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FTSJ1-mediated IL1RN mRNA instability promotes inflammation-driven hepatocellular carcinoma.
BACKGROUND: The role of 2'-O-methyltransferases in hepatocellular carcinoma (HCC) progression, particularly concerning inflammation, remains unclear. This study investigated their prognostic significance, identified key prognostic target FTSJ1, and elucidated its inflammatory-related biological functions and molecular mechanisms. METHODS: Transcriptomic data from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) were integrated to data of subtype HCC patients via consensus clustering based on 2'-O-methyltransferase expression. Single-gene survival analysis linked FTSJ1, FTSJ2, FTSJ3, and FBL to prognosis. A four-gene risk model was built. Multivariate COX regression identified independent risk factors. FTSJ1 expression and prognostic value were validated clinically using quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC). Functional roles were assessed in vitro [Cell Counting Kit-8 (CCK-8), Transwell, apoptosis/cell cycle assays] and in vivo (xenograft models). Mechanisms were explored via RNA sequencing (RNA-seq), gene set enrichment analysis (GSEA), and inflammatory cytokine detection. RESULTS: Consensus clustering defined three subtypes. Subtype 1 (high 2'-O-methyltransferase expression) showed the worst prognosis. FTSJ1/2/3 and FBL correlated significantly with survival. The four-gene risk model predicted survival across cohorts [The Cancer Genome Atlas (TCGA)/Gene Expression Omnibus (GEO) datasets (GSE54236/GSE144269)]. FTSJ1 was an independent risk factor [multivariate Cox, hazard ratio (HR) =2.268, P=0.01] and significantly elevated in HCC tissues. Functionally, FTSJ1 knockdown inhibited proliferation and migration; induced G0/G1 arrest; promoted apoptosis in vitro; and suppressed tumor growth in vivo. Mechanistically, FTSJ1 drove HCC progression by reducing RNA stability of the key anti-inflammatory gene interleukin 1 receptor antagonist (IL1RN), leading to downregulated tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) and enhanced pro-inflammatory signaling. CONCLUSIONS: High 2'-O-methyltransferase abundance predicts poor HCC prognosis. FTSJ1 is a novel independent prognostic biomarker and oncogenic factor that promotes HCC progression by dysregulating the inflammatory response pathway, highlighting its translational potential in inflammation-driven HCC.
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Revelation of prognosis and tumor microenvironment of colorectal cancer based on genes related to antibody-dependent cellular phagocytosis and single-cell landscape.
BACKGROUND: Increasing evidence highlights the crucial role of antibody-dependent cellular phagocytosis (ADCP) in colorectal cancer (CRC). However, how to use ADCP-related genes to predict prognosis in CRC and guide treatment remains unelucidated. METHODS: Gene expression profiles and clinical data information on CRC were sourced from the Cancer Genome Atlas (TCGA) database. We obtained the validation set GSE29621 and CRC single-cell dataset GSE178341 from the Gene Expression Omnibus (GEO) database and the ADCP-related gene set from the literature. Based on the TCGA-CRC cohort, univariate Cox and LASSO Cox regression analyses were employed to screen for ADCP-related genes linked with prognosis. Then a prognostic model was set up through multivariate Cox regression analysis. We further graphed a nomogram based on clinical information and risk scoring and evaluated its prognostic value using Kaplan-Meier (K-M) survival curves and receiver operation characteristic (ROC) curves. Based on the single-cell data analysis model, the expression levels of genes in different cell clusters were evaluated by scoring individual cells using the AUCell R package. Finally, functional enrichment, immune infiltration, and somatic mutation analyses were performed on the high- and low-ADCP-related risk score (ADCPRS) groups clustered by the median value of the ADCPRS. In addition, small molecular drugs for the treatment of CRC patients were analyzed using drug sensitivity analysis of IC50 and molecular docking. RESULTS: This project created a prognostic model based on 7 feature genes using the TCGA training set. The K-M survival curves and ROC curves indicated that the model, as well as the nomogram, was capable of accurately predicting prognosis for CRC patients. Based on scRNA-seq data analysis, the 7 feature genes were examined to be expressed across 8 cell clusters (Monocytes, CD8 + T cells, Epithelial cells, B cells, Macrophages, HSC, Endothelial cells, and Fibroblasts). We scored individual cells and revealed that cells with higher scores were mainly concentrated in B cells and macrophages. Functional enrichment analysis manifested that the upregulated differentially expressed genes (DEGs) in the high-ADCPRS group were mainly enriched in signaling pathways such as the Drug metabolism cytochrome P450, Neuroactive ligand-receptor interaction, and Calcium signaling pathway. Immune infiltration analysis manifested that Th1 cells, iDCs, and Th2 cells had higher abundance in the low-ADCPRS group. Gene mutation analysis uncovered that both high- and low-ADCPRS groups had high mutation rates, with APC and TP53 being the top two genes with the highest mutation rates. Moreover, the drug sensitivity analysis and molecular docking uncovered that Dasatinib, Benzaldehyde, and Tegafur may aid in treating CRC patients. CONCLUSION: The prognostic model developed in this project functioned as a potential tool for risk assessment. The 7 model genes may serve as prognostic biomarkers for CRC, which can guide treatment decisions for CRC patients.
