SuperFeat: Quantitative Feature Learning from Single-cell RNA-seq Data Facilitates Drug Repurposing.

In this study, we devised a computational framework called Supervised Feature Learning and Scoring (SuperFeat) which enables the training of a machine learning model and evaluates the canonical cellular statuses/features in pathological tissues that underlie the progression of disease. This framework also enables the identification of potential drugs that target the presumed detrimental cellular features. This framework was constructed on the basis of an artificial neural network with the gene expression profiles serving as input nodes. The training data comprised single-cell RNA sequencing datasets that encompassed the specific cell lineage during the developmental progression of cell features. A few models of the canonical cancer-involved cellular statuses/features were tested by such framework. Finally, we illustrated the drug repurposing pipeline, utilizing the training parameters derived from the adverse cellular statuses/features, which yielded successful validation results both in vitro and in vivo. SuperFeat is accessible at https://github.com/weilin-genomics/rSuperFeat.

Single-cell transcriptional atlas of human breast cancers and model systems.

BACKGROUND: Breast cancer's complex transcriptional landscape requires an improved understanding of cellular diversity to identify effective treatments. The study of genetic variations among breast cancer subtypes at single-cell resolution has potential to deepen our insights into cancer progression. METHODS: In this study, we amalgamate single-cell RNA sequencing data from patient tumours and matched lymph metastasis, reduction mammoplasties, breast cancer patient-derived xenografts (PDXs), PDX-derived organoids (PDXOs), and cell lines resulting in a diverse dataset of 117 samples with 506 719 total cells. These samples encompass hormone receptor positive (HR+), human epidermal growth factor receptor 2 positive (HER2+), and triple-negative breast cancer (TNBC) subtypes, including isogenic model pairs. Herein, we delineated similarities and distinctions across models and patient samples and explore therapeutic drug efficacy based on subtype proportions. RESULTS: PDX models more closely resemble patient samples in terms of tumour heterogeneity and cell cycle characteristics when compared with TNBC cell lines. Acquired drug resistance was associated with an increase in basal-like cell proportions within TNBC PDX tumours as defined with SCSubtype and TNBCtype cell typing predictors. All patient samples contained a mixture of subtypes; compared to primary tumours HR+ lymph node metastases had lower proportions of HER2-Enriched cells. PDXOs exhibited differences in metabolic-related transcripts compared to PDX tumours. Correlative analyses of cytotoxic drugs on PDX cells identified therapeutic efficacy was based on subtype proportion. CONCLUSIONS: We present a substantial multimodel dataset, a dynamic approach to cell-wise sample annotation, and a comprehensive interrogation of models within systems of human breast cancer. This analysis and reference will facilitate informed decision-making in preclinical research and therapeutic development through its elucidation of model limitations, subtype-specific insights and novel targetable pathways. KEY POINTS: Patient-derived xenografts models more closely resemble patient samples in tumour heterogeneity and cell cycle characteristics when compared with cell lines. 3D organoid models exhibit differences in metabolic profiles compared to their in vivo counterparts. A valuable multimodel reference dataset that can be useful in elucidating model differences and novel targetable pathways.

Discovery of plasma biomarkers related to blood-brain barrier dysregulation in Alzheimer's disease.

Introduction: Blood-based biomarkers are quantitative, non-invasive diagnostic tools. This study aimed to identify candidate biomarkers for Alzheimer's disease (AD) using publicly available omics datasets, using the hypothesis that with blood-brain barrier dysfunction in AD, brain-synthesized proteins can leak into plasma for detection. Methods: Differential abundance results of plasma and brain proteomic datasets were integrated to obtain a list of potential biomarkers. Biological validity was investigated with intercellular communication and gene regulatory analyses on brain single-cell transcriptomics data. Results: Five proteins (APOD, B2M, CFH, CLU, and C3) fit biomarker criteria. 4 corresponding transcripts (APOD, B2M, CLU, and C3) were overexpressed in AD astrocytes, mediated by AD-related dysregulations in transcription factors regulating neuroinflammation. Additionally, CLU specifically induced downstream expression of neuronal death genes. Discussion: In conclusion, a 5-protein panel is shown to effectively identify AD patients, with evidence of disease specificity and biological validity. Future research should investigate the mechanism of protein leakage through the blood-brain barrier.

scEMB: Learning context representation of genes based on large-scale single-cell transcriptomics.

