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Integration of Multi-Omics and Machine Learning Identifies TGFB1 and SERPINE1 as Biomarkers of Vascular Smooth Muscle Cell Senescence in Intracranial Aneurysms.
Intracranial aneurysms (IAs) are severe cerebrovascular disorders lacking effective gene therapy or pharmacological interventions. Vascular smooth muscle cell (VSMC) senescence has been associated with various cardiovascular and cerebrovascular diseases; however, its role in IA pathogenesis remains unexplored, and the key regulatory genes remain unidentified. By integrating multi-omics data, machine learning, and experimental validation, we identified two senescence-associated genes (SAGs) that may serve as VSMC senescence biomarkers in IAs. We integrated single-cell RNA sequencing data from a mouse elastase-induced IA model (GSE193533) with human bulk RNA sequencing and microarray datasets to investigate VSMC senescence in IA. Our analyses included cell clustering, cell-cell communication, differential expression, functional enrichment, pseudotime trajectory inference, and high-dimensional weighted gene co-expression network analysis (hdWGCNA). Machine learning identified candidate SAGs, which were validated using external datasets and immunohistochemical analysis of human IA tissues. Single-cell analysis of the mouse IA model revealed 26 clusters across 10 cell types, with IA samples showing VSMC depletion, immune cell enrichment, and fibroblast expansion. VSMCs were categorized into five subsets (VSMC1-5), with the extracellular matrix remodeling and synthetic-inflammatory subtype (VSMC1) significantly increased. Differential expression analysis of VSMCs intersecting with senescence-associated genes from the Aging Atlas database identified 159 SAGs enriched in inflammatory and apoptotic pathways. Integrating hdWGCNA and bulk transcriptomics identified 45 key SAGs. TGFB1 and SERPINE1 emerged as robust biomarkers of senescence-associated VSMCs, showing high diagnostic accuracy (AUC > 0.75) and upregulation in IA tissues. Our study provides new insights into the pathological mechanisms of intracranial aneurysms. VSMC senescence may contribute to IA progression. TGFB1 and SERPINE1 may serve as biomarkers and promising therapeutic targets for VSMC senescence in IA. However, their specific mechanisms require further investigation and validation.
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Unveiling B7/CD28 family proteins in hepatocellular carcinoma: insights into communication and prognostic significance.
BACKGROUND: Immunotherapy has made remarkable achievements in cancer treatment, but it still faces the challenge of limited response rates in liver cancer therapy. Although there has been extensive research on the role of programmed cell death-ligand 1 (PD-L1) in hepatocellular carcinoma (HCC), our understanding of the effects of other inhibitory B7/CD28 family members is still limited despite advancements in prognostic tools, more specific, accurate, and robust biomarkers are required to improve HCC patient prognoses. METHODS: We acquired the single-cell sequencing data from relevant literature and selected 42 liver tissue samples, including 89,246 cells from HCC patients, to investigate the expression, localization, and intercellular communications of the B7/CD28 family in HCC. Within the Cancer Genome Atlas dataset, we utilized Lasso and Cox regression analyses to develop a risk model for identifying the most pertinent B7/CD28 family proteins associated with prognosis. Subsequently, we conducted a retrospective analysis of 94 HCC patients who underwent hepatectomy at our institution and determined the prognostic significance of this malignancy. RESULTS: Based on the single-cell RNA sequencing data, we have delineated various members of the B7/CD28 family and their corresponding receptors. We have elucidated their distribution on tumor cells and immune cells, revealing active intercellular communications among tumor cells, fibroblasts, and epithelial cells. Through the implementation of Lasso, we have pinpointed a significant correlation between the B7H3 molecule and prognosis. Leveraging multiplex immunofluorescence, we were able to discern three distinct patterns of B7H3 expression-tumor-associated, stroma-associated, and a hybrid form encompassing both. Notably, the presence of B7H3 in the stroma exhibited the most robust correlation with prognosis. Furthermore, the efficacy of our prognostic signature was validated through clinicopathological analyses conducted at our institution. CONCLUSIONS: In conclusion, the B7/CD28 family plays an active role in the tumor immune microenvironment and cellular communication. B7H3 could serve as an indicator for predicting the outcome of HCC. Additional investigation is required to validate these discoveries in future groups of individuals and assess their viability as therapies guided by biomarkers.
