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Eleutheroside A inhibits PI3K/AKT1/mTOR-mediated glycolysis in MDSCs to alleviate their immunosuppressive function in gastric cancer.
BACKGROUND: An immune-suppressive tumor microenvironment (TME) that encourages tumor growth is a hallmark of gastric cancer (GC), which is implicated in the development, metastasis, and unfavorable prognosis of GC. Acanthopanax senticosus (Rupr.&Maxim.) Harms (AS), also called Siberian Ginseng (Chinese: Ci wu jia), is a commonly used traditional Chinese herbal medicine with immune-enhancing, anti-tumor, anti-fatigue, neuroregulatory, blood circulation-improving, and antioxidant properties. Recently, it has also been demonstrated to improve anti-tumor immunity in GC. Eleutheroside A (EA), one of the primary bioactive saponins of AS, has immunoregulatory functions. Given the immunomodulatory and anti-tumor effects of EA, it is crucial to investigate its regulatory impact on the immune landscape of GC. MATERIALS AND METHODS: To determine the effects of EA on immune responses in GC, a subcutaneous GC mouse model was established. Tumor growth, body weight changes, and immune responses in the mice treated with EA were measured. The proportion of CD4+T, CD8+T, B cells, NK cells, TAMs, DCs and MDSCs in the spleens were analyzed using flow cytometry. MDSCs and CD4+/CD8+ T cell infiltration in tumor tissue were analyzed using immunofluorescence. Bulk RNA sequencing (bulk RNA-seq) data from the Cancer Genome Atlas (TCGA) and two single-cell RNA sequencing (scRNA-seq) datasets (accession numbers GSE183904 and GSE150290) were used to examine changes in MDSCs and T cell infiltration within the TME of GC and to identify MDSCs-related targets. Network pharmacology analysis, protein-protein interaction (PPI) network analysis, dynamics simulations, molecular docking and surface plasmon resonance (SPR) were applied to explore the potential mechanisms underlying EA's intervention in MDSCs. Flow cytometry, qPCR, and western blotting and Seahorse assays were applied for analyzing MDSCs isolated from in vivo and in vitro-induced conditions, aiming to delineate the mechanism of EA on MDSCs glycolysis and immunosuppressive functions mediated by the PI3K/AKT1/mTOR signaling pathway. RESULTS: In vivo, EA treatment effectively suppressed GC tumor growth and progression in mice, reducing the prevalence of MDSCs and increasing CD4+/CD8+ T cell levels. In vitro, EA not only decreased the frequency of MDSCs but also alleviated their immune-suppressing capabilities on CD4+/CD8+ T cells. Network pharmacology, coupled with scRNA-seq analysis, dynamic simulations, and molecular docking studies, suggested that EA might modulate the PI3K/AKT1/mTOR signaling pathway to influence glycolysis in MDSCs. Surface plasmon resonance (SPR) analysis confirmed that EA directly interacts with AKT1. Further validation experiments revealed that in the GC TME, EA treatment decreased the expression of p-PI3K, p-AKT1, p-mTOR, HIF1α, as well as glycolytic genes and glycolytic activity in MDSCs. Additionally, EA led to the downregulation of p-STAT3 and its downstream immunosuppressive factors within these cells. Restoring AKT1 activation could reverse the inhibitory effects of EA on MDSCs glycolysis and the downregulation of immunosuppressive molecules. Moreover, HIF-1α inhibition abolished EA's inhibitory effects on MDSCs. CONCLUSION: EA can attenuate the immune-suppressive capacity of MDSCs in GC by inhibiting the PI3K/AKT1/mTOR pathway and suppressing HIF-1α-mediated glycolysis, thereby offering a novel therapeutic approach to targeting the immune-suppressive microenvironment in GC.
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Single-cell characterization of the human C2 dorsal root ganglion recovered from C1-2 arthrodesis surgery: implications for neck pain.
