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PubMed2026

Big data analytics for CLEC5A dynamics based on single cell genomics and proteomics reveal its diverse functions in human diseases.

BACKGROUND: CLEC5A (C-type lectin domain family 5 member A) is an innate immune receptor implicated in inflammatory signaling, contributing to hyperinflammatory responses in infections and sterile inflammation. However, CLEC5A dynamics in human diseases remain to be identified. Here, we systematically characterized CLEC5A dynamics in humans across cells, tissues, and disease states, and to explore the functional significance of CLEC5A in macrophage activation based on single-cell genomics. METHODS: With multi-omics (scRNA-seq, proteomics and big data analytics), we analyzed extensive human transcriptomic datasets (>42,000 samples) to profile CLEC5A expression by cell type, tissue, and disease. Single-nucleus RNA-seq (snRNA-seq) from pediatric congenital heart disease and a virtual CLEC5A gene knockout were also performed to characterize CLEC5A dynamics in humans. RESULTS: CLEC5A is highly enriched in innate immune cells, particularly in macrophages and neutrophils. Baseline CLEC5A in most tissues is low, but it is markedly upregulated in inflammatory and infectious diseases. CLEC5A expression has sex-specific differences in certain organs. Single-cell analysis showed that CLEC5A can be considered novel marker of proinflammatory macrophages with elevated cytokine production, antigen presentation, and impaired phagocytosis. Virtual CLEC5A knockout analysis identified coordinated perturbation of immune-regulatory pathways and overlapping genes linking CLEC5A to macrophage activation networks. CONCLUSION: CLEC5A is predominantly expressed in myeloid cells and acts as a key amplifier of inflammation in human diseases. Our findings highlight CLEC5A as a potential biomarker and therapeutic target in myeloid-driven hyperinflammatory conditions, warranting further experimental and translational validation.

Humans↗

PubMed2024

Machine learning algorithm-based biomarker exploration and validation of mitochondria-related diagnostic genes in osteoarthritis.

The role of mitochondria in the pathogenesis of osteoarthritis (OA) is significant. In this study, we aimed to identify diagnostic signature genes associated with OA from a set of mitochondria-related genes (MRGs). First, the gene expression profiles of OA cartilage GSE114007 and GSE57218 were obtained from the Gene Expression Omnibus. And the limma method was used to detect differentially expressed genes (DEGs). Second, the biological functions of the DEGs in OA were investigated using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Wayne plots were employed to visualize the differentially expressed mitochondrial genes (MDEGs) in OA. Subsequently, the LASSO and SVM-RFE algorithms were employed to elucidate potential OA signature genes within the set of MDEGs. As a result, GRPEL and MTFP1 were identified as signature genes. Notably, GRPEL1 exhibited low expression levels in OA samples from both experimental and test group datasets, demonstrating high diagnostic efficacy. Furthermore, RT-qPCR analysis confirmed the reduced expression of Grpel1 in an in vitro OA model. Lastly, ssGSEA analysis revealed alterations in the infiltration abundance of several immune cells in OA cartilage tissue, which exhibited correlation with GRPEL1 expression. Altogether, this study has revealed that GRPEL1 functions as a novel and significant diagnostic indicator for OA by employing two machine learning methodologies. Furthermore, these findings provide fresh perspectives on potential targeted therapeutic interventions in the future.

Humans↗

PubMed2023

GBMdeconvoluteR accurately infers proportions of neoplastic and immune cell populations from bulk glioblastoma transcriptomics data.

