Early-onset preeclampsia (EOPE) with fetal growth restriction (FGR) is a severe hypertensive disorder of pregnancy characterized by placental dysfunction and estrogen deficiency. Based on single-cell RNA sequencing (scRNA-seq) profiling of specific placental trophoblast subtypes from EOPE-FGR and normotensive pregnancies, we identified HSD17B1, which encodes a key enzyme mediating estradiol conversion, as the central dysregulated node in EOPE pathogenesis. Multi-modal computational analysis (cluster annotation, cellular proportion calculation, comparison of differentially expressed genes, and characterization of cellular developmental trajectories) revealed key expression dynamics during syncytiotrophoblast (SCT) differentiation, with substantial suppression in EOPE specimens. Further validation using clinical placental samples confirmed the downregulation of HSD17B1 at the protein level in patients with EOPE, as demonstrated by immunohistochemistry and western blotting. Mechanistically, HSD17B1 knockdown in BeWo trophoblast models recapitulated the core EOPE phenotypes of impaired SCT differentiation and estrogen biosynthesis blockade. These findings reveal that HSD17B1 is a master coordinator of trophoblast-endocrine crosstalk, the impairment of which in placental trophoblasts may contribute to EOPE pathogenesis. Our findings provide a mechanistic basis for developing HSD17B1-targeted interventions that could contribute to the concurrent restoration of placental competence and hormonal regulation, improving the perinatal outcomes of patients with EOPE.

T cell acute lymphoblastic leukemia (T-ALL) is a heterogeneous disease characterized by a high relapse rate. By single-cell transcriptome analysis, we characterize the bone marrow immune microenvironment in patients with T-ALL, identifying 13 major cell clusters. These patients exhibited abnormally expanded hematopoietic stem cells (HSCs) and granulocyte-monocyte progenitors (GMPs), immunosuppressive traits in CD4+ T, CD8+ T, and natural killer (NK) cells. Subdividing CD4+ T cells reveal two subsets transitioning between T helper (Th)1/Th2, Annexin-A1 (ANXA1)-GATA3-CD4+ T, and ANXA1+GATA3+CD4+ T. Additionally, NK cells demonstrate exhaustion in the tumor microenvironment of patients with relapsed T-ALL, with JUN identified as a critical factor. Additionally, JUN is also highly expressed in T-ALL and is crucial for maintaining its proliferation. The JUN inhibitor exhibited successful lethality toward leukemia cells and ameliorated NK cell exhaustion in relapsed T-ALL cell line, as well as in cell-derived tumor xenograft (CDX), patient-derived tumor xenograft (PDX), and NOTCH1-mutant mouse models. In summary, our findings enhance the understanding of T-ALL relapse mechanisms and support the development of innovative immunotherapies for patients with relapsed T-ALL.

Chimeric antigen receptor CAR T cell therapy faces notable limitations in treatment of solid tumors. The suppressive tumor microenvironment TME, characterized by complex interactions among immune and stromal cells, is gaining recognition in conferring resistance to CAR T cell therapy. Despite the abundance and diversity of macrophages in the TME, their intricate involvement in modulating responses to CAR T cell therapies remains poorly understood. Here, we conducted single-cell RNA sequencing scRNA seq on tumors from 41 glioma patients undergoing IL13Ra2-targeted CAR T cell therapy, identifying elevated suppressive SPP1 signatures predominantly in macrophages from patients who were resistant to treatment. Further integrative scRNA seq analysis of high-grade gliomas as well as an interferon-signaling deficient syngeneic mouse model both resistant to CAR T therapy demonstrated the role of congruent suppressive pathways in mediating resistance to CAR T cells and a dominant role for SPP1+ macrophages. SPP1 blockade with an anti-SPP1 antibody abrogates the suppressive TME effects and substantially prolongs survival in IFN signaling-deficient and glioma syngeneic mouse models resistant to CAR T cell therapy. These findings illuminate the role of SPP1+ macrophages in fueling a suppressive TME and driving solid tumor resistance to CAR cell therapies. Targeting SPP1 may serve as a universal strategy to reprogram immune dynamics in solid tumors mitigating resistance to CAR T therapies.

Allergic asthma in children is typically associated with house dust mites (HDM) as the key allergen. Nevertheless, the diagnostic rate remains below 60% due to the absence of specific symptoms and diagnostic markers, which hinders the implementation of targeted personalized therapies. This study investigates immunological features of asthma with house dust mite (HDM) sensitisation in children, aiming to uncover diagnostic markers at single-cell resolution. The cohort comprised 8 children with physician-diagnosed asthma (age range: 4-11 years), stratified into groups based on HDM sensitization status. Single-cell RNA sequencing of peripheral blood mononuclear cells (PBMCs) was conducted, employing Seurat for cell identification and differential gene expression analysis. Enrichment analyses and LASSO regression identified signature genes related to cellular origin, with protein-protein interaction networks elucidating cellular communication differences between groups. A total of 11 distinct cell types were identified, with classical monocytes and monocytes being the predominant cell types that differentiated the two groups. Among these, 12 genes were up-regulated, and 40 down-regulated, mainly involving MHC-II complex and antigen presentation pathways, as validated by Gene Ontology and Gene Set Enrichment Analysis. The machine learning model accurately predicted cellular groupings, evidenced by an area under the curve of 0.83. Enhanced communication signals in HDM allergy cases involved monocytes, contrasting with reduced interactions in naive CD8 + cells. HLA-DR and HLA-DP were identified as the primary hallmark receptors, and the innate immunity differences with non-dust mite allergic asthma were characterized by 18 genes including top candidates MT-ND4 and RPS3A. Individuals with HDM-sensitized asthma exhibited altered expression of MHC-II complex genes in their PBMCs and distinct gene expression patterns in antigen-presenting cells, highlighting the critical role of HLA-DR and HLA-DP in the HDM allergen presentation.

Tauopathies, including Alzheimer's disease (AD) and frontotemporal dementia (FTD), display sex-specific differences in prevalence and progression, but the underlying molecular mechanisms remain unclear. Single-cell transcriptomic analysis of animal models can reveal how AD pathology affects different cell types across sex and age.

