Single-cell RNA Sequencing Data Research Articles

Neutrophil and macrophage crosstalk might be a potential target for liver regeneration.

The regenerative capability of the liver is remarkable, but further research is required to understand the role that neutrophils play in this process. In the present study, we reanalyzed single-cell RNA sequencing data from a mouse partial hepatectomy (PH) model to track the transcriptional changes in hepatocytes and non-parenchymal cells. Notably, we unraveled the regenerative capacity of hepatocytes at diverse temporal points after PH, unveiling the contributions of three distinct zones in the liver regeneration process. In addition, we observed that the depletion of neutrophils reduced the survival and liver volume after PH, confirming the important role of neutrophils in liver regeneration. CellChat analysis revealed an intricate crosstalk between neutrophils and macrophages promoting liver regeneration and, using weighted gene correlation network analysis, we identified the most significant genetic module associated with liver regeneration. Our study found that hepatocytes in the periportal zone of the liver are more active than in other zones, suggesting that the crosstalk between neutrophils and macrophages might be a potential target for liver regeneration treatment.

Transcriptional repression of the oncofetal LIN28B gene by the transcription factor SOX6

The identification of regulatory networks contributing to fetal/adult gene expression switches is a major challenge in developmental biology and key to understand the aberrant proliferation of cancer cells, which often reactivate fetal oncogenes. One key example is represented by the developmental gene LIN28B, whose aberrant reactivation in adult tissues promotes tumor initiation and progression. Despite the prominent role of LIN28B in development and cancer, the mechanisms of its transcriptional regulation are largely unknown. Here, by using quantitative RT-PCR and single cell RNA sequencing data, we show that in erythropoiesis the expression of the transcription factor SOX6 matched a sharp decline of LIN28B mRNA during human embryo/fetal to adult globin switching. SOX6 overexpression repressed LIN28B not only in a panel of fetal-like erythroid cells (K562, HEL and HUDEP1; ≈92% p < 0.0001, 54% p = 0.0009 and ≈60% p < 0.0001 reduction, respectively), but also in hepatoblastoma HepG2 and neuroblastoma SH-SY5H cells (≈99% p < 0.0001 and ≈59% p < 0.0001 reduction, respectively). SOX6-mediated repression caused downregulation of the LIN28B/Let-7 targets, including MYC and IGF2BP1, and rapidly blocks cell proliferation. Mechanistically, Lin28B repression is accompanied by SOX6 physical binding within its locus, suggesting a direct mechanism of LIN28B downregulation that might contribute to the fetal/adult erythropoietic transition and restrict cancer proliferation.

Using single-cell RNA sequencing and bulk RNA sequencing data to reveal a correlation between smoking and neutrophil activation in esophageal carcinoma patients.

Cigarette smoking is considered as a major risk factor for esophageal carcinoma (ESCA) patients. Neutrophil activation plays a key role in cancer development and progression. However, the relationship between cigarette smoking and neutrophils in ESCA patients remained unclear. Single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing data were obtained from public databases. Uniform manifold approximation and projection (UMAP) was used to perform downscaling and clustering based on scRNA-seq data. The module genes associated with smoking in ESCA patients were filtered by weighted gene co-expression network analysis (WGCNA). Using the "AUCell" package, the enrichment of different cell subpopulations and gene collections were assessed. "CellChat" and "CellphoneDB" were used to infer the probability and significance of ligand-receptor interactions between different cell subpopulations. WGCNA was performed to screened module genes associated with smoking in ESCA patients from MEdarkquosie, MEturquoise, and MEgreenyellow. Next, eight cell clusters were identified, and using the AUCell score, we determined that neutrophil clusters were more active in the gene modules associated with smoking in ESCA patients. Two neutrophil subtypes, Neutrophils 1 and Neutrophils 2, exhibited greater enrichment in inflammatory response regulation, intercellular adhesion, and regulation of T cell activation. Furthermore, we found that neutrophils may pass through AMPT-(ITGA5 + ITGB1) and ICAM1-AREG in order to promote the development of ESCA, and that the expression levels of the receptor genes insulin-degrading enzyme and ITGB1 were significantly and positively correlated with cigarette smoking per day. Combining smoking-related gene modules and scRNA-seq, the current findings revealed the heterogeneity of neutrophils in ESCA and a tumor-promoting role of neutrophils in the tumor microenvironment of smoking ESCA patients.

