Search Results (722)

Glioblastoma (GBM) is an extremely aggressive and incurable primary tumor of the brain. GBM is characterized by interpatient and intratumoral heterogeneity, making this cancer particularly resistant to therapy and likely to recur. Mapping the complex dynamics that underpin the development and evolution of gliomas with human-based in vitro models is difficult. This study aimed to generate 3D glioma patient-derived tumor constructs (PTCs) using a clinically relevant, Matrigel-free, hyaluronic acid system, evaluate their suitability in drug screening assays, and determine the stability of their genetic profiles compared to originating tumors. In this study, we utilized a synthetically modified hyaluronic acid and gelatin hydrogel system to generate tumor constructs containing cells from clinical glioma biospecimens. PTCs were characterized phenotypically, after which they were deployed in chemotherapy drug screens using temozolomide (TMZ) and a P53 activator compound. Drug responses of these 3D cultures were compared with 2D cultures, as well as PTCs that were generated after passaging in 2D. RNA sequencing was used to evaluate genetic parity between PTCs or 2D cultures with originating tumor tissues, using The Cancer Genome Atlas (TCGA) GBM subpopulations for subcategorizing. PTCs were created successfully from five World Health Organization (WHO) grade 4, two grade 3, and two grade 2 gliomas. PTCs were maintained with high viability. Chemotherapy drug screens demonstrated that expected TMZ responses were observed for Isocitrate dehydrogenase (IDH) mutant diffuse gliomas while drug response was variable for IDH wildtype GBM PTCs. PTCs demonstrated stable drug response over time, while 2D passaging resulted in significant shifts in drug sensitivity. RNA sequencing revealed maintenance of subpopulation signatures for PTCs which clustered with their originating patient tumor tissue. In contrast, 2D cultures largely clustered together regardless of the patient. Our PTC approach utilizes a defined hydrogel biomaterial system that maintains the genotypic and drug response characteristics of patient tumors making this an ideal ex vivo model for translational applications. Full article

Background: Ovarian cancer (OC) remains the most common cause of gynecological cancer-related death, and about 70% of these deaths are from advanced high-grade serous ovarian cancer (HGSOC). Cysteine-rich secretory protein 3 (CRISP3) is related to various human diseases; however, the roles and mechanisms of CRISP3 in HGSOC remain unclear. Methods: The clinical significance of CRISP3 in patients with OC was analyzed using the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases. CRISP3 expression in OC tissues was validated by RNA-sequencing (RNA-seq), quantitative PCR, and immunohistochemistry. Furthermore, we explored the effect of CRISP3 expression modulation on the biological behavior of HGSOC through CCK-8, EdU, and Transwell assays in vitro, and the differences in CRISP3 during the progression of HGSOC in vivo. We utilized RNA-seq, GSEA and Western blotting to detect CRISP3’s regulatory mechanisms. Finally, we employed data from the IMvigor210 cohort and TCGA to assess the correlation of CRISP3 with clinical response to immunotherapy, and the landscape of immune cell infiltration. Results: CRISP3 expression was markedly reduced in HGSOC. In vitro studies demonstrated that CRISP3 knockdown significantly enhanced proliferation, migration, and invasion of HGSOC cells, whereas its overexpression suppressed these malignant phenotypes. Moreover, CRISP3 expression was found to be downregulated during OC progression in vivo. Mechanistically, CRISP3 acted as a tumor suppressor through the PI3K/AKT signaling pathway to inhibit the progression and metastasis of HGSOC. Additionally, we observed an association between CRISP3 expression and CD8⁺ T cell, macrophage, neutrophil and Th1 cell infiltration. Conclusions: We demonstrate that CRISP3 suppresses tumorigenesis in HGSOC by regulating the PI3K/AKT pathway, and that alterations in its expression correlate with disease progression, supporting its utility as a biomarker. Full article

