Experimental Framework for Assessing Mouse Retinal Regeneration Through Single-Cell RNA-Sequencing.

Retinal degenerative diseases including age-related macular degeneration and glaucoma are estimated to currently affect more than 14 million people in the United States, with an increased prevalence of retinal degenerations in aged individuals. An expanding aged population who are living longer forecasts an increased prevalence and economic burden of visual impairments. Improvements to visual health and treatment paradigms for progressive retinal degenerations slow vision loss. However, current treatments fail to remedy the root cause of visual impairments caused by retinal degenerations-loss of retinal neurons. Stimulation of retinal regeneration from endogenous cellular sources presents an exciting treatment avenue for replacement of lost retinal cells. In multiple species including zebrafish and Xenopus, Müller glial cells maintain a highly efficient regenerative ability to reconstitute lost cells throughout the organism's lifespan, highlighting potential therapeutic avenues for stimulation of retinal regeneration in humans. Here, we describe how the application of single-cell RNA-sequencing (scRNA-seq) has enhanced our understanding of Müller glial cell-derived retinal regeneration, including the characterization of gene regulatory networks that facilitate/inhibit regenerative responses. Additionally, we provide a validated experimental framework for cellular preparation of mouse retinal cells as input into scRNA-seq experiments, including insights into experimental design and analyses of resulting data.

From single-cell to spatial transcriptomics: decoding the glioma stem cell niche and its clinical implications.

Background: Gliomas are aggressive brain tumors associated with a poor prognosis. Cancer stem cells (CSCs) play a significant role in tumor recurrence and resistance to therapy. This study aimed to identify and characterize glioma stem cells (GSCs), analyze their interactions with various cell types, and develop a prognostic signature. Methods: Single-cell RNA sequencing data from 44 primary glioma samples were analyzed to identify GSC populations. Spatial transcriptomics and gene regulatory network analyses were performed to investigate GSC localization and transcription factor activity. CellChat analysis was conducted to infer cell-cell communication patterns. A GSC signature (GSCS) was developed using machine learning algorithms applied to bulk RNA sequencing data from multiple cohorts. In vitro and in vivo experiments were conducted to validate the role of TUBA1C, a key gene within the signature. Results: A distinct GSC population was identified, characterized by high proliferative potential and an enrichment of E2F1, E2F2, E2F7, and BRCA1 regulons. GSCs exhibited spatial proximity to myeloid-derived suppressor cells (MDSCs). CellChat analysis revealed an active MIF signaling pathway between GSCs and MDSCs. A 26-gene GSCS demonstrated superior performance compared to existing prognostic models. Knockdown of TUBA1C significantly inhibited glioma cell migration, and invasion in vitro, and reduced tumor growth in vivo. Conclusion: This study offers a comprehensive characterization of GSCs and their interactions with MDSCs, while presenting a robust GSCS. The findings offer new insights into glioma biology and identify potential therapeutic targets, particularly TUBA1C, aimed at improving patient outcomes.

Single-cell RNA sequencing and immune repertoire analysis revealed dynamic immune characteristics associated with peripheral blood during sepsis.

Sepsis is a potentially fatal condition arising from an abnormal immune response to an infection, which can result in organ failure and even death. To explore the mechanism underlying the dysregulated immune response during sepsis and identify potential therapeutic targets, single-cell RNA sequencing (scRNA-seq) and immune repertoire analysis were conducted to depict the cellular landscape of peripheral blood cells in septic mice. We observed significant alterations in the number and proportion of peripheral blood cell populations driven by sepsis. By combining single-cell gene expression profiles and B cell receptor (BCR) repertoire analysis, we discerned that infection inflicted serious damage on the antigen presentation ability of B cells and the diversity of BCR in a short time. In addition, we found that the cecal ligation and puncture procedure in mice inhibited the communication signals of CD4+ and CD8+ T cells and decreased the interactions between B cells and other cells. Our study provides detailed insights into the dynamic changes in the biological characteristics of peripheral blood cells driven by sepsis and provides important advances in our understanding of immune disorders during sepsis.