Elevated cathepsin S serum levels in new-onset type 1 diabetes and autoantibody-positive siblings.

Accumulating data suggest a role for the lysosomal protease cathepsin S (CTSS) in type 1 diabetes. Circulating CTSS is increased in type 1 diabetes; however, whether CTSS has protective or deleterious effects is unclear. The study's objectives were to examine the biomarker potential of CTSS in new-onset type 1 diabetes, and to investigate the expression and secretion of CTSS in human islets and β cells. The CTSS level was analyzed in serum from children with new-onset type 1 diabetes and autoantibody-positive and -negative siblings by ELISA. The expression and secretion of CTSS were evaluated in isolated human islets and EndoC-βH5 cells by real-time qPCR, immunoblotting, and ELISA. The CTSS serum level was elevated in children with new-onset type 1 diabetes and positively associated with autoantibody status in healthy siblings. Human islets and EndoC-βH5 cells demonstrated induction and secretion of CTSS after exposure to pro-inflammatory cytokines, a model system of islet inflammation. Analysis of publicly available single-cell RNA sequencing data on human islets showed that elevated CTSS expression was exclusive for the β cells in donors with type 1 diabetes as compared to non-diabetic donors. These findings suggest a potential of CTSS as a diagnostic biomarker in type 1 diabetes.

Abstract PO2-28-02: ROR1 regulates CREB3L1 via a novel signaling pathway in triple negative breast cancer

Abstract Triple negative breast cancer (TNBC) is the most aggressive subtype of breast cancer; it is highly metastatic and incredibly difficult to treat due to its lack of the hormone receptors (estrogen, progesterone, and human epidermal growth factor receptor 2) that are used as therapeutic targets to treat breast cancer patients. TNBC patients are left with limited treatment options besides potent chemotherapy drugs that often leave them with undesirable side effects. My work intends to reveal a novel oncogenic signaling pathway that could be used to specifically target and eliminate TNBC in patients. Our lab is focused on a surface receptor that is found to be highly expressed only in cancerous tissue and during fetal development, Receptor tyrosine kinase-like orphan receptor 1 (ROR1). TNBC patients with high ROR1 expression are found to have poor prognosis and decreased overall survival rate compared to patients with low expression. ROR1 is thought to be a good drug target because it activates various oncogenic pathways such as PI3K/AKT and STAT3 in order to increase TNBC metastasis and chemoresistance. Previous single cell RNA sequencing data showed that TNBC tumors with high ROR1 expression also had reduced expression of cAMP responsive element binding protein 3 like 1 (CREB3L1). Often TNBC patients are found to have low CREB3L1 expression, a transcription factor is thought to play a tumor suppressive role in TNBC by increasing the expression of genes associated with the unfolded protein response (UPR) when ER stress occurs. CREB3L1 silencing in TNBC is due to hypermethylation of its promoter region by DNA methyltransferases (DNMTs). We hypothesize that ROR1 regulates CREB3L1 by influencing DNMT activity. This project aims to reveal the tumor suppressors that are downregulated in TNBC by ROR1 activation. Citation Format: Victoria Reed, Eric Lalu, Bela Peethambaran. ROR1 regulates CREB3L1 via a novel signaling pathway in triple negative breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-28-02.

Single-cell RNA sequencing reveals 2D cytokine assay can model atopic dermatitis more accurately than immune-competent 3D setup.