Fibrosis is a hallmark of the tumor microenvironment in many solid cancers, driving tumor progression, immune evasion, and treatment resistance; however, the molecular and cellular mechanisms underlying fibrogenesis—particularly stromal–immune crosstalk across organs—remain incompletely understood, compounded by organ-specific heterogeneity and a lack of reliable immune-related biomarkers. To address this, we performed an integrative single-cell RNA sequencing (scRNA-seq) analysis of fibrotic tissues from four major organs—liver, lung, heart, and kidney—alongside non-fibrotic controls, applying unsupervised clustering, trajectory inference, cell–cell communication modeling, and gene set variation analysis (GSVA) to map the fibro-immune landscape. Our analysis revealed both conserved and organ-specific features: fibroblasts were the dominant extracellular matrix (ECM)-producing cells in liver and lung, whereas endothelial-derived stromal populations prevailed in heart and kidney. Immune profiling uncovered distinct infiltration patterns—macrophages displayed organ-specific polarization states; T cells were enriched for tissue-resident subsets in lung and mucosal-associated invariant T (MAIT) cells in liver; and B cells exhibited marked heterogeneity, including a pathogenic interferon-responsive subset prominent in pulmonary fibrosis. GSVA further identified divergent signaling programs across organs and lineages, including TGF-β/TNF-α in the heart, NOTCH/mTOR in the kidney, glycolysis/ROS in the lung, and KRAS/interferon pathways in the liver. Cell–cell communication analysis highlighted robust crosstalk between macrophages, T/B cells, and stromal cells mediated by collagen, laminin, and CXCL signaling axes. Together, this cross-organ atlas delineates a highly heterogeneous fibro-immune ecosystem in human fibrotic diseases, revealing shared mechanisms alongside organ-specific regulatory networks, with immediate translational implications for precision anti-fibrotic therapy, immunomodulatory drug repurposing, and the development of context-specific biomarkers for clinical stratification and therapeutic monitoring. Full article

In recent years, several studies have highlighted the ability of malignant cells to use acetate as an alternative energy and biosynthetic source to glucose. In this context, the present study aimed at characterizing the expression profile of genes involved in acetate metabolism in thyroid carcinomas. To this end, we analyzed molecular and clinical data from 496 papillary thyroid cancers (PTCs) and 59 normal thyroid tissues from The Cancer Genome Atlas (TGCA). In addition, we examined 57 PTCs and matched normal tissues, and six anaplastic thyroid carcinomas (ATCs) collected in our institutions, using real time RT-PCR. The results show a downregulation of ACSS1, ACSS2, ACACB, PDHA1, SLC16A3 and SLC16A7 genes in PTCs compared with normal tissues, some of which were significantly lower in BRAF-mutated tumors, the more aggressive tall cell variant, and larger and/or metastatic PTCs. Overall, these findings point to a reduction in mitochondrial oxidative pathways that was more evident in advanced or aggressive disease forms. In ATCs, ACSS2 was the only upregulated gene, suggesting further tumor adaptation to the metabolic stress of rapidly growing cancers. In conclusion, our study demonstrates a dysregulated expression pattern of multiple genes involved in acetate metabolism, which could be exploited for the development of new therapeutic strategies. Full article

Breast cancer (BC) is a global health problem. BC is a biologically heterogeneous disease in which novel immunotherapeutic strategies are needed, particularly in the metastatic setting. The NKG2D/NKG2D ligand (NKG2DL) axis is a key component of innate antitumor immunity and represents a potential therapeutic target, but its relevance in BC has not been fully characterized. We performed an in silico analysis of NKG2DL expression in BC cell lines, healthy breast tissue, and tumor samples using publicly available transcriptomic databases (DSMZCellDive, ShinyTHOR, GTEx, TCGA, Human Protein Atlas), complemented by survival analyses from TCGA and KMPlot and a narrative review of the literature. NKG2DL transcripts were consistently expressed in BC cell lines and tumor tissues, with higher expression observed in ductal histology, higher tumor stage, and basal molecular subtype. Survival analyses showed heterogeneous and generally weak associations between individual NKG2DLs and clinical outcomes. In silico proteomics data are scarce, but the narrative review showed that NKG2DLs are expressed by immunohistochemistry in tumor tissues but absent in surrounding healthy tissues. The literature review also revealed concomitant dysfunction of NKG2D+ effector cells due to multiple resistance mechanisms (including ligand shedding). We also review potential therapeutic approaches. Full article