To understand sex-specific and sex-dimorphic transcriptomic changes in different cell types and their age-dependence in the THY-Tau22 mouse model of AD-linked tauopathy.

We applied single-cell RNA sequencing (scRNA-seq) to cortical tissue from male and female THY-Tau22 and wild-type mice at 17 months of age, when they had prominent tau inclusion pathology, and compared the results with corresponding data previously obtained at 7 months of age. Using differential statistical analysis for individual genes, pathways, and gene regulatory networks, we identified sex-specific, sex-dimorphic, and sex-neutral changes, and looked at how they evolved over age. To validate the most robust findings across distinct mouse models and species, the results were compared with cortical scRNA-seq data from the transgenic hAPP-based Tg2576 mouse model and human AD.

We identified several significant sex-specific and sex-dimorphic differentially expressed genes in neurons, microglia, astrocytes and oligodendrocytes, including both cross-sectional changes and alterations from 7 months to 17 months of age. Key pathways affected in a sex-dependent manner across age included neurotransmitter signaling, RNA processing and splicing, stress response pathways, and protein degradation pathways. In addition, network analysis revealed the AD-associated genes Clu, Mbp, Fos and Junb as relevant regulatory hubs. Analysis of age-dependent changes highlighted genes and pathways associated with inflammatory response (Malat1, Cx3cr1), protein homeostasis (Cst3), and myelin maintenance (Plp1, Cldn11, Mal) that showed consistent sex-dependent changes as the THY-Tau22 mice aged. Multiple genes with established implications in AD, including the long non-coding RNA gene Malat1, displayed concordant sex-specific changes in mouse models and human AD.

This study provides a comprehensive single-cell transcriptomic characterization of sex-linked and age-dependent changes in the THY-Tau22 tauopathy model, revealing new insights into the interplay between age-dependent AD-like pathologies and sex. The identified sex-specific changes and their conservation across models and human AD highlight molecular targets for further preclinical investigation of sex-specific therapeutic strategies in AD.

Acute myeloid leukemia (AML) is one of the most prevalent heterogeneous hematologic malignancies with a complicated etiology. RNA post-transcriptional modifications have been linked to the incidence and progression of AML, while the detailed mechanism remains to be elucidated. In this study, we find that NOP2/Sun domain family member 2 (NSUN2), a methyltransferase of 5-methylcytosine (m5C) RNA methylation, is upregulated in AML and predicts a poor prognosis for patients with AML. Knockdown of NSUN2 in AML cells inhibits proliferation and colony formation and promotes apoptosis. Depletion of NSUN2 in AML mice reduces the tumor burden and prolongs survival. Mechanistically, NSUN2 promotes the expression of phosphoglycerate dehydrogenase (PHGDH) and serine hydroxymethyltransferase 2 (SHMT2), two key enzymes in the serine/glycine biosynthesis pathway, by stabilizing the corresponding mRNAs through regulation of m5C modifications. Overall, our findings demonstrate a critical role of NSUN2 in AML development and highlight the therapeutic potential of targeting the NSUN2/m5C axis for the treatment of this cancer.

In the therapeutic landscape of colorectal cancer (CRC), chemo-resistance poses a significant and prevalent obstacle that complicates treatment efficacy and patient outcomes. Over time, cancer cells can develop mechanisms to resist the toxic effects of chemo-therapy drugs, leading to reduced sensitivity or complete insensitivity to these agents. The enzyme Arylamine N-acetyltransferase 1 (NAT1) has emerged as a promising target in strategies aimed at overcoming this challenge. NAT1 is involved in the metabolism of various xenobiotics, including some chemotherapeutic agents. Understanding the complex interactions between NAT1 and chemotherapeutic agents, as well as the molecular mechanisms underlying chemo-resistance, is crucial for the development of novel therapeutic approaches.

This study aimed to assess the role of NAT1 in mediating chemo-resistance in CRC, with the goal of identifying novel strategies to overcome this clinical challenge.

We conducted a comprehensive analysis using various bioinformatics tools and in vitro experiments to evaluate the effect of NAT1 expression on chemo-resistance in CRC. Furthermore, we employed a multi-omics approach, including metabolomics and next-generation sequencing, to uncover the mechanisms by which NAT1 influences chemo-resistance. Additionally, we utilized single-cell RNA sequencing (scRNA-seq), the Cellchat assay, and western blot to explore the intercellular communication between tumor and endothelial cells in the context of anti-PD-1 therapy and NAT1's impact.

Our study reveals that decreased NAT1 expression in CRC tumor tissues, relative to adjacent normal tissues, is significantly associated with a poorer patient prognosis. Experimental data indicate that silencing NAT1 in CaCO2 and HCT116 cell lines results in heightened resistance to five chemotherapeutic agents: vinblastine, docetaxel, gemcitabine, vincristine, and daporinad. Additionally, NAT1 silencing increases the proportion of LGR5+ cells, which are known to be chemo-resistant. Our research further revealed that exposure to these five drugs induces a decrease in NAT1 expression within CRC cells. Mechanistic insights show that NAT1 knockdown triggers a metabolic reprogramming in CRC cells, shifting from oxidative phosphorylation and the tricarboxylic acid cycle to a preference for glycolysis. Furthermore, silencing of NAT1 in CRC cells leads to an up-regulation of VEGFA expression. Notably, the application of anti-PD-1 therapy was demonstrated to significantly disrupt the VEGFA-VEGFR axis signaling, an interaction critical between CRC cells and endothelial cells. This discovery underscores the potential of targeting the VEGFA pathway as a therapeutic approach to mitigate the adverse effects associated with NAT1 down-regulation in CRC.

Our study underscores the multifaceted role of NAT1 in modulating chemo-sensitivity, cellular metabolism, and angiogenesis in CRC. These findings position NAT1 as a compelling candidate for a biomarker and a potential therapeutic target, offering new avenues for CRC management.