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Cellular Characterization and Interspecies Evolution of the Tree Shrew Retina across Postnatal Lifespan.
Tree shrews (TSs) possess a highly developed visual system. Here, we establish an age-related single-cell RNA sequencing atlas of retina cells from 15 TSs, covering 6 major retina cell classes and 3 glial cell types. An age effect is observed on the cell subset composition and gene expression pattern. We then verify the cell subtypes and identify specific markers in the TS retina including CA10 for bipolar cells, MEGF11 for H1 horizontal cells, and SLIT2, RUNX1, FOXP2, and SPP1 for retinal ganglion cell subpopulations. The cross-species analysis elucidates the cell type-specific transcriptional programs, different cell compositions, and cell communications. The comparisons also reveal that TS cones and subclasses of bipolar and amacrine cells exhibit the closest relationship with humans and macaques. Our results suggests that TS could be used as a better disease model to understand age-dependent cellular and genetic mechanisms of the retina, particularly for the retinal diseases associated with cones.
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Mapk14 is a Prognostic Biomarker and Correlates with the Clinicopathological Features and Immune Infiltration of Colorectal Cancer.
Background: Colorectal cancer (CRC) is one of the most common gastrointestinal tumors, ranking in the top 5 of all common tumors in terms of incidence and mortality. However, the mechanisms driving the evolution of colorectal cancer remain unclear. Therefore, we investigated the association between Mapk14 expression and clinicopathological and tumor-infiltrating immune cells. Methods: In this study, we collected CRC patient data from The Cancer Genome Atlas (TCGA), compared the expression level in CRC and normal colorectal tissue using the Wilcoxon rank sum test and assessed the relationship between Mapk14 and clinicopathological features using the Welch one-way ANOVA test. Kaplan-Meier and timeROC GSE17537 datasets were obtained from the Gene Expression Omnibus (GEO) dataset to assess the prognostic impact of the Mapk14 gene on colorectal cancer. Second, we further explored the methylation level of Mapk14 and its influencing factors. Single-cell sequencing of Mapk14 in the tumor immune microenvironment (TIME) was analyzed using the GSE108989 dataset. Further analyses based on the TIMER method were performed to assess the correlation between Mapk14 and tumor immune infiltration, immune checkpoints, tumor mutational load and microsatellite instability. Finally, the results of the bioinformatics analysis were verified by an immunohistochemical analysis. Results: The results showed that the expression of Mapk14 was upregulated in CRC tumor tissues compared with normal colorectal tissues and the high expression of Mapk14 was associated with poor clinicopathological features and poor prognoses in the CRC array. In addition, cg05798012 and cg25375420 of Mapk14 are the main DNA methylation sites affecting OS. Single-cell sequencing of the tumor immune microenvironment showed that the abundance and cell state of dysfunctional T cells changed greatly. Importantly, the abnormal overexpression of Mapk14 in colorectal cancer is related to the level of immune infiltration of immune cells (including CD8+ T cells, neutrophils, dendritic cells, B cells, CD4+ T cells, and macrophages). The high expression of Mapk14 was significantly correlated with immune checkpoints (including SIGLEC15, TIGIT, LAG3, CTLA4 and PDCDILG2), while the high expression of Mapk14 was negatively correlated with TMB and MSI but mostly positively correlated with drug sensitivity. Finally, the immunohistochemical results confirmed that the clinical stage (Ⅰ, Ⅱ, Ⅲ and Ⅳ) and M stage (M0 and M1) affected the abnormally high expression of Mapk14. Conclusion: A comprehensive bioinformatics study and experimental validation revealed that Mapk14 could serve as a novel prognostic biomarker associated with immune infiltration and pharmacotherapy and may represent a potential therapeutic target for the treatment of CRC.
