Specific Pathways Research Articles

Mouse Corneal Immune Cell Heterogeneity Revealed by Single-Cell RNA Sequencing.

This study aimed to define the heterogeneity, spatial localization, and functional roles of immune cells in the mouse cornea using single-cell RNA sequencing (scRNA-seq) and immunofluorescent staining. Enriched mouse corneal immune cells (C57BL/6 strain, age 16-20 weeks) underwent single-cell RNA sequencing library preparation, sequencing, and analysis with Seurat, Monocle 3, and CellChat packages in R. Pathway analysis used Qiagen Ingenuity Pathway Analysis software. Immunostaining confirmed cell distribution. We identified 14 distinct immune cell clusters (56% myeloid and 44% lymphoid). Myeloid populations included resident macrophages, conventional dendritic cells (cDC2s), Langerhans cells, neutrophils, monocytes, and mast cells. Additionally, lymphocyte subsets (B, CD8, CD4, γδT, natural killer, natural killer T, and group 2 innate lymphoid cells) were found. We also found three new subtypes of resident macrophages in the cornea. Trajectory analysis suggested a differentiation pathway from monocytes to conventional dendritic cells, resident macrophages, and LCs. Intercellular communication network analysis using cord diagram identified amyloid precursor protein, chemokine (C-C motif) ligands (2, 3, 4, 6, 7, 9, and 12), Cxcl2, Mif, Tnf, Tgfb1, Igf1, and Il10 as prominent ligands involved in these interactions. Sexually dimorphic gene expression patterns were observed, with male myeloid cells expressing genes linked to immune regulation (Egr1, Foxp1, Mrc1, and Il1rn) and females showing higher expression of antigen presentation genes (Clic1, Psmb8, and Psmb9). Finally, immunostaining confirmed the spatial distribution of these cell populations within the cornea. This study unveils a diverse immune landscape in the mouse cornea, with evidence for cell differentiation and sex-based differences. Immunostaining validates the spatial distribution of these populations, furthering our knowledge of corneal immune function.

Integrated metabolomics and network pharmacology to explore the clinical efficacy and mechanism of Yinchenhao decoction combined with nucleoside analogues on chronic hepatitis B

Yinchenhao decoction (YCHD) is widely used in the treatment of damp-heat syndrome of chronic hepatitis B (CHB), but it remains unclear about the active compounds in YCHD and its potential mechanism for treating CHB. The purpose of this work is to evaluate the clinical efficacy of YCHD combined with nucleoside analogues (NAs) for the treatment of CHB. Besides, based on the exact clinical efficacy, we combined serum metabolomics and network pharmacology to screen differential metabolites and related pathways regulated by YCHD to investigate the possible mechanism for treating CHB. It revealed that NAs plus YCHD could significantly improve alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels, increase HBV-DNA negative rate (P<0.05), reduce the levels of inflammatory factors and LSM (both P<0.05), regulate lipids (P<0.05), and improve the symptoms of traditional Chinese medicine (TCM) (P<0.05) in CHB patients. YCHD was relatively safe. It showed 30 active compounds including chlorogenic acid, geniposide, emodin, quercetin, kaempferol, β-sitosterol and aloe emodin, and 115 key targets which were related to the regulation of lipids and reduction of oxidative stress related to the effect of YCHD in CHB in the network pharmacology analysis. We found 9 core targets and 4 key metabolites according to metabolomics, which were partly consistent with the network pharmacology findings. It proved that network pharmacology combined with metabolomics can well explain the “multi-component-multi-target” mechanism of complex TCM.

Detection of >400 Cluster of Differentiation Biomarkers and Pathway Proteins in Single Immune Cells by Cyclic Multiplex In Situ Tagging for Single-Cell Proteomic Studies.

