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PubMed2025

Integrative multi-omics analysis proposes a metabolic classification of gliomas: distinct metabolic states, immune infiltration, and prognosis.

BACKGROUND: The tumor microenvironment (TME) of glioma harbors diverse cell types; however, cell metabolic heterogeneity remains to be explored. This study aims to characterize the metabolic features of different cell types in the TME by integrating multiple datasets, including genomics, bulk and single-cell transcriptomics, and metabolomics. METHODS: Unsupervised machine learning was used to construct an energy metabolic classifier based on the metabolic pathways identified from bulk RNA-seq of gliomas in the TCGA dataset. The classifier was externally validated using multiple datasets, including genomics, bulk RNA-seq, snRNA-seq, and the metabolomics data. Furthermore, metabolic heterogeneity associated with the classifier was further characterized at single-cell resolution. RESULTS: The energy metabolism-based classifier stratified patients into two prognostic clusters: patients in cluster 1 were characterized by high pathway activity of glycolysis, the pentose phosphate pathway (PPP), and fatty acid oxidation (FAO), whereas patients in cluster 2 exhibited higher activity in glutaminolysis. This metabolic classifier revealed both intratumoral and intertumoral metabolic heterogeneity, and the complexity was further validated by the metabolomics profiling and snRNA-seq data from the CPTAC dataset. Notably, OSMR, highly expressed in cluster 1, showed significant co-expression with key glycolytic enzyme genes. The OSM/OSMR/JAK1/STAT3 axis potently drives malignant progression of glioma cells, specially enhancing their invasive and migratory capabilities. Single-cell resolution analyses demonstrated that tumor metabolic heterogeneity is primarily driven by malignant cells rather than non-malignant components, while tumor microenvironment (TME) factors were also found to modulate malignant cell metabolism. Significantly, glycolytic activity in glioma cells increased during the phenotypic transition from PN (proneural) to MES (mesenchymal), with cluster 1 metabolic phenotypes predominating in the tumor core. Compared to cluster 2, cluster 1 patients exhibited higher mRNA expression of immunosuppressive checkpoint genes, which correlated with pronounced immunosuppression in the TME. Furthermore, various immune cells demonstrated distinct metabolic preferences at single-cell resolution. CONCLUSIONS: This study developed an energy metabolic-based classifier for gliomas with prognostic and therapeutic potential. Metabolic reprogramming was linked with the PN-to-MES transition of glioma cells and immunosuppression in the tumor microenvironment. Multi-omics data, especially snRNA-seq, offered insights into metabolism heterogeneity at single-cell resolution, enabling personalized treatment strategies.

Humans↗

PubMed2026

Exploration and experimental verification of triaptosis-related prognostic genes and cells in gastric cancer.

BACKGROUND: Triaptosis is a recently characterized form of programmed cell death with unclear implications in cancer. This study aimed to investigate the prognostic significance and biological relevance of triaptosis in gastric cancer (GC). METHODS: Transcriptomic and clinical data from TCGA-STAD and GSE62254, and single-cell RNA sequencing data from GSE183904 were analyzed. Triaptosis-related gene (TRG) scores were calculated using single-sample gene set enrichment analysis. Differentially expressed genes identified in TRG-score and GC-versus-normal comparisons underwent functional enrichment, Cox regression, and least absolute shrinkage and selection operator regression to develop an externally validated signature. Immune profiles, pathway activity, somatic mutations, tumor mutational burden (TMB), predicted drug sensitivity, and clinical features were compared by risk group. Single-cell analyses assessed TRG activity, prognostic gene expression, cell-cell communication, and pseudotime. Reverse transcription-quantitative PCR and Western blotting assessed mRNA expression and protein levels, respectively. RESULTS: A TRG-based prognostic model comprising ASPN, GRB14, and VTN was developed and externally validated, effectively distinguishing patients into two distinct risk groups with notably different survival outcomes. mRNA expression of all three genes and their protein levels were significantly higher in SGC-7901 cells than in GES-1 cells. High-risk patients had higher stromal scores and distinct immune profiles; 15 immune cell types differed between groups. Single-cell analysis revealed fibroblasts and pericytes among high-TRG-active cell types. Prognostic genes were significantly overexpressed in fibroblasts, which also showed high TRG activity. Fibroblasts demonstrated enhanced communication with pericytes, whereas tumor-derived fibroblasts showed weaker communication with macrophages, indicating immune microenvironment remodeling. CONCLUSION: The three-gene prognostic signature predicted GC prognosis and was associated with distinct immune and genomic features, suggesting potential value for risk stratification and personalized treatment.

Humans↗

PubMed2024

Polycystic ovarian syndrome (PCOS) and recurrent spontaneous abortion (RSA) are associated with the PI3K-AKT pathway activation.

