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Analysis of intracellular communication reveals consistent gene changes associated with early-stage acne skin.
A comprehensive understanding of the intricate cellular and molecular changes governing the complex interactions between cells within acne lesions is currently lacking. Herein, we analyzed early papules from six subjects with active acne vulgaris, utilizing single-cell and high-resolution spatial RNA sequencing. We observed significant changes in signaling pathways across seven different cell types when comparing lesional skin samples (LSS) to healthy skin samples (HSS). Using CellChat, we constructed an atlas of signaling pathways for the HSS, identifying key signal distributions and cell-specific genes within individual clusters. Further, our comparative analysis revealed changes in 49 signaling pathways across all cell clusters in the LSS- 4 exhibited decreased activity, whereas 45 were upregulated, suggesting that acne significantly alters cellular dynamics. We identified ten molecules, including GRN, IL-13RA1 and SDC1 that were consistently altered in all donors. Subsequently, we focused on the function of GRN and IL-13RA1 in TREM2 macrophages and keratinocytes as these cells participate in inflammation and hyperkeratinization in the early stages of acne development. We evaluated their function in TREM2 macrophages and the HaCaT cell line. We found that GRN increased the expression of proinflammatory cytokines and chemokines, including IL-18, CCL5, and CXCL2 in TREM2 macrophages. Additionally, the activation of IL-13RA1 by IL-13 in HaCaT cells promoted the dysregulation of genes associated with hyperkeratinization, including KRT17, KRT16, and FLG. These findings suggest that modulating the GRN-SORT1 and IL-13-IL-13RA1 signaling pathways could be a promising approach for developing new acne treatments.
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A molecular map of murine lymph node blood vascular endothelium at single cell resolution.
Blood vascular endothelial cells (BECs) control the immune response by regulating blood flow and immune cell recruitment in lymphoid tissues. However, the diversity of BEC and their origins during immune angiogenesis remain unclear. Here we profile transcriptomes of BEC from peripheral lymph nodes and map phenotypes to the vasculature. We identify multiple subsets, including a medullary venous population whose gene signature predicts a selective role in myeloid cell (vs lymphocyte) recruitment to the medulla, confirmed by videomicroscopy. We define five capillary subsets, including a capillary resident precursor (CRP) that displays stem cell and migratory gene signatures, and contributes to homeostatic BEC turnover and to neogenesis of high endothelium after immunization. Cell alignments show retention of developmental programs along trajectories from CRP to mature venous and arterial populations. Our single cell atlas provides a molecular roadmap of the lymph node blood vasculature and defines subset specialization for leukocyte recruitment and vascular homeostasis.
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Pan-cancer analysis reveals that TK1 promotes tumor progression by mediating cell proliferation and Th2 cell polarization.
BACKGROUND: TK1 (Thymidine kinase 1) is a member of the thymidine kinase family and has been observed to be significantly upregulated in a variety of cancer types. However, the exact roles of TK1 in tumor progression and the tumor immune microenvironment are not fully understood. This study aims to investigate the comprehensive involvement of TK1 in pan-cancer through the utilization of bioinformatics analysis, validation of pathological tissue samples, and in vitro experimental investigations. METHODS: The expression profiles together with diagnostic and prognostic role of TK1 in pan-cancer were investigated though TCGA, TARGET, GTEx, and CPTAC databases. The single-sample gene set enrichment analysis (ssGSEA) and single-cell sequencing datasets were used to examine the relationship between TK1 and immune infiltration. The expression of TK1 were verified in hepatocellular carcinoma (HCC) through qPCR, western blotting and immunohistochemical assays. The proliferative capacity of HCC cell lines was assessed through CCK-8 and colony formation assays, while cytokine levels were measured via ELISA. Furthermore, flow cytometry was utilized to analyze cell cycle distribution and the proportions of Th2 cells. RESULTS: TK1 was overexpressed in most cancers and demonstrated significant diagnostic and prognostic value. Among the various immune cells in pan-cancer, Th2 cells exhibited the closest association with TK1. Furthermore, the single-cell atlas provided insights into the distribution and proportion of TK1 in immune cells of HCC. In vitro experiments revealed an elevated expression of TK1 in HCC tissue and cell lines, and its role in influencing HCC cell proliferation by regulating G0/G1 phase arrest. Additionally, TK1 in cancer cells was found to potentially modulate Th2 cell polarization through the chemokine CCL5. CONCLUSION: TK1 holds immense potential as a biomarker for pan-cancer diagnosis and prognosis. Additionally, targeting the expression of TK1 represents a promising therapeutic approach that can enhance the efficacy of current anti-tumor immunotherapy by modulating Th2 cell polarization and multiple mechanisms.
