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Multi-omics analysis identified and confirmed TNF-α as a key initiator of the inflammatory response following spinal cord injury.
Spinal cord injury (SCI) is a complex central nervous system (CNS) trauma that triggers multifaceted immune responses. In recent years, zinc has garnered considerable attention for its beneficial roles in anti-apoptosis and the attenuation of oxidative stress. However, the regulatory mechanisms by which zinc influence post-SCI immune-inflammatory responses remain insufficiently understood. In this study, we employed a multi-omics approach, combining transcriptomics, metabolomics, and single-cell RNA sequencing, to elucidate the mechanisms through which zinc ions modulate immune responses in injured spinal cord tissues. Our results demonstrate that zinc ions significantly regulate the expression of TNF-α signaling molecules. By inhibiting the TNF-α signaling pathway, zinc ions effectively mitigate apoptosis and reduce immune-inflammatory responses following SCI. Furthermore, through the integration of human and murine immune cell atlases, we performed a cluster analysis of key immune cell populations and constructed an immunological landscape of spinal cord tissues post‑zinc ion treatment. Notably, we identified microglia, key CNS immune cells, as exerting a strong anti-inflammatory effect by suppressing their TNF-α signaling activity. This study not only sheds light on the pivotal immune-inflammatory regulatory mechanisms of TNF-α signaling in zinc ion-mediated SCI therapy but also provides valuable theoretical and experimental insights for advancing preclinical research on SCI.
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Single-Cell Deconvolution of Head and Neck Squamous Cell Carcinoma.
Complexities in cell-type composition have rightfully led to skepticism and caution in the interpretation of bulk transcriptomic analyses. Recent studies have shown that deconvolution algorithms can be utilized to computationally estimate cell-type proportions from the gene expression data of bulk blood samples, but their performance when applied to tumor tissues, including those from head and neck, remains poorly characterized. Here, we use single-cell data (~6000 single cells) collected from 21 head and neck squamous cell carcinoma (HNSCC) samples to generate cell-type-specific gene expression signatures. We leverage bulk RNA-seq data from >500 HNSCC samples profiled by The Cancer Genome Atlas (TCGA), and using single-cell data as a reference, apply two newly developed deconvolution algorithms (CIBERSORTx and MuSiC) to the bulk transcriptome data to quantitatively estimate cell-type proportions for each tumor in TCGA. We show that these two algorithms produce similar estimates of constituent/major cell-type proportions and that a high T-cell fraction correlates with improved survival. By further characterizing T-cell subpopulations, we identify that regulatory T-cells (Tregs) were the major contributor to this improved survival. Lastly, we assessed gene expression, specifically in the Treg population, and found that TNFRSF4 (Tumor Necrosis Factor Receptor Superfamily Member 4) was differentially expressed in the core Treg subpopulation. Moreover, higher TNFRSF4 expression was associated with greater survival, suggesting that TNFRSF4 could play a key role in mechanisms underlying the contribution of Treg in HNSCC outcomes.
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Osteopetrosis-like disorders induced by osteoblast-specific retinoic acid signaling inhibition in mice.
