Single-cell Sequencing Research Articles

Emerging technologies of single-cell multi-omics.

The heterogeneity of the hematopoietic system was largely veiled by traditional bulk sequencing methods, which measure the averaged signals from mixed cellular populations. In contrast, single-cell sequencing has enabled the direct measurement of individual signals from each cell, significantly enhancing our ability to unveil such heterogeneity. Building on these advances, numerous single-cell multi-omics techniques have been developed into high-throughput, routinely accessible platforms, delineating the precise relationships among the different layers of the central dogma in molecular biology. These technologies have uncovered the intricate landscape of genetic clonality and transcriptional heterogeneity in both normal and malignant hematopoietic systems, highlighting their roles in differentiation, disease progression, and therapy resistance. This review aims to provide a brief overview of the principles of single-cell technologies, their historical development, and a subset of ever-expanding multi-omics tools, emphasizing the specific research questions that inspired their creation. Amidst the evolving landscape of single-cell multi-omics technologies, our main objective is to guide investigators in selecting the most suitable platforms for their research needs.

An anoikis-related signature predicts prognosis and immunotherapy response in gastrointestinal cancers

BackgroundGastrointestinal (GI) cancers have high incidence rates and mortality rates. Anoikis is a special type of cell apoptosis, and anoikis resistance has been reported to be associated with tumor malignancy. We aimed to explore the roles of anoikis-related genes (ARGs) in the GI cancer prognosis.MethodsWe extracted RNA sequencing and clinical data from The Cancer Genome Atlas and Gene Expression Omnibu databases for patients with esophageal cancer, gastric cancer, colon cancer and rectal cancer and identified ARGs from GeneCards and Harmonizome. Anoikis-related patterns were identified via unsupervised clustering analysis. We constructed a prognostic signature (Anoscore) based on prognostic ARGs through univariate, LASSO, and multivariate Cox regression analyses. The model was validated and evaluated using Kaplan–Meier analysis, receiver operating characteristic curves, univariate Cox regression analysis, multivariate Cox regression analysis, column charts, and calibration curves. We also performed a single-cell sequencing analysis of candidate genes via TISCH2. A correlation analysis between the Anoscore, the tumor microenvironment and drug sensitivity was conducted in GI cancers. The expression and function of some candidate genes were validated in vitro.ResultsIn terms of prognostic ARGs, two anoikis-related patterns, ARG clusters A and B, were identified. ARG cluster B had a worse prognosis than did ARG cluster A. Subsequently, the Anoscore was developed as an independent prognostic factor. It demonstrated the robust predictive capability for the prognosis of patients with GI cancers. Notably, patients with high Anoscores exhibited poor outcomes. In addition, we established a nomogram (Ano-nomogram) based on the Anoscore and clinicopathological factors of patients to predict the 3-year and 5-year survival probabilities. Moreover, patients with high Anoscores had higher levels of immune cell infiltration and higher immune checkpoint expression. The drug sensitivity analysis revealed that patients with high or low Anoscores were sensitive to different chemotherapies and targeted drugs. S100A11 and TLR3, representative candidate genes, exhibited different expression patterns and biological functions.ConclusionThis study highlighted the significant potential of the Anoscore in predicting prognosis and guiding the selection of personalized therapeutic regimens for patients with GI cancers.

Advancements in single-cell RNA sequencing and spatial transcriptomics: transforming biomedical research

In recent years, significant advancements in biochemistry, materials science, engineering, and computer-aided testing have driven the development of high-throughput tools for profiling genetic information. Single-cell RNA sequencing (scRNA-seq) technologies have established themselves as key tools for dissecting genetic sequences at the level of single cells. These technologies reveal cellular diversity and allow for the exploration of cell states and transformations with exceptional resolution. Unlike bulk sequencing, which provides population-averaged data, scRNA-seq can detect cell subtypes or gene expression variations that would otherwise be overlooked. However, a key limitation of scRNA-seq is its inability to preserve spatial information about the RNA transcriptome, as the process requires tissue dissociation and cell isolation. Spatial transcriptomics is a pivotal advancement in medical biotechnology, facilitating the identification of molecules such as RNA in their original spatial context within tissue sections at the single-cell level. This capability offers a substantial advantage over traditional single-cell sequencing techniques. Spatial transcriptomics offers valuable insights into a wide range of biomedical fields, including neurology, embryology, cancer research, immunology, and histology. This review highlights single-cell sequencing approaches, recent technological developments, associated challenges, various techniques for expression data analysis, and their applications in disciplines such as cancer research, microbiology, neuroscience, reproductive biology, and immunology. It highlights the critical role of single-cell sequencing tools in characterizing the dynamic nature of individual cells.