BACKGROUND: Characterizing and quantifying cell types within glioblastoma (GBM) tumors at scale will facilitate a better understanding of the association between the cellular landscape and tumor phenotypes or clinical correlates. We aimed to develop a tool that deconvolutes immune and neoplastic cells within the GBM tumor microenvironment from bulk RNA sequencing data. METHODS: We developed an IDH wild-type (IDHwt) GBM-specific single immune cell reference consisting of B cells, T-cells, NK-cells, microglia, tumor associated macrophages, monocytes, mast and DC cells. We used this alongside an existing neoplastic single cell-type reference for astrocyte-like, oligodendrocyte- and neuronal progenitor-like and mesenchymal GBM cancer cells to create both marker and gene signature matrix-based deconvolution tools. We applied single-cell resolution imaging mass cytometry (IMC) to ten IDHwt GBM samples, five paired primary and recurrent tumors, to determine which deconvolution approach performed best. RESULTS: Marker-based deconvolution using GBM-tissue specific markers was most accurate for both immune cells and cancer cells, so we packaged this approach as GBMdeconvoluteR. We applied GBMdeconvoluteR to bulk GBM RNAseq data from The Cancer Genome Atlas and recapitulated recent findings from multi-omics single cell studies with regards associations between mesenchymal GBM cancer cells and both lymphoid and myeloid cells. Furthermore, we expanded upon this to show that these associations are stronger in patients with worse prognosis. CONCLUSIONS: GBMdeconvoluteR accurately quantifies immune and neoplastic cell proportions in IDHwt GBM bulk RNA sequencing data and is accessible here: https://gbmdeconvoluter.leeds.ac.uk.

Humans↗

PubMed2006

The Cinderella story of metabolic profiling: does metabolomics get to go to the functional genomics ball?

To date most global approaches to functional genomics have centred on genomics, transcriptomics and proteomics. However, since a number of high-profile publications, interest in metabolomics, the global profiling of metabolites in a cell, tissue or organism, has been rapidly increasing. A range of analytical techniques, including 1H NMR spectroscopy, gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), Fourier Transform mass spectrometry (FT-MS), high performance liquid chromatography (HPLC) and electrochemical array (EC-array), are required in order to maximize the number of metabolites that can be identified in a matrix. Applications have included phenotyping of yeast, mice and plants, understanding drug toxicity in pharmaceutical drug safety assessment, monitoring tumour treatment regimes and disease diagnosis in human populations. These successes are likely to be built on as other analytical and bioinformatic approaches are developed to fully exploit the information obtained in metabolic profiles. To assist in this process, databases of metabolomic data will be necessary to allow the passage of information between laboratories. In this prospective review, the capabilities of metabolomics in the field of medicine will be assessed in an attempt to predict the impact this 'Cinderella approach' will have at the 'functional genomic ball'.

Animals↗

PubMed2006

Differential expression profiling of the hepatic proteome in a rat model of dioxin resistance: correlation with genomic and transcriptomic analyses.

One characteristic feature of acute 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) toxicity is dramatic interspecies and interstrain variability in sensitivity. This complicates dioxin risk assessment for humans. However, this variability also provides a means of characterizing mechanisms of dioxin toxicity. Long-Evans (Turku/AB) rats are orders of magnitude more susceptible to TCDD lethality than Han/Wistar (Kuopio) rats, and this difference constitutes a very useful model for identifying mechanisms of dioxin toxicity. We adopted a proteomic approach to identify the differential effects of TCDD exposure on liver protein expression in Han/Wistar rats as compared with Long-Evans rats. This allows determination of which, if any, protein markers are indicative of differences in dioxin susceptibility and/or responsible for conferring resistance. Differential protein expression in total liver protein was assessed using two-dimensional gel electrophoresis, computerized gel image analysis, in-gel digestion, and mass spectrometry. We observed significant changes in the abundance of several proteins, which fall into three general classes: (i) TCDD-independent and exclusively strain-specific (e.g. isoforms of the protein-disulfide isomerase A3, regucalcin, and agmatine ureohydrolase); (ii) strain-independent and only dependent on TCDD exposure (e.g. aldehyde dehydrogenase 3A1 and rat selenium-binding protein 2); (iii) dependent on both TCDD exposure and strain (e.g. oxidative stress-related proteins, apoptosis-inducing factor, and MAWD-binding protein). By integrating transcriptomic (microarray) data and genomic data (computational search of regulatory elements), we found that protein expression levels were mainly controlled at the level of transcription. These results reveal, for the first time, a subset of hepatic proteins that are differentially regulated in response to TCDD in a strain-specific manner. Some of these differential responses may play a role in establishing the major differences in TCDD response between these two strains of rats. As such, our work is expected to lead to new insights into the mechanism of TCDD toxicity and resistance.