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Development of a prognostic RiskScore model using efferocytosis-related signature genes for lung adenocarcinoma.
BACKGROUND: Lung adenocarcinoma (LUAD) has high incidence and mortality rates. Efferocytosis is involved in the progression of various cancers. The current work set out to develop a prognosis signature using efferocytosis-related genes (ERGs) for LUAD. METHODS: Public databases were accessed to obtain bulk and single-cell data of LUAD. Molecular subtyping of LUAD was performed using ConsensusClusterPlus, and efferocytosis-related candidate genes were screened by weighted gene co-expression network analysis (WGCNA) in combination with differential analysis. Subsequently, Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to construct a prognostic RiskScore model, followed by evaluating the relationship between the RiskScore, immune infiltration, and drug sensitivity. Single-cell transcriptomic profiling of LUAD was performed with the Seurat package to elucidate the cellular origins of the key genes. The expression and potential function of the representative genes were verified by reverse transcriptional quantitative polymerase chain reaction (qPCR) (RT-qPCR), Cell Counting Kit-8 (CCK-8), wound healing, and Transwell assays. RESULTS: Two molecular subtypes of LUAD with different outcomes and clinical features were identified. Candidate ERGs were mainly enriched in inflammatory and immune-related pathways. Subsequently, seven key genes (CD200R1, BTN2A2, STAP1, DNASE2B, SAMD9, SEMA7A, BIRC3) associated with efferocytosis in LUAD were identified to establish a RiskScore model, which exhibited high robustness in predicting patient prognosis. Notably, high-risk group had lower immune scores and more unfavorable prognosis than low-risk group. Moreover, eight drugs were closely linked to the RiskScore, and low-risk group was more sensitive to Doramapimod_1042. Single-cell atlas of LUAD showed that the prognostic ERGs were mainly expressed in mast cells. In vitro experiments revealed that most of the seven ERGs were overexpressed in LUAD cells, and that SEMA7A knockdown could suppress LUAD cell proliferation, migration and invasion. CONCLUSIONS: Our results provided novel insights for the prognosis prediction and personalized treatment of LUAD.
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Dynamic transcriptomic and regulatory networks underpinning the transition from fetal primordial germ cells to spermatogonia in mice.
The transition from fetal primordial germ cells (PGCs) to spermatogonia (SPG) is critical for male germ cell development; however, the detailed transcriptomic dynamics and regulation underlying this transition remain poorly understood. Here by interrogating the comprehensive transcriptome atlas dataset of mouse male germ cells and gonadal cells development, we elucidated the regulatory networks underlying this transition. Our single-cell transcriptome analysis revealed that the transition from PGCs to SPG was characterized by global hypertranscription. A total of 315 highly active regulators were identified to be potentially involved in this transition, among which a non-transcription factor (TF) regulator TAGLN2 was validated to be essential for spermatogonial stem cells (SSCs) maintenance and differentiation. Metabolism profiling analysis also revealed dynamic changes in metabolism-related gene expression during PGC to SPG transition. Furthermore, we uncovered that intricate cell-cell communication exerted potential functions in the regulation of hypertranscription in germ cells by collaborating with stage-specific active regulators. Collectively, our work extends the understanding of molecular mechanisms underlying male germ cell development, offering insights into the recapitulation of germ cell generation in vitro.
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Integrating transcriptomic data and digital pathology for NRG-based prediction of prognosis and therapy response in gastric cancer.