Single-cell sequencing elucidates the mechanism of NUSAP1 in glioma and its diagnostic and prognostic significance

BackgroundPersonalized precision medicine (PPPM) in cancer immunology and oncology is a rapidly advancing field with significant potential. Gliomas, known for their poor prognosis, rank among the most lethal brain tumors. Despite advancements, there remains a critical need for precise, individualized treatment strategies.MethodsWe conducted a comprehensive analysis of RNA-seq and microarray data from the TCGA and GEO databases, supplemented by single-cell RNA sequencing (scRNA-seq) data from glioma patients. By integrating single-cell sequencing analysis with foundational experiments, we investigated the molecular variations and cellular interactions within neural glioma cell subpopulations during tumor progression.ResultsOur single-cell sequencing analysis revealed distinct gene expression patterns across glioma cell subpopulations. Notably, differentiation trajectory analysis identified NUSAP1 as a key marker for the terminal subpopulation. We found that elevated NUSAP1 expression correlated with poor prognosis, prompting further investigation of its functional role through both cellular and animal studies.ConclusionsNUSAP1-based risk models hold potential as predictive and therapeutic tools for personalized glioma treatment. In-depth exploration of NUSAP1’s mechanisms in glioblastoma could enhance our understanding of its response to immunotherapy, suggesting that targeting NUSAP1 may offer therapeutic benefits for glioma patients.

Deterministic genetic barcoding for multiplexed behavioral and single-cell transcriptomic studies

Advances in single-cell sequencing technologies have provided novel insights into the dynamics of gene expression and cellular heterogeneity within tissues and have enabled the construction of transcriptomic cell atlases. However, linking anatomical information to transcriptomic data and positively identifying the cell types that correspond to gene expression clusters in single-cell sequencing data sets remains a challenge. We describe a straightforward genetic barcoding approach that takes advantage of the powerful genetic tools in Drosophila to allow in vivo tagging of defined cell populations. This method, called Targeted Genetically-Encoded Multiplexing (TaG-EM), involves inserting a DNA barcode just upstream of the polyadenylation site in a Gal4-inducible UAS-GFP construct so that the barcode sequence can be read out during single-cell sequencing, labeling a cell population of interest. By creating many such independently barcoded fly strains, TaG-EM enables positive identification of cell types in cell atlas projects, identification of multiplet droplets, and barcoding of experimental timepoints, conditions, and replicates. Furthermore, we demonstrate that TaG-EM barcodes can be read out using next-generation sequencing to facilitate population-scale behavioral measurements. Thus, TaG-EM has the potential to enable large-scale behavioral screens in addition to improving the ability to multiplex and reliably annotate single-cell transcriptomic experiments.

Deterministic genetic barcoding for multiplexed behavioral and single-cell transcriptomic studies.

Advances in single-cell sequencing technologies have provided novel insights into the dynamics of gene expression and cellular heterogeneity within tissues and have enabled the construction of transcriptomic cell atlases. However, linking anatomical information to transcriptomic data and positively identifying the cell types that correspond to gene expression clusters in single-cell sequencing data sets remains a challenge. We describe a straightforward genetic barcoding approach that takes advantage of the powerful genetic tools in Drosophila to allow in vivo tagging of defined cell populations. This method, called Targeted Genetically-Encoded Multiplexing (TaG-EM), involves inserting a DNA barcode just upstream of the polyadenylation site in a Gal4-inducible UAS-GFP construct so that the barcode sequence can be read out during single-cell sequencing, labeling a cell population of interest. By creating many such independently barcoded fly strains, TaG-EM enables positive identification of cell types in cell atlas projects, identification of multiplet droplets, and barcoding of experimental timepoints, conditions, and replicates. Furthermore, we demonstrate that TaG-EM barcodes can be read out using next-generation sequencing to facilitate population-scale behavioral measurements. Thus, TaG-EM has the potential to enable large-scale behavioral screens in addition to improving the ability to multiplex and reliably annotate single-cell transcriptomic experiments.