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A new perspective on endometriosis: Integrating eQTL mendelian randomization with transcriptomics and single-cell data analyses.
Endometriosis is caused by the migration of endometrial cells to locations outside the uterine lining. Despite the increasing prevalence of endometriosis, there has been limited research on genetic effects, and its molecular mechanisms remain unclear. This study aimed to investigate the mechanisms underlying the development of endometriosis and to identify new genetic targets for endometriosis by integrating data from gene chips, single-cell mapping, and genome-wide association study databases. Using the Gene Expression Omnibus database, we downloaded data on normal endometrium, eutopic endometrium, and ectopic lesion tissues to explore the differentially expressed genes (DEGs) between normal and eutopic endometrium, and between eutopic and ectopic endometrium. Assessment of the relationships between DEGs and endometriosis involved differential expression, expression quantitative trait loci (eQTL), and Mendelian randomization (MR) analyses. Two single-cell atlas datasets were then analyzed to explore the mechanisms underlying disease development and progression. Intersection of MR results with DEGs between normal and eutopic endometrium highlighted 28 candidate biomarker genes (17 upregulated and 11 downregulated). Similarly, we identified two additional candidate biomarker genes by intersecting the DEGs between eutopic and ectopic endometrium with MR results. Among these 30 candidates, further filtering using single-cell datasets revealed that the histamine N-methyltransferase (HNMT), coiled-coil domain containing 28 A (CCDC28A), fatty acid desaturase 1 (FADS1) and mahogunin ring finger 1 (MGRN1) genes were differentially expressed between the normal and eutopic groups, consistent with transcriptomic and MR results. Our findings suggested that eutopic endometrium exhibits epithelial-mesenchymal transition (EMT). Cell communication analysis focused on ciliated epithelial cells expressing CDH1 and KRT23 revealed that, in the eutopic endometrium, ciliated epithelial cells are strongly correlated and interact with natural killer cells, T cells, and B cells. We identified four novel biomarker genes and found evidence for EMT in the eutopic endometrium. The mechanism of endometriosis progression may be closely related to EMT and changes in the immune microenvironment triggered by damage to ciliated epithelial cells.
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Single-nucleus transcriptomics reveals the cellular immune responses to Candidatus Liberibacter asiaticus in rough lemon.
Citrus Huanglongbing (HLB) is the most destructive disease in citriculture, mainly caused by Candidatus Liberibacter asiaticus (CLas). However, the immune response of citrus to CLas at the cellular level remains to be elucidated. In this study, the first single-cell atlas of rough lemon (Citrus jambhiri Lush.) root apexes were generated using single-nucleus RNA sequencing at 20 weeks postinoculation with CLas. According to gene expression patterns, the single-cell atlas was partitioned into 20 transcriptionally distinct clusters, and five cell types were identified within these clusters. A significant number of defense-related genes were co-upregulated across the five cell types following CLas infection, whereas genes involved in signal transduction pathways, such as tubulin beta-6 chain (TUBB1) and the phospholipase D alpha 1 (PLD1), were concurrently downregulated. Based on pseudotime trajectory analysis, the key pathways and genes involved in the coordination of cell differentiation and resistance in citrus under CLas infection were characterized. Following CLas infection, the development of phloem cells was significantly delayed, and the differentiation of cambium cells into xylem cells was evident. The expression of genes associated with lignin synthesis was significantly upregulated in these cells. The reduction in phloem cell differentiation and the enhanced differentiation of cambium cells into defense-related xylem cells may represent the primary vascular immune mechanisms exhibited by citrus plants in response to CLas infection. Additionally, DNA-binding one zinc finger transcription factor DOF2.4 was found to potentially serve dual roles in regulating vascular cell development and inducing plant resistance against CLas. In conclusion, this study collectively provides insights into the cellular innate immunity responses of citrus to CLas infection. These findings hold significant implications for the sustainable development of citriculture amidst the ongoing global HLB epidemic, and offer novel insights into vascular immunity and plant defense responses.
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Comprehensive analysis of NT5DC family prognostic and immune significance in breast cancer.
