Combining single-cell and bulk RNA sequencing, NK cell marker genes reveal a prognostic and immune status in pancreatic ductal adenocarcinoma.

The NK cell is an important component of the tumor microenvironment of pancreatic ductal adenocarcinoma (PDAC), also plays a significant role in PDAC development. This study aimed to explore the relationship between NK cell marker genes and prognosis, immune response of PDAC patients. By scRNA-seq data, we found the proportion of NK cells were significantly downregulated in PDAC and 373 NK cell marker genes were screened out. By TCGA database, we enrolled 7 NK cell marker genes to construct the signature for predicting prognosis in PDAC patients. Cox analysis identified the signature as an independent factor for pancreatic cancer. Subsequently, the predictive power of signature was validated by 6 GEO datasets and had an excellent evaluation. Our analysis of relationship between the signature and patients' immune status revealed that the signature has a strong correlation with immunocyte infiltration, inflammatory reaction, immune checkpoint inhibitors (ICIs) response. The NK cell marker genes are closely related to the prognosis and immune capacity of PDAC patients, and they have potential value as a therapeutic target.

Comprehensive investigation of malignant epithelial cell-related genes in clear cell renal cell carcinoma: development of a prognostic signature and exploration of tumor microenvironment interactions.

Clear cell renal cell carcinoma (ccRCC) is a prevalent malignancy with complex heterogeneity within epithelial cells, which plays a crucial role in tumor progression and immune regulation. Yet, the clinical importance of the malignant epithelial cell-related genes (MECRGs) in ccRCC remains insufficiently understood. This research aims to undertake a comprehensive investigation into the functions and clinical relevance of malignant epithelial cell-related genes in ccRCC, providing valuable understanding of the molecular mechanisms and offering potential targets for treatment strategies. Using data from single-cell sequencing, we successfully identified 219 MECRGs and established a prognostic model MECRGS (MECRGs' signature) by synergistically analyzing 101 machine-learning models using 10 different algorithms. Remarkably, the MECRGS demonstrated superior predictive performance compared to traditional clinical features and 92 previously published signatures across six cohorts, showcasing its independence and accuracy. Upon stratifying patients into high- and low-MECRGS subgroups using the specified cut-off threshold, we noted that patients with elevated MECRGS scores displayed characteristics of an immune suppressive tumor microenvironment (TME) and showed worse outcomes after immunotherapy. Additionally, we discovered a distinct ccRCC tumor cell subtype characterized by the high expressions of PLOD2 (procollagen-lysine,2-oxoglutarate 5-dioxygenase 2) and SAA1 (Serum Amyloid A1), which we further validated in the Renji tissue microarray (TMA) cohort. Lastly, 'Cellchat' revealed potential crosstalk patterns between these cells and other cell types, indicating their potential role in recruiting CD163 + macrophages and regulatory T cells (Tregs), thereby establishing an immunosuppressive TME. PLOD2 + SAA1 + cancer cells with intricate crosstalk patterns indeed show promise for potential therapeutic interventions.

A distinct subset of urothelial cells with enhanced EMT features promotes chemotherapy resistance and cancer recurrence by increasing COL4A1-ITGB1 mediated angiogenesis.

