential step towards the detailed understanding of these processes, was to comprehensively define the male haploid transcriptome throughout development. RESULTS: We have developed staged spore isolation procedures for Arabidopsis and used Affymetrix ATH1 genome arrays to identify a total of 13,977 male gametophyte-expressed mRNAs, 9.7% of which were male-gametophyte-specific. The transition from bicellular to tricellular pollen was accompanied by a decline in the number of diverse mRNA species and an increase in the proportion of male gametophyte-specific transcripts. Expression profiles of regulatory proteins and distinct clusters of coexpressed genes were identified that could correspond to components of gametophytic regulatory networks. Moreover, integration of transcriptome and experimental data revealed the early synthesis of translation factors and their requirement to support pollen tube growth. CONCLUSIONS: The progression from proliferating microspores to terminally differentiated pollen is characterized by large-scale repression of early program genes and the activation of a unique late gene-expression program in maturing pollen. These data provide a quantum increase in knowledge concerning gametophytic transcription and lay the foundations for new genomic-led studies of the regulatory networks and cellular functions that operate to specify male gametophyte development.

Arabidopsis↗
PubMed2025

The skeletal muscle of aged male mice exhibits sustained growth regulatory transcriptional profile following glucocorticoid exposure compared with young males.

Excess glucocorticoids induce skeletal muscle myopathy by changing gene expression. Advanced age augments glucocorticoid-mediated muscle phenotypes, yet the transcriptional responses underlying those augmented phenotypes are unclear. The purpose of this study was to define the glucocorticoid-responsive transcriptome in young and aged muscle following both acute and more prolonged glucocorticoid treatment. Young (4-mo-old) or aged (24-mo-old) male mice were administered either an acute injection of dexamethasone (DEX) or vehicle or daily DEX or vehicle injections for 7 days. Muscles were harvested 6.5 h after the final or only injection. The tibialis anterior (TA) was selected for RNA sequencing analysis as DEX treatment lowered TA mass specifically in aged males. In silico analyses identified enriched pathways and transcription factors predicted to regulate DEX-sensitive genes. Acute DEX altered similar numbers of genes in young (950) versus aged males (913), although aged males had greater magnitudes of fold change. After 7 days of DEX treatment, aged muscle exhibited more DEGs compared with acute exposure (1,196 vs. 913), whereas young muscle exhibited fewer DEGs than after acute exposure (599 vs. 950). In aged males, glucocorticoid-sensitive genes were consistently enriched for growth regulatory processes across both time points, a pattern that was not evident in young males. Despite those age-associated transcriptional differences, the transcription factors predicted to regulate the glucocorticoid-sensitive genes were similar in young and aged males. These data expand our understanding into how aging modifies the transcriptional response to excess glucocorticoids in skeletal muscle.NEW & NOTEWORTHY Glucocorticoids promote mass loss in certain muscles with advanced age but not at younger ages. In a muscle whose mass is lost in response to elevated glucocorticoids only in advanced age in males, we show that glucocorticoids initiate a unique and exaggerated transcriptional profile after both acute exposure to the hormone and after prolonged treatment that is consistent with muscle atrophy. These findings expand our understanding of the effect primary aging has on glucocorticoid-induced atrophy in males.

Animals↗
PubMed2004

Post-transcriptional effects of phorbol 12-myristate 13-acetate on transcriptome of U937 cells.

To identify post-transcriptionally modulated genes at the translational level by phorbol 12-myristate 13-acetate (PMA), we investigated mRNA profiles in the polysomal and the cytoplasmic fractions of U937 cells before and after PMA stimulation using microarrays with 15017 oligonucleotide probes. Global comparison of the profiles showed that the cytoplasmic distribution of mRNAs was considerably modulated upon PMA stimulation. The results also indicate that PMA post-transcriptionally regulated at least 0.7% of detectable genes in U937 cells. Thus, besides transcriptional modulation by PMA, changes in the translational state of transcripts seem to play a critical role in PMA-induced differentiation of U937 cells.

Gene Expression Profiling↗
PubMed2006

Aneuploidy-dependent massive deregulation of the cellular transcriptome and apparent divergence of the Wnt/beta-catenin signaling pathway in human rectal carcinomas.