Lung adenocarcinoma (LUAD) remains a leading cause of cancer-related mortality worldwide, highlighting the urgent need to identify novel prognostic biomarkers and therapeutic targets. Kinesin Family Member 18B (KIF18B) is implicated in mitosis, yet its precise role in LUAD pathogenesis remains poorly defined. This study investigates the oncogenic and therapeutic role of KIF18B in LUAD. Integrated analysis of The Cancer Genome Atlas Program (TCGA) and Gene Expression Omnibus (GEO) datasets revealed that KIF18B is significantly upregulated in LUAD tissues, with its elevated expression strongly associated with an advanced pathological stage, high grade, and poor patient survival. Single-cell sequencing data analysis further indicated that KIF18B expression in LUAD is closely linked to key malignant processes, including cell cycle progression, proliferation, migration, and epithelial–mesenchymal transition (EMT). Functional experiments demonstrated that KIF18B knockdown markedly suppressed LUAD cell proliferation, migration, and invasion in vitro and inhibited tumor growth in vivo. Mechanistically, transcriptomic and pathway analyses revealed that KIF18B depletion downregulates Early 2 Factor (E2F) target genes. Luciferase reporter assays confirmed diminished E2F reporter activity as well as E2F2 promoter activity upon KIF18B silencing, while overexpression of E2F1, E2F2, or E2F3 rescued the inhibited proliferative phenotypes induced by KIF18B loss. Collectively, our findings establish KIF18B as an essential driver of LUAD progression that acts through the E2F transcriptional network, nominating it as a promising diagnostic and therapeutic target. Full article

Alzheimer’s disease (AD) is a major public health issue, and the role of peripheral immunity in its pathogenesis remains poorly understood. This study conducted a comprehensive reanalysis of publicly available single-cell transcriptomic and chromatin accessibility datasets to investigate immune cell dynamics in AD. By integrating data from cerebrospinal fluid and peripheral blood samples, we constructed a cross-tissue immune cell atlas. Based on Monocle3 pseudotemporal trajectory analysis, we propose the hypothesis that CD8⁺ TEMRA cells in the cerebrospinal fluid may originate from blood-derived CD8⁺ TPex cells. Furthermore, cell–cell communication analysis revealed a potential interaction mechanism whereby CD8⁺ TPex cells secrete MIF signals to activate monocytes, prompting them to release increased levels of inflammatory factors (IL1B) and adhesion molecules (ICAM1). These inflammatory factors collectively contribute to the disruption of the blood–brain barrier, thereby facilitating immune cell infiltration. Our reanalysis provides a novel interpretation of existing data, establishes a regulatory framework for understanding immune infiltration in AD. Full article

Mitochondrial succinate dehydrogenase subunits are differentially expressed in multiple tumor types, suggesting their role as a cancer type-dependent metabolic target. However, information on the expression of SDH subunits in breast cancer (BC), particularly in South Asian populations, remains scarce. So, we analyze the expression profile of all four SDH subunits in breast cancer patients from Bangladesh. qRT-PCR was carried out to analyze the mRNA expression of four SDH subunits in Luminal A, Luminal B, Her2+, and triple-negative breast cancer subtypes and the results were compared with The Cancer Genome Atlas (TCGA) database. All four succinate dehydrogenase subunits were significantly upregulated in tumor tissues when compared to controls and showed an alignment with the TCGA except SDHD, which was significantly downregulated in TCGA. Subtype-specific analysis demonstrated differential expression patterns. SDHD upregulation has also been connected to worse outcomes for patients which indicates its role in cancer progression. Furthermore, we found a significant upregulation of METTL3 in our patient cohort. Taken together, the elevated SDHD and METTL3 expression suggests a potential epigenetic mechanism-driven SDHD activation, highlighting its previously unreported role in breast cancer biology and revealing a distinct pattern of SDH dysregulation in the Bangladeshi breast cancer population. Full article

The yak (Bos grunniens) thrives under chronic hypoxia and cold on the Qinghai–Tibet Plateau, yet a cross-tissue view of post-transcriptional regulation in this species remains limited. Here, we integrated multi-tissue RNA-seq and miRNA-seq data (tissues pooled from three Maiwa yaks) to construct and compare tissue-specific competing endogenous RNA (ceRNA) networks, while explicitly addressing a major source of false positives in ceRNA inference—misclassified lncRNA candidates with translational signatures. We cataloged 10,037 high-confidence lncRNAs (9360 non-redundant), 234 circRNAs, and 1030 miRNAs across six tissues. We then used Ribo-seq as an orthogonal quality-control layer to remove lncRNA candidates showing clear ribosome-association signals prior to network construction. Using a shared-target strategy (7mer-m8 seed matches; a ceRNA edge required ≥5 shared miRNAs), we assembled ceRNA networks for liver, lung, spleen, testis, and small intestine; skeletal muscle was excluded owing to insufficient Ribo-seq support for consistent filtering. Network topology varied substantially across tissues, with the testis network exhibiting the highest connectivity. ceRNA edges showed minimal overlap between tissues, indicating strong tissue dependence, whereas miRNA load/use profiles were moderately concordant, supporting a hierarchical conserved core—variable periphery organization. Importantly, the Ribo-seq–filtered lncRNA set provides a separate pool of ribosome-associated candidates for targeted follow-up, although ribosome association alone does not establish stable micropeptide production. Together, our results deliver a multi-tissue ceRNA resource and a reproducible, evidence-aware workflow for prioritizing candidate regulators while reducing annotation-driven false positives in yak. Full article