AIMS: We aimed to elucidate the mechanism leading to polycystic ovarian syndrome (PCOS) and recurrent spontaneous abortion (RSA). BACKGROUND: PCOS is an endocrine disorder. Patients with RSA also have a high incidence rate of PCOS, implying that PCOS and RSA may share the same pathological mechanism. OBJECTIVE: The single-cell RNA-seq datasets of PCOS (GSE168404 and GSE193123) and RSA GSE113790 and GSE178535) were downloaded from the Gene Expression Omnibus (GEO) database. METHODS: Datasets of PSCO and RSA patients were retrieved from the Gene Expression Omnibus (GEO) database. The "WGCNA" package was used to determine the module eigengenes associated with the PCOS and RSA phenotypes and the gene functions were analyzed using the "DAVID" database. The GSEA analysis was performed in "clusterProfiler" package, and key genes in the activated pathways were identified using the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Real-time quantitative PCR (RT-qPCR) was conducted to determine the mRNA level. Cell viability and apoptosis were measured by cell counting kit-8 (CCK-8) and flow cytometry, respectively. RESULTS: The modules related to PCOS and RSA were sectioned by weighted gene co-expression network analysis (WGCNA) and positive correlation modules of PCOS and RSA were all enriched in angiogenesis and Wnt pathways. The GSEA further revealed that these biological processes of angiogenesis, Wnt and regulation of cell cycle were significantly positively correlated with the PCOS and RSA phenotypes. The intersection of the positive correlation modules of PCOS and RSA contained 80 key genes, which were mainly enriched in kinase-related signal pathways and were significant high-expressed in the disease samples. Subsequently, visualization of these genes including PDGFC, GHR, PRLR and ITGA3 showed that these genes were associated with the PI3K-AKT signal pathway. Moreover, the experimental results showed that PRLR had a higher expression in KGN cells, and that knocking PRLR down suppressed cell viability and promoted apoptosis of KGN cells. CONCLUSION: This study revealed the common pathological mechanisms between PCOS and RSA and explored the role of the PI3K-AKT signaling pathway in the two diseases, providing a new direction for the clinical treatment of PCOS and RSA.

Humans↗

PubMed2026

transfactor: transcription factor activity estimation via probabilistic gene expression deconvolution.

Gene expression is a primary modality being studied to differentiate between biological cells. Contemporary single-cell studies simultaneously measure genome-wide transcription levels for thousands of individual cells in a single experiment. While the characterization of cell population differences has often occurred through differential gene expression analysis, tiny effect sizes become statistically significant when thousands of cells are available for each population, compromising biological interpretation. Moreover, these large studies have spurred the development of methods to infer gene regulatory networks (GRNs) directly from the data, and GRN databases are becoming more comprehensive. In this work, we propose a statistical model for gene expression measures and an inference method that leverage GRNs to deconvolve transcription factor (TF) activity from gene expression, by probabilistically assigning mRNA molecules to TFs. This shifts the paradigm from investigating gene expression differences to regulatory differences at the level of TF activity, aiding interpretation and allowing prioritization of a limited number of TFs responsible for significant contributions to the observed gene expression differences. The inferred TF activities result in intuitive prioritization of TFs in terms of the (difference in) estimated number of molecules they produce, in contrast to other widely used methods relying on arbitrary enrichment scores. Our model allows the incorporation of prior information on the regulatory potential between each TF and target gene and is able to deal with both repressing and activating interactions. We compare our approach to other TF activity estimation methods using two simulation experiments and two case studies. Single-cell RNA-sequencing; TF activity; bioinformatics; GRN.

Transcription Factors↗

PubMed1992

Phenotypical characterization of the rat striatal neurons expressing muscarinic receptor genes.