The identification and characterization of immune cell subpopulations are critical to reveal cell development throughout life and immune responses to environmental factors. Next-generation sequencing technologies have dramatically advanced single-cell genomics and transcriptomics for immune cell classification. However, gene expression is often not correlated with protein expression, and immunotyping is mostly accepted in protein format. Current single-cell proteomic technologies are either limited in multiplex capacity or not sensitive enough to detect the critical functional proteins. Herein, we present a single-cell cyclic multiplex in situ tagging (CycMIST) technology to simultaneously measure >400 proteins, a scale of >10 times than similar technologies. Such an ultrahigh multiplexity is achieved by reiterative staining of the single cells coupled with a MIST array for detection. This technology has been thoroughly validated through comparison with flow cytometry and fluorescence immunostaining techniques. Both peripheral blood mononuclear cells (PBMCs) and T cells are analyzed by the CycMIST technology, and almost the entire spectrum of cluster of differentiation (CD) surface markers has been measured. The landscape of fluctuation of CD protein expression in single cells has been uncovered by our technology. Further study found T cell activation signatures and protein-protein networks. This study represents the highest multiplexity of single immune cell marker measurement targeting functional proteins. With additional information from intracellular proteins of the same single cells, our technology can potentially facilitate mechanistic studies of immune responses under various disease conditions.

Study on the mechanism of Xinmailong injection against chronic heart failure based on transcriptomics and proteomics

Xinmailong (XML), a traditional Chinese medicine derived from Periplaneta americana, is commonly used in China to treat chronic heart failure (CHF). However, its pharmacological mechanism remains unclear. In our research, we employed Doxorubicin (Dox) to create a CHF animal model and administered XML treatment to investigate the pharmacological effects of XML on CHF rats by combining transcriptomic and proteomic analyses. XML improved dox-induced CHF and improved cardiac function, and a joint multi-omics analysis demonstrated that it reduced cardiomyocyte fibrosis during CHF. There is further evidence that XML may alleviate cardiomyocyte fibrosis through its effects on the cGMP-PKG signaling pathway or by reducing the expression levels of COL1A1, COL3A1, MMP9, and CXCR2. In this study, the effects of XML on rats with CHF are examined at the transcriptional and protein levels, as well as its mechanism and mode of action in treating CHF. There may be novel therapeutic targets or clinical indications for XML-based CHF therapy resulting from the study's identification of significant differential genes and signaling pathways.

Sex-specific phenotypical, functional and metabolic profiles of human term placenta macrophages

BackgroundPlacental macrophages, Hofbauer cells (HBC) are the only fetal immune cell population within the stroma of healthy placenta along pregnancy. They are central players in maintaining immune tolerance during pregnancy. Immunometabolism emerged a few years ago as a new field that integrates cellular metabolism with immune responses, however, the immunometabolism of HBC has not been explored yet. Here we studied the sex-specific differences in the phenotypic, functional and immunometabolic profile of HBC.MethodsHBC were isolated from human term placentas (N = 31, 16 from male and 15 female neonates). Ex vivo assays were carried out to assess active metabolic and endoplasmic reticulum stress pathways by flow cytometry, confocal microscopy, gene expression and in silico approaches.ResultsHBC from female placentas displayed a stronger M2 phenotype accompanied by high rates of efferocytosis majorly sustained on lipid metabolism. On the other hand, male HBC expressed a weaker M2 phenotype with higher glycolytic metabolism. LPS stimulation reinforced the glycolytic metabolism in male but not in female HBC. Physiological endoplasmic reticulum stress activates IRE-1 differently, since its pharmacological inhibition increased lipid mobilization, accumulation and efferocytosis only in female HBC. Moreover, differential sex-associated pathways accompanying the phenotypic and functional profiles of HBC appeared related to the placental villi environment.ConclusionsThese results support sex-associated effects on the immunometabolism of the HBC and adds another layer of complexity to the intricate maternal-fetal immune interaction.Graphical abstract

PhenoMultiOmics: an enzymatic reaction inferred multi-omics network visualization web server.