Background: The rapid advancement of single-cell transcriptomic technologies has led to the curation of millions of cellular profiles, providing unprecedented insights into cellular heterogeneity across various tissues and developmental stages. This growing wealth of data presents an opportunity to uncover complex gene-gene relationships, yet also poses significant computational challenges. Results: We present scEMB, a transformer-based deep learning model developed to capture context-aware gene embeddings from large-scale single-cell transcriptomics data. Trained on over 30 million single-cell transcriptomes, scEMB utilizes an innovative binning strategy that integrates data across multiple platforms, effectively preserving both gene expression hierarchies and cell-type specificity. In downstream tasks such as batch integration, clustering, and cell type annotation, scEMB demonstrates superior performance compared to existing models like scGPT and Geneformer. Notably, scEMB excels in silico correlation analysis, accurately predicting gene perturbation effects in CRISPR-edited datasets and microglia state transition, identifying a few known Alzheimer's disease (AD) risks genes in top gene list. Additionally, scEMB offers robust fine-tuning capabilities for domain-specific applications, making it a versatile tool for tackling diverse biological problems such as therapeutic target discovery and disease modeling. Conclusions: scEMB represents a powerful tool for extracting biologically meaningful insights from complex gene expression data. Its ability to model in silico perturbation effects and conduct correlation analyses in the embedding space highlights its potential to accelerate discoveries in precision medicine and therapeutic development.

Transcriptomic profiling of Schlemm's canal cells reveals a lymphatic-biased identity and three major cell states.

Schlemm's canal (SC) is central in intraocular pressure regulation but requires much characterization. It has distinct inner and outer walls, each composed of Schlemm's canal endothelial cells (SECs) with different morphologies and functions. Recent transcriptomic studies of the anterior segment added important knowledge, but were limited in power by SEC numbers or did not focus on SC. To gain a more comprehensive understanding of SC biology, we performed bulk RNA sequencing on C57BL/6 J SC, blood vessel, and lymphatic endothelial cells from limbal tissue (~4,500 SECs). We also analyzed mouse limbal tissues by single-cell and single-nucleus RNA sequencing (C57BL/6 J and 129/Sj strains), successfully sequencing 903 individual SECs. Together, these datasets confirm that SC has molecular characteristics of both blood and lymphatic endothelia with a lymphatic phenotype predominating. SECs are enriched in pathways that regulate cell-cell junction formation pointing to the importance of junctions in determining SC fluid permeability. Importantly, and for the first time, our analyses characterize three molecular classes of SECs, molecularly distinguishing inner wall from outer wall SECs and discovering two inner wall cell states that likely result from local environmental differences. Further, and based on ligand and receptor expression patterns, we document key interactions between SECs and cells of the adjacent trabecular meshwork (TM) drainage tissue. Also, we present cell type expression for a collection of human glaucoma genes. These data provide a new molecular foundation that will enable the functional dissection of key homeostatic processes mediated by SECs as well as the development of new glaucoma therapeutics.

Single-cell transcriptome analysis reveals immune microenvironment changes and insights into the transition from DCIS to IDC with associated prognostic genes.

BACKGROUND: Ductal carcinoma in situ (DCIS) of the breast is an early stage of breast cancer, and preventing its progression to invasive ductal carcinoma (IDC) is crucial for the early detection and treatment of breast cancer. Although single-cell transcriptome analysis technology has been widely used in breast cancer research, the biological mechanisms underlying the transition from DCIS to IDC remain poorly understood. RESULTS: We identified eight cell types through cell annotation, finding significant differences in T cell proportions between DCIS and IDC. Using this as a basis, we performed pseudotime analysis on T cell subpopulations, revealing that differentially expressed genes primarily regulate immune cell migration and modulation. By intersecting WGCNA results of T cells highly correlated with the subtypes and the differentially expressed genes, we identified six key genes: FGFBP2, GNLY, KLRD1, TYROBP, PRF1, and NKG7. Excluding PRF1, the other five genes were significantly associated with overall survival in breast cancer, highlighting their potential as prognostic biomarkers. CONCLUSIONS: We identified immune cells that may play a role in the progression from DCIS to IDC and uncovered five key genes that can serve as prognostic markers for breast cancer. These findings provide insights into the mechanisms underlying the transition from DCIS to IDC, offering valuable perspectives for future research. Additionally, our results contribute to a better understanding of the biological processes involved in breast cancer progression.