Drug resistance and tumor recurrence remain clinical challenges in the treatment of urothelial carcinoma (UC). However, the underlying mechanism is not fully understood. Here, we performed single-cell RNA sequencing and identified a subset of urothelial cells with epithelial-mesenchymal transition (EMT) features (EMT-UC), which is significantly correlated with chemotherapy resistance and cancer recurrence. To validate the clinical significance of EMT-UC, we constructed EMT-UC like cells by introducing overexpression of two markers, Zinc Finger E-Box Binding Homeobox 1 (ZEB1) and Desmin (DES), and examined their histological distribution characteristics and malignant phenotypes. EMT-UC like cells were mainly enriched in UC tissues from patients with adverse prognosis and exhibited significantly elevated EMT, migration and gemcitabine tolerance in vitro. However, EMT-UC was not specifically identified from tumorous tissues, certain proportion of them were also identified in adjacent normal tissues. Tumorous EMT-UC highly expressed genes involved in malignant behaviors and exhibited adverse prognosis. Additionally, tumorous EMT-UC was associated with remodeled tumor microenvironment (TME), which exhibited high angiogenic and immunosuppressive potentials compared with the normal counterparts. Furthermore, a specific interaction of COL4A1 and ITGB1 was identified to be highly enriched in tumorous EMT-UC, and in the endothelial component. Targeting the interaction of COL4A1 and ITGB1 with specific antibodies significantly suppressed tumorous angiogenesis and alleviated gemcitabine resistance of UC. Overall, our findings demonstrated that the driven force of chemotherapy resistance and recurrence of UC was EMT-UC mediated COL4A1-ITGB1 interaction, providing a potential target for future UC treatment.

Bone marrow cells contribute to seven different endothelial cell populations in the heart.

Understanding the mechanisms underlying vascular regeneration in the heart is crucial for developing novel therapeutic strategies for myocardial ischemia. This study investigates the contribution of bone marrow-derived cells to endothelial cell populations in the heart, and their role in cardiac function and coronary circulation following repetitive ischemia (RI). Chimeric rats were created by transplanting BM cells from GFP female rats into irradiated male recipients. After engraftment chimeras were subjected to RI for 17 days. Vascular growth was assessed from recovery of cardiac function and increases in myocardial blood flow during LAD occlusion. After sorting GFP+ BM cells from heart and bone of Control and RI rats, single-cell RNA sequencing was implemented to determine the fate of BM cells. Our in vivo RI model demonstrated an improvement in cardiac function and myocardial blood flow after 17 days of RI with increased capillary density in the rats subjected to RI compared to Controls. Single-cell RNA sequencing of bone marrow cells isolated from rats' hearts identified distinct endothelial cell (EC) subpopulations. These ECs exhibited heterogeneous gene expression profiles and were enriched for markers of capillary, artery, lymphatic, venous, and immune ECs. Furthermore, BM-derived ECs in the RI group showed an angiogenic profile, characterized by upregulated genes associated with blood vessel development and angiogenesis. This study elucidates the heterogeneity of bone marrow-derived endothelial cells in the heart and their response to repetitive ischemia, laying the groundwork for targeting specific subpopulations for therapeutic angiogenesis in myocardial ischemia.

The Novel-B-Cell-Related Gene Signature Predicts the Prognosis and Immune Status of Patients with Esophageal Carcinoma.

BACKGROUND: The current understanding of the prognostic significance of B cells and their role in the tumor microenvironment (TME) in esophageal carcinoma (ESCA) is limited. METHODS: We conducted a screening for B-cell-related genes through the analysis of single-cell transcriptome data. Subsequently, we developed a B-cell-related gene signature (BRGrisk) using LASSO regression analysis. Patients from The Cancer Genome Atlas cohort were divided into a training cohort and a test cohort. Patients were categorized into high- and low-risk groups based on their median BRGrisk scores. The overall survival was assessed using the Kaplan-Meier method, and a nomogram based on BRGrisk was constructed. Immune infiltration profiles between the risk groups were also compared. RESULTS: The BRGrisk prognostic model indicated significantly worse outcomes for patients with high BRGrisk scores (p < 0.001). The BRGrisk-based nomogram exhibited good prognostic performance. Analysis of immune infiltration revealed that patients in the high-BRGrisk group had notably higher levels of immune cell infiltration and were more likely to be in an immunoresponsive state. Enrichment analysis showed a strong correlation between the prognostic gene signature and cancer-related pathways. IC50 results indicated that patients in the low-BRGrisk group were more responsive to common drugs compared to those in the high-BRGrisk group. CONCLUSIONS: This study presents a novel BRGrisk that can be used to stratify the prognosis of ESCA patients and may offer guidance for personalized treatment strategies aimed at improving prognosis.