A novel protein encoded by porcine circANKRD17 activates the PPAR pathway to regulate intramuscular fat metabolism

BackgroundIntramuscular fat is an important factor in evaluating pork quality and varies widely among different pig breeds. However, the regulatory mechanism of circular RNAs (circRNAs) in lipid metabolism remains largely unexplored.ResultsWe combined circRNA-seq and Ribo-seq data to screen a total of 18 circRNA candidates with coding potential, and circANKRD17 was found to be significantly elevated in the longissimus dorsi muscle of Lantang piglets, with a length of 1,844 nucleotides. Using single-cell sequencing, we identified 477 differentially expressed genes in IMF cells between Lantang and Landrace piglets, with enrichment in the PPAR signaling pathway. These genes included FABP4, FABP5, CPT1A, and UBC, consistent with the high levels of acylcarnitines observed in the longissimus dorsi muscles of the Lantang breed, as determined by lipidomic analysis. Further in vitro and in vivo experiments indicated that circANKRD17 can regulate lipid metabolism through various mechanisms involving the PPAR pathway, including promoting adipocyte differentiation, fatty acid transport and metabolism, triglyceride synthesis, and lipid droplet formation and maturation. In addition, we discovered that circANKRD17 has an open reading frame and can be translated into a novel 571-amino-acid protein that promotes lipid metabolism.ConclusionsOur research provides new insights into the role of protein-coding circANKRD17, especially concerning the metabolic characteristics of pig breeds with higher intramuscular fat content.

Exploring genome-transcriptome correlations in cancer.

We examine the complex relationship between genomic copy number variation (CNV) and gene expression, highlighting the relevance to cancer biology and other biological contexts. By tracing the history of genometranscriptome correlations, we emphasize the complexity and challenges in understanding these interactions, particularly within the heterogeneous landscape of human cancers. Recent advances in computational algorithms and high-throughput single-cell multi-omic sequencing technologies are discussed, demonstrating their potential to refine our understanding of cancer biology and their limitations. The integration of genomic and transcriptomic analyses, which offers novel insights into tumor evolution and heterogeneity as well as therapeutic strategies, is presented as a crucial approach for advancing cancer research.

Identification of mitochondrial carrier homolog 2 as an important therapeutic target of castration-resistant prostate cancer

We here investigate the expression of the mitochondrial carrier homolog 2 (MTCH2) and its potential function in castration-resistant prostate cancer (CRPC). Bioinformatic analyses reveal that MTCH2 overexpression is associated with critical clinical parameters of prostate cancer. Single-cell sequencing data indicate elevated MTCH2 expression in the prostate cancer epithelium. MTCH2 is also upregulated in locally treated CRPC tissue and various primary human CRPC cells. Using genetic silencing via shRNA and knockout (KO) through the CRISPR-sgRNA approach, we showed that the depletion of MTCH2 impaired mitochondrial function, resulting in a reduced oxygen consumption rate, diminished complex I activity, and decreased ATP levels, mitochondrial depolarization, and increased reactive oxygen species production in primary CRPC cells. The silencing or KO of MTCH2 significantly inhibited cell viability, proliferation, and migration, together with a marked increase in apoptosis in the primary CRPC cells. In contrast, ectopic expression of MTCH2 provided CRPC cells with pro-tumorigenic properties, enhancing ATP production and promoting cell proliferation and migration. MTCH2 silencing also markedly inhibited the growth of subcutaneous xenografts of the primary CRPC cells in nude mice. The MTCH2-silenced xenografts exhibited increased apoptosis, elevated lipid peroxidation, and decreased ATP levels. These results provide new insights into the role of MTCH2 in supporting mitochondrial function and CRPC progression.

Usp11 maintained the survival of marginal zone B cells under ionizing radiation by deubiquitinating DLL1 and JAG2.