Inflammation-induced loss of CFTR-expressing airway ionocytes in non-eosinophilic asthma.

BACKGROUND AND OBJECTIVE: Severe asthma is a heterogeneous disease with subtype classification according to dominant airway infiltrates, including eosinophilic (Type 2 high), or non-eosinophilic asthma. Non-eosinophilic asthma is further divided into paucigranulocytic or neutrophilic asthma characterized by elevated neutrophils, and mixed Type 1 and Type 17 cytokines in the airways. Severe non-eosinophilic asthma has few effective treatments and many patients do not qualify for biologic therapies. The cystic fibrosis transmembrane conductance regulator (CFTR) is dysregulated in multiple respiratory diseases including cystic fibrosis and chronic obstructive pulmonary disease and has proven a valuable therapeutic target. We hypothesized that the CFTR may also play a role in non-eosinophilic asthma. METHODS: Patient-derived human bronchial epithelial cells (hBECs) were isolated and differentiated at the air-liquid interface. Single cell RNA-sequencing (scRNAseq) was used to identify epithelial cell subtypes and transcriptional activity. Ion transport was investigated with Ussing chambers and immunofluorescent quantification of ionocyte abundance in human airway epithelial cells and murine models of asthma. RESULTS: We identified that hBECs from patients with non-eosinophilic asthma had reduced CFTR function, and did not differentiate into CFTR-expressing ionocytes compared to those from eosinophilic asthma or healthy donors. Similarly, ionocytes were also diminished in the airways of a murine model of neutrophilic-dominant but not eosinophilic asthma. Treatment of hBECs from healthy donors with a neutrophilic asthma-like inflammatory cytokine mixture led to a reduction in ionocytes. CONCLUSION: Inflammation-induced loss of CFTR-expressing ionocytes in airway cells from non-eosinophilic asthma may represent a key feature of disease pathogenesis and a novel drug target.

Discovery of GJC1 as a prognostic biomarker in glioma cells: insights into its cell-cycle relationship and differential expression in non-neuronal cells.

Background: Gliomas, originating from the most common non-neuronal cells in the brain (glial cells), are the most common brain tumors and are associated with high mortality and poor prognosis. Glioma cells exhibit a tendency to disrupt normal cell-cycle regulation, leading to abnormal proliferation and malignant growth. This study investigated the predictive potential of GJC1 in gliomas and explored its relationship with the cell cycle. Methods: Retrospective analysis of RNA-seq and single-cell sequencing data was conducted using the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases. The differential expression of GJC1 in gliomas with various pathological features and in different non-neuronal cell groups was analyzed. Functional data were examined using gene set variation analysis (GSVA). Furthermore, CellMiner was used to evaluate the relationship between GJC1 expression and predicted treatment response across these databases. Results: GJC1 expression was enriched in high-grade gliomas and 1p/19q non-codeletion gliomas. GJC1 enrichment was observed in classical and mesenchymal subtypes within the TCGA glioma subtype group. In single-cell subgroup analysis, GJC1 expression was higher in glioma tissues compared to other non-neuronal cells. Additionally, the TCGA classical subtype of glioma cells exhibited more GJC1 expression than the other subgroups. GJC1 emerged as an independent prognostic factor for overall survival in glioma. GSVA unveiled potential mechanisms by which GJC1 may impact cell-cycle regulation in glioma. Finally, a significant correlation was observed between GJC1 expression and the sensitivity of multiple anti-cancer drugs. Conclusion: These findings confirmed GJC1 as a novel biomarker and provided insights into the differential gene expression in non-neuronal cells and the impact of the cell cycle on gliomas. Consequently, GJC1 may be used to predict glioma prognosis and has potential therapeutic value.

ScRNAbox: empowering single-cell RNA sequencing on high performance computing systems.

