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Identification and verification of immune-related gene prognostic signature based on ssGSEA for breast cancer.
INTRODUCTION: Breast cancer (BC) is the most common cancer in women worldwide and has a high mortality rate. The fact that the tumor microenvironment affects clinical outcomes of all types of cancers underlines the involvement of various immune-related genes (IRGs). Therefore, this study aimed to establish an IRGs-based signature for the prognosis of BC patients. MATERIAL AND METHODS: In this study, 12 immune cell infiltrating degrees in 1,102 BC cases from The Cancer Genome Atlas (TCGA) database were assessed, and RNA-sequencing (RNA-seq) data of these samples were analyzed by single-sample gene set enrichment analysis (ssGSEA). Based on the results, high, low, and middle immune infiltrating clusters were constructed. A total of 138 overlapped differentially expressed genes (DEGs) were identified in the high and low infiltrating clusters, as well as in normal and BC samples. Univariate Cox regression and LASSO analyses were also performed. Furthermore, GSEA suggested some highly enriched pathways in the different immune infiltrating clusters, leading to a better understanding of potential mechanisms of immune infiltration in BC. RESULTS: Finally, 19 immune-related genes were identified that could be utilized as a potential prognostic biomarker for BC. Kaplan-Meier plot and ROC curve, univariate as well as multivariate Cox analyses were carried out, which suggested that the 19-IRG-based signature is a significant prognosis factor independent of clinical features. Based on the analysis of protein-protein interactions (PPI), the three hub genes were identified. CONCLUSIONS: These results provide a new method to predict the prognosis and survival of BC based on the three genes' features.
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Nidogen-2 (NID2) is a Key Factor in Collagen Causing Poor Response to Immunotherapy in Melanoma.
BACKGROUND: The incidence of cutaneous melanoma continues to rise rapidly and has an extremely poor prognosis. Immunotherapy strategies are the most effective approach for patients who have developed metastases, but not all cases have been successful due to the complex and variable mechanisms of melanoma response to immune checkpoint inhibition. METHODS: We synthesized collagen-coding gene expression data (second-generation and single-cell sequencing) from public Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Bioinformatics analysis was performed using R software and several database resources such as Metascape database, Gene Set Cancer Analysis (GSCA) database, and Cytoscape software, etc., to investigate the biological mechanisms that may be related with collagens. Immunofluorescence and immunohistochemical staining were used to validate the expression and localization of Nidogen-2 (NID2). RESULTS: Melanoma patients can be divided into two collagen clusters. Patients with high collagen levels (C1) had a shorter survival than those with low collagen levels (C2) and were less likely to benefit from immunotherapy. We demonstrated that NID2 is a potential key factor in the collagen phenotype, is involved in fibroblast activation in melanoma, and forms a barrier to limit the proximity of CD8+ T cells to tumor cells. CONCLUSION: We clarified the adverse effects of collagen on melanoma patients and identified NID2 as a potential therapeutic target.
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Comparative single-cell multiome identifies evolutionary changes in neural progenitor cells during primate brain development.
Understanding the cellular and genetic mechanisms driving human-specific features of cortical development remains a challenge. We generated a cell-type resolved atlas of transcriptome and chromatin accessibility in the developing macaque and mouse prefrontal cortex (PFC). Comparing with published human data, our findings demonstrate that although the cortex cellular composition is overall conserved across species, progenitor cells show significant evolutionary divergence in cellular properties. Specifically, human neural progenitors exhibit extensive transcriptional rewiring in growth factor and extracellular matrix (ECM) pathways. Expression of the human-specific progenitor marker ITGA2 in the fetal mouse cortex increases the progenitor proliferation and the proportion of upper-layer neurons. These transcriptional divergences are primarily driven by altered activity in the distal regulatory elements. The chromatin regions with human-gained accessibility are enriched with human-specific sequence changes and polymorphisms linked to intelligence and neuropsychiatric disorders. Our results identify evolutionary changes in neural progenitors and putative gene regulatory mechanisms shaping primate brain evolution.
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Single-cell landscape of peripheral and tumor-infiltrating immune cells in HPV-negative HNSCC.
Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide. HPV-negative HNSCC, arising in diverse upper airway mucosal niches, is particularly aggressive, with poor 5-y survival and a limited response to immune checkpoint inhibitors. A deeper understanding of the tumor-localized immune landscape is essential to uncover actionable immunotherapeutic targets. Here, we integrated two single-cell RNA sequencing (scRNA-seq) datasets from 29 samples totaling nearly 300,000 immune cells to dissect immune rewiring during tumor progression and lymph node metastasis in HPV-negative HNSCC. We identified distinct shifts in adaptive immune cell populations across 14 peripheral blood mononuclear cell (PBMC) and 21 tumor-infiltrating immune cell (TIC) states. Notably, TICs exhibited enriched interferon response and immunomodulatory gene signatures, in contrast to PBMCs, indicating tumor-specific immune imprinting. Ligand-receptor analysis revealed that immunosuppressive crosstalk between macrophages and cytotoxic cells was associated with advanced disease. To spatially validate these transcriptional states, we conducted multiplexed immunofluorescence profiling on nine locally invasive HPV-negative HNSCCs, all from the ventrolateral tongue mucosa. Spatial proteomics confirmed peritumoral enrichment of activated (CD107a+, ICOS+) NK and CD8+ T cells and intratumoral accumulation of exhausted (PD-1+, PD-L1+) phenotypes, mirroring pseudotime trajectories inferred from scRNA-seq. These findings highlight spatially localized cytotoxic cell exhaustion as a key immune evasion mechanism in HPV-negative HNSCC and underscore the value of integrating spatial and single-cell data to reveal therapeutic vulnerabilities.
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Single-cell atlas of epithelial and stromal cell heterogeneity by lobe and strain in the mouse prostate.
BACKGROUND: Evaluating the complex interplay of cell types in the tissue microenvironment is critical to understanding the origin and progression of diseases in the prostate and potential opportunities for intervention. Mouse models are an essential tool to investigate the molecular and cell-type-specific contributions of prostate disease at an organismal level. While there are well-documented differences in the extent, timing, and nature of disease development in various genetically engineered and exposure-based mouse models in different mouse strains and prostate lobes within each mouse strain, the underlying molecular phenotypic differences in cell types across mouse strains and prostate lobes are incompletely understood. METHODS: In this study, we used single-cell RNA-sequencing (scRNA-seq) methods to assess the single-cell transcriptomes of 6-month-old mouse prostates from two commonly used mouse strains, friend virus B/NIH jackson (FVB/NJ) (N = 2) and C57BL/6J (N = 3). For each mouse, the lobes of the prostate were dissected (anterior, dorsal, lateral, and ventral), and individual scRNA-seq libraries were generated. In situ and pathological analyses were used to explore the spatial and anatomical distributions of novel cell types and molecular markers defining these cell types. RESULTS: Data dimensionality reduction and clustering analysis of scRNA-seq data revealed that basal and luminal cells possessed strain-specific transcriptomic differences, with luminal cells also displaying marked lobe-specific differences. Gene set enrichment analysis comparing luminal cells by strain showed enrichment of proto-Oncogene targets in FVB/NJ mice. Additionally, three rare populations of epithelial cells clustered independently of strain and lobe: one population of luminal cells expressing Foxi1 and components of the vacuolar ATPase proton pump (Atp6v0d2 and Atp6v1g3), another population expressing Psca and other stem cell-associated genes (Ly6a/Sca-1, Tacstd2/Trop-2), and a neuroendocrine population expressing Chga, Chgb, and Syp. In contrast, stromal cell clusters, including fibroblasts, smooth muscle cells, endothelial cells, pericytes, and immune cell types, were conserved across strain and lobe, clustering largely by cell type and not by strain or lobe. One notable exception to this was the identification of two distinct fibroblast populations that we term subglandular fibroblasts and interstitial fibroblasts based on their strikingly distinct spatial distribution in the mouse prostate. CONCLUSIONS: Altogether, these data provide a practical reference of the transcriptional profiles of mouse prostate from two commonly used mouse strains and across all four prostate lobes.
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Identifying ARRB2 as a Prognostic Biomarker and Key Player in the Tumor Microenvironment of Pancreatic Cancer through scPagwas Methodology.