RNA-binding protein AZGP1 inhibits epithelial cell proliferation by regulating the genes of alternative splicing in COPD.

BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is characterized by high morbidity, disability, and mortality rates worldwide. RNA-binding proteins (RBPs) might regulate genes involved in oxidative stress and inflammation in COPD patients. Single-cell transcriptome sequencing (scRNA-seq) offers an accurate tool for identifying intercellular heterogeneity and the diversity of immune cells. However, the role of RBPs in the regulation of various cells, especially AT2 cells, remains elusive. MATERIALS AND METHODS: A scRNA-seq dataset (GSE173896) and a bulk RNA-seq dataset acquired from airway tissues (GSE124180) were employed for data mining. Next, RNA-seq analysis was performed in both COPD and control patients. Differentially expressed genes (DEGs) were identified using criteria of fold change (FC ≥ 1.5 or ≤ 1.5) and P value ≤ 0.05. Lastly, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and alternative splicing identification analyses were carried out. RESULTS: RBP genes exhibited specific expression patterns across different cell groups and participated in cell proliferation and mitochondrial dysfunction in AT2 cells. As an RBP, AZGP1 expression was upregulated in both the scRNA-seq and RNA-seq datasets. It might potentially be a candidate immune biomarker that regulates COPD progression by modulating AT2 cell proliferation and adhesion by regulating the expression of SAMD5, DNER, DPYSL3, GBP5, GBP3, and KCNJ2. Moreover, AZGP1 regulated alternative splicing events in COPD, particularly DDAH1 and SFRP1, holding significant implications in COPD. CONCLUSION: RBP gene AZGP1 inhibits epithelial cell proliferation by regulating genes participating in alternative splicing in COPD.

Single-cell analysis of Crohn's disease: Unveiling heterogeneity and evaluating ustekinumab outcomes.

BACKGROUND: The present study aimed to dissect the cellular complexity of Crohn's disease (CD) using single-cell RNA sequencing, focusing on identifying key cell populations and their transcriptional profiles in inflamed tissue. METHODS: We applied scRNA-sequencing to compare the cellular composition of CD patients with healthy controls, utilizing Seurat for clustering and annotation. Differential gene expression analysis and protein-protein interaction networks were constructed to identify crucial genes and pathways. RESULTS: Our study identified eight distinct cell types in CD, highlighting crucial fibroblast and T cell interactions. The analysis revealed key cellular communications and identified significant genes and pathways involved in the disease's pathology. The role of fibroblasts was underscored by elevated expression in diseased samples, offering insights into disease mechanisms and potential therapeutic targets, including responses to ustekinumab treatment, thus enriching our understanding of CD at a molecular level. CONCLUSIONS: Our findings highlight the complex cellular and molecular interplay in CD, suggesting new biomarkers and therapeutic targets, offering insights into disease mechanisms and treatment implications.

CD300LF+ microglia impede the neuroinflammation following traumatic brain injury by inhibiting STING pathway.

INTRODUCTION: The diversity in microglial phenotypes and functions following traumatic brain injury (TBI) is poorly characterized. The aim of this study was to explore precise targets for improving the prognosis of TBI patients from a microglial perspective. OBJECTIVES: To assess whether the prognosis of TBI can be improved by modulating microglia function. RESULTS: In CD300LF-deficient mice, we observed an increase in glial cell proliferation, more extensive neuronal loss, and worsened neurological function post-TBI. Transcriptomic comparisons between CD300LF-positive and CD300LF-negative microglia illuminated that the neuroprotective role of CD300LF is principally mediated by the inhibition of the STING signaling pathway. In addition, this protective effect can be augmented using the STING pathway inhibitor C-176. CONCLUSIONS: Our research indicates that CD300LF reduces neuroinflammation and promotes neurological recovery after TBI, and that microglia are integral to the protective effects of CD300LF in this context. In summary, our findings highlight CD300LF as a critical molecular regulator modulating the adverse actions of microglia following acute brain injury and propose a novel therapeutic approach to enhance outcomes for patients with TBI.