Neurons expressing the m1, m2, and m4 muscarinic receptor genes in the adult rat striatum were identified and characterized by using several in situ hybridization and immunohistochemical procedures. Combined in situ hybridization for the simultaneous detection of two mRNAs in the same section or in adjacent sections as well as in situ hybridization and immunohistochemistry on adjacent sections permitted us to identify the neurons containing m1, m2, or m4 receptor mRNA. Our observations demonstrate that m1, m2, and m4 receptor genes are expressed in one or several phenotypically distinct neuronal populations. The m1 receptor gene was the most widely expressed (85% of the striatal neurons). Most cholinergic neurons (80% or more) contain m1, m2, and m4 receptor mRNAs. Almost all the substance P neurons contain m1 and m4 receptor mRNA. All enkephalinergic neurons contained m1 receptor mRNA, but only 39% contained m4 receptor mRNA. Most somatostatin and neurotensin neurons expressed the m1 receptor gene, but only a few (15% and 9%, respectively) contained m4 receptor mRNA. The present study offers anatomical evidence that ACh may act directly in complex ways on the main neuronal populations of the striatum through muscarinic receptors. The m1, m2, and m4 receptors may act as autoreceptors to control ACh release and possibly other parameters of ACh neurons. On the other hand, the m1 and m4 receptors may act as heteroreceptors in cholinoceptive efferent neurons (enkephalin and substance P neurons) and other neurons (somatostatin/neuropeptide Y and neurotensin neurons). The presence of m4 receptor mRNA in only parts of the enkephalin, somatostatin, and neurotensin neuronal populations indicates that muscarinic receptor gene expression contributes to the functional and anatomical heterogeneity of the striatum that may relate to higher order of organization, including patch-matrix compartmentalization. The wide expression of m1 and m4 receptor genes in the striatum suggests that ACh may directly influence neurotransmitter release and synthesis in striatal efferent and intrinsic neurons. Our results imply that the specific pattern of expression of the muscarinic receptor genes mediates direct effects of ACh on activities and functions of chemically and topologically defined striatal neuronal populations. Since the expression of muscarinic receptors occurred in the three main neuronal populations of the striatum, namely ACh, enkephalins, and substance P neurons that also express dopamine receptors, it is highly probable that ACh and dopamine may act together at the single-cell level to influence striatal functions.

Animals↗

PubMed2025

Founder Homozygous Nonsense CREB3 Variant and Variable-Onset Retinal Degeneration.

IMPORTANCE: Uncovering the genetic basis of inherited retinal diseases (IRDs) can enhance both diagnostic accuracy and the development of targeted treatment strategies. OBJECTIVE: To evaluate the association between a homozygous nonsense variant in CREB3 with IRDs. DESIGN, SETTING, AND PARTICIPANTS: Thirteen patients with a clinical diagnosis of retinitis pigmentosa or cone-rod degeneration were analyzed by whole-genome sequencing (WGS) and whole-exome sequencing (WES). Clinically, patients presented with 2 main phenotypes, rod-cone and cone-rod dystrophies, demonstrating variable electrophysiological and fundoscopic findings. Expression analysis was performed on patient-derived skin fibroblasts using the reverse transcription-polymerase chain reaction and Western blot analysis, and by interrogating previously published retinal single-cell RNA sequence data. Immunohistochemistry staining was performed on wild-type mouse retinal sections using an anti-CREB3 antibody. Patients with variable phenotypes of IRDs were recruited from 3 medical centers in Israel and Italy. Ophthalmologists clinically diagnosed patients at the relevant medical centers and referred them for genetic screening. WES and WGS were performed at different national and international centers, and the findings of the previously unreported gene were shared between investigators. EXPOSURES: CREB3 and IRDs. MAIN OUTCOMES AND MEASURES: The main outcome was evidence supporting an association between CREB3 and IRD. Measures included WES, WGS, and immunohistochemistry staining. RESULTS: A founder homozygous nonsense variant in CREB3 (c.881G>A, p.Trp294*) was identified in 13 patients from 4 unrelated families; 12 descendent from North-African Jewish origins and 1 from Italian origins. All patients manifested retinal degeneration with varying ages at onset. In patient-derived fibroblasts, the variant mRNA transcript generated a truncated CREB3 protein. Expression analysis and immunohistochemistry staining revealed CREB3 RNA and protein expression in various retinal cell types, indicating its vital role in photoreceptor function. CONCLUSIONS AND RELEVANCE: This study found an association between CREB3 and IRDs. CREB3 was previously shown to be upregulated following ultraviolet radiation. This might contribute to the extensive clinical variability observed in this relatively large cohort of homozygous patients with the same truncated variant.

Humans↗

PubMed2026

Atherosclerotic plaque fibroblasts derive from adventitial and medial Pdgfra-lineage-positive cells and predominantly maintain fibroblast identity.