BACKGROUND: Single-cell RNA sequencing (scRNAseq) offers powerful insights, but the surge in sample sizes demands more computational power than local workstations can provide. Consequently, high-performance computing (HPC) systems have become imperative. Existing web apps designed to analyze scRNAseq data lack scalability and integration capabilities, while analysis packages demand coding expertise, hindering accessibility. RESULTS: In response, we introduce scRNAbox, an innovative scRNAseq analysis pipeline meticulously crafted for HPC systems. This end-to-end solution, executed via the SLURM workload manager, efficiently processes raw data from standard and Hashtag samples. It incorporates quality control filtering, sample integration, clustering, cluster annotation tools, and facilitates cell type-specific differential gene expression analysis between two groups. We demonstrate the application of scRNAbox by analyzing two publicly available datasets. CONCLUSION: ScRNAbox is a comprehensive end-to-end pipeline designed to streamline the processing and analysis of scRNAseq data. By responding to the pressing demand for a user-friendly, HPC solution, scRNAbox bridges the gap between the growing computational demands of scRNAseq analysis and the coding expertise required to meet them.

Omics in allergy and asthma.

This review explores the transformative impact of omics technologies on allergy and asthma research in recent years, focusing on advancements in high-throughput technologies related to genomics and transcriptomics. In particular, the rapid spread of single-cell RNA sequencing has markedly advanced our understanding of the molecular pathology of allergic diseases. Furthermore, high-throughput genome sequencing has accelerated the discovery of monogenic disorders that were previously overlooked as ordinary intractable allergic diseases. We also introduce microbiomics, proteomics, lipidomics, and metabolomics, which are quickly growing areas of research interest, although many of their current findings remain inconclusive as solid evidence. By integrating these omics data, we will gain deeper insights into disease mechanisms, leading to the development of precision medicine approaches that promise to enhance treatment outcomes.

Integrating transcriptomics, eQTL, and Mendelian randomization to dissect monocyte roles in severe COVID-19 and gout flare.

Introduction: There are considerable similarities between the pathophysiology of gout flare and the dysregulated inflammatory response in severe COVID-19 infection. Monocytes are the key immune cells involved in the pathogenesis of both diseases. Therefore, it is critical to elucidate the molecular basis of the function of monocytes in gout and COVID-19 in order to develop more effective therapeutic approaches. Methods: The single-cell RNA sequencing (scRNA-seq), large-scale genome-wide association studies (GWAS), and expression quantitative trait loci (eQTL) data of gout and severe COVID-19 were comprehensively analyzed. Cellular heterogeneity and intercellular communication were identified using the scRNA-seq datasets, and the monocyte-specific differentially expressed genes (DEGs) between COVID-19, gout and normal subjects were screened. In addition, the correlation of the DEGs with severe COVID-19 and gout flare was analyzed through GWAS statistics and eQTL data. Results: The scRNA-seq analysis exhibited that the proportion of classical monocytes was increased in both severe COVID-19 and gout patient groups compared to healthy controls. Differential expression analysis and MR analysis showed that NLRP3 was positively associated with the risk of severe COVID-19 and involved 11 SNPs, of which rs4925547 was not significantly co-localized. In contrast, IER3 was positively associated with the risk of gout and involved 9 SNPs, of which rs1264372 was significantly co-localized. Discussion: Monocytes have a complex role in gout flare and severe COVID-19, which underscores the potential mechanisms and clinical significance of the interaction between the two diseases.

Effect of fentanyl on HIV expression in peripheral blood mononuclear cells.