Migraine is a complex neurovascular disorder in which immune signaling intersects with vascular and neural circuits, yet the tissue and cell-type context of common genetic risk remains incompletely defined. We integrated large-scale migraine genome-wide association study (GWAS) summary statistics with Genotype-Tissue Expression (GTEx) v8 expression and splicing quantitative trait loci (eQTLs and sQTLs), Bayesian co-localization, single-cell RNA sequencing of peripheral blood mononuclear cells (PBMCs) from migraine cases and controls, a healthy single-cell multi-omics atlas (assay for transposase-accessible chromatin (ATAC) plus RNA), high-dimensional weighted gene co-expression network analysis (hdWGCNA), and embryo-level spatial transcriptomics. Genetic signals were enriched in peripheral arteries, heart, and blood, and gene-level enrichment highlighted mucosal–smooth muscle organs including the bladder and the cervix endocervix. Cell-type prioritization consistently implicated endothelial and vascular smooth muscle lineages, with additional support for inhibitory interneurons and bladder epithelium. In PBMC T cells, co-expression modules capturing cytotoxic/activation and T-cell receptor signaling programs contained migraine-prioritized genes, including PTK2B, nominating immune activation circuitry as a component of genetic susceptibility. Spatial projection further localized risk concordance to craniofacial/meningeal interfaces and visceral smooth muscle–mucosal structures. Together, these analyses delineate a systemic neuroimmune–vascular architecture for migraine and provide genetically anchored candidate pathways and targets for mechanistic and therapeutic follow-up. Full article

RNA sequencing (scRNA-seq) has emerged as a transformative technology for dissecting cellular heterogeneity and immune complexity in livestock species. This review summarizes recent advances in the application of single-cell transcriptomics to livestock health, with a particular focus on immune system organization and host–pathogen interactions in cattle, pigs, poultry, and small ruminants. We highlight the development of large-scale, multi-tissue cell atlases—such as the Cattle Cell Atlas and resources generated through the Farm Animal Genotype-Tissue Expression (FarmGTEx) consortium—that provide foundational reference frameworks for livestock genomics. These atlases have enabled the identification of tissue- and species-specific immune cell populations, clarified cellular tropism of major bacterial and viral pathogens, and revealed distinctive immunological features, including the prominent role of γδ T cells in ruminant immunity. We discuss how single-cell immune receptor sequencing has advanced monoclonal antibody discovery and informed rational vaccine design. Key technical and analytical challenges, including incomplete genome annotations, tissue processing constraints, and cross-platform data integration, are critically assessed. Finally, we outline future directions integrating spatial transcriptomics and multi-omics approaches to further resolve immune function within tissue contexts. Collectively, these advances position single-cell transcriptomics as a central framework for improving disease resistance, vaccine efficacy, and translational research in livestock health. Full article

Background: Several studies have attempted to identify the initiating drivers of small intestinal neuroendocrine tumor (SI-NET) development and the molecular mechanisms underlying their progression and metastatic spread. Previous gene expression studies have used bulk microarrays or RNA sequencing to compare tumor tissue with normal intestinal mucosa. However, the intestine comprises multiple distinct cell types, and bulk analyses are limited by this cellular heterogeneity, which can confound tumor-specific signals. Methods: We performed single-cell RNA sequencing on primary SI-NETs and paired normal mucosa from two patients to directly compare tumor cells with their cells of origin, the enterochromaffin (EC) cells. To minimize type I errors, we applied a two-step validation strategy by overlapping differentially expressed genes with an external single-cell dataset and cross-referencing candidate genes for enteroendocrine expression in the Human Protein Atlas. Results: For further distinction and characterization, ECs were subdivided into serotonergic and non-serotonergic clusters. This analysis revealed that the SI-NET cells are transcriptionally more similar to serotonergic ECs, consistent with serum metabolite profiles derived from clinical parameters. Our analyses uncovered a loss-of-expression program characterized by regulators of epithelial differentiation and in parallel, a gain-of-expression program displayed neuronal signaling gene induction, implicating functional reprogramming toward neuronal-like properties. Together, these specific losses and gains suggest that our patient-derived SI-NETs undergo adaptation through both loss of enteroendocrine functions and acquisition of neurobiological-promoting signaling pathways. Conclusions: These findings nominate candidate drivers for further functional validation and highlight potential therapeutic strategies in our patient cohort, including restoring suppressed Notch signaling and targeting aberrant neuronal signaling networks. However, even with a two-step validation procedure, the modest cohort size limits statistical power and generalizability, particularly for the proposed association to a serotonergic phenotype. Larger, multi-patient single-cell studies are required to confirm these mechanisms and establish their clinical relevance. Full article