Among the most common malignancies, breast cancer has a high incidence and mortality rate. NT5DC family is a highly well-conserved 5'-nucleotidase. Previous studies showed that the progression of tumors was associated with some NT5DC family members. However, there are no studies about the comprehensive analysis such as expression, prognosis, and immune properties of NT5DC family in breast cancer. Based on the data from The Cancer Genome Atlas database, we used UALCAN, Tumor Immune Estimation Resource, Breast cancer gene-expression miner (Bc-GenExMiner), Kaplan-Meier Plotter, TISIDB, cBioPortal, GeneMANIA, Search Tool for the Retrieval of Interacting Genes, Metascape, Tumor Immune Single-cell Hub, The Database for Annotation, Visualization and Integrated Discovery, and Gene Set Cancer Analysis databases to explore expression, prognostic and diagnostic value, genetic alterations, biological function, immune value and drug sensitivity of NT5DC family in breast cancer patients. There was a downregulation of NT5C2, NT5DC1, and NT5DC3 in breast cancer compared to normal tissues, and NT5DC2 instead. All NT5DC family members were associated with the clinicopathological parameters of breast cancer patients. Survival and ROC analysis revealed that NT5DC family genes were related to the prognosis and diagnosis of breast cancer. NT5DC family were mainly involved in nucleotide metabolism. Moreover, NT5DC family were significantly associated with tumor immune microenvironment, diverse immune cells, and immune checkpoints in breast cancer. This research showed that NT5DC family might be novel prognostic biomarkers and immunotherapeutic targets of breast cancer.
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Long non-coding RNA NEAT1 promotes colorectal cancer progression via interacting with SIRT1.
Nuclear-enriched abundant transcript 1 (NEAT1), a long noncoding RNA, is found to be significantly dysregulated in different types of cancer, including colorectal cancer (CRC). Nevertheless, there is still much to learn about the precise functions and processes of NEAT1 in the progression of CRC. Using The Cancer Genome Atlas (TCGA) database and 50 CRC specimens from the First Affiliated Hospital of Dali University, we assessed the expression of NEAT1 to determine its clinical impact. Through gene set enrichment analysis (GSEA), Cancer Single-cell State Atlas (CancerSEA), and immune infiltration studies, we elucidated key functions of NEAT1. We utilized Cell Counting Kit-8 (CCK8), wound healing, and Transwell assays to investigate the role of NEAT1 in the progression of CRC. Through the use of GSEA and immunohistochemistry, additional investigations were conducted to unveil the downstream targets of NEAT1 and gain insights into their regulatory dynamics. Our in vitro studies confirmed the regulatory role of NEAT1 in CRC. Findings indicate that increased NEAT1 expression correlates with adverse outcomes in colorectal tissues. In the CRC model, reduced levels of NEAT1 lead to reduced cell proliferation, invasion, and migration. Additionally, NEAT1 influenced immune cell infiltration in CRC and functioned as an oncogene by upregulating Sirtuin 1 (SIRT1) expression. This study demonstrates that NEAT1 promotes CRC progression and metastasis through a SIRT1-mediated mechanism, suggesting its potential as a prognostic biomarker and therapeutic target for CRC.
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Characterization of ccl20a.3 and ccl20l as gene markers for Th17 cell in turbot.
T-helper 17 lymphocytes (Th17) are the most common inflammatory cells identified in mammals. However, the identification of Th17 cells and the clarification of their function in teleost fish remain largely unknown. In this study, we took advantage of the single-cell RNA sequencing-based immune cell atlas that was identified in turbot (Scophthalmus maximus), and revealed two chemokine-related genes, ccl20a.3 and ccl20l, that were specifically expressed in Th17 cells. Moreover, through immuno-fluorescence analysis, we found that CCL20a.3 or CCL20l was co-expressed with the classical makers in Th17 cells, including IL17a/f1 and IL22. Furthermore, through a Th17 lineage-specific transcription factor RORc inhibitor GSK805 treatment, we found that the expression of ccl20a.3 and ccl20l was significantly impaired, compared with other T cell markers. Besides, we also found that ccl20a.3 and ccl20l exhibited the same dynamic response with the classical markers that were identified in Th17 cells during bacterial infection. Taken together, these results provide potential gene markers for better understanding of the dynamic immune responses of Th17 cells in teleost fish.
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Spatial Transcriptomic Analysis of Focal and Normal Areas of Myocyte Disarray in Human Hypertrophic Cardiomyopathy.