Introduction: Illicit drug use, particularly the synthetic opioid fentanyl, presents a significant global health challenge. Previous studies have shown that fentanyl enhances viral replication; yet, the mechanisms by which it affects HIV pathogenesis remain unclear. This study investigated the impact of fentanyl on HIV replication in CD4+ T lymphocytes. Methods: CD4+ T lymphocytes from HIV-negative donors were activated, infected with HIVNL4-3, and treated with fentanyl. HIV proviral DNA and p24 antigen expression were quantified using real-time PCR and ELISA, respectively. Single-cell RNA libraries were analyzed to identify differentially expressed genes. Results: Results indicated that fentanyl treatment increased HIV p24 expression and proviral DNA levels, and naltrexone mitigated these effects. Single-cell RNAseq analysis identified significantly altered gene expression in CD4+ T lymphocytes. Discussion: The results of our findings suggest that fentanyl promotes HIV replication ex vivo, emphasizing the need for a deeper understanding of opioid-virus interactions to develop better treatment strategies for individuals with HIV and opioid use disorder.

Revealing the association between East Asian oral microbiome and colorectal cancer through Mendelian randomization and multi-omics analysis.

Background: Colorectal cancer (CRC) poses a global health threat, with the oral microbiome increasingly implicated in its pathogenesis. This study leverages Mendelian Randomization (MR) to explore causal links between oral microbiota and CRC using data from the China National GeneBank and Biobank Japan. By integrating multi-omics approaches, we aim to uncover mechanisms by which the microbiome influences cellular metabolism and cancer development. Methods: We analyzed microbiome profiles from 2017 tongue and 1915 saliva samples, and GWAS data for 6692 CRC cases and 27178 controls. Significant bacterial taxa were identified via MR analysis. Single-cell RNA sequencing and enrichment analyses elucidated underlying pathways, and drug predictions identified potential therapeutics. Results: MR identified 19 bacterial taxa significantly associated with CRC. Protective effects were observed in taxa like RUG343 and Streptococcus_umgs_2425, while HOT-345_umgs_976 and W5053_sp000467935_mgs_712 increased CRC risk. Single-cell RNA sequencing revealed key pathways, including JAK-STAT signaling and tyrosine metabolism. Drug prediction highlighted potential therapeutics like Menadione Sodium Bisulfite and Raloxifene. Conclusion: This study establishes the critical role of the oral microbiome in colorectal cancer development, identifying specific microbial taxa linked to CRC risk. Single-cell RNA sequencing and drug prediction analyses further elucidate key pathways and potential therapeutics, providing novel insights and personalized treatment strategies for CRC.

UCHL1 Overexpression Is Related to the Aggressive Phenotype of Non-small Cell Lung Cancer.

BACKGROUND: Ubiquitin C-terminal hydrolase L1 (UCHL1), which encodes thiol protease that hydrolyzes a peptide bond at the C-terminal glycine residue of ubiquitin, regulates cell differentiation, proliferation, transcriptional regulation, and numerous other biological processes and may be involved in lung cancer progression. UCHL1 is mainly expressed in the brain and plays a tumor-promoting role in a few cancer types; however, there are limited reports regarding its role in lung cancer. METHODS: Single-cell RNA (scRNA) sequencing using 10X chromium v3 was performed on a paired normal-appearing and tumor tissue from surgical specimens of a patient who showed unusually rapid progression. To validate clinical implication of the identified biomarkers, immunohistochemical (IHC) analysis was performed on 48 non-small cell lung cancer (NSCLC) tissue specimens, and the correlation with clinical parameters was evaluated. RESULTS: We identified 500 genes overexpressed in tumor tissue compared to those in normal tissue. Among them, UCHL1, brain expressed X-linked 3 (BEX3), and midkine (MDK), which are associated with tumor growth and progression, exhibited a 1.5-fold increase in expression compared to that in normal tissue. IHC analysis of NSCLC tissues showed that only UCHL1 was specifically overexpressed. Additionally, in 48 NSCLC specimens, UCHL1 was specifically upregulated in the cytoplasm and nuclear membrane of tumor cells. Multivariable logistic analysis identified several factors, including smoking, tumor size, and high-grade dysplasia, to be typically associated with UCHL1 overexpression. Survival analyses using The Cancer Genome Atlas (TCGA) datasets revealed that UCHL1 overexpression is substantially associated with poor survival outcomes. Furthermore, a strong association was observed between UCHL1 expression and the clinicopathological features of patients with NSCLC. CONCLUSION: UCHL1 overexpression was associated with smoking, tumor size, and high-grade dysplasia, which are typically associated with a poor prognosis and survival outcome. These findings suggest that UCHL1 may serve as an effective biomarker of NSCLC.