AIMS: Fibroblasts are mesenchymal cells in the healthy vascular adventitia. In atherosclerosis, single-cell sequencing datasets suggest fibroblasts are abundant in plaques. However, their identity, origin, and fate during plaque progression remain unclear, which we aim to unravel here. APPROACH AND RESULTS: To robustly define fibroblast identity, origin, and fate, we employed meta-analyses of 54 single-cell RNA sequencing libraries, including murine smooth muscle cell (Myh11) and endothelial cell (EC) (Cdh5) lineage reporter mice with and without atherosclerosis; human control and atherosclerotic arteries; and murine adventitia and atherosclerotic plaques processed separately from low-density lipoprotein (LDL) receptor knockout (Ldlr-/-) mice. These meta-analyses showed that murine and human plaque fibroblast identity was robustly defined by Pdgfra, Pi16, Cygb, and Serpinf1 mRNA. Ninety-five percent of plaque fibroblasts do not derive from the Myh11 lineage, while no Cdh5-lineage-positive cells were present in the fibroblast cluster. We identified five murine arterial fibroblast subsets in atherosclerotic murine aorta: progenitor fibroblasts, matrix fibroblasts, inflammatory fibroblasts, an EC-like fibroblast subset, detected in both adventitia and plaques, and Col5a3+ fibroblasts, unique to the adventitia. We next studied fibroblast identity, origin, and fate using pseudotime analysis and Pdgfra-CreERT2/tdTomato lineage reporter mice (Pdgfra Lin+). Healthy Pdgfra Lin+ reporter mice showed predominant adventitial tdTomato expression, and infrequent medial and intimal Pdgfra Lin+ cells co-expressing MYH11 and PECAM1, respectively. The Pdgfra Lin+ plaque area increased with diet duration. Pdgfra Lin+ cells largely maintain fibroblast identity in the plaque, while <10% co-express SMC markers (MYH11, SM22α), or contribute to ACTA2+ cap cells. ECs gaining mesenchymal markers are transcriptionally distinct from Cdh5-lineage-negative fibroblasts gaining EC markers. Plaque-resident EC-like fibroblasts displayed a mesenchymal-to-endothelial transition transcriptome, which was induced in human primary fibroblasts in vitro by starvation, and dampened or reversed by IL1B, TGFB1, TGFB3, and oxidized LDL. Cross-species integration showed that all murine plaque fibroblasts were conserved in human atherosclerosis, with one additional subset partially resembling murine subsets, and three human-specific subsets. Importantly, human fibroblast subsets differentially correlated to human plaque traits, with EC-like fibroblasts correlating to plaque instability. CONCLUSION: Our results indicate that 95% of plaque-residing fibroblasts are Myh11 Lin- Plaque fibroblasts have a dual origin, predominantly adventitial Pdgfra Lin+ progenitor fibroblasts, with a minor contribution from medial Pdgfra Lin+  Myh11+ SMCs. Most plaque fibroblasts maintain fibroblast identity. Murine plaque fibroblast subsets were conserved in human atherosclerosis. EC-like fibroblasts are linked to human plaque instability. Intervening in progenitor-to-specific fibroblast transitions could present a new avenue to promote plaque stability in atherosclerosis.

Atherosclerosis↗

PubMed1992

Reciprocal regulatory effects of IL-4 on cell growth and immunoglobulin production in Ig-secreting human B-cell lines.

The effects of interleukin-4 (IL-4) on cell proliferation and immunoglobulin (Ig) production from three different Ig-secreting B-cell lines (U266, IgE; HSCE-, IgG; LA 350, IgM) were analyzed. Addition of IL-4 increased Ig production by the IgE- and IgG-secreting cell lines and this was paralleled by an inhibition of cellular proliferation. In contrast, the addition of IL-4 to LA 350 cells stimulated cellular proliferation but a decrease in IgM secretion. With each cell line, the IL-4 effects were both dose- and time-dependent and effects were maximal in the presence of 400 U/ml. Further analysis of the mechanism of IL-4 action on Ig production at the single B-cell level using an ELISA spot assay revealed a dualistic effect: increased Ig levels in culture supernatants reflected both an enhancement of single-cell Ig production as well as an increase in numbers of Ig-secreting B cells (IgE and IgG). In LA 350 cells the number of IgM-secreting B cells was suppressed as well as the amount of Ig released by single cells. These data on Ig production were supported by determination of mRNA amounts for the epsilon, gamma, and mu gene transcripts. Addition of IL-4 enhanced the levels of epsilon and gamma message in U266 and HSCE- cells, respectively, and reduced the amount of mu mRNA in LA 350 cells. In the IgE- and IgG-secreting cell lines, the IL-4 effect also correlated with enhanced expression of IL-4 receptor (IL-4R) mRNA levels, whereas IL-4R mRNA levels were unchanged in IgM-producing cells after IL-4 treatment. Incubation of cells with IL-4 and interferon-gamma abolished the stimulatory activities of IL-4 on either cell proliferation (LA 350 cells) or Ig production (HSCE- and U266); but did not influence the inhibitory activities of IL-4 on the cell lines. The immunosuppressive drug cyclosporin A (CsA) inhibited both cell proliferation and Ig production in all three cell lines to a similar degree. Furthermore, in U266 and HSCE- cells, CsA inhibition could not be overcome by IL-4. These data support the conclusion that on Ig-secreting human B-cell lines, IL-4 regulates cell proliferation and Ig production in a reciprocal fashion.