Enzymatic reactions play a pivotal role in regulating cellular processes with a high degree of specificity to biological functions. When enzymatic reactions are disrupted by gene, protein, or metabolite dysfunctions in diseases, it becomes crucial to visualize the resulting perturbed enzymatic reaction-induced multi-omics network. Multi-omics network visualization aids in gaining a comprehensive understanding of the functionality and regulatory mechanisms within biological systems. In this study, we designed PhenoMultiOmics, an enzymatic reaction-based multi-omics web server designed to explore the scope of the multi-omics network across various cancer types. We first curated the PhenoMultiOmics Database (PMODB), which enables the retrieval of cancer-gene-protein-metabolite relationships based on the enzymatic reactions. We then developed the MultiOmics network visualization module to depict the interplay between genes, proteins, and metabolites in response to specific cancer-related enzymatic reactions. The biomarker discovery module facilitates functional analysis through differential omic feature expression and pathway enrichment analysis. PhenoMultiOmics has been applied to analyze transcriptomics data of gastric cancer and metabolomics data of lung cancer, providing insights into interrupted enzymatic reactions and the associated multi-omics network. PhenoMultiOmics is freely accessed at https://phenomultiomics.shinyapps.io/cancer/ with a user-friendly and interactive web interface. Supplementary data are available at Bioinformatics online.

A stepwise approach to deriving functional β-cells from human embryonic or induced pluripotent stem cells

Abstract Our understanding of β-cell differentiation from pluripotent stem cells (PSCs) is rapidly evolving. Although progress has been made, challenges remain, particularly in achieving glucose-stimulated insulin secretion (GSIS). Human embryonic stem cells (hESCs) are valuable due to their pluripotent ability. A fixed protocol targeting master regulatory genes initiates stem cells into pancreatic lineage commitment. Due to the observations that a single stem cell can differentiate into multiple cell types depending on various factors and conditions, non-linear differentiation pathways exist. Co-expression of key factors remains essential for successful β-cell differentiation. The mature β-cell marker MAFA plays a critical role in maintaining the differentiation state and preventing dedifferentiation. Recapitulating pancreatic islet clustering enhances physiological responses, offering potential avenues for diabetes treatment. On the other hand, several enhanced differentiation protocols from induced pluripotent stem cells (iPSCs) have improved the functional insulin producing β-cells generated. These findings, with their potential to revolutionize diabetes treatment, highlight the complexity of β-cell differentiation and guide further advancements in regenerative medicine.

Sex-specific proximal tubular cell differentiation pathways identified by single-nucleus RNA sequencing

Postnatal kidney growth is substantial and involves expansion in kidney tubules without growth of new nephrons, which are the functional units of the kidney. Proliferation and differentiation pathways underpinning nephron elongation are not well defined. To address this, we performed sequential characterization of mouse kidney transcriptomics at the single cell level. Single nuclear RNA sequencing (snRNA-seq) was performed on kidney tissue from male and female mice at 1, 2, 4 and 12 weeks of age using the 10x Chromium platform. Unbiased clustering was performed on 68,775 nuclei from 16 animals. 31 discrete cellular clusters were seen, which were identified through comparison of their gene expression profiles to canonical markers of kidney cell populations. High levels of proliferation were evident at early time points in some cell types, especially tubular cells, but not in other cell types, for example podocytes. Proliferation was especially evident in Proximal Tubular Cells (PTCs) which are the most abundant cell type in the adult kidney. Uniquely when compared to other kidney cell types, PTCs demonstrated sex-specific expression profiles at late, but not early, time points. Mapping of PTC differentiation pathways using techniques including trajectory and RNA Velocity analyses delineated increasing PTC specialization and sex-specific phenotype specification. Our single-cell transcriptomics data characterise cellular states observed during kidney growth. We have identified PTC differentiation pathways that lead to sex-specific tubular cell phenotypes. Tubular proliferative responses are of central importance in postnatal kidney growth and have also been linked to kidney recovery versus fibrosis following injury. Our unbiased and comprehensive dataset of tubular cell development can be used to identify candidate pathways for therapeutic targeting.