Tumor-Infiltrating Lymphocytes (TILs) immunotherapy is a highly promising treatment for Non-small Cell Lung Cancer (NSCLC), which is responsible for 18% of all cancer-related deaths. The heterogeneity of TILs remains poorly understood. Here, we utilized combined single-cell RNA (scRNA)/T cell receptor sequencing (scTCR-seq) data from lung adenocarcinoma (LUAD) patients. Naïve CD4+ and effector memory CD8+ T cells were increased in tumor tissue compared with circulating blood samples. Activated signaling pathways were detected, and GZMA was identified as a potential novel diagnostic biomarker. During the transitional phase, macrophages (FTL) and dendritic (AIF1) cells transported the most CD3 TCR clones to T cells, while cytotoxicity CD8+ T (NKG7) cells transported to terminal exhausted CD8+ T cells. In both transition and expansion phases, T helper cells (CXCL13) are transported to regulatory T cells (Tregs). Additionally, we investigated the expression profiles of key cytokines, checkpoint receptors, and their ligands. Cytotoxicity CD8+ T cells (CCL5 and IFNG), T helper cells (FTL, TNFRSF4, and TIGIT), and regulatory T cells (CTLA4, TIGIT and FTL) exhibited functional roles in both primary and metastatic tumor stages. Taken together, our study provides a single-cell resolution of the TIL immune landscape and suggests potential treatment strategies to overcome drug resistance.

Acute kidney injury (AKI) is a major cause of early graft dysfunction after kidney transplantation, particularly in recipients of high-risk donor kidneys prone to ischemia-reperfusion injury. However, the cellular mechanisms dictating whether injury resolves or progresses to fibrosis remain unclear. This study combines single-nucleus RNA sequencing and imaging mass cytometry (IMC) analysis of human kidney allograft biopsies collected within eight weeks posttransplant, stratified by long-term functional outcomes. Grafts that recovered function were enriched in regenerative proximal tubular (PT) cells co-expressing PROM1, CD24, and injury markers, consistent with scattered tubular cells (STCs). In contrast, non-recovering grafts contained a unique subpopulation of transitional proximal tubule cells (tPT4) characterized by dedifferentiation, loss of epithelial identity, and acquisition of fibroblast-like features. Fibroblast trajectory analysis revealed a profibrotic lineage, progressing from stromal progenitors to myofibroblasts, exclusive to nonrecovery grafts. Immune profiling showed divergent macrophage (MΦ) polarization, with reparative MΦ2 cells and regulatory dendritic cell (DC)-like signatures in recovering grafts, versus inflammatory MΦ1 and pro-fibrotic DCs in non-recovery. IMC confirmed spatial colocalization of injured tubules, activated fibroblasts, and immune cells in fibrotic regions, validated in an independent cohort. Functional assays demonstrated that ischemic epithelial injury activated monocyte-derived MΦs with mixed inflammatory/reparative profiles and induced fibroblast-related gene expression, while PAX8 knockdown impaired epithelial proliferation and promoted pro-inflammatory signaling. These findings reveal epithelial cell plasticity as a central driver of divergent repair outcomes following renal transplant AKI and highlight epithelial-immune-stromal crosstalk as a therapeutic target to promote recovery and prevent chronic graft injury.

Single-cell and spatial mapping of human kidney transplants reveal regenerative and fibrotic cell programs across tubular, immune, and stromal compartments that determine whether acute injury resolves or progresses to chronic allograft injury.

Recent advances have shown that single-nucleus RNA sequencing (snRNA-seq) can be applied to formalin-fixed, paraffin-embedded (FFPE) tissues, opening avenues for transcriptomic analysis of archived specimens. Yet, isolating intact nuclei remains difficult due to RNA cross-linking. Here, we introduce a cryogenic enzymatic dissociation (CED) strategy for rapid, high-yield and fidelity nuclei extraction from FFPE samples and validate its utility with snRandom-seq (snCED-seq) using male C57/BL6 mice. Compared with conventional approaches, CED delivers a tenfold increase in nuclei yield with significantly reduced hands-on time, while minimizing secondary RNA degradation and preserving intranuclear transcripts. snCED-seq enhances gene detection sensitivity, lowers mitochondrial and ribosomal contamination, and increases overall gene expression quantification. In Alzheimer's disease studies, it distinguished two astrocyte subpopulations, microglia, and oligodendrocytes, revealing cellular heterogeneity. Additionally, snCED-seq identify major cell types in a single 50 μm FFPE human lung section. Our results demonstrate that snCED-seq is robust for FFPE specimens and poised to enable multi-omics analyses of clinical samples.

Accurate cell type annotation is fundamentally critical for single-cell sequencing (scRNA-seq) data analysis to provide insightful knowledge of tissue-specific cell heterogeneity and cell state transition tracking. Cell type annotation is usually conducted by comparative analysis with known data (i.e., reference) - which contains a presumably accurate representation of cell types. However, this assumption is often problematic, as factors such as human errors in wet-lab experiments and methodological limitations can introduce annotation errors in the reference dataset. As current pipelines for single-cell transcriptomic analysis do not adequately consider this challenge, there is a major demand for constructing a computational pipeline that achieves high-quality cell type annotation using reference datasets containing inherent errors (referred to as "noise" in this study). Here, we built a Siamese network-based pipeline, termed scRCA, to accurately annotate cell types based on noisy reference data. To help users evaluate the reliability of scRCA annotations, an interpreter was also developed to explore the factors underlying the model's predictions. Our experiments demonstrate that, across 14 datasets, scRCA outperformed other widely adopted reference-based methods for cell type annotation. Using an independent dataset of four multiple myeloma patients, we further illustrated that scRCA can distinguish cancerous cells based on gene expression levels and identify genes closely associated with multiple myeloma through scRCA's interpretable module, providing significant information for subsequent clinical treatments. With these advancements, we anticipate that scRCA will serve as a practical reference-based approach for accurate annotating cell type annotation.