Prostate cancer cancer-associated fibroblasts with stable markers post-androgen deprivation therapy associated with tumor progression and castration resistant prostate cancer.

The specificity and clinical relevance of cancer-associated fibroblasts (CAFs) in prostate cancer (PCa), as well as the effect of androgen deprivation therapy (ADT) on CAFs, remain to be fully elucidated. Using cell lineage diversity and weighted gene co-expression network analysis (WGCNA), we pinpointed a unique CAF signature exclusive to PCa. The specificity of this CAF signature was validated through single-cell RNA sequencing (scRNA-seq), cell line RNA sequencing, and immunohistochemistry. This signature associates CAFs with tumor progression, elevated Gleason scores, and the emergence of castration resistant prostate cancer (CRPC). Using scRNA-seq on collected samples, we demonstrated that the CAF-specific signature is not altered by ADT, maintaining its peak signal output. Identifying a PCa-specific CAF signature and observing signaling changes in CAFs after ADT lay essential groundwork for further PCa studies.

Establishment of an ovarian cancer exhausted CD8+T cells-related genes model by integrated analysis of scRNA-seq and bulk RNA-seq.

Ovarian cancer (OC) was the fifth leading cause of cancer death and the deadliest gynecological cancer in women. This was largely attributed to its late diagnosis, high therapeutic resistance, and a dearth of effective treatments. Clinical and preclinical studies have revealed that tumor-infiltrating CD8+T cells often lost their effector function, the dysfunctional state of CD8+T cells was known as exhaustion. Our objective was to identify genes associated with exhausted CD8+T cells (CD8TEXGs) and their prognostic significance in OC. We downloaded the RNA-seq and clinical data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. CD8TEXGs were initially identified from single-cell RNA-seq (scRNA-seq) datasets, then univariate Cox regression, the least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression were utilized to calculate risk score and to develop the CD8TEXGs risk signature. Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, time-dependent receiver operating characteristics (ROC), nomogram, and calibration were conducted to verify and evaluate the risk signature. Gene set enrichment analyses (GSEA) in the risk groups were used to figure out the closely correlated pathways with the risk group. The role of risk score has been further explored in the homologous recombination repair deficiency (HRD), BRAC1/2 gene mutations and tumor mutation burden (TMB). A risk signature with 4 CD8TEXGs in OC was finally built in the TCGA database and further validated in large GEO cohorts. The signature also demonstrated broad applicability across various types of cancer in the pan-cancer analysis. The high-risk score was significantly associated with a worse prognosis and the risk score was proven to be an independent prognostic biomarker. The 1-, 3-, and 5-years ROC values, nomogram, calibration, and comparison with the previously published models confirmed the excellent prediction power of this model. The low-risk group patients tended to exhibit a higher HRD score, BRCA1/2 gene mutation ratio and TMB. The low-risk group patients were more sensitive to Poly-ADP-ribose polymerase inhibitors (PARPi). Our findings of the prognostic value of CD8TEXGs in prognosis and drug response provided valuable insights into the molecular mechanisms and clinical management of OC.

Imbalance of programmed cell death patterns mediated by dendritic cell subsets in systemic lupus erythematosus and lupus nephritis. / æ ‘çªçŠ¶ç»†èƒžäºšç¾¤ä»‹å¯¼ç³»ç»Ÿæ€§çº¢æ–‘ç‹¼ç–®å’Œç‹¼ç–®è‚¾ç‚Žçš„ç¨‹åºæ€§ç»†èƒžæ­»äº¡æ¨¡å¼å¤±è¡¡ï¼ˆè‹±æ–‡ï¼‰.