Osteopetrosis is an inherited metabolic disease, characterized by increased bone density and narrow marrow cavity. Patients with severe osteopetrosis exhibit abnormal bone brittleness, anemia, and infection complications, which commonly cause death within the first decade of life. Pathologically, osteopetrosis impairs not only the skeletal system, but also the hemopoietic and immune systems during development, while the underlying osteoimmunological mechanisms remain unclear. Osteoclastic mutations are regarded as the major causes of osteopetrosis, while osteoclast non-autonomous theories have been proposed in recent years with unclear underlying mechanisms. Retinoic acid (RA), the metabolite of Vitamin A, is an essential requirement for skeletal and hematopoietic development, through the activation of retinoic acid signaling. RA can relieve osteopetrosis symptoms in some animal models, while its effect on bone health is still controversial and the underlying mechanisms remain unclear. In this study, we constructed an osteoblast-specific inhibitory retinoic acid signaling mouse model and surprisingly found it mimicked the symptoms of osteopetrosis found in clinical cases: dwarfism, increased imperfectly-formed trabecular bone deposition with a reduced marrow cavity, thin cortical bone with a brittle skeleton, and hematopoietic and immune dysfunction. Micro-CT, the three-point bending test, and histological analysis drew a landscape of poor bone quality. Single-cell RNA sequencing (scRNA-seq) of the femur and RNA-seq of osteoblasts uncovered an atlas of pathological skeletal metabolism dysfunction in the mutant mice showing that osteogenesis was impaired in a cell-autonomous manner and osteoclastogenesis was impaired via osteoblast-osteoclast crosstalk. Moreover, scRNA-seq of bone marrow and flow cytometry of peripheral blood, spleen, and bone marrow uncovered pathology in the hematopoietic and immune systems in the mutant mice, mimicking human osteopetrosis. Results showed that hematopoietic progenitors and B lymphocyte differentiation were affected and the osteoblast-dominated cell crosstalk was impaired, which may result from transcriptional impairment of the ligands Pdgfd and Sema4d. In summary, we uncovered previously unreported pathogenesis of osteopetrosis-like disorder in mice with skeletal, hematopoietic, and immune system dysfunction, which was induced by the inhibition of retinoic acid signaling in osteoblasts, and sheds new insights into a potential treatment for osteopetrosis.
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The Novel-B-Cell-Related Gene Signature Predicts the Prognosis and Immune Status of Patients with Esophageal Carcinoma.
BACKGROUND: The current understanding of the prognostic significance of B cells and their role in the tumor microenvironment (TME) in esophageal carcinoma (ESCA) is limited. METHODS: We conducted a screening for B-cell-related genes through the analysis of single-cell transcriptome data. Subsequently, we developed a B-cell-related gene signature (BRGrisk) using LASSO regression analysis. Patients from The Cancer Genome Atlas cohort were divided into a training cohort and a test cohort. Patients were categorized into high- and low-risk groups based on their median BRGrisk scores. The overall survival was assessed using the Kaplan-Meier method, and a nomogram based on BRGrisk was constructed. Immune infiltration profiles between the risk groups were also compared. RESULTS: The BRGrisk prognostic model indicated significantly worse outcomes for patients with high BRGrisk scores (p < 0.001). The BRGrisk-based nomogram exhibited good prognostic performance. Analysis of immune infiltration revealed that patients in the high-BRGrisk group had notably higher levels of immune cell infiltration and were more likely to be in an immunoresponsive state. Enrichment analysis showed a strong correlation between the prognostic gene signature and cancer-related pathways. IC50 results indicated that patients in the low-BRGrisk group were more responsive to common drugs compared to those in the high-BRGrisk group. CONCLUSIONS: This study presents a novel BRGrisk that can be used to stratify the prognosis of ESCA patients and may offer guidance for personalized treatment strategies aimed at improving prognosis.
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Aggrephagy-related gene signature correlates with survival and tumor-associated macrophages in glioma: Insights from single-cell and bulk RNA sequencing.
BACKGROUND: Aggrephagy is a lysosome-dependent process that degrades misfolded protein condensates to maintain cancer cell homeostasis. Despite its importance in cellular protein quality control, the role of aggrephagy in glioma remains poorly understood. OBJECTIVE: To investigate the expression of aggrephagy-related genes (ARGs) in glioma and in different cell types of gliomas and to develop an ARGs-based prognostic signature to predict the prognosis, tumor microenvironment, and immunotherapy response of gliomas. METHODS: ARGs were identified by searching the Reactome database. We developed the ARGs-based prognostic signature (ARPS) using data from the Cancer Genome Atlas (TCGA, n = 669) by Lasso-Cox regression. We validated the robustness of the signature in clinical subgroups and CGGA cohorts (n = 970). Gene set enrichment analysis (GSEA) was used to identify the pathways enriched in ARPS subgroups. The correlations between ARGs and macrophages were also investigated at single cell level. RESULTS: A total of 44 ARGs showed heterogeneous expression among different cell types of gliomas. Five ARGs (HSF1, DYNC1H1, DYNLL2, TUBB6, TUBA1C) were identified to develop ARPS, an independent prognostic factor. GSEA showed gene sets of patients with high-ARPS were mostly enriched in cell cycle, DNA replication, and immune-related pathways. High-ARPS subgroup had higher immune cell infiltration states, particularly macrophages, Treg cells, and neutrophils. APRS had positive association with tumor mutation burden (TMB) and immunotherapy response predictors. At the single cell level, we found ARGs correlated with macrophage development and identified ARGs-mediated macrophage subtypes with distinct communication characteristics with tumor cells. VIM+ macrophages were identified as pro-inflammatory and had higher interactions with malignant cells. CONCLUSION: We identified a novel signature based on ARGs for predicting glioma prognosis, tumor microenvironment, and immunotherapy response. We highlight the ARGs-mediated macrophages in glioma exhibit classical features.