The evolutionary process of intermuscular bones (IBs) is complex, the molecular regulatory mechanisms of their development are not clear, and even the genes involved in the evolution and development of IBs are poorly understood. In this study, comparative genomic analysis of four fish species with IBs and eleven fish species without IBs identified 106 genes that are more conservatively evolved in fish species with IBs, but highly variable in fish species without IBs. These genes are mainly involved in swimming behavior and BMP signaling pathways. We performed single-cell transcriptome sequencing of IBs origin tissues in zebrafish before and after IBs formation and found that osteoblasts and mesenchymal stem cells (MSCs) increased significantly after IBs formation. RNA velocity analysis showed that osteoblasts in IBs differentiate from MSCs, and the differentiation trajectory of MSCs into osteoblasts was successfully constructed by pseudo-time analysis. Combined with the results of multi-omics analysis, seven candidate genes associated with IBs development were screened and knocked out in zebrafish. It was found that foxn3 mutation resulted in a delay in IB development, whereas bmp6 mutation resulted in a total loss of IB. By comparing the transcriptome of IBs tissues between bmp6+/+ zebrafish and bmp6-/- zebrafish, we found that bmp6 deletion may inhibit the differentiation of MSCs into osteoblasts while promoting the formation of osteoclasts and ultimately inhibiting the formation of IBs. This study provides new insights into the molecular regulatory mechanisms and evolutionary processes of IB development.

Non-alcoholic fatty liver disease (NAFLD) is a prevalent chronic condition with an incompletely understood pathogenesis. In this study, five candidate genes-RAG1, CKAP2, CENPK, TYMS, and BUB1-were identified as being associated with NAFLD progression through integrative bioinformatics analyses. A predictive model incorporating these genes demonstrated strong robustness and diagnostic accuracy. Single-nucleus RNA sequencing analysis further revealed that RAG1 plays a potential role in hepatocytes of NAFLD patients. Functional experiments using RNA interference to suppress RAG1 expression in HepG2 cells treated with oleic and palmitic acids showed reduced total glyceride and cholesterol levels, mitigated lipid accumulation, and alterations in pathways related to lipid metabolism, inflammation, and fibrosis. Furthermore, adeno-associated virus-specific knockdown of RAG1 in hepatocytes attenuated hepatic steatosis in high-fat diet-fed mice. These findings suggest that investigating the molecular mechanisms of hub genes like RAG1 may advance our understanding of NAFLD pathogenesis and inform therapeutic development.

The rapid accumulation of single-cell RNA sequencing data has provided unprecedented computational resources for cell type annotation, significantly advancing our understanding of cellular heterogeneity. Leveraging gene expression profiles derived from transcriptomic data, researchers can accurately infer cell types, sparking the development of numerous innovative annotation methods. These methods utilize a range of strategies, including marker genes, correlation-based matching, and supervised learning, to classify cell types. In this review, we systematically examine these annotation approaches based on transcriptomics-specific gene expression profiles and provide a comprehensive comparison and categorization of these methods. Furthermore, we focus on the main challenges in the annotation process, especially the long-tail distribution problem arising from data imbalance in rare cell types. We discuss the potential of deep learning techniques to address these issues and enhance model capability in recognizing novel cell types within an open-world framework.

The lung is a vital organ that undergoes extensive morphological and functional changes during postnatal development. To disambiguate how different cell populations contribute to organ development, we performed proteomic and transcriptomic analyses of four sorted cell populations from the lung of human subjects 0-8 years of age with a focus on early life. The cell populations analyzed included epithelial, endothelial, mesenchymal, and immune cells. Our results revealed distinct molecular signatures for each of the sorted cell populations that enable the description of molecular shifts occurring in these populations during postnatal development. We confirmed that the proteome of the different cell populations was distinct regardless of age and identified functions specific to each population. We identified a series of cell population protein markers, including those located at the cell surface, that show differential expression and distribution on RNA in situ hybridization and immunofluorescence imaging. We validated the spatial distribution of alveolar type 1 and endothelial cell surface markers. Temporal analyses of the proteomes of the four populations revealed processes modulated during postnatal development and clarified the findings obtained from whole-tissue proteome studies. Finally, the proteome was compared with a transcriptomics survey performed on the same lung samples to evaluate processes under post-transcriptional control.

Objective: Anoikis is a kind of programmed cell death that is triggered when cells lose contact with each other or with the matrix. However, the potential value of anoikis-related genes (ARGs) in keloid (KD) has not been investigated. Approach: We downloaded three keloid fibroblast (KF) RNA sequencing (RNA-seq) datasets from the Gene Expression Omnibus (GEO) and obtained 338 ARGs from a search of the GeneCards database and PubMed articles. Weighted correlation network analysis was used to construct the coexpression network and obtain the KF-related ARGs. The LASSO-Cox method was used to screen the hub ARGs and construct the best prediction model. Then, GEO single-cell sequencing datasets were used to verify the expression of hub genes. We used whole RNA-seq for gene-level validation and the correlation between KD immune infiltration and anoikis. Results: Our study comprehensively analyzed the role of ARGs in KD for the first time. The least absolute shrinkage and selection operator (LASSO) regression analysis identified six hub ARGs (HIF1A, SEMA7A, SESN1, CASP3, LAMA3, and SIK2). A large number of miRNAs participate in the regulation of hub ARGs. In addition, correlation analysis revealed that ARGs were significantly correlated with the infiltration levels of multiple immune cells in patients with KD. Innovation: We explored the expression characteristics of ARGs in KD, which is extremely important for determining the molecular pathways and mechanisms underlying KD. Conclusions: This study provides a useful reference for revealing the characteristics of ARGs in the pathogenesis of KD. The identified hub genes may provide potential therapeutic targets for patients. This study provides new ideas for individualized therapy and immunotherapy.

The incidence and mortality rates of lung cancer are exceptionally high. Many patients are diagnosed with early stage lung cancer but experience rapid recurrence post-surgery. Many research studies have shown that the unfavorable prognosis of patients may be associated with micro-metastasis in the lymph nodes. Our research aimed to develop a nomogram to predict the prognosis of lung adenocarcinoma (LUAD).