Single-cell RNA transcriptomics reveals Du-Zhong-Wan promotes osteoporotic fracture healing via YAP/ß-catenin/VEGF axis in BMSCs.

BACKGROUND: Our previous study demonstrated that Du-Zhong-Wan (DZW) promoted osteoporotic fracture (OPF) healing by enhancing osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) and angiogenesis of endothelial cells (ECs). However, the heterogeneity of BMSCs and ECs, as well as the specific molecular mechanism underlying these effects, still require further evaluation. PURPOSE: The primary objective of this study was to elucidate the heterogeneity of BMSCs and ECs, as well as the cellular-level mechanism of DZW against OPF through single-cell RNA sequencing. METHODS: In this study, we presented a single-cell atlas of mouse femoral callus, comparing samples with and without DZW treatment, utilizing single-cell RNA sequencing. Variable genes were identified using the FindVariableGenes (FVG) and principal component analysis (PCA) analysis. Additionally, uniform manifold approximation and projection (U-MAP) was employed to reduce and visualize the distinct subclusters. The CellPhoneDB2 method was employed to analyze intercellular communication and quantify the interaction between ligands and receptors within distinct cell clusters. The osteogenic differentiation capacity of BMSCs was assessed by micro-CT, alkaline phosphatase (ALP), and alizarin red S (ARS) assay. The scratch wound assay and tube formation assay were utilized to assess the angiogenic capabilities of ECs in vitro. Additionally, western blot and immunofluorescence experiments were utilized to elucidate the related protein expression. RESULTS: Consistent with our previous studies, DZW obviously promoted osteoporotic fracture healing. Moreover, this study discovered 14 cell clusters at the femoral fracture callus, where the BMSCs most actively interacted with ECs, through single-cell sequencing. Notably, DZW significantly elevated the proportion of Lepr+ BMSCs and Podxl+ ECs subgroup, which were respectively considered essential cells for osteoblastogenesis and angiogenesis of arteriolar vessels. The increased proportion of Podxl+ ECs was partially attributed to vascular endothelial growth factor (VEGF), secreted by BMSCs, which were able to be reversed by YAP pharmacological inhibitor verteporfin. Furthermore, the western blot assay revealed elevated expression levels of YAP/ß-catenin, VEGF, RUNX2, and OCN in BMSCs treated with DZW, which were counteracted by verteporfin. CONCLUSION: The data above indicates that DZW elevates the proportion of LEPR+ BMSCs and Podxl+ ECs, therefore contributing for the osteogenic ability of BMSCs and BMSCs-mediated angiogenesis via activation of the YAP/ß-catenin/VEGF axis, which provides novel potential targets and mechanism for DZW in treating OPF in sub-clusters and molecular level.

Skin organoid transplantation promotes tissue repair with scarless in frostbite.

Frostbite is the most common cold injury and is caused by both immediate cold-induced cell death and the gradual development of localized inflammation and tissue ischemia. Delayed healing of frostbite often leads to scar formation, which not only causes psychological distress but also tends to result in the development of secondary malignant tumors. Therefore, a rapid healing method for frostbite wounds is urgently needed. Herein, we used a mouse skin model of frostbite injury to evaluate the recovery process after frostbite. Moreover, single-cell transcriptomics was used to determine the patterns of changes in monocytes, macrophages, epidermal cells and fibroblasts during frostbite. Most importantly, human-induced pluripotent stem cell (hiPSC) -derived skin organoids combining with gelatin-hydrogel were constructed for the treatment of frostbite. The results showed that skin organoid treatment significantly accelerated wound healing by reducing early inflammation after frostbite and increasing the proportions of epidermal stem cells. Moreover, in the later stage of wound healing, skin organoids reduced the overall proportions of fibroblasts, significantly reduced fibroblast-to-myofibroblast transition by regulating the integrin α5ß1-FAK pathway, and remodeled the extracellular matrix (ECM) through degradation and reassembly mechanisms, facilitating the restoration of physiological ECM and reducing the abundance of ECM associated with abnormal scar formation. These results highlight the potential application of organoids for promoting the reversal of frostbite-related injury and the recovery of skin functions. This study provides a new therapeutic alternative for patients suffering from disfigurement and skin dysfunction caused by frostbite.