Modelling atopic dermatitis (AD) in vitro is paramount to understand the disease pathophysiology and identify novel treatments. Previous studies have shown that the Th2 cytokines IL-4 and IL-13 induce AD-like features in keratinocytes in vitro. However, it has not been systematically researched whether the addition of Th2 cells, their supernatants or a 3D structure is superior to model AD compared to simple 2D cell culture with cytokines. For the first time, we investigated what in vitro option most closely resembles the disease in vivo based on single-cell RNA sequencing data (scRNA-seq) obtained from skin biopsies in a clinical study and published datasets of healthy and AD donors. In vitro models were generated with primary fibroblasts and keratinocytes, subjected to cytokine treatment or Th2 cell cocultures in 2D/3D. Gene expression changes were assessed using qPCR and Multiplex Immunoassays. Of all cytokines tested, incubation of keratinocytes and fibroblasts with IL-4 and IL-13 induced the closest in vivo-like AD phenotype which was observed in the scRNA-seq data. Addition of Th2 cells to fibroblasts failed to model AD due to the downregulation of ECM-associated genes such as POSTN. While keratinocytes cultured in 3D showed better stratification than in 2D, changes induced with AD triggers did not better resemble AD keratinocyte subtypes observed in vivo. Taken together, our comprehensive study shows that the simple model using IL-4 or IL-13 in 2D most accurately models AD in fibroblasts and keratinocytes in vitro, which may aid the discovery of novel treatment options.

Comprehensive profiling of endocrine metabolism identifies a novel signature with robust predictive value in ovarian cancer.

The cell endocrine pathway is a critical physiological process composed of the endoplasmic reticulum, Golgi apparatus and associated vesicles. Loss of enzymes or proteins can cause dysfunction of endoplasmic reticulum and Golgi apparatus and affect secretion pathways leading to a variety of human diseases, including cancer. The single-cell RNA sequencing and single nucleotide variant principal component analysis data of ovarian cancer were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus (GEO) datasets. Eighty-four genes from SECRETORY_PATHWAYs were obtained from the gene set enrichment analysis (GSEA) website. Univariate cox regression analyses and ConsensusClusterPlus were used to identify prognostic genes and molecular subtypes, which were validated using the tumor immune dysfunction and exclusion (i.e. TIDE) analysis and gene mutation analysis. A prognosis model was established by randomForestSRC. Abundant infiltrated immune cells and pathway enrichment analyses were carried out, respectively, through ssGSEA, ESTIMATE, MCP-counter and GSEA. The drug sensitive analysis was performed using pRRophetic package. Immunotherapy datasets and pan-carcinoma analysis were used to examine the performance of prognostic model. Eighteen prognostic genes from SECRETORY_PATHWAYs were found in both TCGA and GEO datasets. Next, two clusters (C1 and C2) were determined, for which C1 with a poor prognosis had higher immune infiltration. Tumor-related pathways, such as PATHWAYS_IN_CANCER and B_CELL_RECEPTOR_SIGNALING_PATHWAY, were enriched in C1. Moreover, C2 was suitable for immunotherapy. A four-gene (DNAJA1, NDRG3, LUZP1 and ZCCHC24) signature was developed and successfully validated. RiskScore of higher levels were significantly associated with worse prognoses. An enhanced immune infiltration, increased pathways score and inappropriate immunotherapy were observed in the high RiskScore group. The high- and low-RiskScore groups had different drug sensitivities. Immunotherapy datasets and pan-carcinoma analysis indicated that the low RiskScore group may benefit from immunotherapy. Based on the perspective of the secretory signaling pathway, a robust prognostic signature with great performances was determined, which may provide clues for clinical precision treatment of ovarian cancer.

Single-cell analyzing of tumor microenvironment and cell adhesion between early and late-stage lung cancer

Lung adenocarcinoma (LUAD) is a highly heterogeneous disease that threaten human life with serious incidence and high mortality. High heterogeneity of tumor microenvironment (TME) was reported in multiple studies. However, the factor of controlling the tumor migration progression between eary and late-stage LUAD is still not fully understood. In this study, we conducted a comprehensive analysis of single-cell RNA sequencing (scRNA-seq) data of LUAD obtained from the GEO database. The identification of cell clusters revealed significant expansion of epithelial cells in late-stage patients. Interpretation of the cell-cell communication results between early-stage and late-stage patient samples indicated that early tumor cells may interact with epithelial cells through the TGF-β pathway to promote tumor progression. The cell cycle analysis demonstrated a significant increase in the number of cells in the G2 and M phases in late-stage lung cancer. Further analysis using Non-negative Matrix Factorization (NMF) revealed early-stage cell-specific gene features involved in cell adhesion-related biological processes. Among these, the Tensin (TNS) gene family, particularly TNS1, showed high expression in epithelial cells and fibroblasts of early-stage samples, specifically associated with cell adhesion. Survival analysis using TCGA database for LUAD demonstrated that patients with high expression of TNS1 exhibited significantly higher overall survival rates compared to those with low expression. Immunofluorescence experiments have demonstrated co-expression of TNS1 with fibroblast and tumor cell markers (α-SMA and EPCAM). Immunohistochemistry experiments further validated the significantly higher expression levels of TNS1 in early-stage LUAD tissues compared to late-stage lung cancer tissues (P<0.05). Pathway experiments have shown that early-stage tumor patients with high expression of TNS1 exhibit stronger phosphorylation levels of Akt and mTOR, indicating a more potent activation of the Akt/mTOR signaling pathway. In conclusion, the results of this study demonstrate that TNS1 is an adhesive molecule in the immune microenvironment of early-stage tumor cells, and it may serve as a novel prognostic marker for lug cancer.