OBJECTIVES: Abnormal programmed cell death in immune cells is associated with autoimmune diseases, but the patterns of programmed cell death in systemic lupus erythematosus (SLE) and especially lupus nephritis (LN) remain unclear. This study aims to explore the association between SLE, LN, and immune cell death patterns. METHODS: Bulk RNA sequencing (bulk RNA-seq) and single-cell RNA sequencing (scRNA-seq) data were downloaded from the Gene Expression Omnibus (GEO) database. Bioinformatic analysis was conducted to explore the expression levels of genes related to 3 cell death patterns in peripheral blood mononuclear cells of SLE patients. Key cell subsets involved in the imbalance of cell death patterns were identified through scRNA-seq. Immunofluorescence was used to detect the expression levels of receptor interacting serine/threonine kinase 3 (RIPK3), mixed-lineage kinase domain-like protein (MLKL), phosphorylated MLKL (pMLKL), caspase 1 (CASP1), CD1c molecule (CD1C), C-type lectin domain containing 9A (CLEC9A), and X-C motif chemokine receptor 1 (XCR1) in dendritic cells (DC). scRNA-seq was performed on kidney tissues collected from LN patients and healthy controls (HC) at the Third Xiangya Hospital of Central South University, followed by bioinformatic analysis to identify key cell subsets involved in the imbalance of cell death patterns. Pseudotime analysis and ligand-receptor analysis were used to explore the differentiation direction and cell communication of different DC subsets. Transient transfection was used to transfect RAW264.7 cells with empty plasmid, empty plasmid+dsDNA (HSV-DNA), empty plasmid+200 µmol/L tert-butyl hydroperoxide (TBHP), stimulator of interferon genes (STING) shRNA plasmid, STING shRNA plasmid+dsDNA (HSV-DNA), and STING shRNA plasmid+200 µmol/L TBHP. Annexin V-mCherry and SYTOX Green staining were used to detect cell death in each group. Western blotting was used to detect the activation of CASP1, gasdermin D (GSDMD), RIPK3, and MLKL in each group. RESULTS: Bioinformatic analysis showed an imbalance in 3 cell death patterns in SLE and LN patients: Pro-inflammatory pyroptosis and necroptosis were activated, while anti-inflammatory apoptosis was inhibited. The key cell subsets involved were DC subsets, particularly focusing on CLEC9A+cDC1. Immunofluorescence results showed that the expression levels of RIPK3, MLKL, and CASP1 in DCs were higher in the SLE group compared to the HC group. pMLKL and CASP1 expression levels in renal cDC1 marked by CLEC9A and XCR1 were higher in the LN group than in the HC group. Pseudotime analysis and ligand-receptor analysis suggested that the CLEC9A+cDC1 subset in LN kidney tissues originated from peripheral circulation. Annexin V-mCherry and SYTOX Green staining results showed that the number of dead cells decreased in the STING shRNA transfection group compared to the empty plasmid group in RAW264.7 cells. Western blotting results showed that the activation of CASP1, GSDMD, RIPK3, and MLKL was decreased in the STING shRNA transfection group compared to the empty plasmid group. CONCLUSIONS: This study provides novel insights into the role of CLEC9A+cDC1 in the imbalance of cell death patterns in SLE and LN.

Single-cell transcriptome analysis reveals two subtypes of tumor cells of sclerosing pneumocytoma with distinct molecular features and clinical implications.