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Multi-Omics Characterization of a Glycerolipid Metabolism-Related Gene Enrichment Score in Colon Cancer.
BACKGROUND: Glycerolipid metabolism is involved in the genesis and progression of colon cancer. The current study aims at exploring the prognostic value and potential molecular mechanism of glycerolipid metabolism-related genes in colon cancer from the perspective of multi-omics. METHODS: Clinical information and mRNA expression data of patients with colon cancer were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Single-sample gene set enrichment analysis (ssGSEA) was applied to calculate the glycerolipid metabolism-related gene enrichment score (GLMS). Univariable and multivariable Cox regression analyses were used to study the prognostic value of GLMS in TCGA-COAD and GSE39582 cohorts. The molecular mechanism of the prognostic factor was investigated via immune cell infiltration estimation and correlation analysis of cancer hallmark pathways. Single-cell transcriptomic dataset GSE146771 was used to identify the cell populations which glycerolipid metabolism targeted on. RESULTS: The GLMS was found to be associated with tumor location and consensus molecular types (CMSs) of colon cancer in TCGA-COAD cohort (P < 0.05). Patients in the low-GLMS group exhibited poorer overall survival (OS) in TCGA cohort (P = 0.03; HR, 0.63; 95% CI, 0.42-0.94), which was further validated in the GSE39582 dataset (P < 0.001; HR, 0.57; 95% CI, 0.43-0.76). The association between the GLMS and OS remained significant in the multivariable analysis (TCGA cohort: P = 0.04; HR, 0.64; 95% CI, 0.42-0.98; GSE39582 cohort: P < 0.001; HR, 0.60; 95% CI, 0.45-0.80). The GLMS was positively correlated with cancer hallmark pathways including bile acid metabolism, xenobiotic metabolism, and peroxisome and negatively correlated with pathways such as interferon gamma response, allograft rejection, apoptosis, and inflammatory response (P < 0.05). Increased immune infiltration and upregulated expression of immune checkpoints were observed in patients with lower GLMS (P < 0.05). Single-cell datasets verified the different distribution of GLMS in cell subsets, with significant enrichment of GLMS in malignant cells and Tprolif cells. CONCLUSION: We demonstrated that GLMS was a potential independent prognostic factor for colon cancer. The GLMS was also correlated with several cancer hallmark pathways, as well as immune microenvironment.
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Dynamic molecular atlas of cardiac fibrosis at single-cell resolution shows CD248 in cardiac fibroblasts orchestrates interactions with immune cells.
Post-injury remodeling is a complex process involving temporal specific cellular interactions in the injured tissue where the resident fibroblasts play multiple roles. Here, we performed single-cell and spatial transcriptome analysis in human and mouse infarcted hearts to dissect the molecular basis of these interactions. We identified a unique fibroblast subset with high CD248 expression, strongly associated with extracellular matrix remodeling. Genetic Cd248 deletion in fibroblasts mitigated cardiac fibrosis and dysfunction following ischemia/reperfusion. Mechanistically, CD248 stabilizes type I transforming growth factor beta receptor and thus upregulates fibroblast ACKR3 expression, leading to enhanced T cell retention. This CD248-mediated fibroblast-T cell interaction is required to sustain fibroblast activation and scar expansion. Disrupting this interaction using monoclonal antibody or chimeric antigen receptor T cell reduces T cell infiltration and consequently ameliorates cardiac fibrosis and dysfunction. Our findings reveal a CD248+ fibroblast subpopulation as a key regulator of immune-fibroblast cross-talk and a potential therapy to treat tissue fibrosis.
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Comprehensive pan-cancer analysis of HSPG2 as a marker for prognosis.