To identify genetic alterations underlying rectal carcinogenesis, we used global gene expression profiling of a series of 17 locally advanced rectal adenocarcinomas and 20 normal rectal mucosa biopsies on oligonucleotide arrays. A total of 351 genes were differentially expressed (P < 1.0e-7) between normal rectal mucosa and rectal carcinomas, 77 genes had a >5-fold difference, and 85 genes always had at least a 2-fold change in all of the matched samples. Twelve genes satisfied all three of these criteria. Altered expression of genes such as PTGS2 (COX-2), WNT1, TGFB1, VEGF, and MYC was confirmed, whereas our data for other genes, like PPARD and LEF1, were inconsistent with previous reports. In addition, we found deregulated expression of many genes whose involvement in rectal carcinogenesis has not been reported. By mapping the genomic imbalances in the tumors using comparative genomic hybridization, we could show that DNA copy number gains of recurrently aneuploid chromosome arms 7p, 8q, 13q, 18q, 20p, and 20q correlated significantly with their average chromosome arm expression profile. Taken together, our results show that both the high-level, significant transcriptional deregulation of specific genes and general modification of the average transcriptional activity of genes residing on aneuploid chromosomes coexist in rectal adenocarcinomas.

Adenocarcinoma↗
PubMed2005

Integrating time-course microarray gene expression profiles with cytotoxicity for identification of biomarkers in primary rat hepatocytes exposed to cadmium.

MOTIVATION: DNA microarrays can provide information about the expression levels of thousands of genes simultaneously at the transcriptomic level, while conventional cell viability and cytotoxicity measurement methods provide information about the biological functions at the cellular level. Integrating these data at different levels provides a promising approach for evaluating or predicting how cells respond to chemical exposure. It is important to investigate the multi-scale biological system in a systematic way to better understand the gene regulation networks and signal transduction pathways involved in the cellular responses to environmental factors. RESULTS: Primary rat hepatocytes were exposed to cadmium acetate at 0, 1.25 and 2 microM. mRNA expression profiles at 0, 3, 6, 12 and 24 h were measured using the Affymetrix RatTox U34 GeneChip arrays. Simultaneously, cytotoxicity was assessed by lactase dehydrogenase leakage assay. Gene expression profiles at different time points were used to evaluate cytotoxicity at subsequent time points using partial least squares, and it was found that gene expression profiles at 0 h had the best prediction accuracy for the cytotoxicity observed at 12 h. Some biomarkers whose expression profiles showed strong relationship with cytotoxicity were identified and the underlying pathways were reconstructed to illustrate how hepatocytes respond to cadmium exposure. Permutation studies were also applied to assess the reliability of the predictive models. AVAILABILITY: Matlab source code is available upon request and DNA microarray data are available at GEO (http://www.ncbi.nlm.nih.gov/geo).

Algorithms↗
PubMed2026

Integrative genetic and transcriptomic analyses prioritize CDC16 as a candidate marker for gastric cancer.

BackgroundGastric cancer (GC) remains a major cause of cancer-related mortality, and biomarkers for early detection are needed.MethodsStomach and blood expression quantitative trait loci were integrated with two GC genome-wide association studies using Mendelian randomization (MR), Bayesian colocalization, and summary-data-based MR/heterogeneity in dependent instruments (SMR/HEIDI) testing. Bulk and single-cell transcriptomic analyses characterized candidate expression and lesion-associated patterns. CDC16 protein expression was evaluated by immunohistochemistry in 53 paired GC and non-neoplastic tissues, followed by paired and exploratory receiver operating characteristic analyses.ResultsMR prioritized PILRB, CDC16, and GABPB1-AS1; SMR/HEIDI provided complementary support, while colocalization for CDC16 and GABPB1-AS1 was suggestive and model-dependent. Bulk-tissue CDC16 abundance was higher in GC, but the modest TCGA-STAD tumor-normal difference (log2FC = 0.210, FDR = 0.019) was attenuated after proliferation adjustment (log2FC = -0.002, FDR = 0.987), indicating close coupling with proliferative activity. Single-cell analysis localized CDC16 predominantly to epithelial populations, and the proportion of CDC16-detectable epithelial cells increased across lesion categories (&#x3c1; = 0.735; permutation P = 0.031). CDC16 H-scores were higher in GC than in paired non-neoplastic tissues (161.15 &#xb1; 45.11 vs 102.15 &#xb1; 54.50; P < 0.001), with higher cancer-tissue scores in 41 of 53 cases. Exploratory AUC was 0.794 (95% CI, 0.704-0.874; sensitivity, 66.0%; specificity, 79.2%).ConclusionsConvergent genetic, transcriptomic, and protein-level evidence prioritizes CDC16 as a GC-associated candidate tissue marker whose expression is closely linked to proliferative activity. Prospective validation in independent cohorts, including appropriate disease controls and blood-based evaluation, is warranted.