Integrated single-cell and bulk RNA-sequencing data reveal molecular subtypes based on lactylation-related genes and prognosis and therapeutic response in glioma

Integrated single-cell and bulk RNA-sequencing data reveal molecular subtypes based on lactylation-related genes and prognosis and therapeutic response in glioma

Novel insights into the protective effects of leonurine against acute kidney injury: inhibition of ER stress-associated ferroptosis via regulating ATF4/CHOP/ACSL4 pathway

Acute kidney injury (AKI) is a common and serious global health problem with high risks of mortality and the development of chronic kidney diseases. Leonurine is a unique bioactive component from Leonurus japonicus Houtt. and exerts antioxidant, antiapoptotic or anti-inflammatory properties. This study aimed to explore the benefits of leonurine on AKI and the possible mechanisms involved, with a particular foc on the regulation of ferroptosis and endoplasmic reticulum (ER) stress. Our results showed that leonurine exhibited prominent protective effects against AKI, as evidenced by the amelioration of histopathological alterations and reduction of renal dysfunction. In addition, leonurine significantly suppressed ferroptosis in AKI both in vivo and in vitro by effectively restoring ultrastructural abnormalities in mitochondria, decreasing ASCL4 and 4-HNE levels, scavenging reactive oxygen species (ROS), as well as increasing GPX4 and GSH levels. In parallel, leonurine also markedly mitigated ER stress via down-regulating PERK, eIF-2α, ATF4, CHOP and CHAC1. Further studies suggested that ER stress was closely involved in erastin-induced ferroptosis, and leonurine protected tubular epithelial cells in vitro by inhibiting ER stress-associated ferroptosis via regulating ATF4/CHOP/ASCL4 signalling pathway. Mechanistically, ATF4 silencing in vitro regulated CHOP and ACSL4 expressions, ultimately weakening both ER stress and ferroptosis. Notably, analyses of single-cell RNA sequencing data revealed that ATF4, CHOP and ASCL4 in renal tubular cells were all abnormally upregulated in patients with AKI compared to healthy controls, suggesting their contributions to the pathogenesis of AKI. Altogether, these findings suggest that leonurine alleviates AKI by inhibiting ER stress-associated ferroptosis via regulating ATF4/CHOP/ASCL4 signalling pathway, thus providing novel mechanisms for AKI treatment.

Associations in cell type-specific hydroxymethylation and transcriptional alterations of pediatric central nervous system tumors

Although intratumoral heterogeneity has been established in pediatric central nervous system tumors, epigenomic alterations at the cell type level have largely remained unresolved. To identify cell type-specific alterations to cytosine modifications in pediatric central nervous system tumors, we utilize a multi-omic approach that integrated bulk DNA cytosine modification data (methylation and hydroxymethylation) with both bulk and single-cell RNA-sequencing data. We demonstrate a large reduction in the scope of significantly differentially modified cytosines in tumors when accounting for tumor cell type composition. In the progenitor-like cell types of tumors, we identify a preponderance differential Cytosine-phosphate-Guanine site hydroxymethylation rather than methylation. Genes with differential hydroxymethylation, like histone deacetylase 4 and insulin-like growth factor 1 receptor, are associated with cell type-specific changes in gene expression in tumors. Our results highlight the importance of epigenomic alterations in the progenitor-like cell types and its role in cell type-specific transcriptional regulation in pediatric central nervous system tumors.