Tertiary lymphoid structure formation: A matter of tumor-immune co-evolution.

The immune make-up of human tumors is dynamic over the course of cancer progression. However, what factors drive spatiotemporal changes in the tumor-immune landscape is not well-known. In issue 3 of Cell Reports Medicine, Liu, You, Lan and Ren et al. demonstrate that the development of tertiary lymphoid structures (TLSs) is a stepwise process that co-occurs with tumor progression in patients with lung adenocarcinoma (LUAD).

Systematic analysis of human colorectal cancer scRNA-seq revealed limited pro-tumoral IL-17 production potential in gamma delta T cells.

Gamma delta T cells play a crucial role in anti-tumor immunity due to their cytotoxic properties. However, the role and extent of γδ T cells in production of pro-tumorigenic interleukin-17 (IL-17) within the tumor microenvironment of colorectal cancer (CRC) remains controversial. In this study, we re-analyzed nine published human CRC whole-tissue single-cell RNA sequencing datasets, identifying 18,483 γδ T cells out of 951,785 total cells, in the neoplastic or adjacent normal tissue of 165 human CRC patients. Our results confirm that tumor-infiltrating γδ T cells exhibit high cytotoxicity-related transcription in both tumor and adjacent normal tissues, but critically, none of the γδ T cell clusters showed IL-17 production potential. We also identified various γδ T cell subsets, including poised effector-like T cells, tissue-resident memory T cells, progenitor exhausted-like T cells, and exhausted T cells, and noted an increased expression of cytotoxic molecules in tumor-infiltrating γδ T cells compared to their normal area counterparts. We proposed anti-tumor γδ T effector cells may arise from tissue-resident progenitor cells based on the trajectory analysis. Our work demonstrates that γδ T cells in CRC primarily function as cytotoxic effector cells rather than IL-17 producers, mitigating the concerns about their potential pro-tumorigenic roles in CRC, highlighting the importance of accurately characterizing these cells for cancer immunotherapy research and the unneglectable cross-species discrepancy between the mouse and human immune system in the study of cancer immunology.

Method of moments framework for differential expression analysis of single-cell RNA sequencing data.

Differential expression analysis of single-cell RNA sequencing (scRNA-seq) data is central for characterizing how experimental factors affect the distribution of gene expression. However, distinguishing between biological and technical sources of cell-cell variability and assessing the statistical significance of quantitative comparisons between cell groups remain challenging. We introduce Memento, a tool for robust and efficient differential analysis of mean expression, variability, and gene correlation from scRNA-seq data, scalable to millions of cells and thousands of samples. We applied Memento to 70,000 tracheal epithelial cells to identify interferon-responsive genes, 160,000 CRISPR-Cas9 perturbed T cells to reconstruct gene-regulatory networks, 1.2 million peripheral blood mononuclear cells (PBMCs) to map cell-type-specific quantitative trait loci (QTLs), and the 50-million-cell CELLxGENE Discover corpus to compare arbitrary cell groups. In all cases, Memento identified more significant and reproducible differences in mean expression compared with existing methods. It also identified differences in variability and gene correlation that suggest distinct transcriptional regulation mechanisms imparted by perturbations.

The role of PAR2 in regulating MIF release in house dust mite-induced atopic dermatitis.