The effect of anti‐imbalance on glycolipid metabolic homeostasis via the liver–gut axis intervened by 3′‐sialyllactose in obese mice

AbstractSialic acid could ameliorate disorders associated with glycolipid metabolism. 3′‐Sialyllactose (3′‐SL), a type of oligosaccharide, contains sialic acid. We examined the effects of 3′‐SL on glycolipid metabolism in obese mice with high fat diet and explore the underlying mechanisms. A total of 160 male C57BL/6J mice were fed with high‐fat diet for 8 weeks to construct obese mice model. Sixty successfully constructed obese mice were randomly divided three 3′‐SL dosage‐dependent groups, one free sialic acid N‐acetylneuraminic acid (Neu5Ac) group, and one blank control group. Each group of obese mice (n = 12) was continuously supplemented by 3′‐SL or Neu5Ac for 10 weeks. Ten‐week 3′‐SL supplementation and Neu5Ac supplementation both yielded remarkedly lower body weight, reduced fat content, increased energy expenditure and active daily exercises with improved glycolipid biomarkers, and attenuated proinflammation. 3′‐SL increased the colonic abundances of Akkermansia, Lactobacillus, and Solibacillus and reduced those of Enterobacter and Enterococcus. Changes were also observed in colonic and liver transcript and metabolites, which were mainly enriched in glycolipid metabolism, ameliorated immune function, and mitigated inflammatory signals, autophagy, bile acid metabolism, and insulin resistance. Akkermansia and Solibacillus were significantly associated with changes in colonic metabolites and transcriptome genes. The liver bile component and glucose metabolites were significantly correlated with transcriptional gene expression in the aforementioned differential pathways. Therefore, 3′‐SL can enhance the gut microbiota, regulate intestinal immunity and bile acid metabolism, reduce liver oxidative stress and autophagy processes, alleviate chronic inflammation levels, and improve islet function and lower blood sugar levels by acting through the gut–liver axis.

Vertebrate endocrine disruptors induce sex-reversal in blue mussels

Mollusks are the second most diverse animal phylum, yet little is known about their endocrinology or how they respond to endocrine disrupting compound (EDC) pollution. Characteristic effects of endocrine disruption are reproductive impairment, skewed sex ratios, development of opposite sex characteristics, and population decline. However, whether classical vertebrate EDCs, such as steroid hormone-like chemicals and inhibitors of steroidogenesis, exert effects on mollusks is controversial. In the blue mussel, Mytilus edulis, EDC exposure is correlated with feminized sex ratios in wild and laboratory mussels, but sex reversal has not been confirmed. Here, we describe a non-destructive qPCR assay to identify the sex of M. edulis allowing identification of males and females prior to experimentation. We exposed male mussels to 17α-ethinylestradiol and female mussels to ketoconazole, EDCs that mimic vertebrate steroid hormones or inhibit their biosynthesis. Both chemicals changed the sex of individual mussels, interfered with gonadal development, and disrupted gene expression of the sex differentiation pathway. Impacts from ketoconazole treatment, including changes in steroid levels, confirmed a role for steroidogenesis and steroid-like hormones in mollusk endocrinology. The present study expands the possibilities for laboratory and field monitoring of mollusk species and provides key insights into endocrine disruption and sexual differentiation in bivalves.

Genetic architectures of the human hippocampus and those involved in neuropsychiatric traits

