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Prediction of cell states and key transcription factors of the human cornea through integrated single-cell omics analyses.
The cornea, a transparent tissue composed of multiple layers, allows light to enter the eye. Several single-cell RNA-seq (scRNA-seq) analyses have been performed to explore the cell states and to understand the cellular composition of the human cornea. However, inconsistences in cell state annotations between these studies complicate the application of these findings in corneal studies. To address this, we integrated scRNA-seq data from four published studies and created a human corneal cell state meta-atlas. This meta-atlas was subsequently evaluated in two applications. First, we developed a machine learning pipeline cPredictor, using the human corneal cell state meta-atlas as input, to annotate corneal cell states. We demonstrated the accuracy of cPredictor and its ability to identify novel marker genes and rare cell states in the human cornea. Furthermore, cPredictor revealed the differences of the cell states between pluripotent stem cell-derived corneal organoids and the human cornea. Second, we integrated the scRNA-seq-based cell state meta-atlas with chromatin accessibility data, conducting motif-focused and gene regulatory network analyses. These approaches identified distinct transcription factors (TFs) driving cell states of the human cornea. The novel marker genes and TFs were validated by immunohistochemistry. Overall, this study offers a reliable and accessible reference for profiling corneal cell states, which facilitates future research in cornea development, disease, and regeneration.
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SIRT1 promotes glucolipid metabolic conversion to facilitate tumor development in colorectal carcinoma.
Background: Fatty acid oxidation (FAO) is a major alternate energy metabolism pathway in tumor cells subjected to metabolic stress caused by glucose deficiency during rapid progression. However, the mechanism of metabolic reprogramming between glycolysis and FAO in tumor cells is unknown. Therefore, identifying the metabolic glucolipid conversion hub in tumor cells is crucial. Methods: We used single-cell RNA sequencing (scRNA-Seq), RNA sequencing (RNA-Seq), The Cancer Genome Atlas (TCGA), and chromatin immunoprecipitation sequencing (ChIP-Seq) to predict the critical regulator and mechanism of metabolic glucolipid conversion in colorectal cancer (CRC) tumor cells. We used Seahorse metabolic analysis, immunoblotting, immunofluorescence, and immunohistochemical (IHC) technology to verify the prediction and mechanism of this regulator in cancer cell lines, a nude mouse xenograft model, and clinical CRC samples. Results: We demonstrated that sirtuin-1 (SIRT1) was upregulated in CRC cells in response to glucose deprivation and oxidative stress. SIRT1 was also a hub of metabolic glucolipid conversion. SIRT1 upregulation deacetylated β-catenin, translocated it from the nucleus to the cytoplasm, attenuated glycolysis, and was positively correlated with fatty acid oxidation (FAO). Clinical analysis of SIRT1 expression in tumor tissues showed the SIRT1High profile was associated with poor prognosis in CRC patients. SIRT1 interference therapy significantly suppressed tumors in the mouse xenograft model. Conclusions: In hostile, glucose-deficient TMEs, SIRT1 is upregulated, and CRC cells transform the Warburg phenotype to FAO. SIRT1 indicates the frequency of glucolipid transformation and rapid tumor progression and is a promising therapeutic target of CRC.
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Distinct cuproptosis patterns in hepatocellular carcinoma patients correlate with unique immune microenvironment characteristics and cell-cell communication, contributing to varied overall survival outcomes.
BACKGROUND: Hepatocellular carcinoma (HCC), a prevalent cancer, is linked to cuproptosis in tumor progression. However, cuproptosis's impact on HCC prognosis and its role in the tumor microenvironment remain unclear. We aimed to explore the correlation between cellular cuproptosis and the immune microenvironment in HCC, providing potential immunotherapeutic insights. METHODS: Examining cuproptosis-related genes and the immune microenvironment through consensus clustering and WGCNA. Risk models were constructed using LASSO Cox analysis and validated in an independent cohort. Gene expression data from The Cancer Genome Atlas (TCGA) database and single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database were utilized. We scored cuproptosis expression and explored immunoinfiltration and cell-cell communication. Differential signals in T_memory cells were compared across different cuproptosis levels. RESULTS: Cuproptosis genes associated with fibroblast recruitment (GLS) and macrophage infiltration (FDX1). Liver cancer patients categorized into two subtypes based on cuproptosis gene expression. High expression of DLAT, GLS, and CDKN2A linked to immunosuppression (TGF-β), while high FDX1, MTF1, LIAS, and LIPT1 expression enhanced communication with non-immune cells. Developed reliable prognostic signature score and nomogram using cuproptosis-related genes. Single-cell analysis revealed differences in T_memory and TAM infiltration based on cuproptosis scores, with SPP1 and MIF as dominant signaling molecules. Finally, the results of in vitro experiments showed that when DLAT or CDKN2A was knocked down, the proliferation, migration, and invasion of HCC cells were significantly decreased. CONCLUSION: Our study demonstrates that cuproptosis affects the immune microenvironment and cell-cell communication. Identified 9 genetic markers predicting survival outcomes and immunotherapy responses. Evaluating cuproptosis signaling can optimize immunotherapeutic strategies for hepatocellular carcinoma.