Neurons in the dorsal root ganglion (DRG) receive and transmit sensory information from the tissues they innervate and from the external environment. Upper cervical (C1-C2) DRGs are functionally unique as they receive input from the neck, head, and occipital cranial dura, the latter two of which are also innervated by the trigeminal ganglion (TG). The C2 DRG also plays an important role in neck pain, a common and disabling disorder that is poorly understood. Advanced transcriptomic approaches have significantly improved our ability to characterize RNA expression patterns at single-cell resolution in the DRG and TG, but no previous studies have characterized the C2 DRG. Our aim was to use single-nucleus and spatial transcriptomic approaches to create a molecular map of C2 DRGs from patients undergoing arthrodesis surgery with ganglionectomy. Patients with acute (<3 months) or chronic (≥3 months) neck pain were enrolled and completed patient-reported outcomes and quantitative sensory testing prior to surgery. C2 DRGs were characterized with bulk, single nucleus, and spatial RNA sequencing technologies from 22 patients. Through a comparative analysis to published datasets of the lumbar DRG and TG, neuronal clusters identified in both TG and DRG were identified in the C2 DRG. Therefore, our study definitively characterizes the molecular composition of human C2 neurons and establishes their similarity with unique characteristics of subsets of TG neurons. We identified differentially expressed genes in endothelial, fibroblast and myelinating Schwann cells associated with chronic pain, including FGFBP2, C8orf34 and EFNA1 which have been identified in previous genome and transcriptome wide association studies (GWAS/TWAS). Our work establishes an atlas of the human C2 DRG and identifies altered gene expression patterns associated with chronic neck pain. This work establishes a foundation for the exploration of painful disorders in humans affecting the cervical spine.
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Predicting breast cancer drug response using a multiple-layer cell line drug response network model.
BACKGROUND: Predicting patient drug response based on a patient's molecular profile is one of the key goals of precision medicine in breast cancer (BC). Multiple drug response prediction models have been developed to address this problem. However, most of them were developed to make sensitivity predictions for multiple single drugs within cell lines from various cancer types instead of a single cancer type, do not take into account drug properties, and have not been validated in cancer patient-derived data. Among the multi-omics data, gene expression profiles have been shown to be the most informative data for drug response prediction. However, these models were often developed with individual genes. Therefore, this study aimed to develop a drug response prediction model for BC using multiple data types from both cell lines and drugs. METHODS: We first collected the baseline gene expression profiles of 49 BC cell lines along with IC50 values for 220 drugs tested in these cell lines from Genomics of Drug Sensitivity in Cancer (GDSC). Using these data, we developed a multiple-layer cell line-drug response network (ML-CDN2) by integrating a one-layer cell line similarity network based on the pathway activity profiles and a three-layer drug similarity network based on the drug structures, targets, and pan-cancer IC50 profiles. We further used ML-CDN2 to predict the drug response for new BC cell lines or patient-derived samples. RESULTS: ML-CDN2 demonstrated a good predictive performance, with the Pearson correlation coefficient between the observed and predicted IC50 values for all GDSC cell line-drug pairs of 0.873. Also, ML-CDN2 showed a good performance when used to predict drug response in new BC cell lines from the Cancer Cell Line Encyclopedia (CCLE), with a Pearson correlation coefficient of 0.718. Moreover, we found that the cell line-derived ML-CDN2 model could be applied to predict drug response in the BC patient-derived samples from The Cancer Genome Atlas (TCGA). CONCLUSIONS: The ML-CDN2 model was built to predict BC drug response using comprehensive information from both cell lines and drugs. Compared with existing methods, it has the potential to predict the drug response for BC patient-derived samples.
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High-dimensional spatiotemporal single-cell atlas and 3D imaging of the bone marrow microenvironment during CML progression.