BACKGROUND: Cancer is characterized by its ability to resist cell death, and emerging evidence suggests a potential correlation between non-apoptotic regulated cell death (RCD), tumor progression, and therapy response. However, the prognostic significance of non-apoptotic RCD-related genes (NRGs) and their relationships with immune response in gastric cancer (GC) remain unclear. METHODS: In this study, RNA-seq gene expression and clinical information of GC patients were acquired from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Cox and LASSO regression analyses were used to construct the NRG signature. Moreover, we developed a deep learning model based on ResNet50 to predict the NRG signature from digital pathology slides. The expression of signature hub genes was validated using real-time quantitative PCR and single-cell RNA sequencing data. RESULTS: We identified 13 NRGs as signature genes for predicting the prognosis of patients with GC. The high-risk group, characterized by higher NRG scores, demonstrated a shorter overall survival rate, increased immunosuppressive cell infiltration, and immune dysfunction. Moreover, associations were observed between the NRG signature and chemotherapeutic drug responsiveness, as well as immunotherapy effectiveness in GC patients. Furthermore, the deep learning model effectively stratified GC patients based on the NRG signature by leveraging morphological variances, showing promising results for the classification of GC patients. Validation experiments demonstrated that the expression level of SERPINE1 was significantly upregulated in GC, while the expression levels of GPX3 and APOD were significantly downregulated. CONCLUSION: The NRG signature and its deep learning model have significant clinical implications, highlighting the importance of individualized treatment strategies based on GC subtyping. These findings provide valuable insights for guiding clinical decision-making and treatment approaches for GC.
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KIF18B Is Essential for Lung Adenocarcinoma Progression Through the E2F Transcriptional Network.
Lung adenocarcinoma (LUAD) remains a leading cause of cancer-related mortality worldwide, highlighting the urgent need to identify novel prognostic biomarkers and therapeutic targets. Kinesin Family Member 18B (KIF18B) is implicated in mitosis, yet its precise role in LUAD pathogenesis remains poorly defined. This study investigates the oncogenic and therapeutic role of KIF18B in LUAD. Integrated analysis of The Cancer Genome Atlas Program (TCGA) and Gene Expression Omnibus (GEO) datasets revealed that KIF18B is significantly upregulated in LUAD tissues, with its elevated expression strongly associated with an advanced pathological stage, high grade, and poor patient survival. Single-cell sequencing data analysis further indicated that KIF18B expression in LUAD is closely linked to key malignant processes, including cell cycle progression, proliferation, migration, and epithelial-mesenchymal transition (EMT). Functional experiments demonstrated that KIF18B knockdown markedly suppressed LUAD cell proliferation, migration, and invasion in vitro and inhibited tumor growth in vivo. Mechanistically, transcriptomic and pathway analyses revealed that KIF18B depletion downregulates Early 2 Factor (E2F) target genes. Luciferase reporter assays confirmed diminished E2F reporter activity as well as E2F2 promoter activity upon KIF18B silencing, while overexpression of E2F1, E2F2, or E2F3 rescued the inhibited proliferative phenotypes induced by KIF18B loss. Collectively, our findings establish KIF18B as an essential driver of LUAD progression that acts through the E2F transcriptional network, nominating it as a promising diagnostic and therapeutic target.
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Mesenchymal stem cell-derived extracellular vesicles attenuate liver transplantation-induced ischemia/reperfusion injury by suppressing hepatocellular complement C5 expression.
BACKGROUND & AIMS: Hepatic ischemia-reperfusion injury (HIRI) is an unavoidable complication of liver transplantation (LT) that drives allograft dysfunction and mortality. Mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) show therapeutic promise, yet their actions within the hepatic network remain incompletely defined. We investigated how MSC-EVs protect against LT-induced HIRI, focusing on intercellular communication and complement-mediated inflammation. METHODS: Single-cell RNA sequencing, single-nucleus ATAC-seq, and spatial transcriptomics were performed in rat LT and mouse HIRI livers with or without MSC-EV treatment. Cell migration assays, AAV-mediated overexpression, and PTPN13-knockdown MSC-EVs were used to prove cellular function and mechanisms. RESULTS: MSC-EVs attenuated HIRI, improving liver function and reducing histologic injury and hepatocyte apoptosis. Single-cell analyses showed selective curtailment of mononuclear phagocyte and neutrophil recruitment to injured liver. Mechanistically, HIRI induced hepatocyte C5 and C5a, which engaged C5aR1 on mononuclear phagocytes and neutrophils to drive chemotaxis. Consistent with this pathway, MSC-EVs delivered PTPN13 to hepatocytes, lowering C5 and promoting ERK1/2 dephosphorylation and enhanced C/EBPα activity. Elevated C/EBPα activity directly suppressed C5 transcription, whereas PTPN13-depleted MSC-EVs showed diminished efficacy. CONCLUSIONS: We present a single-cell multi-omics atlas of MSC-EV therapy across rat LT and mouse HIRI, supported by clinical data. MSC-EVs mitigated HIRI by lowering hepatocyte C5 and reducing mononuclear phagocyte and neutrophil recruitment. MSC-EV delivery of PTPN13 dephosphorylated ERK1/2 and enhanced C/EBPα, repressing hepatocyte C5 and dampening C5a-C5aR1 signaling. These findings position MSC-EVs as a translational nanotherapy to improve graft outcomes after LT.