Immunometabolic changes and potential biomarkers in CFS peripheral immune cells revealed by single-cell RNA sequencing.

The pathogenesis of Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) remains unclear, though increasing evidence suggests inflammatory processes play key roles. In this study, single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) was used to decipher the immunometabolic profile in 4 ME/CFS patients and 4 heathy controls. We analyzed changes in the composition of major PBMC subpopulations and observed an increased frequency of total T cells and a significant reduction in NKs, monocytes, cDCs and pDCs. Further investigation revealed even more complex changes in the proportions of cell subpopulations within each subpopulation. Gene expression patterns revealed upregulated transcription factors related to immune regulation, as well as genes associated with viral infections and neurodegenerative diseases.CD4+ and CD8+ T cells in ME/CFS patients show different differentiation states and altered trajectories, indicating a possible suppression of differentiation. Memory B cells in ME/CFS patients are found early in the pseudotime, indicating a unique subtype specific to ME/CFS, with increased differentiation to plasma cells suggesting B cell overactivity. NK cells in ME/CFS patients exhibit reduced cytotoxicity and impaired responses, with reduced expression of perforin and CD107a upon stimulation. Pseudotime analysis showed abnormal development of adaptive immune cells and an enhanced cell-cell communication network converging on monocytes in particular. Our analysis also identified the estrogen-related receptor alpha (ESRRA)-APP-CD74 signaling pathway as a potential biomarker for ME/CFS in peripheral blood. In addition, data from the GSE214284 database confirmed higher ESRRA expression in the monocyte cell types of male ME/CFS patients. These results suggest a link between immune and neurological symptoms. The results support a disease model of immune dysfunction ranging from autoimmunity to immunodeficiency and point to amyloidotic neurodegenerative signaling pathways in the pathogenesis of ME/CFS. While the study provides important insights, limitations include the modest sample size and the evaluation of peripheral blood only. These findings highlight potential targets for diagnostic biomarkers and therapeutic interventions. Further research is needed to validate these biomarkers and explore their clinical applications in managing ME/CFS.

Integrative cross-species transcriptome analysis reveals earlier occurrence of myelopoiesis in pre-circulation primates compared to mice.

Hematopoiesis originates in the yolk sac, which forms prior to the establishment of blood circulation and exhibits distinct developmental processes between primates and mice. Despite increasing appreciation of yolk sac hematopoiesis for its lifelong contribution to the adult hematopoietic system and its regulatory roles in organogenesis, cross-species differences, particularly before the onset of blood circulation, remain incompletely understood. In this study, we constructed an integrative cross-species transcriptome atlas of pre-circulation hematopoiesis in humans, monkeys ( Macaca fascicularis), and mice. This analysis identified conserved populations between primates and mice, while also revealing more differentiated myeloid, erythroid, and megakaryocytic lineages in pre-circulation primates compared to mice. Specifically, SPP1-expressing macrophages were detected in primates before the onset of blood circulation but were absent in mice. Cell-cell communication analysis identified CSF1 + extraembryonic mesoderm cells as a potential supportive niche for macrophage generation, with ligand-receptor interactions between macrophages and other cell populations in the human yolk sac. Interestingly, pre-circulation SPP1 + macrophages exhibited hallmark signatures reminiscent of a macrophage subset that positively regulates hematopoietic stem cell generation. Our findings provide a valuable cross-species resource, advancing our understanding of human pre-circulation yolk sac hematopoiesis and offering a theoretical basis for the regeneration of functional blood cells.