Pulmonary sclerosing pneumocytoma (PSP) is a rare, distinctive benign lung adenoma of pneumocyte origin. Despite its rarity, the tumor's unique cellular morphology has sparked ongoing debates regarding the origin of its constituent cells. This study aimed to elucidate the molecular features of PSP tumor cells and enhance our understanding of the cellular processes contributing to PSP formation and biological behavior. Tissue samples from PSP and corresponding normal lung tissues (n = 4) were collected. We employed single-cell RNA sequencing and microarray-based spatial transcriptomic analyses to identify cell types and investigate their transcriptomes, with a focus on transcription factors, enriched gene expression, and single-cell trajectory evaluations. Our analysis identified two types of tumor cells: mesenchymal epithelial dual phenotype cells (MEDPs) and a distinct subpopulation of type II alveolar epithelial cells exhibiting characteristics slightly reminiscent of type I alveolar epithelial cells (AT2Cs), corresponding to histological round stromal cells and surface cuboidal cells, respectively. MEDPs displayed weak alveolar epithelial differentiation but strong collagen production capabilities, as indicated by the expression of both TTF-1 and vimentin. These cells played a pivotal role in forming the solid and sclerotic areas of PSP. Moreover, MEDPs exhibited a pronounced propensity for epithelial-mesenchymal transition, suggesting a greater potential for metastasis compared to AT2Cs. The capillary endothelial cells of PSP displayed notable diversity. Overall, this study provides, for the first time, a comprehensive mapping of the single-cell transcriptome profile of PSP. Our findings delineate two distinct subtypes of tumor cells, MEDPs and AT2Cs, each with its own biological characteristics and spatial distribution. A deeper understanding of these cell types promises insights into the histology and biological behaviors of this rare tumor.

Deciphering brain cellular and behavioral mechanisms: Insights from single-cell and spatial RNA sequencing.

The brain is a complex computing system composed of a multitude of interacting neurons. The computational outputs of this system determine the behavior and perception of every individual. Each brain cell expresses thousands of genes that dictate the cell's function and physiological properties. Therefore, deciphering the molecular expression of each cell is of great significance for understanding its characteristics and role in brain function. Additionally, the positional information of each cell can provide crucial insights into their involvement in local brain circuits. In this review, we briefly overview the principles of single-cell RNA sequencing and spatial transcriptomics, the potential issues and challenges in their data processing, and their applications in brain research. We further outline several promising directions in neuroscience that could be integrated with single-cell RNA sequencing, including neurodevelopment, the identification of novel brain microstructures, cognition and behavior, neuronal cell positioning, molecules and cells related to advanced brain functions, sleep-wake cycles/circadian rhythms, and computational modeling of brain function. We believe that the deep integration of these directions with single-cell and spatial RNA sequencing can contribute significantly to understanding the roles of individual cells or cell types in these specific functions, thereby making important contributions to addressing critical questions in those fields. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA in Disease and Development > RNA in Development RNA in Disease and Development > RNA in Disease.

Dual-specificity phosphatases 13 and 27 as key switches in muscle stem cell transition from proliferation to differentiation.

Muscle regeneration depends on muscle stem cell (MuSC) activity. Myogenic regulatory factors, including myoblast determination protein 1 (MyoD), regulate the fate transition of MuSCs. However, the direct target of MYOD in the process is not completely clear. Using previously established MyoD knock-in (MyoD-KI) mice, we revealed that MyoD targets dual-specificity phosphatase (Dusp) 13 and Dusp27. In Dusp13:Dusp27 double knock-out (DKO) mice, the ability for muscle regeneration after injury was reduced. Moreover, single-cell RNA sequencing of MyoD-high expressing MuSCs from MyoD-KI mice revealed that Dusp13 and Dusp27 are expressed only in specific populations within MyoD-high MuSCs, which also express Myogenin. Overexpressing Dusp13 in MuSCs causes premature muscle differentiation. Thus, we propose a model where DUSP13 and DUSP27 contribute to the fate transition of MuSCs from proliferation to differentiation during myogenesis.

Thyroid hormone T4 mitigates traumatic brain injury in mice by dynamically remodeling cell type specific genes, pathways, and networks in hippocampus and frontal cortex.