The bone marrow microenvironment (BMME) is essential for hematopoiesis and immunity, yet spatiotemporal single-cell analysis during leukemogenesis remains challenging. We characterized the BMME in femurs from wild-type and chronic myeloid leukemia (CML) mice at 7, 14, and 21 days after induction by highly multiplexed and 3-dimensional (3D) microscopy. Using a 54-marker codetection by indexing panel, we profiled 2 033 725 cells in 55 regions of interest and identified 41 cell types. During CML progression, we observed myeloid and progenitor cell expansion, increased programmed death ligand 1-positive leukemic cells, programmed death 1 (PD-1) upregulation on CD4+ and CD8+ T cells, and a profound loss of B cells, plasma cells, and bone cells. Advanced CML exhibited a striking expansion of immature, pericyte-deficient vasculature that disrupted vascular niches and impaired hematopoietic stem/progenitor cell positioning. Spatial mapping revealed leukemia-specific cellular neighborhoods enriched in PD-1+CD8+ T cells, suggesting localized immune exhaustion. Early CML showed increased contacts between plasmacytoid dendritic cells and megakaryocytes (MKs), whereas advanced CML featured heightened MK emperipolesis of nonleukemic granulocytes. MKs were morphologically irregular in CML mice and patient bone marrow biopsies. In contrast, in mice with acute myeloid leukemia, vasculature and MKs were reduced, whereas the remaining MKs retained normal morphology. Laser-capture microdissected MKs from patients with newly diagnosed CML had reduced cytoskeleton gene expression, which was reversed in advanced cases treated with tyrosine kinase inhibitors. 3D imaging revealed vascular disorganization and depleted MKs in the diaphysis, underscoring region-specific pathology. Together, this study provides a spatiotemporal single-cell atlas of the BMME during leukemic progression, showing how leukemic cells reprogram it to support their expansion and immune evasion.
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Evolution of neuronal cell classes and types in the vertebrate retina.
The basic plan of the retina is conserved across vertebrates, yet species differ profoundly in their visual needs (Baden et al., 2020). One might expect that retinal cell types evolved to accommodate these varied needs, but this has not been systematically studied. Here, we generated and integrated single-cell transcriptomic atlases of the retina from 17 species: humans, two non-human primates, four rodents, three ungulates, opossum, ferret, tree shrew, a teleost fish, a bird, a reptile and a lamprey. Molecular conservation of the six retinal cell classes (photoreceptors, horizontal cells, bipolar cells, amacrine cells, retinal ganglion cells [RGCs] and Muller glia) is striking, with transcriptomic differences across species correlated with evolutionary distance. Major subclasses are also conserved, whereas variation among types within classes or subclasses is more pronounced. However, an integrative analysis revealed that numerous types are shared across species based on conserved gene expression programs that likely trace back to the common ancestor of jawed vertebrates. The degree of variation among types increases from the outer retina (photoreceptors) to the inner retina (RGCs), suggesting that evolution acts preferentially to shape the retinal output. Finally, we identified mammalian orthologs of midget RGCs, which comprise >80% of RGCs in the human retina, subserve high-acuity vision, and were believed to be primate-specific (Berson, 2008); in contrast, the mouse orthologs comprise <2% of mouse RGCs. Projections both primate and mouse orthologous types are overrepresented in the thalamus, which supplies the primary visual cortex. We suggest that midget RGCs are not primate innovations, but descendants of evolutionarily ancient types that decreased in size and increased in number as primates evolved, thereby facilitating high visual acuity and increased cortical processing of visual information.
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A novel risk score model of lactate metabolism for predicting outcomes and immune signatures in acute myeloid leukemia.
Acute myeloid leukemia (AML) is a malignant tumor with high recurrence and refractory rates and low survival rates. Increased glycolysis is characteristic of metabolism in AML blast cells and is also associated with chemotherapy resistance. The purpose of this study was to use gene expression and clinical information from The Cancer Genome Atlas (TCGA) database to identify subtypes of AML associated with lactate metabolism. Two different subtypes linked to lactate metabolism, each with specific immunological features and consequences for prognosis, were identified in this study. Using the TCGA and International Cancer Genome Consortium (GEO) cohorts, a prognostic model composed of genes (LMNA, RETN and HK1) for the prognostic value of the lactate metabolism-related risk score prognostic model was created and validated, suggesting possible therapeutic uses. Additionally, the diagnostic value of the prognostic model genes was explored. LMNA and HK1 were ultimately identified as hub genes, and their roles in AML were determined through immune infiltration, GeneMANIA, GSEA, methylation analysis and single-cell analysis. LMNA was upregulated in AML associating with a poor prognosis while HK1 was downregulated in AML associating with a favorable prognosis. The findings underscore the noteworthy impact of genes linked to lactate metabolism in AML and illustrate the possible therapeutic usefulness of the lactate metabolism-related risk score and the hub lactate metabolism-related genes in guiding AML patients' treatment choices.