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Multi-omics integrative analysis of the mechanisms linking environmental pollutant exposure to bladder cancer pathogenesis.
Bladder cancer (BCa), the most prevalent malignancy of the urinary system, is strongly associated with environmental factors including smoking and industrial chemical exposure. Although previous studies have explored the relationship between various environmental pollutants and BCa mechanisms, there is still a need for an in-depth analysis of the specific effects and particular roles of these pollutants. This study investigates the molecular mechanisms linking environmental pollutant exposure to bladder carcinogenesis through a multi-omics integrative analysis that systematically elucidates the environment-gene interaction network. By integrating transcriptomic data from multiple BCa cohorts with the Comparative Toxicogenomics Database (CTD) gene-chemical-disease network, we identified 168 environment-responsive differentially expressed genes (DEGs). Subsequent Mendelian Randomization (MR), Summary-data-based MR (SMR), and colocalization analyses revealed three causal hub genes (CTSK, GSTM5, and PAFAH1B3; PP4 > 0.70) and associated them with 34 high-risk environmental pollutants. Molecular docking demonstrated strong binding affinities between these hub genes and more than ten pollutants, with bisphenol A, sodium arsenite, and tetrachlorodibenzodioxin (TCDD) differentially regulating distinct targets: significantly suppressing tumor-suppressor genes CTSK (OR = 0.91, p = 0.004) and GSTM5 (OR = 0.77, p < 0.001) while upregulating the oncogenic factor PAFAH1B3 (OR = 2.11, p < 0.001). Single-cell RNA sequencing (scRNA-seq) analysis and Human Protein Atlas (HPA) database validation confirmed tissue-specific expression patterns of these hub genes in bladder tissues. Our findings establish a comprehensive evidence chain connecting "environmental pollutant exposure - gene interaction - bladder carcinogenesis," providing novel biomarkers and preventive targets for molecular subtyping and precision prevention of environmentally associated BCa.
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The construction of a breast cancer prognostic model by combining genes related to hypoxia and endoplasmic reticulum stress.
Breast cancer (BC) is a malignant tumor that occurs in breast tissue. This project aims to predict the prognosis of BC patients using genes related to hypoxia and endoplasmic reticulum stress (ERS). RNA-seq and clinical data for BC were downloaded from TCGA and GEO databases. Hypoxia and ERS-related genes were collected from the Genecards database. Univariate/multivariate Cox regression and Lasso regression analyses were used to screen genes and construct prognostic models. Patients were divided into high-risk (HR) and low-risk (LR) groups based on risk scores. The CIBERSORT algorithm was used to analyze differences in immune infiltration between the two groups. The mutations of the two groups were analyzed statistically. The CellMiner database was used for drug prediction and the TISCH database for single-cell sequencing analysis. We screened 8 feature genes to construct a prognostic model. Patients in the HR group had a remarkably worse prognosis. TP53 exhibited a higher mutation frequency in the HR group. CIBERSORT analysis uncovered a remarkable increase in the infiltration levels of Macrophages M0 and Tregs in cancer patients and HR patients. Drug sensitivity prediction demonstrated that the expression of IVL was greatly negatively linked with the sensitivity of COLCHICINE. PTGS2 had a remarkably negative correlation with the Vincristine sensitivity. The prognostic model based on 8 hypoxia and ERS-related genes can predict the survival, immune status, and potential drugs of BC patients, bringing a new perspective on individualized treatment.
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Heterogeneity and synaptic plasticity analysis of hippocampus based on db-/- mice induced diabetic encephalopathy.