BackgroundThe hippocampus, with its complex subfields, is linked to numerous neuropsychiatric traits. While most research has focused on its global structure or a few specific subfields, a comprehensive analysis of hippocampal substructures and their genetic correlations across a wide range of neuropsychiatric traits remains underexplored. Given the hippocampus’s high heritability, considering hippocampal and subfield volumes (HASV) as endophenotypes for neuropsychiatric conditions is essential.MethodsWe analyzed MRI-derived volumetric data of hippocampal and subfield structures from 41,525 UK Biobank participants. Genome-wide association studies (GWAS) on 24 HASV traits were conducted, followed by genetic correlation, overlap, and Mendelian randomization (MR) analyses with 10 common neuropsychiatric traits. Polygenic risk scores (PRS) based on HASV traits were also evaluated for predicting these traits.ResultsOur analysis identified 352 independent genetic variants surpassing a significance threshold of 2.1 × 10−9 within the 24 HASV traits, located across 93 chromosomal regions. Notably, the regions 12q14.3, 17q21.31, 12q24.22, 6q21, 9q33.1, 6q25.1, and 2q24.2 were found to influence multiple HASVs. Gene set analysis revealed enrichment of neural differentiation and signaling pathways, as well as protein binding and degradation. Of 240 HASV-neuropsychiatric trait pairs, 75 demonstrated significant genetic correlations (P < 0.05/240), revealing 433 pleiotropic loci. Particularly, genes like ACBD4, ARHGAP27, KANSL1, MAPT, ARL17A, and ARL17B were involved in over 50 HASV-neuropsychiatric pairs. Leveraging Mendelian randomization analysis, we further confirmed that atrophy in the left hippocampus, right hippocampus, right hippocampal body, and right CA1-3 region were associated with an increased risk of developing Parkinson’s disease (PD). Furthermore, PRS for all four HASVs were significantly linked to a higher risk of Parkinson’s disease (PD), with the highest hazard ratio (HR) of 1.30 (95% CI 1.18–1.43, P = 6.15 × 10⁻⁸) for right hippocampal volume.ConclusionsThese findings highlight the extensive distribution of pleiotropic genetic determinants between HASVs and neuropsychiatric traits. Moreover, they suggest a significant potential for effectively managing and intervening in these diseases during their early stages.

SnRNA-seq reveals differential functional transcriptional pathway alterations in three mutant types of dilated cardiomyopathy

Dilated cardiomyopathy (DCM) is a leading cause of heart failure, characterized by ventricular dilation, thinning of the ventricular walls, and systolic dysfunction in either the left or both ventricles, often accompanied by fibrosis. Human cardiac tissue is composed of various cell types, including cardiomyocytes (CMs), fibroblasts (FBs), endothelial cells (ECs), macrophages, lymphocytes and so on. In DCM patients, these cells frequently undergo functional and phenotypic changes, contributing to contractile dysfunction, inflammation, fibrosis, and cell death, thereby increasing the risk of heart failure. This study focuses on DCM patients with mutations (LMNA, RBM20, and TTN) and analyzes functional changes in subpopulations of four cardiac cell types. The study involves functional annotation of subpopulations within each cell type and explores the association between gene mutations and specific functions and pathways. Additionally, the SCENIC method is employed of a particular cell subpopulation with significant functional importance, aiming to identify key transcriptional regulators in specific cell states. By analyzing the expression levels of ligand-receptor pairs in vCM4, vFB2, EC5.0, T cells, and NK cells across the DCM mutant genotypes, we predicted their signaling pathways and communications. This research provides insights into the molecular mechanisms of DCM and potential therapeutic targets.

Metabolic profiling of blood plasma in depression in pregnant women during early pregnancy.

The study aimed to perform metabolic profiling of serum samples using liquid chromatography with mass spectroscopy (LC-MS) and to explore potential biomarkers of early trimester depression. Using the Edinburgh Postnatal Depression Scale (EPDS), participants were randomly divided into study and control groups. Serum metabolic profiles of the two groups were analysed by using LC-MS. Differential metabolite and pathway analysis were identified by using orthogonal projections to latent structure-discriminant analysis (OPLS-DA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Additionally, least absolute shrinkage and selection operator (LASSO) logistic and receiver operating characteristic (ROC) curve analyses were also conducted to explore potential biomarkers of antenatal depression (AD). The study included 41 participants, consisting of 16 subjects with AD and 25 controls. A total of 22 different metabolites were identified (p < .005), mainly affecting glycerophospholipid metabolism, linoleic acid metabolism, synthesis and degradation of ketone bodies, phenylalanine metabolism, and butanoate metabolism. The area under the ROC curve (AUC) for the LysoPC (24:0) was 0.858. This suggests that LysoPC (24:0) may be a potentially effective predictor of risk factors for AD. The study suggests that LysoPC (24:0) may be an effective and specific lipid biomarker for early trimester depression.