Atopic dermatitis (AD) is a chronic disease characterized by relapsed eczema and intractable itch, and is often triggered by house dust mites (HDM). PAR2 is a G-protein coupled receptor on keratinocytes and may be activated by HDM to affect AD processes. We first established a HDM-derived AD mouse model in wild-type (WT) and Par2-/- mice. Single cell RNA sequencing of the diseased skins found a stronger cellular communication between the ligand macrophage migration inhibitory factor (MIF) from keratinocytes and its receptors on antigen-presenting cells, suggesting the critical role of MIF in AD. HDM-WT mice showed severer skin lesions and pathological changes with stronger immunofluorescence MIF signals in skin sections than HDM-Par2-/- mice. Primary keratinocytes from WT mice stimulated with HDM or SLIGRL (PAR2 agonist) secreted more MIF in cultured medium and induced stronger immunofluorescence MIF signals than those from Par2-/- mice. The skin section of HDM-WT mice showed higher immunofluorescence signals of P115 (relating to MIF secretion) and KIF13B (possibly relating to intracellular trafficking of MIF) than that of HDM-Par2-/- mice. Acetylation of α-tubulin increased after stimulation by SLIGRL in WT keratinocytes but not in Par2-/- keratinocytes. HDM-WT mice treated with the MIF antagonist ISO-1 displayed improvement of AD-like presentations and lower expressions of IL-4, IL-13, TSLP and Arg1 (a biomarker of M2 macrophage) mRNAs. We conclude that MIF is an important cytokine and is significantly increased in the AD model. PAR2 affects AD changes by regulating the expression, intracellular trafficking, and secretion of MIF in epidermis.

Multimodal screen identifies noise-regulatory proteins.

Gene-expression noise can influence cell-fate choices across pathology and physiology. However, a crucial question persists: do regulatory proteins or pathways exist that control noise independently of mean expression levels? Our integrative approach, combining single-cell RNA sequencing with proteomics and regulator enrichment analysis, identifies 32 putative noise regulators. SON, a nuclear speckle-associated protein, alters transcriptional noise without changing mean expression levels. Furthermore, SON's noise control can propagate to the protein level. Long-read and total RNA sequencing shows that SON's noise control does not significantly change isoform usage or splicing efficiency. Moreover, SON depletion reduces state switching in pluripotent mouse embryonic stem cells and impacts their fate choice during differentiation. Collectively, we demonstrate a class of proteins that control noise orthogonally to mean expression levels. This work serves as a proof of concept that can identify other functional noise regulators throughout development and disease progression.

Unraveling aging from transcriptomics.

Research into aging constitutes a pivotal endeavor aimed at elucidating the underlying biological mechanisms governing aging and age-associated diseases, as well as promoting healthy longevity. Recent advances in transcriptomic technologies, such as bulk RNA sequencing (RNA-seq), single-cell transcriptomics, and spatial transcriptomics, have revolutionized our ability to study aging at unprecedented resolution and scale. These technologies present novel opportunities for the discovery of biomarkers, elucidation of molecular pathways, and development of targeted therapeutic strategies for age-related disorders. This review surveys recent breakthroughs in different types of transcripts on aging, such as mRNA, long noncoding (lnc)RNA, tRNA, and miRNA, highlighting key findings and discussing their potential implications for future studies in this field.

Overabundant endocannabinoids in neurons are detrimental to cognitive function.

2-Arachidonoylglycerol (2-AG) is the most prevalent endocannabinoid involved in maintaining brain homeostasis. Previous studies have demonstrated that inactivating monoacylglycerol lipase (MAGL), the primary enzyme responsible for degrading 2-AG in the brain, alleviates neuropathology and prevents synaptic and cognitive decline in animal models of neurodegenerative diseases. However, we show that selectively inhibiting 2-AG metabolism in neurons impairs cognitive function in mice. This cognitive impairment appears to result from decreased expression of synaptic proteins and synapse numbers, impaired long-term synaptic plasticity and cortical circuit functional connectivity, and diminished neurogenesis. Interestingly, the synaptic and cognitive deficits induced by neuronal MAGL inactivation can be counterbalanced by inhibiting astrocytic 2-AG metabolism. Transcriptomic analyses reveal that inhibiting neuronal 2-AG degradation leads to widespread changes in expression of genes associated with synaptic function. These findings suggest that crosstalk in 2-AG signaling between astrocytes and neurons is crucial for maintaining synaptic and cognitive functions and that excessive 2-AG in neurons alone is detrimental to cognitive function.