Single-cell RNA sequencing reveals heterogeneity of ALI model and epithelial cell alterations after exposure to electronic cigarette aerosol.

Electronic cigarettes (e-cigarettes) have been advertised as a healthier alternative to traditional cigarettes; however, their exact effects on the bronchial epithelium are poorly understood. Air-liquid interface culture human bronchial epithelium (ALI-HBE) contains various cell types, including basal cell, ciliated cell and secretory cell, providing an in vitro model that simulates the biological characteristics of normal bronchial epithelium. Multiplex single-cell RNA sequencing of ALI-HBE was used to reveal previously unrecognized transcriptional heterogeneity within the human bronchial epithelium and cell type-specific responses to acute exposure to e-cigarette aerosol (e-aerosol) containing distinct components (nicotine and/or flavoring). The findings of our study show that nicotine-containing e-aerosol affected gene expression related to transformed basal cells into secretory cells after acute exposure; inhibition of secretory cell function by down-regulating genes related to epithelial cell differentiation, calcium ion binding, extracellular exosomes, and secreted proteins; and enhanced interaction between secretory cells and other cells. On the other hand, flavoring may alter the growth pattern of epithelial cells and make basal cells more susceptible to SARS-CoV infection. Besides, the data also indicate factors that may promote SARS-CoV-2 infection and suggest therapeutic targets for restoring normal bronchial epithelium function after e-cigarette use. In summary, the current study offered fresh perspectives on alterations in the cellular landscape and cell type-specific responses in human bronchial epithelium that are brought about by e-cigarette use.

Prognostic modeling and Emerging therapeutic targets Unveiled through single-cell sequencing in esophageal squamous Cell carcinoma.

ESCC presents a significant global health challenge due to its high mortality rates and varying responses to treatment. This underscores the critical need for novel diagnostic and predictive biomarkers to improve treatment outcomes. Initially, we conducted single-cell transcriptome sequencing on a total of 128,688 cells obtained from 10 patients as part of our research. Utilizing machine learning and cross-validation techniques, we developed a model incorporating 12 genes that distinguish malignant cells from non-malignant ones. In vitro, we explored the effects of IGFBP2 knockdown on the proliferation, invasion, and migration of ESCC cells. The clinical relevance of IGFBP2 was confirmed through IHC and Kaplan-Meier survival analyses. Furthermore, using bioinformatics tools such as GSVA and xCell on public databases, we discovered that high expression of IGFBP2 is associated with an immunosuppressive tumor microenvironment in ESCC, characterized by reduced CD8+ T cell infiltration. This was validated then through IHC. In summary, our study integrates single-cell sequencing and sophisticated computational techniques to highlight IGFBP2 as a promising biomarker and therapeutic target in ESCC.

Altered immune cell in human severe acute pancreatitis revealed by single-cell RNA sequencing.

Background: Severe acute pancreatitis (SAP) is characterized by inflammation, with inflammatory immune cells playing a pivotal role in disease progression. This study aims to understand variations in specific immune cell subtypes in SAP, uncover their mechanisms of action, and identify potential biological markers for predicting Acute Pancreatitis (AP) severity. Methods: We collected peripheral blood from 7 untreated SAP patients and employed single-cell RNA sequencing for the first time to construct a transcriptome atlas of peripheral blood mononuclear cells (PBMCs) in SAP. Integrating SAP transcriptomic data with 6 healthy controls from the GEO database facilitated the analysis of immune cell roles in SAP. We obtained comprehensive transcriptomic datasets from AP samples in the GEO database and identified potential biomarkers associated with AP severity using the "Scissor" tool in single-cell transcriptomic data. Results: This study presents the inaugural construction of a peripheral blood single-cell atlas for SAP patients, identifying 20 cell subtypes. Notably, there was a significant decrease in effector T cell subsets and a noteworthy increase in monocytes compared to healthy controls. Moreover, we identified a novel monocyte subpopulation expressing high levels of PPBP and PF4 which was significantly elevated in SAP. The proportion of monocyte subpopulations with high CCL3 expression was also markedly increased compared to healthy controls, as verified by flow cytometry. Additionally, cell communication analysis revealed insights into immune and inflammation-related signaling pathways in SAP patient monocytes. Finally, our findings suggest that the subpopulation with high CCL3 expression, along with upregulated pro-inflammatory genes such as S100A12, IL1B, and CCL3, holds promise as biomarkers for predicting AP severity. Conclusion: This study reveals monocytes' crucial role in SAP initiation and progression, characterized by distinct pro-inflammatory features intricately linked to AP severity. A monocyte subpopulation with elevated PPBP and CCL3 levels emerges as a potential biomarker and therapeutic target.