Screening core genes for minimal change disease based on bioinformatics and machine learning approaches.

Based on bioinformatics and machine learning methods, we conducted a study to screen the core genes of minimal change disease (MCD) and further explore its pathogenesis. First, we obtained the chip data sets GSE108113 and GSE200828 from the Gene Expression Comprehensive Database (GEO), which contained MCD information. We then used R software to analyze the gene chip data and performed functional enrichment analysis. Subsequently, we employed Cytoscape to screen the core genes and utilized machine learning algorithms (random forest and LASSO regression) to accurately identify them. To validate and analyze the core genes, we conducted immunohistochemistry (IHC) and gene set enrichment analysis (GSEA). Our results revealed a total of 394 highly expressed differential genes. Enrichment analysis indicated that these genes are primarily involved in T cell differentiation and p13k-akt signaling pathway of immune response. We identified NOTCH1, TP53, GATA3, and TGF-β1 as the core genes. IHC staining demonstrated significant differences in the expression of these four core genes between the normal group and the MCD group. Furthermore, GSEA suggested that their up-regulation may be closely associated with the pathological changes in MCD kidneys, particularly in the glycosaminoglycans signaling pathway. In conclusion, our study highlights NOTCH1, TP53, GATA3, and TGF-β1 as the core genes in MCD and emphasizes the close relationship between glycosaminoglycans and pathogenesis of MCD.

Spatial Transcriptomics Unravel the Tissue Complexity of Oral Pathogenesis.

Spatial transcriptomics (ST) is a cutting-edge methodology that enables the simultaneous profiling of global gene expression and spatial information within histological tissue sections. Traditional transcriptomic methods lack the spatial resolution required to sufficiently examine the complex interrelationships between cellular regions in diseased and healthy tissue states. We review the general workflows for ST, from specimen processing to ST data analysis and interpretations of the ST dataset using visualizations and cell deconvolution approaches. We show how recent studies used ST to explore the development or pathogenesis of specific craniofacial regions, including the cranium, palate, salivary glands, tongue, floor of mouth, oropharynx, and periodontium. Analyses of cranial suture patency and palatal fusion during development using ST identified spatial patterns of bone morphogenetic protein in sutures and osteogenic differentiation pathways in the palate, in addition to the discovery of several genes expressed at critical locations during craniofacial development. ST of salivary glands from patients with Sjögren's disease revealed co-localization of autoimmune antigens with ductal cells and a subpopulation of acinar cells that was specifically depleted by the dysregulated autoimmune response. ST of head and neck lesions, such as premalignant leukoplakia progressing to established oral squamous cell carcinomas, oral cancers with perineural invasions, and oropharyngeal lesions associated with HPV infection spatially profiled the complex tumor microenvironment, showing functionally important gene signatures of tumor cell differentiation, invasion, and nontumor cell dysregulation within patient biopsies. ST also enabled the localization of periodontal disease-associated gene expression signatures within gingival tissues, including genes involved in inflammation, and the discovery of a fibroblast subtype mediating the transition between innate and adaptive immune responses in periodontitis. The increased use of ST, especially in conjunction with single-cell analyses, promises to improve our understandings of craniofacial development and pathogenesis at unprecedented tissue-level resolution in both space and time.