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Identification of LIPH as an unfavorable biomarkers correlated with immune suppression or evasion in pancreatic cancer based on RNA-seq.
BACKGROUND: It is widely considered that pancreatic cancer (PC) is an immunosuppressive cancer. Immune-based therapies remain promising therapeutic strategies for PC. Overexpression of lipase H (LIPH) was reported to be related to immunity in cattle and has also been demonstrated to promote tumor progression in several tumors, but its role in pancreatic carcinogenesis remains unclear. Study on LIPH in PC might provide a new insight into the immunosuppression in PC. METHODS: The potential biological and clinical significance of LIPH was evaluated by bioinformatics analysis. We further investigated potential associations between the expression of LIPH and tumor immune infiltration using the CIBERSORT algorithm, the ESTIMAT algorithm, and single sample gene set enrichment analysis (ssGSEA). RESULTS: LIPH was significantly overexpressed in tumor tissues compared with normal tissues. LIPH overexpression correlated with tumor recurrence, advanced histologic grade, and poorer overall survival (OS). Four of the most common somatic mutation, including KRAS, TP53, CDKN2A, and SMAD4, in PC were all correlated with high LIPH expression. And high LIPH expression was significantly correlated with KRAS activation and SMAD4 inactivation. Besides, LIPH expression was involved in various biological pathways such as negative regulation of cell-cell adhesion, actin cytoskeleton, EMT, angiogenesis, and signaling by MST1. And LIPH overexpression caused high infiltration of TAMs, Treg cells, and Th2/Th1, but reduced the infiltration of CD8+ T cells and Th1 cells. CONCLUSIONS: Our findings demonstrated that LIPH correlated with immune suppression or evasion and may function as a novel unfavorable prognostic biomarker in PC.
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Multidimensional dissection of shared genetic susceptibility in ulcerative colitis and colorectal cancer: novel insights from integrative single-cell and multi-omics analysis.
BACKGROUND: Ulcerative colitis (UC) patients carry a 2.5-fold increased risk of colorectal cancer (CRC), yet the shared multi-scale genetic architecture remains poorly understood. We constructed an integrative framework across tissue, cellular, and variant levels to systematically dissect the pathogenic evolution of this comorbidity across spatiotemporal dimensions. METHODS: We integrated GWAS data from 100,204 CRC cases and 12,160 UC patients with tissue-specific MAGMA enrichment, embryonic spatial mapping (gsMap), and multidimensional single-cell prioritization (ECLIPSER, CELLECT, scDRS). We further resolved cell-specific co-expression patterns using hdWGCNA and identified high-confidence causal variants and genes through Bayesian fine-mapping (eCAVIAR, fastenloc) and Open4Gene analysis. RESULTS: Genetic susceptibility for both diseases was significantly enriched in the terminal ileum and transverse colon, anchored to E16.5 embryonic gut programs. CD4 + T cells emerged as the core immune hub in UC, exhibiting profound immunometabolic polarization (Th17/IL-17 axis and Warburg effect), while progenitors were identified as the primary cellular origin for CRC malignancy. Pathological progression was characterized by a transition from chronic inflammatory stress toward p53-mediated genomic instability, epithelial-mesenchymal transition (EMT), and vascular remodeling. We prioritized Tier 1 candidate genes-ARPC5, PTGER4, CIB1, PREX1, and S100A10-as key mediators of the comorbidity association between inflammation and cancer. CONCLUSIONS: These findings partially support a "genetic programming-microenvironment triggering" hypothesis, where regional vulnerabilities established by embryonic developmental programs are activated by postnatal insults, though its broad applicability warrants caution. This study provides a comprehensive multi-scale molecular framework for understanding UC-CRC comorbidity, offering potential targets for risk stratification and therapeutic intervention.