Antibody-Producing Cells↗

PubMed2026

A single-nucleus transcriptome atlas of soybean anthers.

Anther development is crucial for plant sexual reproduction. However, a high-resolution, cell-type-specific transcriptomic atlas of this process is lacking for the legume crop soybean (Glycine max). Here, we construct a comprehensive transcriptional atlas of developing soybean anthers using single-nucleus RNA sequencing (snRNA-seq). We identify and characterize nine distinct cell types spanning both somatic and reproductive lineages. Our analysis reveals robust transcriptional continuity across anther developmental stages and dynamic reprogramming during key transitions. Notably, the shift from diploid meiocytes to haploid unicellular microspores is marked by the induction of previously inactive genes, despite an overall reduction in transcript abundance. Subsequently, within bicellular microspores, generative and vegetative cell lineages exhibit sharply divergent transcriptional programs: generative cells specialize in mRNA export and turnover, whereas vegetative cells up-regulate translational machinery. Evolutionary analysis further indicates that generative-cell-specific genes are subject to more relaxed purifying selection compared to those specific to vegetative cells. Functional validation using mutants generated by CRISPR/Cas9-mediated genome editing and EMS mutagenesis reveals the essential roles of OSD1A and PKSA in pollen development and fertility. This high-resolution atlas provides fundamental insights into the transcriptional regulation of soybean anther development and serves as a valuable resource for manipulating male fertility to advance hybrid breeding programs. The data are available at https://databases.genedenovo.com/pollen.

Glycine max↗

PubMed1992

Dopamine receptor subtypes colocalize in rat striatonigral neurons.

Dopaminergic neurons of the substantia nigra provide one of the major neuromodulatory inputs to the neostriatum. Recent in situ hybridization experiments have suggested that postsynaptic dopamine receptors are segregated in striatonigral and striatopallidal neurons. We have tested this hypothesis in acutely isolated, retrogradely labeled striatonigral neurons by examining the neuromodulatory effects of selective dopaminergic agonists on Na currents and by probing single-cell antisense RNA populations with dopamine receptor cDNAs. In most of the neurons examined (20/31), the application of the D1 dopamine receptor agonist SKF 38393 reduced evoked whole-cell Na+ current. The D2 agonists quinpirole and bromocriptine had mixed effects; in most neurons (23/42), whole-cell Na+ currents were reduced, but in others (8/42), currents were increased. In cell-attached patch recordings, bath application of SKF 38393 decreased currents as in whole-cell recordings, whereas quinpirole consistently (6/10) enhanced currents--suggesting that D2-like receptors could act through membrane delimited and non-delimited pathways. Changes in evoked current were produced by modulation of peak conductance and modest shifts in the voltage dependence of steady-state inactivation. Antisense RNA probes of dopamine receptor cDNA Southern blots consistently (5/5) revealed the presence of D1, D2, and D3 receptor mRNA in single striatonigral neurons. These findings argue that, contrary to a strict receptor segregation hypothesis, many striatonigral neurons colocalize functional D1, D2, and D3 receptors.

2,3,4,5-Tetrahydro-7,8-dihydroxy-1-phenyl-1H-3-ben↗

PubMed2025

Enhancing and accelerating cell type deconvolution of large-scale spatial transcriptomics slices with dual network model.

MOTIVATION: Cell type deconvolution deciphers spatial distribution of mRNA transcripts at single cell level by integrating single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics data to infer mixture of cell types of spots in slices. Current algorithms are criticized for neglecting connection between scRNA-seq and spatial transcriptomics data, as well as time-consuming, hampering their application to large-scale datasets. RESULTS: In this study, we propose a joint learning nonnegative matrix factorization algorithm for fast cell type deconvolution (aka jMF2D), which integrates scRNA-seq and spatial transcriptomics data with network models. To bridge scRNA-seq and spatial transcriptomics data, jMF2D jointly learns cell type similarity network to enhance quality of signatures of cell types, thereby promoting accuracy and efficiency of deconvolution. Experiments demonstrate that jMF2D outperforms state-of-the-art baselines in terms of accuracy by saving about 90% running time on various datasets generated by different platforms. Furthermore, it can also facilitates the identification of spatial domains and bio-marker genes, providing an efficient and effective model for analyzing spatial transcriptomics data. AVAILABILITY AND IMPLEMENTATION: The software is coded using python, and is free available for academic https://github.com/xkmaxidian/jMF2D.

Algorithms↗

PubMed1990

Fluorescent in-situ hybridization to detect cellular RNA by flow cytometry and confocal microscopy.