Animals↗

PubMed2005

Group A Streptococcus transcriptome dynamics during growth in human blood reveals bacterial adaptive and survival strategies.

The molecular basis for bacterial responses to host signals during natural infections is poorly understood. The gram-positive bacterial pathogen group A Streptococcus (GAS) causes human mucosal, skin, and life-threatening systemic infections. During the transition from a throat or skin infection to an invasive infection, GAS must adapt to changing environments and host factors. To better understand how GAS adapts, we used transcript profiling and functional analysis to investigate the transcriptome of a wild-type serotype M1 GAS strain in human blood. Global changes in GAS gene expression occur rapidly in response to human blood exposure. Increased transcription was observed for many genes that likely enhance bacterial survival, including those encoding superantigens and host-evasion proteins regulated by a multiple gene activator called Mga. GAS also coordinately expressed genes involved in proteolysis, transport, and catabolism of oligopeptides to obtain amino acids in this protein-rich host environment. Comparison of the transcriptome of the wild-type strain to that of an isogenic deletion mutant (DeltacovR) mutated in the two-component regulatory system designated CovR-CovS reinforced the hypothesis that CovR-CovS has an important role linking key biosynthetic, catabolic, and virulence functions during transcriptome restructuring. Taken together, the data provide crucial insights into strategies used by pathogenic bacteria for thwarting host defenses and surviving in human blood.

DNA, Complementary↗

PubMed2025

Genomic and transcriptomic insights into the virulence and adaptation of shock syndrome-causing Streptococcus anginosus.

Streptococcus anginosus is a common isolate of the oral cavity and an opportunistic pathogen for systemic infections. Although the pyogenic infections caused by S. anginosus are similar to those caused by Streptococcus pyogenes, S. anginosus lacks most of the well-characterized virulence factors of S. pyogenes. To investigate the pathogenicity of S. anginosus, we analysed the genome of a newly identified S. anginosus strain, KH1, which was associated with toxic shock-like syndrome in an immunocompetent adolescent. The genome of KH1 contains nine genomic islands, two Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated systems and many phage-related proteins, indicating that the genome is influenced by prophages and horizontal gene transfer. Comparative genome analysis of 355 S. anginosus strains revealed a significant difference between the sizes of the pan genome and core genome, reflecting notable strain variations. We further analysed the transcriptomes of KH1 under conditions mimicking either the oral cavity or the bloodstream. We found that in an artificial saliva medium, the expression of a putative quorum quenching system and pyruvate oxidase for H2O2 production was upregulated, which could optimize the competitiveness of S. anginosus in the oral ecosystem. Conversely, in a modified serum medium, purine and glucan biosynthesis, competence and bacteriocin production were significantly upregulated, likely facilitating the survival of KH1 in the bloodstream. These findings indicate that S. anginosus can utilize diverse mechanisms to adapt to different environmental niches and establish infection, despite its lack of toxin production.

Streptococcus anginosus↗

PubMed2006

Integrated analysis of metabolite and transcript levels reveals the metabolic shifts that underlie tomato fruit development and highlight regulatory aspects of metabolic network behavior.

Tomato (Solanum lycopersicum) is a well-studied model of fleshy fruit development and ripening. Tomato fruit development is well understood from a hormonal-regulatory perspective, and developmental changes in pigment and cell wall metabolism are also well characterized. However, more general aspects of metabolic change during fruit development have not been studied despite the importance of metabolism in the context of final composition of the ripe fruit. In this study, we quantified the abundance of a broad range of metabolites by gas chromatography-mass spectrometry, analyzed a number of the principal metabolic fluxes, and in parallel analyzed transcriptomic changes during tomato fruit development. Metabolic profiling revealed pronounced shifts in the abundance of metabolites of both primary and secondary metabolism during development. The metabolite changes were reflected in the flux analysis that revealed a general decrease in metabolic activity during ripening. However, there were several distinct patterns of metabolite profile, and statistical analysis demonstrated that metabolites in the same (or closely related) pathways changed in abundance in a coordinated manner, indicating a tight regulation of metabolic activity. The metabolite data alone allowed investigations of likely routes through the metabolic network, and, as an example, we analyze the operational feasibility of different pathways of ascorbate synthesis. When combined with the transcriptomic data, several aspects of the regulation of metabolism during fruit ripening were revealed. First, it was apparent that transcript abundance was less strictly coordinated by functional group than metabolite abundance, suggesting that posttranslational mechanisms dominate metabolic regulation. Nevertheless, there were some correlations between specific transcripts and metabolites, and several novel associations were identified that could provide potential targets for manipulation of fruit compositional traits. Finally, there was a strong relationship between ripening-associated transcripts and specific metabolite groups, such as TCA-cycle organic acids and sugar phosphates, underlining the importance of the respective metabolic pathways during fruit development.