The small inhibitor WM-1119 effectively targets KAT6A-rearranged AML, but not KMT2A-rearranged AML, despite shared KAT6 genetic dependency

BackgroundThe epigenetic factors KAT6A (MOZ/MYST3) and KMT2A (MLL/MLL1) interact in normal hematopoiesis to regulate progenitors’ self-renewal. Both proteins are recurrently translocated in AML, leading to impairment of critical differentiation pathways in these malignant cells. We evaluated the potential of different KAT6A therapeutic targeting strategies to alter the growth of KAT6A and KMT2A rearranged AMLs.MethodsWe investigated the action and potential mechanisms of the first-in-class KAT6A inhibitor, WM-1119 in KAT6A and KMT2A rearranged (KAT6Ar and KMT2Ar) AML using cellular (flow cytometry, colony assays, cell growth) and molecular (shRNA knock-down, CRISPR knock-out, bulk and single-cell RNA-seq, ChIP-seq) assays. We also used two novel genetic murine KAT6A models combined with the most common KMT2Ar AML, KMT2A::MLLT3 AML. In these murine models, the catalytic activity of KAT6A, or the whole protein, can be conditionally abrogated or deleted. These models allowed us to compare the effects of specific KAT6A KAT activity inhibition with the complete deletion of the whole protein. Finally, we also tested these therapeutic approaches on human AML cell lines and primary patient AMLs.ResultsWe found that WM-1119 completely abrogated the proliferative and clonogenic potential of KAT6Ar cells in vitro. WM-1119 treatment was associated with a dramatic increase in myeloid differentiation program. The treatment also decreased stemness and leukemia pathways at the transcriptome level and led to loss of binding of the fusion protein at critical regulators of these pathways. In contrast, our pharmacologic and genetic results indicate that the catalytic activity of KAT6A plays a more limited role in KMT2Ar leukemogenicity, while targeting the whole KAT6A protein dramatically affects leukemic potential in murine KMT2A::MLLT3 AML.ConclusionOur study indicates that inhibiting KAT6A KAT activity holds compelling promise for KAT6Ar AML patients. In contrast, targeted degradation of KAT6A, and not just its catalytic activity, may represent a more appropriate therapeutic approach for KMT2Ar AMLs.

12353 Differential Gene Expression And Pathway Analysis In Growth Hormone Secreting Pituitary Tumors According To Granulation Pattern

Abstract Disclosure: H. Shin: None. Differential gene expression and pathway analysis in growth hormone-secreting pituitary tumors according to granulation pattern. Hye Ju Shin [1], Kyung Won Kim[2], Chan Woo Kang[2], Eun Jig Lee[2], Cheol Ryong Ku[2]. [1]Department of Clinical Drug Discovery &amp; Development, Yonsei University College of Medicine, Seoul, Republic of Korea, [2]Endocrinology, Institute of Endocrine Research, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea Objective: The purpose of this research is to explain clinical variations in patients with acromegaly by exploring gene expression differences according to granulation patterns in growth hormone (GH)-secreting pituitary tumors. Materials &amp; methods: Transcriptome analysis was conducted on 6 normal pituitary tissues and 15 GH-secreting pituitary tumors, including 9 densely granulated somatotroph tumors (DGSTs) and 6 sparsely granulated somatotroph tumors (SGSTs). Results: The median age at diagnosis was 50 years, with a predominance of female patients (60%). We identified 3111 differentially expressed genes (DEGs) in tumors compared to normal pituitaries, with 1117 DEGs unique to a specific granulation within tumors. SGST showed enriched the pathways involved in neuronal development (axon development, axonogenesis, axon guidance, synapse and presynapse organization, gliogenesis, glial cell differentiation, nerve development, synaptic membrane adhesion, semaphorin-plexin signaling pathway involved in neuron projection guidance) and acute inflammatory response. No pathways were significantly downregulated in SGST compared with those in DGST. Three signaling pathways (JAK-STAT, phosphatidylinositol 3-kinase, and MAP cascade) and three neuronal development processes (generation of neurons, nerve development, and neurogenesis) were significantly enriched in both GO and GSEA analysis. The PPI networks constructed with the up- and downregulated DEGs consisted of 128 and 132 PPI pairs, respectively. There were 10 hub proteins, top highly connected DEGs: ANLN, TLE3, TLE2, DMD, ADRA1A, RBFOX1, MMP2, LMO1, RUNX1T1, and NPPA. Conclusion: The results indicate that granulation-specific gene expression may underpin diverse clinical characteristics in acromegaly. Overall, this study emphasizes the potential for further investigation into these transcriptomic variations and their roles in disease pathology, particularly the involvement of genes linked to neuronal development, inflammatory response, and JAK-STAT signaling in SGST. Presentation: 6/3/2024