Efficacy of radiation therapy is compromised by hematopoietic and immune impairments, with elusive underlying causes. This study aimed to elucidate Usp11's role in radiation-induced injuries and uncover related mechanisms. Utilized ARS mouse model to observe survival rates of Usp11-/- (KO) mice post-TBI (Total Body Irradiation). Assessed lymphocyte and MZ B (Marginal Zone B) cell rates using histological analysis, single-cell sequencing, immunofluorescence (IF), immunohistochemistry (IHC), and flow cytometry (FCM). Conducted Co-IP and ubiquitination experiments for mechanism elucidation. Quantified IgM and IgG using ELISA and FC. Explored public databases for potential correlation molecules. Our findings indicated that Usp11-/- mice exhibited improved survival rates following TBI, with the spleen playing a pivotal role. HE staining revealed a wider marginal zone in the spleen of Usp11+/+ mice post-irradiation. Single-cell sequencing, IF, IHC, and FCM analyses revealed a higher survival rate of MZ B cells in Usp11-/- mice after irradiation. Furthermore, treatment with the Usp11 inhibitor, mitoxantrone, successfully targeted and inhibited Usp11, thereby alleviating the reduction in MZ B cells in the spleen following total body irradiation. Mechanistically, Usp11 sustained the survival of MZ B cells by regulating the ubiquitination of Notch's ligands, DLL1 and JAG2, thereby promoting immune cell remodeling in the spleen. In conclusion, Usp11 played a crucial role in modulating immune system damage induced by ionizing radiation, primarily through ubiquitination of Notch ligands. This study provides insights into radiation-induced immune injuries and suggests Usp11 as a potential therapeutic target.

O-GlcNAcylation attenuates ischemia-reperfusion-induced pulmonary epithelial cell ferroptosis via the Nrf2/G6PDH pathway

BackgroundLung ischemia–reperfusion (I/R) injury is a common clinical pathology associated with high mortality. The pathophysiology of lung I/R injury involves ferroptosis and elevated protein O-GlcNAcylation levels, while the effect of O-GlcNAcylation on lung I/R injury remains unclear. This research aimed to explore the effect of O-GlcNAcylation on reducing ferroptosis in pulmonary epithelial cells caused by I/R.ResultsFirst, we identified O-GlcNAc transferase 1 (Ogt1) as a differentially expressed gene in lung epithelial cells of acute lung injury/acute respiratory distress syndrome (ALI/ARDS) patients, using single-cell sequencing, and Gene Ontology analysis (GO analysis) revealed the enrichment of the ferroptosis process. We found a time-dependent dynamic alteration in lung O-GlcNAcylation during I/R injury. Proteomics analysis identified the differentially expressed proteins enriched in ferroptosis and multiple redox-related pathways based on KEGG annotation. Thus, we generated Ogt1-conditional knockout mice and found that Ogt1 deficiency aggravated ferroptosis, as evidenced by lipid reactive oxygen species (lipid ROS), malondialdehyde (MDA), Fe2+, as well as alterations in critical protein expression glutathione peroxidase 4 (GPX4) and solute carrier family 7 member 11 (SLC7A11). Consistently, we found that elevated O-GlcNAcylation inhibited ferroptosis sensitivity in hypoxia/reoxygenation (H/R) injury-induced TC-1 cells via O-GlcNAcylated NF-E2-related factor-2 (Nrf2). Furthermore, both the chromatin immunoprecipitation (ChIP) assay and the dual-luciferase reporter assay indicated that Nrf2 could bind with translation start site (TSS) of glucose-6-phosphate dehydrogenase (G6PDH) and promote its transcriptional activity. As an important rate-limiting enzyme in the pentose phosphate pathway (PPP), elevated G6PDH provided a mass of nicotinamide adenine dinucleotide phosphate (NADPH) to improve the redox state of glutathione (GSH) and eventually led to ferroptosis resistance. Rescue experiments proved that Nrf2 knockdown or Nrf2-T334A (O-GlcNAcylation site) mutation abolished the protective effect of ferroptosis resistance.ConclusionsIn summary, we revealed that O-GlcNAcylation could protect against I/R lung injury by reducing ferroptosis sensitivity via the Nrf2/G6PDH pathway. Our work will provide a new basis for clinical therapeutic strategies for pulmonary ischemia–reperfusion-induced acute lung injury.