Hidden syndinian and perkinsid infections in dinoflagellate hosts revealed by single-cell transcriptomics.

Free-living core dinoflagellates are commonly infected by members of two parasitic clades that are themselves closely related to dinoflagellates, the marine alveolates and perkinsids. These parasites are abundant and ecologically important, but most species have been difficult to observe directly or cultivate, so our knowledge of them is usually restricted to environmental 18S rRNA gene sequences, as genome-scale molecular data are not available for most species. Here, we report the finding of several of these parasites infecting free-living dinoflagellates. Of the 14 infected host cells collected, only five were identified as containing parasites via light microscopy at the time of collection. Single-cell transcriptome sequencing yielded relatively high transcriptomic coverage for parasites as well as their hosts. Host and parasite homologs were distinguished phylogenetically, allowing us to infer a robust phylogenomic tree based on 192 genes. The tree showed one parasite belongs to an undescribed lineage that is sister to perkinsids, whereas the remainder are members of the syndinian clade within the marine alveolates. Close relatives of all these parasites have been observed in 18S rRNA gene surveys, but until now none had been linked to a specific host. These findings illustrate the efficacy of single-cell isolation and transcriptome sequencing as strategies for gaining deeper insights into the evolutionary history and host relationships of hidden single-celled parasites.

Functional gene signature offers a powerful tool for characterizing clinicopathological features and depicting tumor immune microenvironment of colorectal cancer.

BACKGROUND: Colorectal cancer, a prevalent malignancy worldwide, poses a significant challenge due to the lack of effective prognostic tools. In this study, we aimed to develop a functional gene signature to stratify colorectal cancer patients into different groups with distinct characteristics, which will greatly facilitate disease prediction. RESULTS: Patients were stratified into high- and low-risk groups using a prediction model built based on the functional gene signature. This innovative approach not only predicts clinicopathological features but also reveals tumor immune microenvironment types and responses to immunotherapy. The study reveals that patients in the high-risk group exhibit poorer pathological features, including invasion depth, lymph node metastasis, and distant metastasis, as well as unfavorable survival outcomes in terms of overall survival and disease-free survival. The underlying mechanisms for these observations are attributed to upregulated tumor-related signaling pathways, increased infiltration of pro-tumor immune cells, decreased infiltration of anti-tumor immune cells, and a lower tumor mutation burden. Consequently, patients in the high-risk group exhibit a diminished response to immunotherapy. Furthermore, the high-risk group demonstrates enrichment in extracellular matrix-related functions and significant infiltration of cancer-associated fibroblasts (CAFs). Single-cell transcriptional data analysis identifies CAFs as the primary cellular type expressing hub genes, namely ACTA2, TPM2, MYL9, and TAGLN. This finding is further validated through multiple approaches, including multiplex immunohistochemistry (mIHC), polymerase chain reaction (PCR), and western blot analysis. Notably, TPM2 emerges as a potential biomarker for identifying CAFs in colorectal cancer, distinguishing them from both colorectal cancer cell lines and normal colon epithelial cell lines. Co-culture of CAFs and colorectal cancer cells revealed that CAFs could enhance the tumorigenic biofunctions of cancer cells indirectly, which could be partially inhibited by knocking down CAF original TPM2 expression. CONCLUSIONS: This study introduces a functional gene signature that effectively and reliably predicts clinicopathological features and the tumor immune microenvironment in colorectal cancer. Moreover, the identification of TPM2 as a potential biomarker for CAFs holds promising implications for future research and clinical applications in the field of colorectal cancer.

Genome-Wide Identification of Cell Type-Specific Susceptibility Genes for SLE Through the Analysis of RNA Modification-Associated SNPs.