Single-cell RNA sequencing (scRNA-seq) data were analyzed to identify 11 cell clusters. Patterns of incoming and outgoing signals were identified across the entire cell population. A weighted gene co-expression network analysis (WGCNA) was conducted to uncover critical genes in LUAD. The intersecting marker genes were used to construct the prognostic model.

scRNA-seq data were analyzed to identify 19 cell clusters. We identified 3,464 marker genes from the scRNA-seq dataset, 1,994 differentially expressed genes from the bulk RNA sequencing (RNA-seq) dataset, and 1,863 genes associated with a key module identified by the WGCNA. After performing the intersection, univariate Cox, and least absolute shrinkage and selection operator analyses, a prognostic model was established based on the expression levels of 13 signature genes. Subsequent functional experiments confirmed the role of selected regulated genes.

Through the integration of scRNA-seq data and bulk RNA-seq data, we developed an innovative model to predict the prognosis of patients. The risk score was found to be a significant independent predictor and clinical-pathological features of LUAD.

The pathophysiology of idiopathic normal pressure hydrocephalus (iNPH) remains unclear, and the treatment strategy remains suboptimal. This study aims to identify biomarkers for shunt prognosis by cerebrospinal fluid (CSF) proteomic profiling.

CSF samples collected from 37 iNPH patients from the discovery cohort and 12 iNPH patients from an independent validation cohort (71.9 ± 6.1 years (mean ± SD)), and 16 age-balanced controls (69.9 ± 7.6 years (mean ± SD)) were collected from September 2020 to December 2023. 53 CSF samples were analyzed using a mass spectrometry-based proteomic workflow. Clinical evaluations were performed on all iNPH patients, and 44 patients underwent ventriculoperitoneal shunting. Postoperative CSF were also collected from 10 iNPH patients who underwent shunting surgery. Bioinformatics, machine learning, and enzyme-linked immunosorbent assay (ELISA) were performed to identify CSF proteome changes related to pathophysiology in iNPH, and screen for biomarkers associated with shunt response.

39 and 285 proteins significantly increased and decreased in iNPH CSF compared to the control group. Gene ontology analysis revealed that the noticeably increased proteins were mainly associated with myeloid leukocyte migration and extracellular matrix organization, and significantly decreased proteins were primarily associated with axon development and synapse organization. Machine learning identified 6 candidate biomarkers that potentially predicted the response to shunt surgery. Among these, QPCT levels were found to be elevated in non-responders, while RBP4 levels were decreased, and both of these changes were validated through ELISA.

Our findings provide support for the hypothesis that the pathophysiology of iNPH is characterized by a state of neuroinflammation, extracellular matrix remodeling, and neurodegeneration, and CSF shunting can reverse such pathological state. Machine learning using preoperative proteomic profiles satisfactorily predicted the clinical outcome of the shunt procedure in iNPH. Future research targeting specific proteins in iNPH may be warranted to better comprehend the disease mechanism and design patient-tailored treatments.

Rationale: Short-term starvation (STS) has been shown to enhance the sensitivity of tumors to chemotherapy while concurrently safeguarding normal cells from its detrimental side effects. Nonetheless, the extent to which STS relies on the anti-tumor immune response to impede the progression of hepatocellular carcinoma (HCC) remains uncertain. Methods: In this study, we employed mass cytometry, flow cytometry, immunoprecipitation, immunoblotting, CUT&Tag, RT-qPCR, and DNA pull-down assays to evaluate the relationship between STS and T-cell antitumor immunity in HCC. Results: We demonstrated that STS alleviated T cell exhaustion in HCC. This study elucidated the mechanism by which STS blocked CD36 N-glycosylation, leading to the upregulation of AMPK phosphorylation and the downregulation of USP7 UFMylation, thus enhancing ubiquitination and destabilized USP7. Consequently, diminished USP7 levels facilitated the ubiquitination and subsequent degradation of RBPJ, thereby inhibiting T cell exhaustion through the IRF4/TNFRSF1B axis. From a therapeutic standpoint, STS not only suppressed the growth of patient-derived orthotopic xenografts but also enhanced their sensitivity to immunotherapy. Conclusions: These findings uncovered a novel mechanism by which N-glycosylation participated in UFMylation/ubiquitination to regulate T cell exhaustion, and we underscored the potential of targeting USP7 and RBPJ in anti-tumor immunotherapy strategies.

Osteosarcoma (OS) presents significant treatment challenges due to chemoresistance. This study explores the molecular mechanisms underlying chemoresistance in OS, focusing on the novel fusion gene RPS27-RPS24. Using single-cell multi-omics techniques, we identified a significant upregulation of RPS27-RPS24 in chemoresistant OS cells. Our analyses revealed that RPS27-RPS24 enhances glutaminase (GLS)-mediated glutamine metabolism and inhibits copper-induced cell death, thereby promoting chemoresistance. In vitro experiments with adriamycin-resistant (ADMR) OS cells confirmed that overexpression of RPS27-RPS24 leads to increased cell viability and proliferation under chemotherapy. In vivo studies further validated these findings, demonstrating that targeting glutamine metabolism can reverse chemoresistance. Our results suggest that the RPS27-RPS24 fusion gene plays a critical role in OS chemoresistance through metabolic reprogramming, providing a potential therapeutic target for improving OS treatment outcomes. The application of multiple analytical techniques in this study (as shown in the upper image) and the hypothesized mechanism (as shown in the lower image).

The high heterogeneity between patients can complicate the diagnosis and treatment of pancreatic ductal adenocarcinoma (PDAC). Here, we explored the association of universally differentially expressed genes (UDEGs) with resistance to chemotherapy and immunotherapy in the context of pancreatic cancer. In this work, sixteen up-regulated and three down-regulated genes that were dysregulated in more than 85% of 102 paired and 5% of 521 unpaired PDAC samples were identified and defined as UDEGs. A single-cell level analysis further validated the high expression levels of the up-UDEGs and the low levels of the down-UDEGs in cancer-related ductal cells, which could represent the malignant changes seen in pancreatic cancer. Based on a drug sensitivity analysis, we found that ANLN, GPRC5A and SERPINB5 are closely related to the resistance mechanism of PDAC, and their high expression predicted worse survival for PDAC patients. This suggests that targeting these genes could be a potential way to reduce drug resistance and improve survival. Based on the immune infiltration analysis, the abnormal expression of the UDEGs was found to be related to the formation of an immunosuppressive tumor microenvironment. In conclusion, these UDEGs are common features of PDAC and could be involved in the resistance of pancreatic cancer and might serve as novel drug targets to guide research into drug repurposing.