Carbon↗

PubMed2006

Genome-wide expression studies of atherosclerosis: critical issues in methodology, analysis, interpretation of transcriptomics data.

During the past 6 years, gene expression profiling of atherosclerosis has been used to identify genes and pathways relevant in vascular (patho)physiology. This review discusses some critical issues in the methodology, analysis, and interpretation of the data of gene expression studies that have made use of vascular specimens from animal models and humans. Analysis of gene expression studies has evolved toward the genome-wide expression profiling of large series of individual samples of well-characterized donors. Despite the advances in statistical and bioinformatical analysis of expression data sets, studies have not yet fully exploited the potential of gene expression data sets to obtain novel insights into the molecular mechanisms underlying atherosclerosis. To assess the potential of published expression data, we compared the data of a CC chemokine gene cluster between 18 murine and human gene expression profiling articles. Our analysis revealed that an adequate comparison is mainly hindered by the incompleteness of available data sets. The challenge for future vascular genomic profiling studies will be to further improve the experimental design, statistical, and bioinformatical analysis and to make data sets freely accessible.

Animals↗

PubMed2026

Molecular and immune profiling of HER2-low, HER2 ultra-low, and HER2-null male breast cancer.

BACKGROUND: HER2 expression is described along a biological continuum from null to positive and serves as a critical biomarker for therapeutic guidance in breast cancer (BC). While HER2-low and ultra-low categories have emerged as actionable targets for antibody-drug conjugates (ADCs) in female BC, their molecular and immune characteristics remain largely unexplored in male breast cancer. METHODS: We profiled 214 male breast tumors using next-generation sequencing and whole-transcriptome sequencing to assess mutational, transcriptomic, and immune landscapes. Tumor mutational burden (TMB) was defined as high if > 10 mutations/Mb. Immune cell fractions were inferred using Quantiseq deconvolution. RESULTS: Among 214 samples, 66 (30.8%) were HER2-null, 53 (24.8%) HER2 ultra-low, 80 (37.4%) HER2-low, and 15 (7.0%) HER2-positive. HER2 ultra-low tumors exhibited a higher prevalence of PIK3CA mutations (39.2% vs 22.6%, p ≤ 0.05) compared to HER2-null. No significant differences were observed in TMB-high frequency or PD-L1 expression across subgroups. Immune composition differed primarily between HER2-null and HER2-expressing subgroups: HER2-ultra-low tumors showed higher B-cell infiltration, whereas HER2-null tumors were enriched in neutrophils. Transcriptomic analysis revealed upregulation of selected stemness-associated genes (NANOG, KLF4, POU5F1) and CEACAM1 in HER2-null tumors, while HER2-low and HER2-ultra-low tumors were largely similar across most molecular and immune readouts in this cohort. CONCLUSIONS: HER2-null male breast cancer appears to represent the most biologically divergent subgroup within the HER2-negative spectrum, whereas HER2-low and HER2-ultra-low tumors were largely similar in this cohort. These findings support further investigation of HER2-null disease as a distinct biological state and provide hypothesis-generating data for biomarker development in this rare population.

Male↗

PubMed2005

Visualizing chromosomes as transcriptome correlation maps: evidence of chromosomal domains containing co-expressed genes--a study of 130 invasive ductal breast carcinomas.