Association of circulating cytokine levels and tissue-infiltrating myeloid cells with achalasia: results from Mendelian randomization and validation through clinical characteristics and single-cell RNA sequencing.

BACKGROUND: Achalasia is a rare motility disorder of the esophagus often accompanied by immune dysregulation, yet specific underlying mechanisms remain poorly understood. METHODS: We utilized Mendelian randomization (MR) to explore the causal effects of cytokine levels on achalasia, with cis-expression/protein quantitative trait loci (cis-eQTLs/pQTLs) for 47 cytokines selected from a genome-wide association study (GWAS) meta-analysis and GWAS data for achalasia obtained from FinnGen. For cytokines significantly linked to achalasia, we analyzed their plasma concentrations and expression differences in the lower esophageal sphincter (LES) using enzyme-linked immunosorbent assay and single-cell RNA sequencing (scRNA-seq) profiling, respectively. We further employed bioinformatics approaches to investigate underlying mechanisms. RESULTS: We revealed positive associations of circulating Eotaxin, macrophage inflammatory protein-1b (MIP1b), soluble E-selectin (SeSelectin) and TNF-related apoptosis-inducing ligand (TRAIL) with achalasia. When combining MR findings with scRNA-seq data, we observed upregulation of TRAIL (OR = 2.70, 95% CI, 1.20-6.07), encoded by TNFSF10, in monocytes and downregulation of interleukin-1 receptor antagonist (IL-1ra) (OR = 0.70, 95% CI 0.59-0.84), encoded by IL1RN, in FOS_macrophages in achalasia. TNFSF10high monocytes in achalasia displayed activated type I interferon signaling, and IL1RNlow FOS_macrophages exhibited increased intercellular communications with various lymphocytes, together shaping the proinflammatory microenvironment of achalasia. CONCLUSIONS: We identified circulating Eotaxin, MIP1b, SeSelectin and TRAIL as potential drug targets for achalasia. TNFSF10high monocytes and IL1RNlow macrophages may play a role in the pathogenesis of achalasia.

Identification and Verification of Key Genes in Colorectal Cancer Liver Metastases Through Analysis of Single-Cell Sequencing Data and TCGA Data.

BACKGROUND: Colorectal cancer (CRC) is highly prevalent worldwide, with more patients experiencing colorectal cancer liver metastases (CRLM). This study aimed to identify key genes in CRLM through single-cell sequencing data reanalysis and experimental validation. METHODS: The study analyzed single-cell RNA-sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for gene functional enrichment analysis. The Cancer Genome Atlas (TCGA) data enabled bulk-RNA expression and survival prognosis analysis. Real-time polymerase chain reaction (qPCR) detected mRNA expression, whereas Western blot determined protein levels. Cell function experiments assessed SPARC's impact on CRC cell behavior. RESULTS: Cluster analysis showed 23 classes among 17 CRLM samples, representing six cell types. A GO and KEGG analysis identified interleukin-1 beta (IL1B), CD2 molecule (CD2), and C-X-C motif chemokine ligand 8 (CXCL8) as significant prognostic factors in CRC. Secreted protein acidic and cysteine rich (SPARC) was one of the top differentially expressed genes (DEGs) in tissue stem cells, confirmed in primary and metastatic lesions. Metastatic lesions showed higher expression of SPARC and CRC stem cell marker leucine-rich repeat containing G protein-coupled receptor 5 (LGR5), which was significantly correlated positively with LGR5 expression. Knockdown of SPARC reduced CRC cell sphere- and colony-formation, invasion, and migration abilities. Overexpression of SPARC significantly increased the malignancy of CRC cells. CONCLUSIONS: Several key genes were identified in the process of CRLM. In CRLM samples and those corresponding to CRC stem cells, SPARC was significantly upregulated. In the therapy of CRLM, SPARC might be a potential target.