Stomach Neoplasms↗
PubMed2005

Toxicogenomics concepts and applications to study hepatic effects of food additives and chemicals.

Transcriptomics, proteomics and metabolomics are genomics technologies with great potential in toxicological sciences. Toxicogenomics involves the integration of conventional toxicological examinations with gene, protein or metabolite expression profiles. An overview together with selected examples of the possibilities of genomics in toxicology is given. The expectations raised by toxicogenomics are earlier and more sensitive detection of toxicity. Furthermore, toxicogenomics will provide a better understanding of the mechanism of toxicity and may facilitate the prediction of toxicity of unknown compounds. Mechanism-based markers of toxicity can be discovered and improved interspecies and in vitro-in vivo extrapolations will drive model developments in toxicology. Toxicological assessment of chemical mixtures will benefit from the new molecular biological tools. In our laboratory, toxicogenomics is predominantly applied for elucidation of mechanisms of action and discovery of novel pathway-supported mechanism-based markers of liver toxicity. In addition, we aim to integrate transcriptome, proteome and metabolome data, supported by bioinformatics to develop a systems biology approach for toxicology. Transcriptomics and proteomics studies on bromobenzene-mediated hepatotoxicity in the rat are discussed. Finally, an example is shown in which gene expression profiling together with conventional biochemistry led to the discovery of novel markers for the hepatic effects of the food additives butylated hydroxytoluene, curcumin, propyl gallate and thiabendazole.

Animals↗
PubMed2006

Human fetal neuroblast and neuroblastoma transcriptome analysis confirms neuroblast origin and highlights neuroblastoma candidate genes.

BACKGROUND: Neuroblastoma tumor cells are assumed to originate from primitive neuroblasts giving rise to the sympathetic nervous system. Because these precursor cells are not detectable in postnatal life, their transcription profile has remained inaccessible for comparative data mining strategies in neuroblastoma. This study provides the first genome-wide mRNA expression profile of these human fetal sympathetic neuroblasts. To this purpose, small islets of normal neuroblasts were isolated by laser microdissection from human fetal adrenal glands. RESULTS: Expression of catecholamine metabolism genes, and neuronal and neuroendocrine markers in the neuroblasts indicated that the proper cells were microdissected. The similarities in expression profile between normal neuroblasts and malignant neuroblastomas provided strong evidence for the neuroblast origin hypothesis of neuroblastoma. Next, supervised feature selection was used to identify the genes that are differentially expressed in normal neuroblasts versus neuroblastoma tumors. This approach efficiently sifted out genes previously reported in neuroblastoma expression profiling studies; most importantly, it also highlighted a series of genes and pathways previously not mentioned in neuroblastoma biology but that were assumed to be involved in neuroblastoma pathogenesis. CONCLUSION: This unique dataset adds power to ongoing and future gene expression studies in neuroblastoma and will facilitate the identification of molecular targets for novel therapies. In addition, this neuroblast transcriptome resource could prove useful for the further study of human sympathoadrenal biogenesis.

Databases, Genetic↗
PubMed2005

Genetic expression profile of olfactory ensheathing cells is distinct from that of Schwann cells and astrocytes.