Hypertrophic Cardiomyopathy (HCM) is a common inherited disorder that can lead to heart failure and sudden cardiac death, characterized at the histological level by focal areas of myocyte disarray, hypertrophy and fibrosis, and only a few disease-targeted therapies exist. To identify the focal and spatially restricted alterations in the transcriptional pathways and reveal novel therapeutic targets, we performed a spatial transcriptomic analysis of the areas of focal myocyte disarray compared to areas of normal tissue using a commercially available platform (GeoMx, nanoString). We analyzed surgical myectomy tissue from four patients with HCM and the control interventricular septum tissue from two unused organ donor hearts that were free of cardiovascular disease. Histological sections were reviewed by an expert pathologist, and 72 focal areas with varying degrees of myocyte disarray (normal, mild, moderate, severe) were chosen for analysis. Areas of interest were interrogated with the Human Cancer Transcriptome Atlas designed to profile 1800 transcripts. Differential expression analysis revealed significant changes in gene expression between HCM and the control tissue, and functional enrichment analysis indicated that these genes were primarily involved in interferon production and mitochondrial energetics. Within the HCM tissue, differentially expressed genes between areas of normal and severe disarray were enriched for genes related to mitochondrial energetics and the extracellular matrix in severe disarray. An analysis of the gene expression of the ligand-receptor pair revealed that the HCM tissue exhibited downregulation of platelet-derived growth factor (PDGF), NOTCH, junctional adhesion molecule, and CD46 signaling while showing upregulation of fibronectin, CD99, cadherin, and amyloid precursor protein signaling. A deconvolution analysis utilizing the matched single nuclei RNA-sequencing (snRNA-seq) data to determine cell type composition in areas of interest revealed significant differences in fibroblast and vascular cell composition in areas of severe disarray when compared to normal areas in HCM samples. Cell composition in the normal areas of the control tissue was also divergent from the normal areas in HCM samples, which was consistent with the differential expression results. Overall, our data identify novel and potential disease-modifying targets for therapy in HCM.
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Integrated post-GWAS, single-cell, and functional analyses prioritize TCTN2 at an osteoarthritis locus associated with innate immunity-related cartilage remodeling.
BACKGROUND: Post-genome-wide association study (GWAS) interpretation of osteoarthritis (OA) increasingly requires integration with single-cell biology because many risk loci likely act through sterile inflammatory remodeling, regulatory and inflammatory chondrocyte states, and tissue-stress biology rather than through large disease-stage expression shifts. We therefore asked whether a published Transformer-based post-GWAS prioritization strategy could refine a multi-gene chr12 susceptibility locus into a tractable TCTN2-centered effector-gene hypothesis. METHODS: Using combined hip and knee osteoarthritis summary statistics (213,839 cases and 1,080,481 controls), we built a transfer-learning variant-prioritization layer that scored 20,651,210 variants with 21 engineered features, combined these with LDSC, positional MAGMA, fibroblast and muscle eMAGMA, six-tissue SMR, and fine-mapping, and then integrated the prioritized locus with a 56,000-cell chondrocyte atlas, independent OA cartilage expression resources, OA primary-tissue eQTL maps, and ATDC5 perturbation experiments. RESULTS: The prioritization model, used solely as a ranking layer, assigned a high prioritization score (≥ 0.99) to 17,150 variants, including the chr12 lead rs11611450 (prioritization score 0.999853), and highlighted 6,275 additional non-genome-wide-significant high-priority variants. Positional MAGMA nominated eight Bonferroni-significant genes, and eMAGMA nominated four genes in skeletal muscle and seven in fibroblasts. Within the rs11611450-linked five-gene cluster, TCTN2 showed the strongest cross-layer convergence, with SMR support in five of six tissues, fibroblast eMAGMA support (P = 8.34 × 10-10), hypertrophic-chondrocyte enrichment (z = 2.20), and localization to regulatory and inflammatory chondrocyte states. Independent validation showed modestly higher TCTN2 abundance in OA than in normal cartilage (delta = 0.45, P = 2.8 × 10-2), no high-grade-versus-low-grade cartilage shift (logFC = 0.053, FDR = 1.0), and strong OA-cartilage eQTL support in both low-grade and high-grade cartilage (q = 4.86 × 10-4 and 1.13 × 10-2). In ATDC5 cells, Tctn2 knockdown reduced expression to 0.21-fold of Mock and increased Col10a1, Mmp13, and Runx2 to 2.71-, 2.98-, and 3.53-fold, respectively, whereas overexpression and rescue reversed the same markers. CONCLUSIONS: This staged analysis nominates TCTN2 as a plausible candidate within an unresolved chr12 osteoarthritis locus; ATDC5 perturbation indicates that TCTN2 can modulate hypertrophic markers. Because the human-tissue association is directionally discordant, we present a locus-to-cell-state hypothesis rather than a complete genetics-to-mechanism chain, with cross-sectional shifts remaining modest and context-dependent.
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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.