High throughput single cell metagenomic sequencing with semi-permeable capsules: unraveling microbial diversity at the single-cell level in sewage and fecal microbiomes

Single-cell sequencing may serve as a powerful complementary technique to shotgun metagenomics to study microbiomes. This emerging technology allows the separation of complex microbial communities into individual bacterial cells, enabling high-throughput sequencing of genetic material from thousands of singular bacterial cells in parallel. Here, we validated the use of microfluidics and semi-permeable capsules (SPCs) technology (Atrandi) to isolate individual bacterial cells from sewage and pig fecal samples. Our method involves extracting and amplifying single bacterial DNA within individual SPCs, followed by combinatorial split-and-pool single-amplified genome (SAG) barcoding and short-read sequencing. We tested two different sequencing approaches with different numbers of SPCs from the same sample for each sequencing run. Using a deep sequencing approach, we detected 1,796 and 1,220 SAGs, of which 576 and 599 were used for further analysis from one sewage and one fecal sample, respectively. In shallow sequencing data, we aimed for 10-times more cells and detected 12,731 and 17,909 SAGs, of which we used 2,456 and 1,599 for further analysis for sewage and fecal samples, respectively. Additionally, we identified the top 10 antimicrobial resistance genes (ARGs) in both sewage and feces samples and linked them to their individual host bacterial species.

BRD4 Induces Esophageal Squamous Cell Carcinoma Progression via the Wnt/β-catenin Pathway.

BRD4, part of the bromodomain and extra terminal domain (BET) protein family, plays a pivotal role in gene transcription, DNA replication, and repair via transcription regulators. Despite its established involvement in various human diseases, its function in esophageal squamous cell carcinoma (ESCC) has not been fully explored. Our research investigated the association of BRD4 in ESCC and its underlying molecular mechanisms. The findings revealed that BRD4 knockdown notably diminished the cells' proliferation, migration, invasion capabilities and induced apoptosis and cell cycle arrest. Conversely, overexpression of BRD4 can reverse these phenotypes. Pearson correlation and enrichment analyses indicated that BRD4 expression was associated with the cell cycle and Wnt/β-catenin signaling pathway. Further validation confirmed that reduced BRD4 expression downregulates Cyclin D1 and c-Myc, and suppresses epithelial-to-mesenchymal transition (EMT) and Wnt/β-catenin signaling pathway. Furthermore, rescue experiments showed that overexpressing c-Myc significantly mitigated the inhibitory impact of BRD4. Moreover, by employing single-cell transcriptome sequencing, we explored the impact of the tumor microenvironment on BRD4 overexpression in ESCC cells. These insights confirmed BRD4's potential as a therapeutic target, suggesting that modulating its expression could yield promising strategies for ESCC treatment.

Efficient Identification of Monoclonal Antibodies Against Rift Valley Fever Virus Using High-Throughput Single Lymphocyte Transcriptomics of Immunized Mice

Background: Rift Valley fever virus (RVFV) is a zoonotic virus that poses a significant threat to both livestock and human health and has caused outbreaks in endemic regions. In humans, most patients experience a febrile illness; however, in some patients, RVF disease may result in hemorrhagic fever, retinitis, or encephalitis. While several veterinary vaccines are being utilized in endemic countries, currently, there are no licensed RVF vaccines or therapeutics for human use. Neutralizing antibodies specifically targeting vulnerable pathogen epitopes are promising candidates for prophylactic and therapeutic interventions. In the case of RVFV, the surface glycoproteins Gc and Gn, which harbor neutralizing epitopes, represent the primary targets for vaccine and neutralizing antibody development. Methods: We report the implementation of advanced 10x Genomics technology, enabling high-throughput single-cell analysis for the identification of rare and potent antibodies against RVFV. Following the immunization of mice with live attenuated rMP-12-GFP virus and successive Gc/Gn boosts, memory B cell populations (both general and antigen-specific) were sorted from splenocytes by flow cytometry. Deep sequencing of the antibody repertoire at a single-cell resolution, together with bioinformatic analyses, was applied for BCR pair selection based on their abundance and specificity. Results: Twenty-three recombinant monoclonal antibodies (mAbs) were selected and expressed, and their antigen-binding capacities were characterized. About half of them demonstrated specific binding to their cognate antigen with relatively high binding affinities. Conclusions: These antibodies could be used for the future development of efficacious therapeutics, as well as for studying virus-neutralizing mechanisms. The current study, in which the single-cell sequencing approach was implemented for the development of antibodies targeting the RVFV surface proteins Gc and Gn, demonstrates the effective applicability of this technique for antibody discovery purposes.