The complex pathology of mild traumatic brain injury (mTBI) is a main contributor to the difficulties in achieving a successful therapeutic regimen. Thyroxine (T4) administration has been shown to prevent the cognitive impairments induced by mTBI in mice but the mechanism is poorly understood. To understand the underlying mechanism, we carried out a single cell transcriptomic study to investigate the spatiotemporal effects of T4 on individual cell types in the hippocampus and frontal cortex at three post-injury stages in a mouse model of mTBI. We found that T4 treatment altered the proportions and transcriptomes of numerous cell types across tissues and timepoints, particularly oligodendrocytes, astrocytes, and microglia, which are crucial for injury repair. T4 also reversed the expression of mTBI-affected genes such as Ttr, mt-Rnr2, Ggn12, Malat1, Gnaq, and Myo3a, as well as numerous pathways such as cell/energy/iron metabolism, immune response, nervous system, and cytoskeleton-related pathways. Cell-type specific network modeling revealed that T4 mitigated select mTBI-perturbed dynamic shifts in subnetworks related to cell cycle, stress response, and RNA processing in oligodendrocytes. Cross cell-type ligand-receptor networks revealed the roles of App, Hmgb1, Fn1, and Tnf in mTBI, with the latter two ligands having been previously identified as TBI network hubs. mTBI and/or T4 signature genes were enriched for human genome-wide association study (GWAS) candidate genes for cognitive, psychiatric and neurodegenerative disorders related to mTBI. Our systems-level single cell analysis elucidated the temporal and spatial dynamic reprogramming of cell-type specific genes, pathways, and networks, as well as cell-cell communications as the mechanisms through which T4 mitigates cognitive dysfunction induced by mTBI.

Identification of New Chemoresistance-Associated Genes in Triple-Negative Breast Cancer by Single-Cell Transcriptomic Analysis.

Triple-negative breast cancer (TNBC) is a particularly aggressive mammary neoplasia with a high fatality rate, mainly because of the development of resistance to administered chemotherapy, the standard treatment for this disease. In this study, we employ both bulk RNA-sequencing and single-cell RNA-sequencing (scRNA-seq) to investigate the transcriptional landscape of TNBC cells cultured in two-dimensional monolayers or three-dimensional spheroids, before and after developing resistance to the chemotherapeutic agents paclitaxel and doxorubicin. Our findings reveal significant transcriptional heterogeneity within the TNBC cell populations, with the scRNA-seq identifying rare subsets of cells that express resistance-associated genes not detected by the bulk RNA-seq. Furthermore, we observe a partial shift towards a highly mesenchymal phenotype in chemoresistant cells, suggesting the epithelial-to-mesenchymal transition (EMT) as a prevalent mechanism of resistance in subgroups of these cells. These insights highlight potential therapeutic targets, such as the PDGF signaling pathway mediating EMT, which could be exploited in this setting. Our study underscores the importance of single-cell approaches in understanding tumor heterogeneity and developing more effective, personalized treatment strategies to overcome chemoresistance in TNBC.

Macrophage iron dyshomeostasis promotes aging-related renal fibrosis.

Renal aging, marked by the accumulation of senescent cells and chronic low-grade inflammation, leads to renal interstitial fibrosis and impaired function. In this study, we investigate the role of macrophages, a key regulator of inflammation, in renal aging by analyzing kidney single-cell RNA sequencing data of C57BL/6J mice from 8 weeks to 24 months. Our findings elucidate the dynamic changes in the proportion of kidney cell types during renal aging and reveal that increased macrophage infiltration contributes to chronic low-grade inflammation, with these macrophages exhibiting senescence and activation of ferroptosis signaling. CellChat analysis indicates enhanced communications between macrophages and tubular cells during aging. Suppressing ferroptosis alleviates macrophage-mediated tubular partial epithelial-mesenchymal transition in vitro, thereby mitigating the expression of fibrosis-related genes. Using SCENIC analysis, we infer Stat1 as a key age-related transcription factor promoting iron dyshomeostasis and ferroptosis in macrophages by regulating the expression of Pcbp1, an iron chaperone protein that inhibits ferroptosis. Furthermore, through virtual screening and molecular docking from a library of anti-aging compounds, we construct a docking model targeting Pcbp1, which indicates that the natural small molecule compound Rutin can suppress macrophage senescence and ferroptosis by preserving Pcbp1. In summary, our study underscores the crucial role of macrophage iron dyshomeostasis and ferroptosis in renal aging. Our results also suggest Pcbp1 as an intervention target in aging-related renal fibrosis and highlight Rutin as a potential therapeutic agent in mitigating age-related renal chronic low-grade inflammation and fibrosis.