Completion of the working draft of the human genome has made it possible to analyze the expression of genes according to their position on the chromosomes. Here, we used a transcriptome data analysis approach involving for each gene the calculation of the correlation between its expression profile and those of its neighbors. We used the U133 Affymetrix transcriptome data set for a series of 130 invasive ductal breast carcinomas to construct chromosomal maps of gene expression correlation (transcriptome correlation map). This highlighted nonrandom clusters of genes along the genome with correlated expression in tumors. Some of the gene clusters identified by this method probably arose because of genetic alterations, as most of the chromosomes with the highest percentage of correlated genes (1q, 8p, 8q, 16p, 16q, 17q, and 20q) were also the most frequent sites of genomic alterations in breast cancer. Our analysis showed that several known breast tumor amplicons (at 8p11-p12, 11q13, and 17q12) are located within clusters of genes with correlated expression. Using hierarchical clustering on samples and a Treeview representation of whole chromosome arms, we observed a higher-order organization of correlated genes, sometimes involving very large chromosomal domains that could extend to a whole chromosome arm. Transcription correlation maps are a new way of visualizing transcriptome data. They will help to identify new genes involved in tumor progression and new mechanisms of gene regulation in tumors.

Breast Neoplasms↗

PubMed2025

Distinct spatial transcriptomic patterns of substantia Nigra in Parkinson disease and Parkinsonian subtype of multiple system atrophy.

To investigate transcriptomic signatures of Parkinson's disease (PD) and the Parkinsonian subtype of Multiple System Atrophy (MSA-P) in substantia nigra pars compacta (SNpc), we conducted transcriptome analysis using in-situ hybridization on paraffin-embedded SNpc tissues from post-mortem brains. The study included 2 MSA-P patients, 2 PD patients, and 2 healthy controls (HC), with 12 regions of interest (ROIs) selected from the dorsal to ventral and medial to lateral aspects of the SNpc. A total of 72 ROIs from 6 participants were analyzed, and differentially expressed genes (DEGs) were identified by comparing MSA-P, PD and HC groups. The MSA-P group showed 88 upregulated DEGs and 326 downregulated DEGs (adjusted 𝑝<0.05) compared to HC. The downregulated DEGs were significantly enriched in pathways related to ribosomal translation, immune processes, mitochondrial function, and autophagy. Notably, the dorsomedial quadrant was uniquely linked to antigen presentation, while other quadrants showed downregulation of protein synthesis. The PD group exhibited 165 upregulated DEGs and 350 downregulated DEGs (adjusted 𝑝<0.05) compared to HC, with downregulated DEGs associated with ribosomal translation, mitochondrial function, and the ubiquitin-proteasome system. In both MSA-P and PD, the upregulated DEGs were not associated with any pathways or biological process in gene enrichment analysis. In network propagation analysis, amyloid precursor protein was the most significant network hub among DEGs in both MSA-P and PD. Comparing the transcriptomic signatures of SNpc between MSA-P and PD, we found immune/inflammation, mitochondrial function and neural signaling related genes were significantly downregulated in MSA-P compared to PD. Overall, the transcriptomic signature of the SNpc in MSA-P and PD revealed overlapping but distinct features, including alterations in protein synthesis, immune processes, mitochondrial function, and protein degradation systems. Future studies with larger cohorts and functional validation are needed to further elucidate these findings.

Humans↗

PubMed2006

Global analysis of the human gastric epithelial transcriptome altered by Helicobacter pylori eradication in vivo.