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Single-cell and bulk transcriptomic analyses define an IFI27-centered interferon-response epithelial state in bladder cancer and its transcriptional response to irradiation.
BACKGROUND: Interferon-responsive tumor-cell states can simultaneously increase immune visibility and induce immune-regulatory programs, yet their epithelial-cell distribution and treatment responsiveness in bladder cancer remain incompletely defined. We sought to resolve a reproducible epithelial interferon-response state across patients, characterize its immune context, and determine whether its transcriptional components respond to ionizing radiation in vitro. METHODS: Single-cell RNA sequencing data from seven primary bladder tumors and one adjacent normal sample were reanalyzed with uniform quality control and doublet removal. After broad-lineage annotation, 29,777 identity-gated tumor epithelial cells were reclustered and analyzed by repeated non-negative matrix factorization across ranks and random seeds. An NMF-informed three-gene interferon-response score based on IFI27, ISG15, and IFI6 was used to define patient-internal upper- and lower-quartile states. Differential expression was assessed by patient-blocked pseudobulk edgeR models, followed by Hallmark, Gene Ontology, and Reactome enrichment, leave-one-patient-out analyses, immune-feature scoring, balanced CellChat analysis, and TCGA-BLCA corroboration. T24 bladder cancer cells were exposed to 0, 2, 4, or 8 Gy, and selected transcripts were quantified by qRT-PCR 24 h later. RESULTS: The final atlas comprised 39,224 cells assigned to six broad lineages. Repeated NMF reproducibly identified an IFI27-centered epithelial program, and the corresponding score showed marked interpatient variation while remaining detectable across all seven tumors. Patient-blocked analysis identified 179 genes with false-discovery rate <0.05 and absolute log2FC ≥ 0.5; IFIT1, CXCL10, IFI44L, IFITM1, HLA-B, B2M, CD74, IFI6, and ISG15 were representative upregulated genes. IFN-response-score-high epithelial cells showed strong enrichment of interferon-gamma response, interferon-alpha response, inflammatory response, IL6-JAK-STAT3 signaling, antigen processing and presentation, and chemokine-response programs. MHC-I, MHC-II, CXCL9/10/11-related, and immune-regulatory ligand scores increased in all seven patient-paired comparisons, whereas CD274 itself remained sparsely detected and was not stably associated with the continuous score. Balanced pooled CellChat analyses prioritized relatively enriched MDK-SDC1, MDK-SDC2, and MDK-ITGA6/ITGB1 candidate interactions. TCGA-BLCA analyses corroborated the broader interferon and antigen-presentation context at gene and pathway levels. Irradiation induced dose-associated increases in IFI27, ISG15, IFI6, IFIT1, CXCL10, and IFITM1 transcripts, accompanied by increases in CD274, VIM, and SNAI1 and a decrease in CDH1. CONCLUSION: Bladder tumors contain a reproducible IFI27-centered epithelial interferon-response state with coordinated antigen-presentation, chemokine-related, and selected immune-regulatory transcriptional features. Its molecular context is supported across patients and in bulk transcriptomes, while irradiation-associated qRT-PCR changes suggest that components of the program are treatment responsive. These findings define a hypothesis-generating epithelial immune state and candidate communication axes for future spatial, protein-level, and functional validation.