ITGAM: A Pivotal Regulator in Macrophage Dynamics and Cardiac Function During Sepsis-Induced Cardiomyopathy.

Sepsis-induced cardiomyopathy (SIC) is a critical complication arising from sepsis characterized by reversible myocardial dysfunction. Despite the increasing attention to SIC in research, the underlying molecular mechanisms remain poorly comprehended. In this study, we utilized bioinformatics to analyze RNA-sequencing (RNA-seq) and single-cell RNA-sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database to identify key immune cell populations and molecular markers associated with SIC. Our experimental approach combined in vitro and in vivo studies to investigate the roles of integrin alpha M(ITGAM) and intracellular adhesion molecule-1(ICAM-1) in macrophage recruitment and phenotypic polarization, as well as their impact on cardiac function during SIC. The bioinformatics analysis disclosed significant alterations in gene expression and immune cell composition within the cardiac tissue during SIC, where macrophages emerged as the predominant immune cell type. Notably, ITGAM was identified as a key regulatory molecule that modulates macrophage function, driving the pathogenesis of SIC through its influence on the recruitment and functional reprogramming of these cells. In vitro experiments revealed that lipopolysaccharide (LPS) stimulation triggered an upregulation of ITGAM in macrophages and ICAM-1 in endothelial cells, underscoring their critical roles in immune cell mobilization and intercellular communication. The strategic administration of ITGAM-neutralizing antibodies to SIC mice resulted in a marked decrease in macrophage infiltration within the cardiac tissue, which was initially associated with an improvement in cardiac function. However, this intervention paradoxically resulted in an increased mortality rate during the later phases of SIC, underscoring the complex and dualistic function of ITGAM. This study provides new insights into the complex dynamics of immune cells within the cardiac environment during SIC, with a particular emphasis on the modulatory role of ITGAM in shaping macrophage behavior. The findings shed light on the reversible nature of myocardial dysfunction in SIC and emphasize the importance of targeted therapeutic strategies for the effective management of SIC.

Deciphering Cuproptosis-related Signatures in Pediatric Allergic Asthma using Integrated scRNA-seq and Bulk RNA-seq Analysis

Objective Allergic asthma (AA) is common in children. Excess copper is observed in AA patients. It is currently unclear whether copper imbalance can cause cuproptosis in pediatric AA. Methods The datasets about pediatric AA (GSE40732 and GSE40888) were obtained from Gene Expression Omnibus (GEO) database. The expression of cuproptosis-related genes (CRGs) and immune cell infiltration in pediatric AA samples were analyzed. Single-cell RNA sequencing (scRNA-seq) data (GSE193816) were used to evaluate the expression patterns of CRGs in AA. The identification of differentially expressed genes within clusters was conducted using weighted gene co-expression network analysis. Subsequently, disease progression and cuproptosis-related models were screened using random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and general linear model (GLM) algorithms. Results Four CRGs were notably increased in pediatric AA samples. CD4+ T cells, macrophages and mast cells exhibited a lower cuproptosis score in AA samples, indicating that these immune cells may be closely associated with cuproptosis in AA development. Co-expression network of CRGs in AA was constructed. AA samples were divided into two cuprotosis clusters. Following construction of four machine-learning models, SVM model exhibited the highest efficacy of prediction in the testing set (AUC = 0.952). SVM model containing five important variables can be used for prediction of AA. Conclusion This work provided a machine learning model containing five important variables, which may have good diagnostic efficiency for pediatric AA.

Comprehensive Analysis of a Dendritic Cell Marker Genes Signature to Predict Prognosis and Immunotherapy Response in Lung Adenocarcinoma.