A fluorescent in-situ hybridization procedure was developed which is suitable for detection of specific cellular RNA in cells fixed in suspension. The procedure was originally developed for analysis of single-cell suspensions by flow cytometry. The resulting fluorescent cells proved to have their 3-D morphology perfectly preserved. The spatial distribution of specific ribosomal RNA and messenger RNA could then be analysed by confocal microscopy of individual cells. In the hybridization procedure, biotinylated single-stranded RNA probes were used that were produced by transcription from cloned DNA fragments. Detection of poly-(A)+ RNA was performed with a poly-biotin-d(U)-tailed oligo-d(T) probe. Bound probe was detected using streptavidin-fluorescein isothiocyanate. For flow cytometry, nuclear DNA was counterstained with di-amidine-2-phenyl indol. Multi-parameter flow cytometry was used to quantify the fluorescence intensity, i.e. the hybridization signal, of thousands of cells. Confocal scanning microscopy on individual cells revealed the intracellular distribution of the target RNA. The distribution of ribosomal RNA and poly-(A)+ RNA mRNA in mouse bone marrow and the human leukaemia cell line HL60 cells was investigated. Ribosomal RNA was confined to the cytoplasm of the cells, although in many cells the nucleoli could also be distinguished. Poly-(A)+ RNA in HL60 cells was found both in the cytoplasm and nucleus. A granular cytoplasmic distribution was seen in part of these cells.

Animals↗

PubMed1991

Heterogeneity in lymphokine profiles of CD4+ and CD8+ T cells and clones activated in vivo and in vitro.

Analysis of lymphokine mRNA expression and protein secretion by about 100 short-term alloreactive T-cell clones revealed marked heterogeneity in the combinations of lymphokines synthesized. This finding argues against a simple model in which T cells express either an unrestricted (Th0) or a restricted (Th1 or Th2) lymphokine profile. Lymphokine titers appeared to be normally distributed, with the percentage of positive clones for any one product determined by the threshold of detection. Accordingly, the observation that CD4+ clones on average produced higher titers of most lymphokines than CD8+ clones indicated that apparent differences between the lymphokine profiles of these two subsets were quantitative rather than qualitative. Patterns of lymphokine gene expression detected in whole tissues or by analysis of single cells and clones were markedly influenced by in vivo priming. Relative levels of expression of IL-4, IFN-gamma and GM-CSF in lymphoid tissues differed in mice undergoing a GvHR or following contact sensitization with OX or immunization with KLH in adjuvant. Consistent with the finding that IL-4 was the major lymphokine mRNA detected in lymph nodes of KLH-primed mice, most short-term KLH-specific clones derived from such mice also expressed IL-4. A similar approach to the detection of lymphokine-secreting T-cell precursors activated late in L. major infection showed that most clones from the L. major-resistant strain, C57BL/6, secreted IFN-gamma without IL-4 whereas most clones from the susceptible strain, BALB/c, secreted IL-4 without IFN-gamma. Differences were also noted in anti-CD3-induced IL-3 production at the single-cell level between CD8+ cells activated in the GvHR or against a tumor allograft. Con A-induced, filler cell-dependent cloning of CD4+ T cells from unprimed mice gave rise both to IFN-gamma-producing and to IL-4-producing clones. A requirement for an undefined, filler cell-dependent signal for development of IL-4-secreting clones was suggested by the finding that clones of normal CD4+ and CD8+ T cells activated in an anti-CD3-induced, filler cell-free system exclusively produced IFN-gamma and IL-3 without detectable IL-4 or IL-6. With a view to developing a single-cell approach to the analysis of lymphokine profiles of in vivo-activated T cells, sensitive assays for IL-3 and other lymphokines were used to measure secreting cells activated in the GvHR or against a tumor allograft.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗

PubMed2024

Identification of key immune-related genes and potential therapeutic drugs in diabetic nephropathy based on machine learning algorithms.

BACKGROUND: Diabetic nephropathy (DN) is a major contributor to chronic kidney disease. This study aims to identify immune biomarkers and potential therapeutic drugs in DN. METHODS: We analyzed two DN microarray datasets (GSE96804 and GSE30528) for differentially expressed genes (DEGs) using the Limma package, overlapping them with immune-related genes from ImmPort and InnateDB. LASSO regression, SVM-RFE, and random forest analysis identified four hub genes (EGF, PLTP, RGS2, PTGDS) as proficient predictors of DN. The model achieved an AUC of 0.995 and was validated on GSE142025. Single-cell RNA data (GSE183276) revealed increased hub gene expression in epithelial cells. CIBERSORT analysis showed differences in immune cell proportions between DN patients and controls, with the hub genes correlating positively with neutrophil infiltration. Molecular docking identified potential drugs: cysteamine, eltrombopag, and DMSO. And qPCR and western blot assays were used to confirm the expressions of the four hub genes. RESULTS: Analysis found 95 and 88 distinctively expressed immune genes in the two DN datasets, with 14 consistently differentially expressed immune-related genes. After machine learning algorithms, EGF, PLTP, RGS2, PTGDS were identified as the immune-related hub genes associated with DN. In addition, the mRNA and protein levels of them were obviously elevated in HK-2 cells treated with glucose for 24 h, as well as their mRNA expressions in kidney tissues of mice with DN. CONCLUSION: This study identified 4 hub immune-related genes (EGF, PLTP, RGS2, PTGDS), as well as their expression profiles and the correlation with immune cell infiltration in DN.