This study investigated the regulatory mechanisms of cuproptosis-related genes (CRGs) in spinal cord injury (SCI) and explored the therapeutic potential of neurotrophin-3 (NT3)-loaded chitosan in promoting functional recovery.

We conducted integrated bulk RNA-seq and single-cell RNA-seq (scRNA-seq) analyses of mouse spinal cord tissue at various time points after SCI. The key CRGs were identified using differential expression analysis, weighted gene co-expression network analysis, and machine learning. The therapeutic effects of NT3-loaded chitosan were evaluated using animal models and molecular docking analysis.

We identified four key CRGs (Atp7a, Cp, Loxl2, and Pde3b) and three key transcription factors (C/EBPα, Stat6, and Runx1) that were upregulated post-SCI, promoting cuproptosis and neuroinflammation. NT3-loaded chitosan treatment significantly inhibited CRG expression and enhanced functional recovery in the animal models. Molecular docking analysis demonstrated binding interactions between chitosan and key CRGs, suggesting a potential mechanism for their therapeutic effects.

Our findings highlight the critical role of CRGs in SCI progression and the potential of NT3-loaded chitosan as a therapeutic strategy for inhibiting cuproptosis and promoting functional recovery. Future studies should focus on validating these findings in larger cohorts and exploring the detailed mechanisms by which NT3-loaded chitosan modulates CRG expression.

The dysregulated host response to infections can lead to sepsis, a complex disease characterized by a spectrum of clinical phenotypes. Using scRNA-seq, we analyzed the immune cell of survived and non-survived CLP-septic mice to gain insights into the immunological mechanisms by which neutrophils contribute to the hyperinflammatory phenotype. Our findings reveal that non-survived mice exhibit increased frequencies of immature CXCR4+ PD-L1+ neutrophils in the bloodstream, accompanied by an accumulation of trafficking-specific CXCR4+ PD-L1+ neutrophils into the lungs. The IFN-gamma and LPS promote the PD-L1 expression on neutrophils and an activation profile associated with inflammation and organ damage. Notably, abrogating the IFN-gamma reduced susceptibility to CLP-sepsis and diminished CXCR4+ PD-L1+ neutrophils frequency. This study provides insights into the immune cell activation profiles associated with the worsening of the CLP-sepsis, and the CXCR4+ PD-L1+ neutrophils population highlighted here represents a promising target for therapeutic modulation in clinical sepsis hyperinflammatory phenotype.

Wilms Tumor (WT), a prevalent pediatric renal malignancy, exhibits marked heterogeneity and variable clinical outcomes. Epithelial-mesenchymal transition (EMT), a biological process enabling epithelial cells to acquire mesenchymal traits associated with enhanced migratory and invasive capacities, plays a crucial role in cancer progression. Protein Regulator of Cytokinesis 1 (PRC1) is a critical protein in cell division, whose overexpression is linked to poor prognosis in various cancers. This study investigates the role of PRC1 as a key prognostic factor in WT and explore the mechanism through comprehensive bioinformatic and experimental approaches. Through bulk RNA-seq data from the TARGET database, we identified PRC1 as significantly up-regulated in WT and associated with poor overall survival. Functional enrichment analyses (GO, KEGG, GSEA) demonstrated PRC1's involvement in cell division, chromatin dynamics, and activation of oncogenic pathways including Wnt/β-catenin, PI3K/AKT/mTOR, and Hedgehog signaling. Immunological analysis showed that elevated PRC1 expression correlates with diminished immune cell activity, particularly in NK cells, suggesting potential immune evasion mechanisms. Single-cell RNA-seq analysis (GSE200256) confirmed PRC1's elevated expression in anaplastic Wilms tumor (AWT) compared to favorable Wilms tumor (FWT), and highlighted its involvement in intercellular communication and metastasis via the EMT process. Genomic analyses identified copy number variations (CNVs) and downregulated PRC1-targeting microRNAs as drivers of its overexpression. In vitro, PRC1 knockdown in WIT-49 cells significantly impaired migratory capacity, invasive potential, EMT progression, and glycolytic metabolism. These findings collectively position PRC1 as a promising therapeutic target and prognostic biomarker in WT.

Abdominal aortic aneurysm (AAA) is a life-threatening disorder with limited therapeutic options. Neutrophil extracellular traps (NETs) are formed by a process known as "NETosis" that has been implicated in AAA pathogenesis, yet the roles and prognostic significance of NET-related genes in AAA remain poorly understood. This study aimed to identify key AAA- and NET-related genes (AAA-NETs-RGs), elucidate their potential mechanisms in contributing to AAA, and explore potential therapeutic compounds for AAA therapy. Through bioinformatics analysis of multiomics and machine learning, we identified six AAA-NETs-RGs: DUSP26, FCN1, MTHFD2, GPRC5C, SEMA4A, and CCR7, which exhibited strong diagnostic potential for predicting AAA progression, were significantly enriched in pathways related to cytokine-cytokine receptor interaction and chemokine signaling. Immune infiltration analysis revealed a causal association between AAA-NETs-RGs and immune cell infiltration. Cell-cell communication analysis indicated that AAA-NETs-RGs predominantly function in smooth muscle cells, B cells, T cells, and NK cells, primarily through cytokine and chemokine signaling. Gene profiling revealed that CCR7 and MTHFD2 exhibited the most significant upregulation in AAA patients compared to non-AAA controls, as well as in in vitro AAA models. Notably, genetic depletion of CCR7 and MTHFD2 strongly inhibited Ang II-induced phenotypic switching, functional impairment, and senescence in vascular smooth muscle cells (VSMCs). Based on AAA-NETs-RGs, molecular docking analysis combined with the Connectivity Map (CMap) database identified mirdametinib as a potential therapeutic agent for AAA. Mirdametinib effectively alleviated Ang II-induced phenotypic switching, biological dysfunction, and senescence. These findings provide valuable insights into understanding the pathophysiology of AAA and highlight promising therapeutic strategies targeting AAA-NETs-RGs.