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Integrated multi-omics analysis reveals common genetic architecture between ulcerative colitis and psoriasis.
BACKGROUND: Ulcerative colitis (UC) and psoriasis (PS) are both chronic inflammatory disorders that frequently occur together in clinical settings. Nevertheless, the common genetic basis and biological mechanisms underlying this comorbidity remain insufficiently understood. METHODS: We integrated genome-wide association study summary data with UC and PS single-cell transcriptomic data and performed reference-atlas-based spatial mapping using an E16.5 mouse embryonic spatial transcriptomic atlas to comprehensively investigate their shared genetic relationships, polygenic overlap, tissue-specific enrichment, reference-atlas-based anatomical enrichment patterns, disease-relevant cell populations, and potential candidate genes. RESULTS: Our analyses demonstrated a significant common genetic foundation between UC and PS at both the global and local genomic scales, together with marked polygenic sharing. Enrichment and reference-atlas-based analyses suggested that UC- and PS-associated genetic signals converged on immune-, intestinal- and epidermis-related tissue contexts. Integration of the four-component descriptive prioritization framework identified T cells among the prioritized candidate cell types in both diseases, with concordant support from the CELLECT-S-LDSC and CELLECT-MAGMA components. In addition, several candidate genes, including PARK7, C2orf74, PUS10, and TNFSF15, were prioritized, among which PARK7 showed significant case-control differential expression in T-cell subsets in both UC and PS. CONCLUSION: These findings suggest that UC and PS may share genetic and biological features across tissue and cellular contexts. This study provides a hypothesis-generating framework for investigating their comorbidity and highlights candidate genes with potential therapeutic relevance.
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MicroRNA-155 coordinates the immunological landscape within murine melanoma and correlates with immunity in human cancers.
miR-155 has recently emerged as an important promoter of antitumor immunity through its functions in T lymphocytes. However, the impact of T cell-expressed miR-155 on immune cell dynamics in solid tumors remains unclear. In the present study, we used single-cell RNA sequencing to define the CD45+ immune cell populations at different time points within B16F10 murine melanoma tumors growing in either wild-type or miR-155 T cell conditional knockout (TCKO) mice. miR-155 was required for optimal T cell activation and reinforced the T cell response at the expense of infiltrating myeloid cells. Further, myeloid cells from tumors growing in TCKO mice were defined by an increase in wound healing genes and a decreased IFN-γ-response gene signature. Finally, we found that miR-155 expression predicted a favorable outcome in human melanoma patients and was associated with a strong immune signature. Moreover, gene expression analysis of The Cancer Genome Atlas (TCGA) data revealed that miR-155 expression also correlates with an immune-enriched subtype in 29 other human solid tumors. Together, our study provides an unprecedented analysis of the cell types and gene expression signatures of immune cells within experimental melanoma tumors and elucidates the role of miR-155 in coordinating antitumor immune responses in mammalian tumors.
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Single cell atlas of lung-resident innate lymphoid cells shows impact of age and dysbiosis on epigenetic and transcriptomic programming.