BACKGROUND: In recent years, several studies have shown that HSPG2 is associated with the prognosis of specific cancers. The aim of this study was to investigate the prognostic value of HSPG2 in pan-cancer and to analyze its possible mechanisms. METHODS: We used The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) to explore the expression of HSPG2 in 33 tumors and corresponding controls. Univariate Cox regression and Kaplan-Meier survival analysis were applied to detect the effects of HSPG2 on overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in patients with these tumors, and to analyze the relationship between HSPG2 and clinical characteristics. And we further analyzed the relationship between HSPG2 and immune infiltration, DNA methylation and single cell function. And GO and KEGG enrichment analyses were performed using HSPG2 co-expressed genes. Finally, we explored the diagnostic efficacy of HSPG2 for diseases of interest and validated it using qPCR experiment. RESULTS: HSPG2 was lowly expressed in 17 cancers and highly expressed in 11 cancers, and was correlated with patient's clinical characteristics in many cancers. Multivariate regression analysis showed that HSPG2 was an independent prognostic factor for DSS, OS, and PFI in bladder urothelial carcinoma (BLCA) and Mesothelioma (MESO). HSPG2 was correlated with DNA methylation, single-cell function, and immune infiltration in a variety of cancers. HSPG2 exhibited a good diagnostic efficacy for BLCA and MESO. qPCR and western blot results showed that HSPG2 expression was increased in mesothelioma compared to normal controls. CONCLUSION: These findings suggest that HSPG2 could be considered as a potential diagnostic and prognostic marker for BLCA and MESO.
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Identification and validation of Cystatin A as a novel promising therapeutic target for gastric cancer.
BACKGROUND: The effect of pharmacological treatment of gastric cancer (GC) is limited, thus, it holds significant scientific importance to thoroughly investigate the molecular mechanisms underlying GC development and identify novel molecules capable of substantially extending patients' survival. This study utilized bioinformatics techniques to identify 11 genes associated with recurrence-free survival (RFS) in GC patients and investigated the potential biological functions of these genes through single-cell transcriptomic analysis. Subsequently, a single gene Cystatin A (CSTA) was selected for further analysis to explore its impact on signaling pathways and treatment. METHODS: Differentially expressed genes (DEGs) were identified and overlapped in the analysis of RFS to identify potential prognostic genes for GC patients, based on data from the Cancer Genome Atlas-stomach adenocarcinoma (TCGA-STAD) and GSE54129. Subsequently, a prognostic model based on RFS in GC patients was established. Single-cell sequencing data were employed to explore the potential functions of these model genes. CSTA, one of the RFS-related genes, was further investigated using immunohistochemistry (IHC), Cell Counting Kit 8 (CCK-8), transwell, scratch, colony formation assays, flow cytometry, and Western blotting methods. RESULTS: Through bioinformatics analysis, we identified 23 RFS-related genes in GC. Using the least absolute shrinkage and selection operator (LASSO)-Cox method, an RFS prognostic model was developed which pinpointed 11 GC prognosis-related (GPR) genes as significant factors influencing RFS in GC patients. The single-cell analysis revealed their potential role in affecting differentiation and maturation of pre-fibroblasts thereby impacting RFS in GC patients. CSTA exhibited low expression levels in GC tissues. Overexpression of CSTA promoted apoptosis in GC cells through the caspase-dependent apoptotic pathway and enhanced their response to cisplatin via this same pathway. CONCLUSIONS: The 11 GPR genes are primarily enriched within a specific type of stromal cell exhibiting heightened communication, metabolism, and differentiation levels. The gene signature of these stromal cells has implications for patient prognosis. Additionally, CSTA, a gene related to prognosis, has been shown to influence apoptosis levels in GC cells.
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Spatial Proteomics and Epigenomics Reveal Cell Morphology and Epigenetic Gene Regulation in Human Hippocampus.
We present the first spatial tri-omic (proteomic, transcriptomic, and epigenomic) taxonomy of human hippocampus, addressing two key challenges in single-cell and spatial transcriptomics: visualizing cell morphology and epigenetic gene regulation in situ. By designing and multiplex imaging a novel panel of 25 protein targets, we generated the first large scale spatial proteomics map of the hippocampus at single cell resolution (330 nanometers). Through integrated spatial proteomic and transcriptomic analyses, we identified canonical hippocampal subfields and distinct cell types within the dentate gyrus and cornu Ammonis (CA). RNA synthesis rates were the highest in the CA pyramidal neurons than any other hippocampal subfields. To map gene regulation, we applied state-of-art spatial ATAC-seq to identify open chromatin regions and cis-regulatory elements, revealing how chromatin landscapes differ across hippocampal subfields. These regional differences help explain why certain neurons are more excitable and recruited for circuit formation, as their chromatin is open and responsive to transcription factors. Together, these approaches created the most comprehensive spatial atlas of the human hippocampus to date, consisting of over 1.6 million single cells from 16 individuals. This study demonstrates the use of spatial proteomics and epigenomics to investigate the molecular neuropathology of human brain in both healthy and diseased states.