Diabetic Nephropathies↗

PubMed2025

Targeting RECQL4 in hepatocellular carcinoma: from prognosis to therapeutic potential.

OBJECTIVE: The aim of this study is to assess the clinical utility of RecQ Like Helicase 4 (RECQL4) as a prognostic marker in hepatocellular carcinoma (HCC) and investigate its associations with various biological processes, angiogenesis-related factors, immune cell infiltration, immune checkpoints, and drug sensitivity. METHODS: RECQL4 expression was analyzed across a range of cancer types utilizing data from the TCGA database. Disparities in RECQL4 expression levels between normal and malignant tissues were evaluated, alongside an analysis of progression-free interval (PFI), disease-specific survival (DSS), and overall survival (OS) curves. Exploration of pertinent pathways, immune cell infiltration, single-cell RNA-seq data, and drug sensitivity was conducted employing The Cancer Genome Atlas (TCGA) and Tumor Immune Single-Cell Hub (TISCH) databases. Furthermore, validation of in-silico results was validated through qPCR, Western blotting, CCK-8 assay, EdU assay, clonogenic assay, wound-healing assay, and transwell assay. RESULTS: In HCC, RECQL4 was highly expressed and associated with poorer prognosis (p < 0.05). It positively correlated with pathways related to MYC targets, DNA replication, PI3K/AKT/mTOR signaling, DNA repair mechanisms, and the G2/M checkpoint (R > 0.24, p < 0.001). RECQL4 also showed significant correlations with angiogenesis-related genes, including PTK2 (R > 0.4, p < 0.05), suggesting a potential role in angiogenesis regulation. Immune analysis indicated that RECQL4 was associated with immune cell types such as T helper 2 cells, NK CD56bright cells, and follicular helper T cells, suggesting a positive relationship with their infiltration. High RECQL4 expression was also linked to increased sensitivity to drugs including Sorafenib, 5-Fluorouracil, Cisplatin, and Doxorubicin. Cellular experiments showed that RECQL4 expression at the mRNA and protein levels were significantly higher in HCC cell lines Hep3B and Huh7 compared to the normal liver cell line MHA. Moreover, RECQL4 knockdown resulted in reduced proliferation and migration in HCC cell lines (p < 0.05). CONCLUSIONS: RECQL4 shows promise as a biomarker for predicting recurrence and survival in HCC and may affect angiogenesis regulation. Its expression also appears to impact sensitivity to drugs such as Sorafenib, 5-Fluorouracil, Cisplatin, and Doxorubicin. Furthermore, silencing RECQL4 significantly inhibits HCC cell line proliferation and migration.

Humans↗

PubMed2025

Putative function and prognostic molecular marker of mast cells in colorectal cancer.

BACKGROUND: The increased demand for markers for colorectal cancer (CRC) highlights the importance of investigating immune cells involved in CRC progression. This study aims to dissect the mast cells in CRC, characterize the role of mast cells in CRC development, coordinate molecular communication between mast cells and malignant cells, and construct and validate a prognostic classification model based on mast cell markers. METHODS: Single-cell transcriptome data of CRC patients were extracted from GSE146771 for cell classification and annotation. The malignant cells were identified by copykat and the communication between mast cells and malignant cells was analyzed by CellChat. Least absolute shrinkage and selection operator (LASSO) regression analysis and Cox regression analysis of mast cell markers were performed in the TCGA-COAD cohort to construct a prognostic classification model. qRT-PCR was performed to detect the mRNA expression of the molecules in the classification model in P815 and MC-9 cells. The co-culture experiment of MC38 and P815 cells were performed in 12-well transwell dish. Wound healing assay and Transwell assay were performed to detect cell migration and invasion. RESULTS: 10,186 high-quality cells in GSE146771 were annotated to 9 cell types. Six markers in mast cells (HDC, GATA2, ASAH1, BTBD19, TIMP1, FAM110A) were selected to construct a classification model. The high-risk score defined showed high infiltration of immunosuppressive cells, including endothelial cells, CAFs, Tregs and high angiogenesis and epithelial-mesenchymal transition (EMT) activities. In the model, HDC were abnormally low expressed in P815 cells, while BTBD19, FAM110A, GATA2, ASAH1 and TIMP1 showed excessive expression in P815 cells. Knockdown of GATA2 in the co-culture system of P815 and MC38 cells blocked cell migration and invasion. CONCLUSION: This study identified the cell types within CRC, elaborated the cellular functions of mast cells in CRC development and their molecular communication to coordinate malignant cells, and highlighted the molecular components and biological features that constitute promising prognostic classification model.