Phospho-seq: integrated, multi-modal profiling of intracellular protein dynamics in single cells

Cell signaling plays a critical role in neurodevelopment, regulating cellular behavior and fate. While multimodal single-cell sequencing technologies are rapidly advancing, scalable and flexible profiling of cell signaling states alongside other molecular modalities remains challenging. Here we present Phospho-seq, an integrated approach that aims to quantify cytoplasmic and nuclear proteins, including those with post-translational modifications, and to connect their activity with cis-regulatory elements and transcriptional targets. We utilize a simplified benchtop antibody conjugation method to create large custom neuro-focused antibody panels for simultaneous protein and scATAC-seq profiling on whole cells, alongside both experimental and computational strategies to incorporate transcriptomic measurements. We apply our workflow to cell lines, induced pluripotent stem cells, and months-old retinal and brain organoids to demonstrate its broad applicability. We show that Phospho-seq can provide insights into cellular states and trajectories, shed light on gene regulatory relationships, and help explore the causes and effects of diverse cell signaling in neurodevelopment.

Single-cell sequencing provides clues about the developmental genetic basis of evolutionary adaptations in syngnathid fishes

Seahorses, pipefishes, and seadragons are fishes from the family Syngnathidae that have evolved extraordinary traits including male pregnancy, elongated snouts, loss of teeth, and dermal bony armor. The developmental genetic and cellular changes that led to the evolution of these traits are largely unknown. Recent syngnathid genome assemblies revealed suggestive gene content differences and provided the opportunity for detailed genetic analyses. We created a single-cell RNA sequencing atlas of Gulf pipefish embryos to understand the developmental basis of four traits: derived head shape, toothlessness, dermal armor, and male pregnancy. We completed marker gene analyses, built genetic networks, and examined the spatial expression of select genes. We identified osteochondrogenic mesenchymal cells in the elongating face that express regulatory genes bmp4, sfrp1a, and prdm16. We found no evidence for tooth primordia cells, and we observed re-deployment of osteoblast genetic networks in developing dermal armor. Finally, we found that epidermal cells expressed nutrient processing and environmental sensing genes, potentially relevant for the brooding environment. The examined pipefish evolutionary innovations are composed of recognizable cell types, suggesting that derived features originate from changes within existing gene networks. Future work addressing syngnathid gene networks across multiple stages and species is essential for understanding how the novelties of these fish evolved.

Single-cell sequencing provides clues about the developmental genetic basis of evolutionary adaptations in syngnathid fishes.

Seahorses, pipefishes, and seadragons are fishes from the family Syngnathidae that have evolved extraordinary traits including male pregnancy, elongated snouts, loss of teeth, and dermal bony armor. The developmental genetic and cellular changes that led to the evolution of these traits are largely unknown. Recent syngnathid genome assemblies revealed suggestive gene content differences and provided the opportunity for detailed genetic analyses. We created a single-cell RNA sequencing atlas of Gulf pipefish embryos to understand the developmental basis of four traits: derived head shape, toothlessness, dermal armor, and male pregnancy. We completed marker gene analyses, built genetic networks, and examined the spatial expression of select genes. We identified osteochondrogenic mesenchymal cells in the elongating face that express regulatory genes bmp4, sfrp1a, and prdm16. We found no evidence for tooth primordia cells, and we observed re-deployment of osteoblast genetic networks in developing dermal armor. Finally, we found that epidermal cells expressed nutrient processing and environmental sensing genes, potentially relevant for the brooding environment. The examined pipefish evolutionary innovations are composed of recognizable cell types, suggesting that derived features originate from changes within existing gene networks. Future work addressing syngnathid gene networks across multiple stages and species is essential for understanding how the novelties of these fish evolved.