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A new CCCH-type zinc finger-related lncRNA signature predicts the prognosis of clear cell renal cell carcinoma patients.
Background: Clear cell renal cell carcinoma (ccRCC) is the main component of renal cell carcinoma (RCC), and advanced ccRCC frequently indicates a poor prognosis. The significance of the CCCH-type zinc finger (CTZF) gene in cancer has been increasingly demonstrated during the past few years. According to studies, targeted radical therapy for cancer treatment may be a revolutionary therapeutic approach. Both lncRNAs and CCCH-type zinc finger genes are essential in ccRCC. However, the predictive role of long non-coding RNA (lncRNA) associated with the CCCH-type zinc finger gene in ccRCC needs further elucidation. This study aims to predict patient prognosis and investigate the immunological profile of ccRCC patients using CCCH-type zinc finger-associated lncRNAs (CTZFLs). Methods: From the Cancer Genome Atlas database, RNA-seq and corresponding clinical and prognostic data of ccRCC patients were downloaded. Univariate and multivariate Cox regression analyses were conducted to acquire CTZFLs for constructing prediction models. The risk model was verified using receiver operating characteristic curve analysis. The Kaplan-Meier method was used to analyze the overall survival (OS) of high-risk and low-risk groups. Multivariate Cox and stratified analyses were used to assess the prognostic value of the predictive feature in the entire cohort and different subgroups. In addition, the relationship between risk scores, immunological status, and treatment response was studied. Results: We constructed a signature consisting of eight CTZFLs (LINC02100, AC002451.1, DBH-AS1, AC105105.3, AL357140.2, LINC00460, DLGAP1-AS2, AL162377.1). The results demonstrated that the prognosis of ccRCC patients was independently predicted by CTZFLs signature and that the prognosis of high-risk groups was poorer than that of the lower group. CTZFLs markers had the highest diagnostic adequacy compared to single clinicopathologic factors, and their AUC (area under the receiver operating characteristic curve) was 0.806. The overall survival of high-risk groups was shorter than that of low-risk groups when patients were divided into groups based on several clinicopathologic factors. There were substantial differences in immunological function, immune cell score, and immune checkpoint expression between high- and low-risk groups. Additionally, Four agents, including ABT737, WIKI4, afuresertib, and GNE 317, were more sensitive in the high-risk group. Conclusion: The Eight-CTZFLs prognostic signature may be a helpful prognostic indicator and may help with medication selection for clear cell renal cell carcinoma.
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Key genes and associated mechanisms of PCOS and EC comorbidity: A bioinformatics analysis.
Endometrial cancer (EC) is a major reproductive system tumor and a common cancer in women. Polycystic ovary syndrome (PCOS) is one of the most prevalent female reproductive endocrine disorders. The incidence of EC is significantly higher in individuals with PCOS. This study seeks to elucidate the organic correlations and interaction mechanisms between the 2 diseases through series of exploration of key genes with a bioinformatics analysis. The PCOS sample data and the EC single-cell dataset were downloaded from the gene expression omnibus database. The EC sample data were retrieved from the cancer genome atlas public database. The random survival forest method was employed to identify key genes associated with the prognosis of PCOS and EC comorbidity. Corresponding analyses on functional pathway enrichment, regulatory networks, and immune micro-environment are conducted. From a bioinformatics perspective, the association and interaction mechanisms between PCOS and EC comorbidity were explored to provide research and development references for the prevention and control of PCOS and EC comorbidity. Five key genes associated with the prognosis of PCOS and EC comorbidity were identified using the random survival forest method. The identified genes are SYTL1, PARVG, ID4, IL1RN, and S100A9. The abnormal expression of these key genes has impacted various enrichment pathways, including the TGF-β signaling-pathway, motif regulatory networks (such as motif cisbp__M4556), and miRNA regulatory networks, which encompass genes such as ATM, BARD1 and BRCA1. Furthermore, these also influence the immune cell microenvironment, such as T cells regulatory. Collectively, these key genes play a significant role in the occurrence and progression of comorbidities through the pathways mentioned above. The dysregulation of key genes (SYTL1, PARVG, ID4, IL1RN, S100A9) in the context of PCOS-EC comorbidities, along with their associated enrichment pathways, including the TGF-β signaling-pathway and immune microenvironment, plays a significant role in the occurrence and progression of EC.