Mast Cells↗

PubMed2026

NPLOC4 Constructs Tumor Immunosuppressive Microenvironment in Pan-cancer and Hepatocellular Carcinoma.

INTRODUCTION: NPLOC4 (nuclear protein localization 4 homolog) is mainly involved in DNA damage, cell cycle, and ubiquitination promotion. Nonetheless, the role of NPLOC4 in the tumor immune microenvironment (TIME) and its potential as a promising tumor therapeutic target remains unclear. METHODS: Therefore, analyses of NPLOC4 mRNA and protein expression, RNA subcellular localization, and patient prognosis associated with NPLOC4 expression were conducted across multiple tumor types. Additionally, the correlations between NPLOC4 and immune cells, non-immune cells, and immune molecules within the tumor immune microenvironment (TIME) were investigated. These analyses utilized data from various public resources, including the Genotype-Tissue Expression (GTEx) project, The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), The Human Protein Atlas (HPA), Clinical Proteomic Tumor Analysis Consortium (CPTAC), TIMER2.0, KM-Plotter, The University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN), and Tumor Immune Single-cell Hub 2 (TISCH2). Subsequently, we utilized hepatocellular carcinoma (HCC) patients' cancer and adjacent tissues plus tumor cell lines to verify the differential RNA and protein expression of NPLOC4 via qRT-PCR and immunohistochemistry (IHC). Then, the relationship of NPLOC4 expression level with immune infiltration score, infiltration of effector immune cells, suppressive immune cells, and several vital immune checkpoints was analyzed in HCC immune microenvironment. Furthermore, the distribution of expression of NPLOC4 in various cells in the HCC microenvironment was determined through single-cell sequencing analysis. RESULTS: We discovered that NPLOC4 was up-regulated in a variety of tumors and was correlated with poor prognosis. NPLOC4 not only had the potential as a tumor prognostic marker and therapeutic target but also was strongly linked to immune cells, immune checkpoints, and immune-related molecules and pathways in HCC immune microenvironment. CONCLUSION: In summary, NPLOC4 may serve as a promising target for immunotherapy.

Humans↗

PubMed2026

Placenta-derived Exosomes Mitigate Hypoxia-Induced Trophoblast Apoptosis and Inflammatory Progression via SASH1.

SASH1 is a signal adaptor protein involved in cell growth, apoptosis, and immune regulation, and has been increasingly studied in tumor and immune cells. Emerging evidence suggests that SASH1 plays an important role in inflammatory responses and cellular homeostasis, processes that are closely associated with the development of PE. This study aimed to determine whether SASH1 contributes to trophoblast apoptosis and inflammatory responses in PE and whether P-EXOS exerts protective effects through SASH1 regulation. In this study, three PE-related transcriptomic datasets (GSE75010, GSE10588, and GSE60438) were analyzed to identify shared differentially expressed genes (DEGs), followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Machine learning algorithms were further applied to screen key candidate genes, and single-cell RNA sequencing data were used to characterize cellular heterogeneity in placental tissue and to determine cell type-specific expression patterns. SASH1 was identified as a consensus candidate gene and was significantly upregulated in trophoblast cells from PE samples. In vitro, a hypoxia-treated HTR-8/SVneo trophoblast cell model was established, combined with SASH1 knockdown, SASH1 overexpression, and co-culture with P-EXOS. Functional experiments showed that knockdown of SASH1 significantly suppressed hypoxia-induced trophoblast apoptosis and reduced the secretion of pro-inflammatory cytokines, including IL-6, IL-1β, and TNF-α, whereas SASH1 overexpression promoted apoptosis and inflammatory responses. In addition, P-EXOS treatment markedly reduced SASH1 expression at both mRNA and protein levels and attenuated hypoxia-induced trophoblast injury, while SASH1 overexpression largely abolished these protective effects. Taken together, these findings indicate that SASH1 plays a critical role in trophoblast apoptosis and inflammatory responses in PE. P-EXOS may alleviate hypoxia-induced trophoblastic injury by suppressing SASH1 expression, providing new insights into the molecular mechanisms and potential therapeutic targets for PE.

Trophoblasts↗