The mechanisms underlying innate lymphoid cell (ILC) development and function in the neonatal lung remain incompletely defined. ILCs are critical mediators of early-life innate immune responses in the lung. Dysregulation of ILC homeostasis has both immediate and long-lasting effects on lung health. We generated single-cell transcriptomic and epigenetic datasets from the lungs of neonatal and young adult mice that includes subsets of type 1 (natural killer, NK cells) type 2 (ILC2) and type 3 (ILC3) cells. These datasets include mice subjected to early life antibiotic-induced dysbiosis, thereby modeling a common perturbation of the developing immune system in humans. Analysis of cell-cell communication and gene regulation in these datasets reveals underappreciated aspects of lung ILC biology, including marked interleukin-4 (IL-4) signaling in neonatal lung ILC2. This data represents a valuable resource for hypothesis generation regarding the molecular regulation of ILC gene expression and function in the neonatal lung.
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Cuproptosis-related gene CEP55 as a biomarker of pancreatic adenocarcinoma via multi-omics techniques and experimental validation.
BACKGROUND: Background. Pancreatic adenocarcinoma (PAAD) is a malignancy with a very poor prognosis. The clinical significance of cuproptosis in PAAD combining single cell data with The Cancer Genome Atlas (TCGA) data is unclear. MATERIALS AND METHODS: In this study, we first identified gene modules associated with cuproptosis by performing single-cell analysis and weighted co-expression network analysis (WCGNA). According to TCGA data, Cox regression and LASSO regression analysis were used to establish prognostic models, and PAAD patients were divided into high-risk and low-risk groups according to cuproptosis-related risk score. Then 7 algorithms were used to evaluate cancer immune microenvironment, followed by the mutation analysis. The expression levels and prognostic significance of the 8 model genes were analysed using single-gene analysis, Kaplan-Meier survival plots, and quantitative PCR (qPCR) validation. Finally, the biological function of CEP55 in PAAD was verified by in vitro experiments. RESULTS: We identified cuproptosis-related genes (CRG) in PAAD by performing single-cell analysis and WCGNA, and constructed a cuproptosis-related prognostic model of PAAD by comprehensive bioinformatics analyses. Based on cuproptosis-related risk score, there were significant differences in survival time between two groups. We further constructed a cuproptosis-related risk score-based nomogram to accurately assess PAAD patient prognosis. Immune infiltration analysis revealed that PAAD samples with higher cuproptosis-related scores exhibited significantly lower immune infiltration levels, which may mechanistically underlie their poorer clinical outcomes. Furthermore, the high-risk group had a higher mutation rate of the same mutated gene, which means that they are more likely to benefit from immunotherapy. Finally, we identified that CEP55 was significantly overexpressed in PAAD and correlated with poor patient prognosis. In vitro knockdown of CEP55 effectively suppressed proliferation and invasion capabilities in pancreatic cancer cell lines. CONCLUSIONS: In this study, a novel prognostic model of PAAD was constructed to evaluate the prognosis and immune microenvironment of PAAD patients, and CEP55 was identified as a central gene of PAAD. In vitro studies verified the biological function of CEP55, providing a new potential target for the treatment of PAAD.
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STAMP: Single-cell transcriptomics analysis and multimodal profiling through imaging.
Single-cell RNA sequencing has revolutionized our understanding of cellular diversity but remains constrained by scalability, high costs, and the destruction of cells during analysis. To overcome these challenges, we developed STAMP (single-cell transcriptomics analysis and multimodal profiling), a highly scalable approach for the profiling of single cells. By leveraging transcriptomics and proteomics imaging platforms, STAMP eliminates sequencing costs, enabling cost-efficient single-cell genomics of millions of cells. Immobilizing (stamping) cells in suspension onto imaging slides, STAMP supports multimodal (RNA, protein, and H&E) profiling, while retaining cellular structure and morphology. We demonstrate STAMP's versatility by profiling peripheral blood mononuclear cells, cell lines, and stem cells. We highlight the capability of STAMP to identify ultra-rare cell populations, simulate clinical applications, and show its utility for large-scale perturbation studies. In total, we present data for 10,962,092 high-quality cells/nuclei and 6,030,429,954 transcripts. STAMP makes high-resolution cellular profiling more accessible, scalable, and affordable.