Sepsis is closely linked to immunity. Our research aimed to identify key genes associated with sepsis immunity utilizing single-cell RNA sequencing (scRNA-seq) data. This study obtained the GSE167363 and GSE54514 datasets from the Gene Expression Omnibus (GEO). The GSE167363 dataset was subjected to cluster analysis, cell proportion analysis, cell interaction analysis, and gene set enrichment analysis (GSEA). The differentially expressed genes (DEGs) of CD8+ T cells were intersected with the DEGs in the GSE54514 dataset, and key genes related to immunity in sepsis patients were identified through Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Finally, we validated the gene expression levels in a mouse model of sepsis caused by cecum ligation and puncture (CLP). Findings indicated that intercellular communication of Cytotoxic CD8+ T cells was reduced in the sepsis survivors compared to non-survivors. The expression of 3 down-regulated key DEGs (ITGB2, SELL and ICAM3) was negatively correlated with the abundance of CD8+ T cells. Moreover, Cytotoxic CD8+ T cells with low expression of ITGB2, SELL and ICAM3 were more adverse to the survival of sepsis as compared to those with high expression of the above genes. These genes may predict increased survival in sepsis by regulating intercellular communication in cytotoxic CD8+ T cells, suggesting that they are potential therapeutic targets for improving sepsis prognosis.

Advanced esophageal squamous cell carcinoma (ESCC) is characterized by molecular heterogeneity and distinct patterns of immune cell infiltration. Regulatory T cells (Tregs), in particular, play a critical role in shaping an immunosuppressive tumor microenvironment (TME), which is associated with poor clinical outcomes.

We developed a prognostic model by integrating GEO-derived bulk RNA sequencing data and single-cell transcriptome. Model predictions were confirmed through RT-qPCR, Western blot, and immunohistochemistry on clinical specimens, while in vitro assays (CCK8, transwell invasion, scratch, colony formation, and immunofluorescence) validated the function of SAP18 in cell proliferation, invasion, and ECM remodeling.

Expression patterns of the 5 Tregs-associated genes in clinical specimens aligned with model predictions, underscoring the model's robustness. The high-risk subgroup was associated with upregulated extracellular matrix (ECM) remodeling, an abundance of immune-suppressive cells, higher TP53 mutation rate, and limited benefit from immunotherapy. In contrast, the low-risk subgroup exhibited anti-tumor immunity. Cell-cell communication analysis also implicated the collagen pathway in Tregs-mediated immune evasion in ESCC. Functional assays indicated that SAP18 in the prognostic model significantly promotes proliferation, invasion, and ECM reconstruction, further highlighting its potential as a therapeutic target.

Our findings elucidate the role of Tregs in the TME, underscoring significant potential of SAP18, which is essential for assessing patient prognosis and may facilitate the development of personalized therapies for ESCC.

We conducted a spatial analysis of stage III colorectal adenocarcinomas using Hyperion Imaging Mass Cytometry, examining 52 tumors to assess the tumor microenvironment at the single-cell level. This approach identified 10 distinct cell phenotypes in the tumor microenvironment, including stromal and immune cells, with a subset showing a proliferative phenotype. By focusing on spatial neighborhood interactions and tissue niches, particularly regions with tumor-infiltrating lymphocytes, we investigated how cellular organization relates to clinicopathological and molecular features such as microsatellite instability (MSI) and recurrence. We determined that microsatellite stable (MSS) colorectal cancers had an increased risk of recurrence if they had the following features: 1) a low level of stromal tumor-infiltrating lymphocytes, and 2) low interactions between CD4 + T cells and stromal cells. Our results point to the utility of spatial single-cell interaction analysis in defining novel features of the tumor immune microenvironments and providing useful clinical cell-related spatial biomarkers.

T cells have been reported to play critical roles in preventing of microsporidia dissemination. However, there roles and functions of each subset remain unclear. Here in the study, we performed a thorough analysis of murine splenic T-cell response analysis via single-cell RNA sequencing during microsporidia E. cuniculi infection. We demonstrated that Type I T helper (Th1) cells, T follicular helper (Tfh) cells, effector CD8 + T cells and proliferating CD8 + T cells were activated and expanded after infection. Activated Th1 cells and Tfh cells presented significantly upregulated gene expression of Ifng and Il21, respectively. A subcluster of Th1 cells with high Csf1 expression was detected after infection. Subsets of activated CD8 + T cells were markedly enriched with high expression of cytotoxic-function related genes such as Gzma and Gzmb, whereas some active CD8 T cells were enriched with proliferation-function related genes Mki67 and Stmn1. Other subsets of T cells including NK T cells, Myb+ T cells, γδ T cells and Cxcr6+ T cells, were also analyzed in this study yet no expansion was observed. In summary, our findings provide in-depth and comprehensive insights into T-cell responses during microsporidia infection, which will be valuable for further investigations.

Lysyl oxidases (LOX/LOXL1-4) are crucial for cancer progression, yet their transcriptional regulation, potential therapeutic targeting, prognostic value and involvement in immune regulation remain poorly understood. This study comprehensively evaluates LOX/LOXL expression in cancer and highlights cancer types where targeting these enzymes and developing LOX/LOXL-based prognostic models could have significant clinical relevance.

We assessed the association of LOX/LOXL expression with survival and drug sensitivity via analyzing public datasets (including bulk and single-cell RNA sequencing data of six datasets from Gene Expression Omnibus (GEO), Chinese Glioma Genome Atlas (CGGA) and Cancer Genome Atlas Program (TCGA)). We performed comprehensive machine learning-based bioinformatics analyses, including unsupervised consensus clustering, a total of 10 machine-learning algorithms for prognostic prediction and the Connectivity map tool for drug sensitivity prediction.