New generalized metric based on branch length distance to compare B cell lineage trees

The B cell lineage tree encapsulates the successive phases of B cell differentiation and maturation, transitioning from hematopoietic stem cells to mature, antibody-secreting cells within the immune system. Mathematically, this lineage can be conceptualized as an evolutionary tree, where each node represents a distinct stage in B cell development, and the edges reflect the differentiation pathways. To compare these lineage trees, a rigorous mathematical metric is essential. Analyzing B cell lineage trees mathematically and quantifying changes in lineage attributes over time necessitates a comparison methodology capable of accurately assessing and measuring these changes. Addressing the intricacies of multiple B cell lineage tree comparisons, this study introduces a novel metric that enhances the precision of comparative analysis. This metric is formulated on principles of metric theory and evolutionary biology, quantifying the dissimilarities between lineage trees by measuring branch length distance and weight. By providing a framework for systematically classifying lineage trees, this metric facilitates the development of predictive models that are crucial for the creation of targeted immunotherapy and vaccines. To validate the effectiveness of this new metric, synthetic datasets that mimic the complexity and variability of real B cell lineage structures are employed. We demonstrated the ability of the new metric method to accurately capture the evolutionary nuances of B cell lineages.

Bioinformatic analysis of molecular characteristics and oncogenic features of CARD14 in human cancer

Aberrant caspase recruitment domain family member 14 (CARD14) signaling has been strongly associated with inflammatory skin conditions. CARD14 acts as a scaffold protein, ultimately activating the transcription factor NF-KB. Although primarily studied in the context of inflammation, recent research has suggested its potential implications in tumorigenesis. In this study, we gathered The Cancer Genome Atlas (TCGA) tumor data to gauge the involvement of CARD14 in cancer, including genetic alterations, expression patterns, survival correlations, immune cell infiltration and functional interactions across diverse cancer types. We found heightened CARD14 expression in most tumors and there was a significant correlation between CARD14 expression and the prognosis of patients for certain tumors. For instance, patients with higher CARD14 expression had a better prognosis in sarcoma, lung, cervix and head and neck cancers. Moreover, CARD14 expression positively correlated with neutrophil infiltration in most of the cancer types analyzed. Finally, enrichment analysis showed that epithelial development and differentiation pathways were involved in the functional mechanism of CARD14. Our results show that CARD14 may have the potential to become a prognostic biomarker in several cancers, hence, further prospective studies will be required for its validation.

NCAM and attached polysialic acid affect behaviors of breast epithelial cells through differential signaling pathways.

Neural cell adhesion molecule (NCAM), a common mammalian cell surface glycoprotein, is the major substrate of polysialic acid (polySia). Polysialylated NCAM occurs in many types of cancer, but rarely in normal adult tissues. The functional role of NCAM hypersialylation in the epithelial-mesenchymal transition (EMT) process remains unclear. The present study indicates that NCAM and attached polysialic acid affect behaviors of breast epithelial cells through differential signaling pathways. NCAM and polysialylated NCAM are aberrantly regulated in breast cancer cells. They are both upregulated in normal breast epithelial cells undergoing EMT. Western blot analysis demonstrates that NCAM-140 overexpression induces EMT in breast epithelial cells and promotes cell proliferation and migration through activation of the β-catenin/slug signaling pathway. Modification of polySia attached to NCAM modulates cell adhesion and promotes cell motility through activation of the EGFR/STAT3 pathway. These observations contribute to clarifying the molecular mechanisms by which polysialic acid and its major substrate, NCAM, modulate cell behaviors, and highlight the significance of increased polysialylated expression on NCAM during EMT and tumor development.