Single-cell landscape of dynamic changes in CD8+ T cells, CD4+ T cells and exhausted T cells in hepatocellular carcinoma

Hepatocellular carcinoma has a high incidence and poor prognosis. In this study, we investigated the value of T-cell-related genes in prognosis by single-cell sequencing data in hepatocellular carcinoma. Twelve cases of hepatocellular carcinoma single-cell sequencing were included in the study. The high dimensional weighted gene co-expression network analysis (hdWGCNA) was used to identify gene modules associated with CD4+ T cells, CD8+ T cells and exhausted T cells. Altered signaling pathway activity in exhausted T cells was uncovered by the AUCell algorithm. xCELL, TIMER, QUANTISEQ, CIBERSORT and CIBERSORT-abs were performed to explore immune cell infiltration. Immune checkpoint inhibitor genes and TIDE methods were used to predict immunotherapy response. Finally, immunohistochemistry and real-time PCR were used to verify gene expression. The hdWGCNA algorithm identified 40 genes strongly associated with CD4+ T cells, CD8+ T cells and exhausted T cells. Seven genes were finally selected for transcriptome data modeling. The results of the three independent datasets suggested that the model had strong prognostic value. Model genes were critical factors influencing CD4+ T cell and CD8+ T cell infiltration in patients. The efficacy of PD-1 immunotherapy was higher in patients belonging to the low-risk group. Alterations in signaling pathways’ activity within exhausted T cells were crucial factors contributing to the decline in immune function. Differential expression of seven genes in CD8+ T cells, CD4+ T cells and exhausted T cells were key targets for improving immunotherapy response in HCC.

Mendelian randomization and multiomics comprehensively reveal the causal relationship and potential mechanism between atrial fibrillation and gastric cancer

ObjectiveGastric cancer is a harmful disease, the comorbidity mechanism and causality relationship between this disease and other diseases are worth studying.MethodsUsing a two-sample Mendelian Randomization method, this study revealed the potential causal effect of atrial fibrillation (AF) on gastric cancer (GC) risk by constructing a genetic instrument containing 136 AF associated SNPs. Subsequently, analysis identifies 62 AF-GC co-associated genes and constructs a protein-protein interaction network of key genes. High-throughput sequencing data were further used to analyze the association between the two and their impact on the survival outcome of gastric cancer.ResultsThe results showed that AF was negatively associated with gastric cancer, and further analysis revealed that this relationship was independent of GC risk factors such as chronic gastritis, Helicobacter pylori infection, and alcohol consumption. Enrichment analysis reveals associations of key genes with pathways related to cardiovascular disease, inflammatory gastrointestinal diseases, and tumorigenesis. Through single-cell sequencing data analysis, fibroblast subpopulations associated with the key gene set are identified in GC, showing significant correlations with cancer progression and inflammation regulation pathways. Transcription factor analysis and developmental trajectory analysis reveal the potential role of fibroblasts in GC development. Finally, prognosis analysis and gene mutation analysis using TCGA-STAD data indicate an adverse prognosis associated with the key gene set in GC.ConclusionThis study provides new insights into the association between AF and GC and offers novel clues for understanding its impact on the pathogenesis and therapeutic strategies of GC.

Unraveling the tumor microenvironment of esophageal squamous cell carcinoma through single-cell sequencing: A comprehensive review.

Esophageal squamous cell carcinoma (ESCC) is a highly heterogeneous and aggressive malignancy. The progression, invasiveness, and metastatic potential of ESCC are shaped by a multitude of cells within the tumor microenvironment (TME), including tumor cells, immune cells, endothelial cells, as well as fibroblasts and other cell types. Recent advancements in single-cell sequencing technologies have significantly enhanced our comprehension of the diverse landscape of ESCC. Single-cell multi-omics technology, particularly single-cell transcriptome sequencing, have shed light on the expression profiles of individual cells and the molecular characteristics of distinct tumor cell populations. This review summarizes the latest literature on single-cell research in the field of ESCC, aiming to elucidate the heterogeneity of tumor cells, immune cells, and stromal cells at the single-cell level. Furthermore, it explores the impact of cellular interactions within the TME on the progression of ESCC. By compiling a comprehensive overview of single-cell omics research on ESCC, this article aims to enhance our understanding of ESCC diagnosis and treatment by elucidating the intricate interplay within the TME. It explores the cellular composition, spatial arrangement, and functional attributes of the ESCC TME, offering potential therapeutic targets and biomarkers for personalized treatment strategies.