INTRODUCTION: This study aimed to elucidate the functional genes associated with systemic lupus erythematosus (SLE) in various cell types through the utilization of RNAm-SNPs. METHODS: Utilizing large-scale genetic data, we identified associations between RNAm-SNPs and SLE. The association between RNAm-SNPs and bulk and single-cell mRNA expression (eQTL) and protein levels (pQTL) were examined. Mendelian randomization and differential expression analyses were conducted to explore the links between gene expression, protein levels, and SLE. RESULTS: We identified 41 RNAm-SNPs that were significantly associated with SLE. The GWAS signals exhibited notable enrichment in m6A-SNPs and m7G-SNPs. These RNAm-SNPs showed both eQTL and pQTL effects. In our single-cell analysis, 16 RNAm-SNPs exhibited associations with gene expression levels across 13 distinct cell types, including HLA-A, HLA-B, HLA-C, HLA-DQA1, HLA-DQB1, HLA-DRB1 and IRF7. We identified 58 noteworthy associations between the expression levels of 20 genes and SLE across 12 distinct immune cell types. Notably, HLA-DQB1, HLA-DRB1 and IRF7 exhibited abnormalities in CD8+ T cells, IRF7 displayed abnormal expression in CD4+ T cells, while HLA-DRB1 and IRF7 were also distinctly perturbed in natural killer cells. DISCUSSION: This study advances our understanding of the genetic basis of SLE by highlighting the significance of RNAm-SNPs and immune cell gene expression in SLE.

A new exploration: characterization of the differentiation trajectory of prostate cancer cells.

Prostate cancer is one of the most common malignant tumors in men, and in-depth study of its gene expression patterns is crucial for understanding the formation and development of prostate cancer. Although single-cell transcriptomics has deeply explored the heterogeneous expression characteristics of prostate cancer, given that normal epithelial cells themselves have different states of differentiation, these normal differentiation characteristics may lead to confusion with heterogeneous tumor characteristics. In this study, we used single-cell data from the GEO database to analyze in detail the heterogeneity of prostate cancer tumor cells/tumor-associated epithelium cells (TAECs), with a particular focus on the differentiation state of epithelial cells in matching normal tissue. We found that after subtype pairing analysis of normal tissue and tumor tissue epithelium based on differentiation status, the characteristics identified later were not consistent with the general characteristics originally exhibited by different TAECs subpopulations. Among them, all TAECs subpopulations showed P53 enrichment and downregulation of the apoptotic pathway, and expressed higher levels of EGFR, ERBB2, interferon receptors, MIF, and cell adhesion-related signals; through transcription factor regulatory network analysis, we observed that YY1, NKX3-1, and EHF had higher transcriptional activity in TAECs subpopulations than normal epithelial cells at the same differentiation stage, while ATF3 was the opposite. Among them, YY1 may act as an upstream regulator of the MIF signaling pathway, and ATF3 is a key upstream transcriptional regulator of differentially expressed genes in the P53 and apoptotic pathways. Immune infiltration analysis showed that the above four transcription factors were significantly correlated with the infiltration of immune cells in prostate cancer, and pan-cancer analysis showed that their expression-related survival risks were widely present in different cancers. It is worth noting that this is merely a preliminary, exploratory study, which inevitably has some deficiencies and limitations. Despite this, this study is committed to bringing a novel and unique perspective to the field through this work, with the hope of opening up new levels of understanding and stimulating more in-depth research and discussion.

Single-cell transcriptomics reveals neural stem cell trans-differentiation and cell subpopulations in whole heart decellularized extracellular matrix.

The whole heart decellularized extracellular matrix (ECM) has become a promising scaffold material for cardiac tissue engineering. Our previous research has shown that the whole heart acellular matrix possesses the memory function regulating neural stem cells (NSCs) trans-differentiating to cardiac lineage cells. However, the cell subpopulations and phenotypes in the trans-differentiation of NSCs have not been clearly identified. Here, we performed single-cell RNA sequencing and identified 2,765 cells in the recellularized heart with NSCs revealing the cellular diversity of cardiac and neural lineage, confirming NSCs were capable of trans-differentiating into the cardiac lineage while maintaining the original ability to differentiate into the neural lineage. Notably, the trans-differentiated heart-like cells have dual signatures of neuroectoderm and cardiac mesoderm. This study unveils an in-depth mechanism underlying the trans-differentiation of NSCs and provides a new opportunity and theoretical basis for cardiac regeneration.