OBJECTIVE: The transcriptional profile of gastric epithelial cell lines cocultured with Helicobacter pylori and the global gene expression of whole gastric mucosa has been described previously. We aimed to overcome limitations of previous studies by determining the effects of H pylori eradication on the transcriptome of purified human gastric epithelium using each patient as their own control. DESIGN: Laser capture microdissection (LCM) was used to extract mRNA from paraffin-embedded antral epithelium from 10 patients with peptic ulcer disease, before and after H pylori eradication. mRNA was reverse transcribed and applied on to Affymetrix cDNA microarray chips customised for formalin-fixed tissue. Differentially expressed genes were identified and a subset validated by real-time polymerase chain reaction (PCR). RESULTS: A total of 13 817 transcripts decreased and 9680 increased after H pylori eradication. Applying cut-off criteria (p<0.02, fold-change threshold 2.5) reduced the sample to 98 differentially expressed genes. Genes detected included those previously implicated in H pylori pathophysiology such as interleukin 8, chemokine ligand 3, beta defensin and somatostatin, as well as novel genes such as GDDR (TFIZ1), chemokine receptors 7 and 8, and gastrokine. CONCLUSIONS: LCM of archival specimens has enabled the identification of gastric epithelial genes whose expression is considerably altered after H pylori eradication. This study has confirmed the presence of genes previously implicated in the pathogenesis of H pylori, as well as highlighted novel candidates for further investigation.

Adult↗

PubMed2026

Immune profiling in a living human recipient of a gene-edited pig kidney.

Xenotransplantation of gene-edited pig kidneys offers a promising solution to the shortage of kidneys for organ transplantation. We recently performed a gene-edited pig kidney transplantation into a living human recipient with end-stage kidney disease. Here, using transcriptomics, proteomics, metabolomics and multiplexed imaging, we conducted high-dimensional immune profiling in this individual. Despite profound depletion of circulating T cells, early T cell-mediated rejection occurred within 1 week after transplantation, likely driven by subtherapeutic immunosuppression and the presence of residual CD8+ T cells in lymph nodes. This T cell-mediated rejection event was reversed by intensified immunosuppression. After treatment, adaptive immunity remained suppressed, whereas innate immune activation, characterized by sustained monocyte and macrophage activity along with elevated levels of interleukin-1 beta and granulocyte-macrophage colony-stimulating factor, persisted. Comparative transcriptomic analysis showed that xenograft rejection profiles resembled those typically observed in human allograft rejection, while also revealing unique innate immune signatures. We did not detect antibody-mediated rejection. The levels of circulating pig donor-derived cell-free DNA rose during the initial rejection episode and declined with treatment, supporting the potential of cell-free DNA measurements as a noninvasive biomarker of xenograft rejection. These findings define the distinct immune landscape of kidney xenotransplantation and highlight the need for regimens targeting both innate and adaptive immunity to improve outcomes.

Animals↗

PubMed2005

Proteomics in nutrition and health.

Proteomics, the comprehensive analysis of a protein complement in a cell, tissue or biological fluid at a given time, has been enabled by quantum leaps in mass spectrometric technology, which allowed identification of large, involatile biomolecules. Over the last two decades, this discipline evolved from the sole delivery of protein identities to a platform, which reveals clues to function through e.g. characterisation of protein modifications and interactions as well as through quantitative proteomics, i.e. the global comparison of protein amounts between two defined biological states. Proteomics is an integral part and key player in the family of -omic disciplines as there are genomics (gene analysis), transcriptomics (gene expression analysis) and metabolomics (metabolite profiling). Considering the complexity, dynamics and protein concentration range of any given proteome, proteomics is the most challenging -omic discipline and requires the most sophisticated analysis pipeline. Proteomics represents an established technology in the pharmaceutical industry mainly for biomarker and drug target discovery. The potential of proteomics for research in the food industry is increasingly being recognised and the employment of proteomic approaches to nutrition and health issues is now emerging. This review summarizes (i) major technological achievements in mass spectrometry and proteomics, (ii) deliverables of proteomics in the context of nutrition and health, and (iii) applications of proteomics, and -- if appropriate -- transcriptomics to the research fields of digestive health, obesity and diabetes, immunity and allergy, probiotics, milk, and food preference.

Complex Mixtures↗

PubMed2026

Changes of DNA methylation and gene expression profile in placental villi and chorioamniotic membranes under preeclampsia.