With the development of immune checkpoints inhibitors (ICIs), immunotherapy has recently taken center stage in cancer treatment. Dendritic cells exert complicated and important functions in antitumor immunity. This study aims to construct a novel dendritic cell marker gene signature (DCMGS) to predict the prognosis and immunotherapy response of lung adenocarcinoma (LUAD). DC marker genes in LUAD were identified by analysis of single-cell RNA sequencing data. 6 genes (G0S2, KLF4, ALDH2, IER3, TXN, CD69) were screened as the most prognosis-related genes for constructing DCMGS on a training cohort from TCGA data set. Patients were divided into high-risk and low-risk groups by DCMGS risk score based on overall survival time. Then, the predictive ability of the risk model was validated in 6 independent cohorts. DCMGS was verified to be an independent prognostic factor in multivariate analysis. Furthermore, we performed pathway enrichment analysis to explore possible biological mechanisms of the powerful predictive ability of DCMGS, and immune cell infiltration landscape and inflammatory activities were exhibited to reflect the immune profile. Notably, we bridged DCMGS with expression of immune checkpoints and TCR/BCR repertoire diversity that can inflect immunotherapy response. Finally, the predictive ability of DCMGS in immunotherapy response was also validated by 2 cohorts that had received immunotherapy. As a result, the patients with lower DCMGS risk scores showed a better prognosis and immunotherapy response. In conclusion, DCMGS was suggested to be a promising prognostic indicator for LUAD and a desirable predictor for immunotherapy response.

Cauchy hyper-graph Laplacian nonnegative matrix factorization for single-cell RNA-sequencing data analysis.

Many important biological facts have been found as single-cell RNA sequencing (scRNA-seq) technology has advanced. With the use of this technology, it is now possible to investigate the connections among individual cells, genes, and illnesses. For the analysis of single-cell data, clustering is frequently used. Nevertheless, biological data usually contain a large amount of noise data, and traditional clustering methods are sensitive to noise. However, acquiring higher-order spatial information from the data alone is insufficient. As a result, getting trustworthy clustering findings is challenging. We propose the Cauchy hyper-graph Laplacian non-negative matrix factorization (CHLNMF) as a unique approach to address these issues. In CHLNMF, we replace the measurement based on Euclidean distance in the conventional non-negative matrix factorization (NMF), which can lessen the influence of noise, with the Cauchy loss function (CLF). The model also incorporates the hyper-graph constraint, which takes into account the high-order link among the samples. The CHLNMF model's best solution is then discovered using a half-quadratic optimization approach. Finally, using seven scRNA-seq datasets, we contrast the CHLNMF technique with the other nine top methods. The validity of our technique was established by analysis of the experimental outcomes.

Dissection and integration of bursty transcriptional dynamics for complex systems

RNA velocity estimation is a potentially powerful tool to reveal the directionality of transcriptional changes in single-cell RNA-sequencing data, but it lacks accuracy, absent advanced metabolic labeling techniques. We developed an approach, TopicVelo, that disentangles simultaneous, yet distinct, dynamics by using a probabilistic topic model, a highly interpretable form of latent space factorization, to infer cells and genes associated with individual processes, thereby capturing cellular pluripotency or multifaceted functionality. Focusing on process-associated cells and genes enables accurate estimation of process-specific velocities via a master equation for a transcriptional burst model accounting for intrinsic stochasticity. The method obtains a global transition matrix by leveraging cell topic weights to integrate process-specific signals. In challenging systems, this method accurately recovers complex transitions and terminal states, while our use of first-passage time analysis provides insights into transient transitions. These results expand the limits of RNA velocity, empowering future studies of cell fate and functional responses.

The role of proliferating stem-like plasma cells in relapsed or refractory multiple myeloma: Insights from single-cell RNA sequencing and proteomic analysis.

The management and comprehension of relapsed or refractory multiple myeloma (RRMM) continues to pose a significant challenge. By integrating single-cell RNA sequencing (scRNA-seq) data of 15 patients with plasma cell disorders (PCDs) and proteomic data obtained from mass spectrometry-based analysis of CD138+ plasma cells (PCs) from 144 PCDs patients, we identified a state of malignant PCs characterized by high stemness score and increased proliferation originating from RRMM. This state has been designated as proliferating stem-like plasma cells (PSPCs). NUCKS1 was identified as the gene marker representing the stemness of PSPCs. Comparison of differentially expressed genes among various PC states revealed a significant elevation in LGALS1 expression in PSPCs. Survival analysis on the MMRF CoMMpass dataset and GSE24080 dataset established LGALS1 as a gene associated with unfavourable prognostic implications for multiple myeloma. Ultimately, we discovered three specific ligand-receptor pairs within the midkine (MDK) signalling pathway network that play distinct roles in facilitating efficient cellular communication between PSPCs and the surrounding microenvironment cells. These insights have the potential to contribute to the understanding of molecular mechanism and the development of therapeutic strategies involving the application of stem-like cells in RRMM treatment.