INTRODUCTION: Pancreatic Cancer (PC) is recognized as a highly aggressive malignancy and is anticipated to become the second leading cause of cancer-associated deaths across the United States by 2030. Owing to its late-stage diagnosis and the substantial risk of metastasis, current therapeutic strategies exhibit limited efficacy, resulting in a five-year survival rate below 10%. Consequently, identifying reliable biomarkers and therapeutic approaches remains imperative for enhancing treatment effectiveness. METHODS: In this study, using the data of Cancer Genome Atlas (TCGA) and Genome-Wide Association Study (GWAS), we identified macrophage subsets and key gene arrb2 closely related to the progression of Pancreatic Adenocarcinoma (PAAD) via the scpagwas method combined with single- cell and bulk transcriptome analysis. RESULTS: The results showed that in macrophage subpopulations closely related to disease progression, the ARRB2 gene was significantly associated with the prognosis of patients, and low expression suggested poor survival outcomes. The high-expression subgroup of ARRB2 exhibited higher sensitivity to a variety of drugs, and i-bet-762 showed strong molecular binding ability with ARRB2. The experimental detection further confirmed the low expression of ARRB2 in PAAD tissue, which provided the basis for its use as a prognostic marker and potential therapeutic target. DISCUSSION: The results of this study suggest that ARRB2 is not only a prognostic biomarker of PAAD but may also be involved in the regulation of metabolic and immune pathways, thereby affecting drug responsiveness. There was a significant difference in drug sensitivity between the high and low-expression subgroups of ARRB2, suggesting that there may be a potential mechanism between the signal pathway and the therapeutic effect, which warrants further functional research. Considering the heterogeneity of the macrophage population and its dual role in tumor promotion and inhibition, in-depth analysis of the context-dependent function of ARRB2 in the immune-rich microenvironment is expected to provide new insights for the development of combination therapy, especially the potential of combining it with BET inhibitors (such as i-bet-762). CONCLUSION: Macrophages, along with ARRB2, serve an essential function in the progression of PAAD and immune regulation. The identification of ARRB2 as a prognostic biomarker and its involvement in critical oncogenic pathways furnish a theoretical foundation for targeted therapeutic interventions. These discoveries contribute to the ongoing exploration of diagnostic, prognostic, and treatment strategies for PAAD.
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Targeting LHPP in neoadjuvant chemotherapy resistance of gastric cancer: insights from single-cell and multi-omics data on tumor immune microenvironment and stemness characteristics.
Gastric cancer (GC) is a highly heterogeneous and complex malignancy, often characterized by tumor stemness and immune evasion mechanisms, which contribute to a poor response to neoadjuvant chemotherapy (NAC) and treatment resistance. In this study, we performed a comprehensive analysis using single-cell and multi-omics approaches on 375 GC samples from The Cancer Genome Atlas database, along with 141 clinical samples from patients who underwent NAC. We identified key gene modules associated with stemness and immune traits, and developed a novel stem cell-immune risk score. This score effectively distinguished responders from non-responders to chemotherapy, and was significantly associated with overall survival. Through multi-omics analysis, we further elucidated the role of phospholysine phosphohistidine inorganic pyrophosphatase (LHPP) in the tumor immune microenvironment. Our findings showed that high LHPP expression was closely linked to the increased infiltration of antitumor immune cells, such as CD8+ T cells, and significantly suppressed the development of stemness characteristics in GC. Additionally, single-cell sequencing data revealed that tumor epithelial cells with low LHPP expression exhibited heightened stemness and demonstrated the strongest communication with CD8+-exhausted T cells. We also observed that LHPP inhibited stemness and chemotherapy resistance in GC cells by regulating the phosphorylation of GSK-3β. In conclusion, LHPP plays a critical regulatory role in the stemness features and tumor immune microenvironment of GC, presenting a promising biomarker and potential therapeutic target for personalized treatment of GC.
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The Regulation Network of Glycerolipid Metabolism as Coregulators of Immunotherapy-Related Myocarditis.
BACKGROUND: To date, immunotherapy for patients with malignant tumors has shown a significant association with myocarditis. However, the mechanism of metabolic reprogramming changes for immunotherapy-related cardiotoxicity is still not well understood. METHODS: The CD45+ single-cell RNA sequencing (scRNA-seq) of the Pdcd1-/-Ctla4+/- and wild-type mouse heart in GSE213486 was downloaded to demonstrate the heterogeneity of immunocyte atlas in immunotherapy-related myocarditis. The liquid chromatography-tandem mass spectrometry (LC-MS/MS) spectrum metabolomics analysis detects the metabolic network differences. The drug prediction, organelle level interaction, mitochondrial level regulatory network, and phosphorylation site prediction for key regulators have also been screened via multibioinformatics analysis methods. RESULTS: The scRNA analysis shows that the T cell is the main regulatory cell subpopulation in the pathological progress of immunotherapy-related myocarditis. Mitochondrial regulation pathway significantly participated in pseudotime trajectory- (PTT-) related differential expressed genes (DEGs) in the T cell subpopulation. Additionally, both the gene set enrichment analysis (GSEA) of PTT-related DEGs and LC-MS/MS metabolomics analysis showed that mitochondrial-regulated glycerolipid metabolism plays a central role in metabolic reprogramming changes for immunotherapy-related cardiotoxicity. Finally, the hub-regulated protease of diacylglycerol kinase zeta (Dgkz) was significantly identified and widely played various roles in glycerolipid metabolism, oxidative phosphorylation, and lipid kinase activation. CONCLUSION: Mitochondrial-regulated glycerolipid metabolism, especially the DGKZ protein, plays a key role in the metabolic reprogramming of immunotherapy-related myocarditis.