Single-cell transcriptome and chromatin accessibility mapping of upper lip and primary palate fusion.

Cleft lip and/or primary palate (CL/P) represent a prevalent congenital malformation, the aetiology of which is highly intricate. Although it is generally accepted that the condition arises from failed fusion between the upper lip and primary palate, the precise mechanism underlying this fusion process remains enigmatic. In this study, we utilized transposase-accessible chromatin sequencing (scATAC-seq) and single-cell RNA sequencing (scRNA-seq) to interrogate lambdoidal junction tissue derived from C57BL/6J mouse embryos at critical stages of embryogenesis (10.5, 11.5 and 12.5 embryonic days). We successfully identified distinct subgroups of mesenchymal and ectodermal cells involved in the fusion process and characterized their unique transcriptional profiles. Furthermore, we conducted cell differentiation trajectory analysis, revealing a dynamic repertoire of genes that are sequentially activated or repressed during pseudotime, facilitating the transition of relevant cell types. Additionally, we employed scATAC data to identify key genes associated with the fusion process and demonstrated differential chromatin accessibility across major cell types. Finally, we constructed a dynamic intercellular communication network and predicted upstream transcriptional regulators of critical genes involved in important signalling pathways. Our findings provide a valuable resource for future studies on upper lip and primary palate development, as well as congenital defects.

Integrated analysis of single-cell RNA-seq and bulk RNA-seq revealed key genes for bone metastasis and chemoresistance in prostate cancer.

BACKGROUND: Prostate cancer (PCa) is a serious malignancy. The main causes of PCa aggravation and death are unexplained resistance to chemotherapy and bone metastases. OBJECTIVE: This study aimed to investigate the molecular mechanisms associated with the dynamic processes of progression, bone metastasis, and chemoresistance in PCa. METHODS: Through comprehensive analysis of single-cell RNA sequencing (scRNA-seq) data, Gene Expression Omnibus (GEO) tumor progression and metastasis-related genes were identified. These genes were subjected to lasso regression modeling using the Cancer Genome Atlas (TCGA) database. Tartrate-resistant acid phosphatase (TRAP) staining and real-time quantitative PCR (RT-qPCR) were used to evaluate osteoclast differentiation. CellMiner was used to confirm the effect of LDHA on chemoresistance. Finally, the relationship between LDHA and chemoresistance was verified using doxorubicin-resistant PCa cell lines. RESULTS: 7928 genes were identified as genes related to tumor progression and metastasis. Of these, 7 genes were found to be associated with PCa prognosis. The scRNA-seq and TCGA data showed that the expression of LDHA was higher in tumors and associated with poor prognosis of PCa. In addition, upregulation of LDHA in PCa cells induces osteoclast differentiation. Additionally, high LDHA expression was associated with resistance to Epirubicin, Elliptinium acetate, and doxorubicin. Cellular experiments demonstrated that LDHA knockdown inhibited doxorubicin resistance in PCa cells. CONCLUSIONS: LDHA may play a potential contributory role in PCa initiation and development, bone metastasis, and chemoresistance. LDHA is a key target for the treatment of PCa.