Olfactory ensheathing cells (OECs) accompany the axons of olfactory receptor neurons, which regenerate throughout life, from the olfactory mucosa into the olfactory bulb. OECs have shown widely varying efficacy in repairing the injured nervous system. Analysis of the transcriptome of OECs will help in understanding their biology and will provide tools for investigating the mechanisms of their efficacy and interactions with host tissues in lesion models. In this study, we compared the transcriptional profile of cultured OECs with that of Schwann cells (SCs) and astrocytes (ACs), two glial cell types to which OECs have similarities. Two biological replicates of RNA from cultured OECs, SCs, and ACs were hybridized to long oligo rat 5K arrays against a common reference pool of RNA (50% cultured fibroblast RNA and 50% neonatal rat brain RNA). Transcriptional profiles were analyzed by hierarchical clustering, Principal Components Analysis, and the Venn diagram. The three glial cell types had similarly increased or decreased expression of numerous transcripts compared with the reference. However, OECs were distinguishable from both SCs and ACs by a modest number of transcripts, which were significantly enriched or depleted. Furthermore, OECs and SCs were more closely related to each other than to ACs. Expression of selected transcripts not previously characterized in OECs, such as Lyz, Timp2, Gro1 (Cxcl1), Ccl2 (MCP1), Ctgf, and Cebpb, was validated by real-time reverse transcription-polymerase chain reaction (RT-PCR); immunohistochemistry in cultured OECs, SCs, and ACs, and adult tissues was performed to demonstrate their expression at the protein level.

Animals↗
PubMed2026

Hyperprogression Upon Cemiplimab Alone or With Short Course Chemotherapy in PD-L1 &#x2265; 50% Non-small Cell Lung Cancer: A Biomarker Guided Multicenter International Phase 2 Trial-HYPERBOLIC Study.

BACKGROUND: Immune checkpoint inhibitor (ICI) monotherapy is the standard first-line treatment for advanced non-small cell lung cancer (NSCLC) with PD-L1 &#x2265; 50%; however, up to 30% of patients experience early progression or death, including cases of hyperprogressive disease (HPD). High baseline levels (&#x2265; 30.5%) of circulating CD10- low-density neutrophils (LDNs) have been associated with increased HPD occurrence. Emerging evidence suggests that combining ICI with platinum-based chemotherapy (PCT) may mitigate the risk of HPD. Currently, no prospective studies have addressed HPD prevention in this context. PATIENTS AND METHODS: HYPERBOLIC (NCT07274384) is a phase 2, randomized, open-label, multicenter, international trial evaluating whether adding 3 cycles of PCT to first-line cemiplimab reduces HPD rate in stage IV NSCLC with PD-L1 &#x2265; 50% and CD10- LDNs (identified by flow cytometry as CD15&#x207a;CD11b&#x207a; within the PBMC fraction, with immature cells defined by loss of CD10) &#x2265; 30.5%. Seventy-four patients will be randomized (1:1 ratio) to receive cemiplimab alone or cemiplimab plus 3 PCT cycles, followed by cemiplimab maintenance. Randomization will be stratified by Lung Immune Prognostic Index. The first computed tomography scan at week 7 after treatment start will assess HPD occurrence, defined as RECIST v 1.1. disease progression with a delta tumor growth rate (&#x394;TGR) &#x2265; 50% and/or TGR ratio &#x2265; 2. The primary endpoint will be the combined rate of HPD and early death (death within 12 weeks with no radiological evaluation). Secondary endpoints will be HPD rate according to alternative definitions, overall survival, progression free survival, objective response rate, and safety. An extensive translational research platform will include spatial transcriptomics of tumor tissue, single-cell RNA sequencing of PBMCs, circulating-free DNA and plasma factors profiling, and saliva/stool microbiome genomics and metabolomics, to longitudinally explore tumor-host dynamic interactions during treatment. CONCLUSION: to our knowledge, HYPERBOLIC is the first prospective, biomarker-driven trial investigating early treatment escalation based on HPD risk in PD-L1-high NSCLC.

CD10↗
PubMed2004

Analysis of gene expression data using functional principal components.

The large amount of data involved in DNA microarrays implies the development of efficient computer algorithms to analyze the gene expressions, and thus to study the transcriptome. Numerous techniques already exist and we propose a new method based on the key idea that gene profiles may be considered as continuous curves. The analysis of the set of curves stemming from the DNA microarray may be then performed using a functional analysis which can exhibit the main modes of variations in this set, gather genes with similar variations and extract characteristic parameters of gene profiles. We aim here at introducing this method, called the Functional Principal Component Analysis. A prospective study has been performed on two available datasets, concerning on the one hand the sporulation data of the Saccharomyces cerevisiae, and on the other hand data of tumor cell lines. Results are very promising: the method is able to extract characteristic parameters from the datasets, to extract significant modes of variations in the set of gene profiles, and to link these variations to biological processes already studied in literature.