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Identification of HMGB2 associated with proliferation, invasion and prognosis in lung adenocarcinoma via weighted gene co-expression network analysis.
BACKGROUND: High mobility group protein B2 (HMGB2) is a multifunctional protein that plays various roles in different cellular compartments. Moreover, HMGB2 serves as a potential prognostic biomarker and therapeutic target for lung adenocarcinoma (LUAD). METHODS: In this study, the expression pattern, prognostic implication, and potential role of HMGB2 in LUAD were evaluated using the integrated bioinformatics analyses based on public available mRNA expression profiles from The Cancer Genome Atlas and Gene Expression Omnibus databases, both at the single-cell level and the tissue level. Further study in the patient-derived samples was conducted to explore the correlation between HMGB2 protein expression levels with tissue specificity, (tumor size-lymph node-metastasis) TNM stage, pathological grade, Ki-67 status, and overall survival. In vitro experiments, such as CCK-8, colony-formation and Transwell assay, were performed with human LUAD cell line A549 to investigate the role of HMGB2 in LUAD progression. Furthermore, xenograft tumor model was generated with A549 in nude mice. RESULTS: The results showed that the HMGB2 expression was higher in the LUAD samples than in the adjacent normal tissues and was correlated with high degree of malignancy in different public data in this study. Besides, over-expression of HMGB2 promoted A549 cells proliferation and migration while knocking down of HMGB2 suppressed the tumor promoting effect. CONCLUSIONS: Our study indicated that HMGB2 was remarkably highly expressed in LUAD tissues, suggesting that it is a promising diagnostic and therapeutic marker for LUAD in the future.
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Unveiling the ZNF384-INTS13-hnRNPC axis as a therapeutic vulnerability in cervical cancer.
Cervical cancer remains a major global health burden, necessitating the identification of novel therapeutic targets to overcome the limitations of current treatments. Here, we comprehensively investigated the role of integrator complex subunit 13 (INTS13) in cervical cancer progression. Our analysis of publicly available The Cancer Genome Atlas (TCGA) datasets revealed that INTS13 is significantly overexpressed in cervical cancer tissues across various histological subtypes, correlating with advanced tumor T-stage and predicting poorer overall survival. Single-cell RNA sequencing further localized INTS13 expression predominantly to malignant epithelial cells within the tumor microenvironment, where its expression correlated with genes involved in critical cellular processes. Furthermore, elevated expression has been observed in cervical cancer tissues from surgically-treated patients and in various primary human cervical cancer cells. In vitro functional studies demonstrated that genetic silencing or CRISPR/Cas9-mediated knockout of INTS13 significantly inhibited the proliferation, migration, and invasion of primary cervical cancer cells, while selectively inducing apoptosis. Conversely, ectopic INTS13 overexpression markedly enhanced these malignant phenotypes. Mechanistically, we identified heterogeneous nuclear ribonucleoprotein C (hnRNPC) as a critical downstream effector, with INTS13 regulating hnRNPC expression, and the restoration of hnRNPC effectively reversing the anti-cervical cancer effects observed upon INTS13 silencing. Furthermore, the transcription factor ZNF384 (zinc finger protein 384) was identified as an upstream regulator that directly binds to and positively governs INTS13 expression. Finally, in vivo animal models confirmed that targeted silencing of INTS13 significantly impeded cervical cancer xenograft growth in nude mice, reduced cellular proliferation, and augmented apoptosis, consistently accompanied by a reduction in hnRNPC expression. These findings collectively establish INTS13 as a crucial precancerous gene in cervical cancer, promoting malignant phenotypes primarily through the ZNF384-INTS13-hnRNPC signaling axis.