The clinical significance of the LOX/LOXL family was evaluated across 33 cancer types. Overexpression of LOX/LOXL showed a strong correlation with tumor progression and poor survival, particularly in glioma. Therefore, we developed a novel prognostic model for glioma by integrating LOX/LOXL expression and its co-expressed genes. This model was highly predictive for overall survival in glioma patients, indicating significant clinical utility in prognostic assessment. Furthermore, our analysis uncovered a distinct LOXL2-overexpressing malignant cell population in recurrent glioma, characterized by activation of collagen, laminin, and semaphorin-3 pathways, along with enhanced epithelial-mesenchymal transition. Apart from glioma, our data revealed the role of LOXL3 overexpression in macrophages and in predicting the response to immune checkpoint blockade in bladder and renal cancers. Given the pro-tumor role of LOX/LOXL genes in most analyzed cancers, we identified potential therapeutic compounds, such as the VEGFR inhibitor cediranib, to target pan-LOX/LOXL overexpression in cancer.

Our study provides novel insights into the potential value of LOX/LOXL in cancer pathogenesis and treatment, and particularly its prognostic significance in glioma.

The peritoneum is a common site of metastasis in gastric cancer (GC), associated with poor prognosis and significant morbidity. The proclivity of GCs to metastasize to the peritoneum has been hypothesized to occur due the latter's immunosuppressive microenvironment, such as stromal infiltration and M2 macrophage enrichment, which are associated with increased risk of PM. As far as we know, a model that can effectively predict the prognosis of patients with GCPM is still lacking. Consequently, we constructed a prognostic risk model based on M2 macrophages associated with gastric cancer peritoneal metastasis, aiming to enhance predictive precision and guide tailored therapeutic interventions.

M2 macrophage-associated genes were identified in combination with marker genes from single-cell RNA sequencing (scRNA-seq) and modular genes from weighted gene coexpression network analysis (WGCNA). A prognostic model was constructed via LASSO analysis and validated in internal and external cohorts. We further compared the immune microenvironment, immune checkpoints, and chemotherapeutic drug sensitivity between patient groups stratified by risk to clarify the immune landscape in the GCPM.

Our study identified 38 M2 macrophage-related genes via single-cell and bulk RNA sequencing. We developed a prognostic model based on the expression levels of 4 signature genes: DAB2, SPARC, PLTP, and FOLR2. The feasibility of the model was validated with internal and external validation sets (TCGA, GSE62254 and IMvigor210). The model also supported the prediction results of prognosis on the basis of the immunohistochemical results. Notably, patients with higher risk scores had a lower proportion of MSI-H and TMB, a higher prevalence of stages III-IV, and a lower likelihood of responding favorably to immunotherapy.

Our prognostic risk model could effectively predict the prognosis and response to chemo-immune therapy in patients with GCPM. The risk score is a promising independent prognostic factor that is closely correlated with the immune microenvironment and clinicopathological characteristics.

Objective: Fibroblasts (FBs) are the cytological basis of keloid (KD) formation. This study aimed to identify the key pathogenic target cell subpopulation involved in KD recurrence. Approach: Single-cell RNA sequencing data were retrieved from public databases, revealing distinct gene expression patterns in FB subpopulations. Flow cytometry (FCM) was used to identify the surface molecular phenotypes of FBs that affect KD recurrence. Simultaneously, logistic regression analysis was performed to assess the predictive value of changes in FB subpopulation percentages for clinical KD recurrence. Results: The percentage of keloid fibroblasts was significantly greater than that in normal tissues. Through further clustering analysis of the FB population, we obtained four subpopulations, FB1-FB4, in which the percentages of FB1 subpopulation were increased, and functional enrichment analysis suggested that the FB1 subpopulation may play a greater role in extracellular matrix collagen oversynthesis in KD. In addition, the gene expression of CD26 (DPP4), CD117 (c-KIT), and CD34 in the FB1 subpopulation was significantly higher than that in FB2-4 subpopulations. Moreover, the percentage of CD26+/CD117+/CD34+ cell subpopulations in the FCM data of patients with KD recurrence was significantly increased. Regression analysis confirmed that the CD26+/CD117+/CD34+ FB subpopulation was a risk factor for relapse. Innovation: We demonstrated that the molecular phenotypic and functional heterogeneity of FBs influences KD recurrence. Conclusion: We identified key pathogenic FB subpopulations that may affect KD development, which can be used as potential markers to predict recurrence and provide potential target cell populations for future clinical treatment.

Chromatin remodelers have emerged as prominent regulators of hematopoietic cell development and potential drivers of various human hematological malignancies. ATP-dependent BAF chromatin remodeling complexes, related to yeast SWI/SNF, determine gene expression programs and consequently contribute to the self-renewal, commitment, and lineage-specific differentiation of hematopoietic stem cells (HSCs) and progenitors. Here, we investigated the elusive biological function of the core Bcl7b and Bcl7c subunits of BAF complexes in hematopoietic tissue. Our analysis of mouse constitutive knockout alleles revealed that both Bcl7b and Bcl7c are dispensable for animal survival and steady-state adult hematopoiesis. Bcl7b and Bcl7c double knockout (dKO) mice can maintain long-term hematopoiesis with no observable effect on the HSC compartment. Moreover, we show that Bcl7b/Bcl7c dKO HSCs are capable of normal multilineage hematopoietic reconstitution after competitive serial transplantation. Collectively, these studies suggest that the Bcl7b and Bcl7c subunits of BAF complexes are dispensable for normal hematopoiesis.

At now, the majority of approaches rely on manual techniques for annotating cell types subsequent to clustering the data obtained from single-cell RNA sequencing (scRNA-seq). These approaches require a significant amount of physical exertion and depend substantially on the user's skill, perhaps resulting in uneven outcomes and inconsistency in treatment. In this paper, we provide a computer-assisted interpretation of every single cell of a tissue sample, along with an in-depth exploration of an individual cell's molecular, phenotypic and functional attributes. The paper will also perform k-means clustering followed by silhouette validation based on similar phenotype and functional attributes, and also, cell type annotation is performed, where we match a cell's gene profile against some known database by applying certain statistical conditions. Finally, all the genes are mapped spatially on the tissue sample. This paper is an aid to medicine to know which cells are expressed/not expressed in a tissue sample and their spatial location on the tissue sample.