Single-cell RNA Sequencing Identifies a Novel Subtype of Microglia with High Cd74 Expression that Facilitates White Matter Inflammation During Chronic Cerebral Hypoperfusion.

Vascular dementia (VaD) causes progressive cognitive decline in the elderly population, but there is short of available therapeutic measures. Microglia-mediated neuroinflammation is vigorously involved in the pathogenesis of VaD, but the traditional classification of microglial M1/M2 phenotypes remains restrictive and controversial. This study aims to investigate whether microglia transform into novel subtypes in VaD. Chronic cerebral hypoperfusion (CCH) rat model was constructed to mimic VaD. Microglia were isolated via magnetic-activated cell sorting and analyzed by single-cell RNA sequencing (scRNA-seq) and bioinformatics. The findings inferred from scRNA-seq and bioinformatics were further validated through in vivo experiments. In this study, microglia were divided into eight clusters. The proportion of MG5 cluster was significantly increased in the white matter of the CCH group compared with the Sham group and was named chronic ischemia-associated microglia (CIAM). Immunity- and inflammation-related genes, including RT1-Db1, RT1-Da, RT1-Ba, Cd74, Spp1, C3, and Cd68, were markedly upregulated in CIAM. Enrichment analysis illustrated that CIAM possessed the function of evoking neuroinflammation. Further studies unveiled that Cd74 is associated with the most abundant GO terms involved in inflammation as well as cell proliferation and differentiation. In addition, microglia-specific Cd74 knockdown mediated by adeno-associated virus decreased the abundance of CIAM in the white matter, thereby mitigating inflammatory cytokine levels, alleviating white matter lesions, and improving cognitive impairment for CCH rats. These findings indicate that Cd74 is the core molecule of CIAM to trigger neuroinflammation and induce microglial differentiation to CIAM, suggesting that Cd74 may be a potential therapeutic target for VaD.

Exploring the Pathogenesis of Autoimmune Liver Diseases from the Heterogeneity of Target Cells.

The incidence of autoimmune liver diseases (ALDs) and research on their pathogenesis are increasing annually. However, except for autoimmune hepatitis, which responds well to immunosuppression, primary biliary cholangitis and primary sclerosing cholangitis are insensitive to immunosuppressive therapy. Besides the known effects of the environment, genetics, and immunity on ALDs, the heterogeneity of target cells provides new insights into their pathogenesis. This review started by exploring the heterogeneity in the development, structures, and functions of hepatocytes and epithelial cells of the small and large bile ducts. For example, cytokeratin (CK) 8 and CK18 are primarily expressed in hepatocytes, while CK7 and CK19 are primarily expressed in intrahepatic cholangiocytes. Additionally, emerging technologies of single-cell RNA sequencing and spatial transcriptomic are being applied to study ALDs. This review offered a new perspective on understanding the pathogenic mechanisms and potential treatment strategies for ALDs.

Characterizing efficient feature selection for single-cell expression analysis.

Unsupervised feature selection is a critical step for efficient and accurate analysis of single-cell RNA-seq data. Previous benchmarks used two different criteria to compare feature selection methods: (i) proportion of ground-truth marker genes included in the selected features and (ii) accuracy of cell clustering using ground-truth cell types. Here, we systematically compare the performance of 11 feature selection methods for both criteria. We first demonstrate the discordance between these criteria and suggest using the latter. We then compare the distribution of selected genes in their means between feature selection methods. We show that lowly expressed genes exhibit seriously high coefficients of variation and are mostly excluded by high-performance methods. In particular, high-deviation- and high-expression-based methods outperform the widely used in Seurat package in clustering cells and data visualization. We further show they also enable a clear separation of the same cell type from different tissues as well as accurate estimation of cell trajectories.