GHCU, a Molecular Chaperone, Regulates Leaf Curling by Modulating the Distribution of KNGH1 in Cotton.

Leaf shape is considered to be one of the most significant agronomic traits in crop breeding. However, the molecular basis underlying leaf morphogenesis in cotton is still largely unknown. In this study, through genetic mapping and molecular investigation using a natural cotton mutant cu with leaves curling upward, the causal gene GHCU is successfully identified as the key regulator of leaf flattening. Knockout of GHCU or its homolog in cotton and tobacco using CRISPR results in abnormal leaf shape. It is further discovered that GHCU facilitates the transport of the HD protein KNOTTED1-like (KNGH1) from the adaxial to the abaxial domain. Loss of GHCU function restricts KNGH1 to the adaxial epidermal region, leading to lower auxin response levels in the adaxial boundary compared to the abaxial. This spatial asymmetry in auxin distribution produces the upward-curled leaf phenotype of the cu mutant. By analysis of single-cell RNA sequencing and spatiotemporal transcriptomic data, auxin biosynthesis genes are confirmed to be expressed asymmetrically in the adaxial-abaxial epidermal cells. Overall, these findings suggest that GHCU plays a crucial role in the regulation of leaf flattening through facilitating cell-to-cell trafficking of KNGH1 and hence influencing the auxin response level.

Single-Cell RNA Sequencing Reveals Cardiac Fibroblast-Specific Transcriptomic Changes in Dilated Cardiomyopathy

Dilated cardiomyopathy (DCM) is the most common cause of heart failure, with a complex aetiology involving multiple cell types. We aimed to detect cell-specific transcriptomic alterations in DCM through analysis that leveraged recent advancements in single-cell analytical tools. Single-cell RNA sequencing (scRNA-seq) data from human DCM cardiac tissue were subjected to an updated bioinformatic workflow in which unsupervised clustering was paired with reference label transfer to more comprehensively annotate the dataset. Differential gene expression was detected primarily in the cardiac fibroblast population. Bulk RNA sequencing was performed on an independent cohort of human cardiac tissue and compared with scRNA-seq gene alterations to generate a stratified list of higher-confidence, fibroblast-specific expression candidates for further validation. Concordant gene dysregulation was confirmed in TGFβ-induced fibroblasts. Functional assessment of gene candidates showed that AEBP1 may play a significant role in fibroblast activation. This unbiased approach enabled improved resolution of cardiac cell-type-specific transcriptomic alterations in DCM.

Identifying Candidate Gene Drivers Associated with Relapse in Pediatric T-Cell Acute Lymphoblastic Leukemia Using a Gene Co-Expression Network Approach

Pediatric T-cell Acute Lymphoblastic Leukemia (T-ALL) relapses are still associated with a dismal outcome, justifying the search for new therapeutic targets and relapse biomarkers. Using single-cell RNA sequencing (scRNAseq) data from three paired samples of pediatric T-ALL at diagnosis and relapse, we first conducted a high-dimensional weighted gene co-expression network analysis (hdWGCNA). This analysis highlighted several gene co-expression networks (GCNs) and identified relapse-associated hub genes, which are considered potential driver genes. Shared relapse-expressed genes were found to be related to antigen presentation (HLA, B2M), cytoskeleton remodeling (TUBB, TUBA1B), translation (ribosomal proteins, EIF1, EEF1B2), immune responses (MIF, EMP3), stress responses (UBC, HSP90AB1/AA1), metabolism (FTH1, NME1/2, ARCL4C), and transcriptional remodeling (NF-κB family genes, FOS-JUN, KLF2, or KLF6). We then utilized sparse partial least squares discriminant analysis to select from a pool of 481 unique leukemic hub genes, which are the genes most discriminant between diagnosis and relapse states (comprising 44, 35, and 31 genes, respectively, for each patient). Applying a Cox regression method to these patient-specific genes, along with transcriptomic and clinical data from the TARGET-ALL AALL0434 cohort, we generated three model gene signatures that efficiently identified relapsed patients within the cohort. Overall, our approach identified new potential relapse-associated genes and proposed three model gene signatures associated with lower survival rates for high-score patients.