Algorithms↗
PubMed2006

Nutrigenomics: from molecular nutrition to prevention of disease.

Until recently, nutrition research concentrated on nutrient deficiencies and impairment of health. The advent of genomics-interpreted broadly as a suite of high throughput technologies for the generation, processing, and application of scientific information about the composition and functions of genomes-has created unprecedented opportunities for increasing our understanding of how nutrients modulate gene and protein expression and ultimately influence cellular and organismal metabolism. Nutritional genomics (nutrigenomics), the junction between health, diet, and genomics, can be seen as the combination of molecular nutrition and genomics. The diverse tissue and organ-specific effects of bioactive dietary components include gene-expression patterns (transcriptome); organization of the chromatin (epigenome); protein-expression patterns, including posttranslational modifications (proteome); as well as metabolite profiles (metabolome). Nutrigenomics will promote an increased understanding of how nutrition influences metabolic pathways and homeostatic control, how this regulation is disturbed in the early phases of diet-related disease, and the extent to which individual sensitizing genotypes contribute to such diseases. Eventually, nutrigenomics will lead to evidence-based dietary intervention strategies for restoring health and fitness and for preventing diet-related disease. In this review, we provide a brief overview of nutrigenomics from our point of view by describing current strategies, future opportunities, and challenges.

Chronic Disease↗
PubMedDate not supplied

Identification of differentially expressed genes in Dreissena polymorpha exposed to contaminants.

Development of transcriptome analysis methods such as differential display PCR and construction of subtractive libraries now makes it possible to profile gene expression in response to xenobiotic exposure. As an example of application of these methods, zebra mussels (Dreissena polymorpha) were treated with various contaminants such as Aroclor 1254, 3-methylcholanthrene, chrysene and atrazine. A total of 242 mRNAs were identified as differentially expressed. Analysis of these mRNAs should provide valuable information regarding detoxification mechanisms in this bivalve species. In addition, the use of cDNA array technology applied to these gene products may constitute a multi-marker approach to monitor the effect of contamination on this aquatic species.

Animals↗
PubMed2026

An Instrumental Optimization of a Label-Free Proteomic Method for Trace Protein Input.

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics of trace-level samples, such as tens of cells or spatially resolved tissue regions, offers unique biological insights but is often constrained by the requirement for specialized, costly instrumentation. In this study, we developed a scalable workflow for the deep proteomic analysis of low- to ultralow-input samples by systematically optimizing a widely adopted Orbitrap and UHPLC platform to maximize sensitivity, precision, and throughput. This optimized workflow identified over 5600 proteins from 5 ng of peptides and 3400 proteins from 20 sorted cells, achieving a throughput of 30 analyses per day while maintaining deep proteome coverage and high quantitative reproducibility. Furthermore, by applying this method to spatially resolved proteomics, we identified over 6100 proteins from microscale regions of interest (ROIs) within a formalin-fixed, paraffin-embedded (FFPE) tissue. A data-driven normalization strategy was employed to correct for variable cellularity across tissue regions, effectively revealing intratumor heterogeneity and distinct molecular and functional signatures, including pathway activations not apparent in parallel spatial transcriptomic analysis. Ultimately, this accessible, high-performance method substantially lowers the instrumentation barrier for the deep proteomic profiling of trace-level biological samples.

Proteomics↗
PubMed2025

Multimodal profiling reveals tissue-directed signatures of human immune cells altered with age.

The immune system comprises multiple cell lineages and subsets maintained in tissues throughout the lifespan, with unknown effects of tissue and age on immune cell function. Here we comprehensively profiled RNA and surface protein expression of over 1.25 million immune cells from blood and lymphoid and mucosal tissues from 24 organ donors aged 20-75&#x2009;years. We annotated major lineages (T&#x2009;cells, B&#x2009;cells, innate lymphoid cells and myeloid cells) and corresponding subsets using a multimodal classifier and probabilistic modeling for comparison across tissue sites and age. We identified dominant site-specific effects on immune cell composition and function across lineages; age-associated effects were manifested by site and lineage for macrophages in mucosal sites, B&#x2009;cells in lymphoid organs, and circulating T&#x2009;cells and natural killer cells across blood and tissues. Our results reveal tissue-specific signatures of immune homeostasis throughout the body, from which to define immune pathologies across the human lifespan.

Humans↗