BACKGROUND: Preeclampsia (PE) is a serious pregnancy complication with elusive pathogenesis. Although epigenetic dysregulation is implicated, its layer-specific placental roles are poorly defined. This study aimed to identify shared and layer-specific epigenetic alterations in PE by profiling DNA methylation and gene expression in placental villi (PV) and chorioamniotic membranes (CAM). RESEARCH DESIGN AND METHODS: PV and CAM samples were collected from 7 normal and 8 PE pregnancies, and three public DNA methylation datasets (GSE98224, GSE44667, GSE75196) were integrated. Differentially methylated genes (DMGs) and differentially expressed genes (DEGs) were identified based on whole-genome methylation and transcriptome sequencing. Layer-specific and shared gene sets were identified by cross-analysis, with functional annotation using Gene Ontology (GO). RESULTS: EM-seq revealed a hypermethylation-dominant, tissue-specific methylation landscape in PE placentas. Cross-tissue comparison identified shared DMGs between the two layers, including nine key genes consistently altered in public datasets. Integrated analysis in PV further identified 22 co-dysregulated genes, enriched in thermoregulation, maternal-fetal immunity, signal transduction, and cell differentiation. CONCLUSIONS: This study elucidates the shared and layer-specific dysregulation of gene networks at methylomic and transcriptomic levels in PE placenta. Comparing PV and CAM highlights placental epigenetic heterogeneity and dysfunction, offering novel clues for mechanistic research and layer-targeted therapies.

Humans↗

PubMed2004

Transcriptional profiling of circadian patterns of mRNA expression in the chick retina.

Previous transcriptome analyses have identified candidate molecular components of the avian pineal clock, and herein we employ high density cDNA microarrays of pineal gland transcripts to determine oscillating transcripts in the chick retina under daily and constant darkness conditions. Subsequent comparative transcriptome analysis of the pineal and retinal oscillators distinguished several transcriptional similarities between the two as well as significant differences. Rhythmic retinal transcripts were classified according to functional categories including phototransductive elements, transcription/translation factors, carrier proteins, cell signaling molecules, and stress response genes. Candidate retinal clock transcripts were also organized relative to time of day mRNA abundance, revealing groups accumulating peak mRNA levels across the circadian day but primarily reaching peak values at subjective dawn or subjective dusk. Comparison of the chick retina transcriptome to the pineal transcriptome under constant conditions yields an interesting group of conserved genes. This group includes putative clock elements cry1 and per3 in addition to several previously unidentified and uninvestigated genes exhibiting profiles of mRNA abundance that varied markedly under daily and constant conditions. In contrast, many transcripts were differentially regulated, including those believed to be involved in both melatonin biosynthesis and circadian clock mechanisms. Our results indicate an intimate transcriptional relationship between the avian pineal and retina in addition to providing previously uncharacterized molecular elements that we hypothesize to be involved in circadian rhythm generation.

Animals↗

PubMed2025

Intratumoral B cell and interferon signatures in newly diagnosed glioblastoma are associated with longer survival in patients treated with SurVaxM.

Glioblastoma (GBM) has proved difficult to treat, and there is dire need for more effective therapies. In a single arm phase IIa trial (NCT02455557), treatment of newly diagnosed GBM patients with the peptide vaccine SurVaxM resulted in promising median progression-free and overall survival. To investigate molecular features that associate with GBM responsiveness to SurVaxM, retrospective whole exome and RNA sequencing was performed on patient tumors (n = 34) collected prior to standard of care treatment plus SurVaxM. Differential gene expression and mutational profiles were characterized between patients with short-term (OS < 18 months) or long-term (OS ≥ 18 months) overall survival. Greater expression of interferon, complement, and humoral immunity signatures were associated with long-term survival. Deconvolution of transcriptomes identified enrichment of intratumoral memory B cell populations in long-term survivors that were validated by CD20 staining in matched samples. A five-gene expression signature and a B cell specific signature predicted survival within the SurVaxM-treated cohort, however, these signatures were not associated with improved outcomes in a similarly treated population obtained from The Cancer Genome Atlas (TCGA) that did not receive immunotherapeutic intervention. Although prospective validation is ongoing, the findings in this discovery cohort specify molecular features of GBM associated with better overall survival and potential responsiveness to immunotherapy with SurVaxM.

Humans↗