Melanoma-associated antigens (MAGEs) are cancer-testis antigens (CTAs) aberrantly expressed in multiple cancer types, including hepatocellular carcinoma (HCC), and associated with aggressive phenotypes. Although MAGE proteins are widely studied as cancer immunotherapy targets, their roles in HCC and the regulation of their expression during liver pathogenesis in mouse models, including dietary effects, remain poorly understood. We analyzed Mage gene expression in liver tissues from 78 C3H/HeJ mice with chronic diet-induced obesity. While type I MAGE genes are frequently expressed in human HCC, we found no evidence of their expression in mouse liver tumors, suggesting species-specific regulation. In contrast, type II Maged2, previously reported to be upregulated in human HCC, was significantly increased in mouse liver tumors. Analysis of human HCC samples from The Cancer Genome Atlas (TCGA) database confirmed MAGED2 upregulation and its association with patient prognosis. Together, these findings identify MAGED2 as a conserved marker of liver cancer in both humans and mice and emphasize the importance of cross-species comparative approaches for selecting appropriate models and accurately interpreting results, particularly for CTAs, which often evolved recently and in a species-specific manner. Full article

Approximately 50% of individuals diagnosed with Stage I liver cancer live beyond four years; however, a small subset of Stage I patients die within the first year. A prognostic biomarker panel that can identify high-risk Stage I patients may be extremely valuable. In this study, we used the Long–Evans Cinnamon (LEC) rat model of Wilson’s Disease and hepatocellular carcinoma (HCC), along with data from The Cancer Genome Atlas (TCGA) human database, to create a novel biomarker panel. We generated and analyzed a rat microarray gene expression profile by comparing liver tumor tissues with adjacent normal tissues from the same animals, covering approximately 30,000 genes. The microarray results were translated into a five-gene panel associated with 1-year survival in Stage I liver cancer patients based on TCGA data, in combination with machine learning and bioinformatics approaches. The panel was internally validated following the “REporting recommendations for Tumor MARKer prognostic studies (REMARK)” guidelines. With no existing Stage-I-specific prognostic tools, a biomarker panel associated with 1-year survival in patients with Stage I liver cancer is a potential candidate for rigorous external validation. Full article

The mechanisms driving the crown-to-root transition in tooth development remain incompletely understood, particularly the functional heterogeneity of dental epithelium. To address this gap and deconstruct this complexity, we aimed to analyze dental epithelial heterogeneity during this critical transition and to identify subpopulation-specific programs relevant to root development. We therefore established a single-cell transcriptomic atlas of the mouse molar at postnatal days 3.5 and 7.5, integrating 30,951 cells to profile the pan-tissue landscape and performing an in-depth analysis of 4323 dental epithelial cells. Our results reveal that the dental epithelium is composed of seven distinct subpopulations with a clear lineage hierarchy, originating from multipotent progenitors and bifurcating into self-renewing and differentiating trajectories. The identified particular functions of each subcluster include the following: structural maintaining progenitor that inhibits mineralization (Cluster 4), proliferation driver (Cluster 0), key signaling center (Cluster 1), terminally differentiated executing enamel formation (Cluster 3 and Cluster 6), and extracellular matrix-organizing hub (Cluster 5), communicating extensively via the Bmp, Tgf-β, and Wnt pathways. Our work defines dental epithelium as a dynamic and heterogeneous orchestrator of root morphogenesis, providing a foundational framework for understanding developmental biology and pioneering future regenerative strategies based on precise epithelial cell functions. Full article