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Rethinking the Estrogen Receptor Beta Dominance Hypothesis in Endometriosis: Insights from Single Cell RNA Sequencing Meta-analysis.
BACKGROUND: Endometriosis is a chronic, estrogen-dependent disease characterized by the presence of endometrial-like tissue growing outside the uterus. The molecular and clinical heterogeneity of endometriosis complicate diagnostic and treatment options -- diagnostic delays of seven to ten years are common and therapies often lack long-term efficacy. Estrogen signaling and estrogen receptor beta (ERβ) expression is thought to be increased in endometriosis, contributing to increased cell proliferation in lesions. The "ERβ dominance hypothesis" is a prevailing hypothesis in the field, setting ERβ as a high-priority therapeutic target. If effectively modulated, ERβ could be the first therapy to directly target lesion biology, rather than only managing symptoms. OBJECTIVES: We aimed to characterize ERβ's expression in endometriosis by cell type and evaluate its therapeutic relevance, primarily assessing the validity of the ERβ dominance hypothesis. STUDY DESIGN: We reanalyzed scRNAseq data from eight previously published studies. Our final filtered dataset included 557,061 cells, the largest endometriosis single cell atlas ever constructed. We quantified gene expression levels of ESR1 and ESR2, which encode ERɑ and ERβ respectively, across each tissue and cell type, to identify cell-type specific drivers of ESR2/ERβ expression across diseased and healthy tissues. To characterize the differences between cells that uniquely express ESR1 versus those that uniquely express ESR2, we performed differential gene expression and pathway enrichment analyses. RESULTS: Count and distribution analyses revealed no significant ESR2/ERβ dominance in any cell or tissue type by Fisher's Exact Tests and Wilcoxon Rank Sum Tests. Differential gene expression and pathway enrichment analyses suggest distinct roles of each estrogen receptor isoform. CONCLUSIONS: Overall, our results argue against a simplified model of ERβ dominance and instead propose a dual-isoform and cell and tissue-specific framework for understanding estrogen receptor signaling in endometriosis. These findings hold important implications for future therapeutic strategies. Specifically, treatments that target ERβ alone may fail to account for the functional role and relative abundance of ERα. In the future, therapeutic approaches that consider isoform-specific, tissue-specific, and cell-specific expression patterns may prove most effective in reducing recurrence and improving outcomes for patients.
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Pan-cancer single-cell atlas of immunotherapy response identifies ZNF385A as a regulator of immune evasion in small cell lung cancer.
Although immune checkpoint inhibitors (ICIs) have revolutionized the treatment landscape of solid tumors, response rates in patients with small cell lung cancer (SCLC) remain limited, and acquired resistance is highly prevalent. The underlying mechanisms of this immunotherapy resistance remain to be fully elucidated. Clinically, SCLC typically manifests as an "immune-cold" tumor, characterized by a low abundance of CD8+ T cell infiltration and the rare formation of tertiary lymphoid structures (TLS). While DNA damage repair (DDR) is closely linked to innate immune responses, how DDR networks orchestrate the SCLC immune microenvironment remains obscure. In this study, we integrated single-cell transcriptomic data (comprising 344,447 high-quality cells) from six cancer types (BCC, CRC, HCC, HNSCC, iCCA, and SCLC). Our comparative analysis revealed a fundamental depletion of TLS-associated cellular subpopulations (e.g., CXCL13+ CD8+ T cells, HLA-DRB5+ B cells, and CXCL9+ dendritic cells) in SCLC, which was significantly correlated with aberrant DDR activity. Through high-dimensional weighted gene co-expression network analysis (hdWGCNA), we identified ZNF385A as the core hub gene within the DDR-associated module. ZNF385A is highly expressed in SCLC and is associated with poorer prognosis. In vitro, ZNF385A depletion suppressed SCLC cell proliferation and induced apoptosis, accompanied by R-loop accumulation and activation of cGAS-STING signaling, indicating a potential link between ZNF385A, genomic stability and tumor-intrinsic innate immune signaling. Collectively, these findings identify ZNF385A as a potential regulator associated with TLS deficiency and immune evasion in SCLC.