Chronic hyperglycemia can cause changes in synaptic plasticity of hippocampal cells, which has accelerated the pathological process of cognitive dysfunction. However, the heterogeneity of the hippocampal cell populations under long term high glucose statement remains largely unknown. To mimic chronic hyperglycemia induced cognitive function deficit in vivo, db-/- diabetic mice was selected and Novel Object Recognition(NOR) behavior tests were performed. Based on diabetic induced cognitive impairment(CI) animal model, single-cell RNA sequencing was performed in the hippocampus of CI group (21,379 cells) or control group (20,045 cells), and single cell RNA sequencing was applied, and then the single cell atlas of gene expression was profiled. The comprehensive analysis explicated 18 nerve cell clusters, including 9 distinct sub-clusters, More in-depth analysis of oligodendrocyte precursor cells(OPCs) showed five distinct OPCs sub-clusters including expressing marker gene Lingo2-OPCs, Kcnc1-OPCs, Sst-OPCs, Slc6a1-OPCs and Lhfpl3-OPCs, which seems to be able to proliferate, migrate, and finally differentiate into mature oligodendrocytes and produce myelin. To be noted, differentially expressed genes(DEGs) of the Sst-OPCs sub-cluster indicated that the genes participating in neuroactive ligand-receptor interaction, nervous system development and inflammatory process were up-regulated in diabetic induced cognitive impairment(DCI) groups compared to normal control groups. Integrating the data of neuroplasticity regulation, the 20th top-enriched biological process was associated with neuroplasticity regulation in CI groups compared to control groups. Among these neuroplasticity-related genes, the intersectional gene Sstr2 may play an important role in neuroplasticity regulation. Focused on neuroplasticity regulation and its related specific genes may provide potential new clues for the treatment of diabetes mellitus complicated with cognitive impairment. In summary, we showed the comprehensively transcriptional landscape of hippocampal cells in the db-/- diabetic mice with cognitive dysfunction, distinctive cell sub-clusters and the gene expression characteristics were identified, and also their special functions were proposed, which may give new clues and potential targets for diagnosis and treatment of diabetic encephalopathy.
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A novel lactylation-related gene signature deciphers the immunosuppressive microenvironment and stratifies precision therapy in colorectal cancer.
BACKGROUND: Colorectal cancer (CRC) remains a leading cause of cancer mortality, largely due to the heterogeneity of the tumor microenvironment (TME) and the limited efficacy of immunotherapy in microsatellite stable (MSS) tumors. Histone lactylation, a post-translational modification derived from the Warburg effect, serves as a critical bridge linking metabolic reprogramming to gene regulation and immune evasion; however, its specific prognostic value and clinical implications in CRC remain to be fully elucidated. METHODS: In this study, we systematically analyzed transcriptome profiling data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts, supplemented by single-cell RNA sequencing (scRNA-seq) analysis and Human Protein Atlas (HPA) protein-level validation. By integrating univariate Cox regression, Least Absolute Shrinkage and Selection Operator (LASSO) analysis, and multivariate Cox regression, we constructed a novel lactylation-related gene (LRG) risk signature. We extensively evaluated the association between this risk signature and patient prognosis, immune infiltration patterns, somatic mutations, and therapeutic sensitivity. RESULTS: A robust 9-gene prognostic signature (DHRS7, SPR, MBD2, RBM17, CSRP2, S100A4, TMSB4X, TKT, COPS4) was identified and corroborated at the protein level. Patients with high risk scores exhibited significantly worse overall survival (OS) across the training and two independent validation cohorts. Immunogenomic and scRNA-seq analyses revealed that high-risk tumors were characterized by an immunosuppressive and stromal-dense microenvironment-with stromal cells exhibiting the highest lactylation risk scores-enriched with regulatory T cells (Tregs), and frequently harbored PIK3CA mutations. Differential expression analysis indicated that this immune exclusion is structurally maintained by enriched extracellular matrix (ECM) organization and TGF-β signaling. Conversely, low-risk tumors displayed an inflamed phenotype with active antitumor immunity. Pharmacogenomic prediction identified distinct therapeutic stratifications: low-risk patients exhibited significant sensitivity to standard chemotherapeutics (fluorouracil, oxaliplatin) and EGFR/HER2 inhibitors (e.g., lapatinib, erlotinib). In contrast, high-risk patients showed specific vulnerabilities to novel targeted agents, including PI3K pathway inhibitors (TG-100-115, XL765), microenvironment-modulating agents (sildenafil, GANT-61), and epigenetic inhibitors (UNC0638). CONCLUSION: We established a novel lactylation-related risk signature that effectively stratifies CRC patients by prognosis and TME characteristics. By elucidating the crosstalk between metabolic dysregulation, stromal barriers, and immune exclusion, this study provides potential biomarkers and stratified therapeutic strategies-ranging from standard chemotherapy to targeted metabolic and stromal interventions-to optimize precision medicine for CRC patients.
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Integration of Imaging-based and Sequencing-based Spatial Omics Mapping on the Same Tissue Section via DBiTplus.
Spatially mapping the transcriptome and proteome in the same tissue section can significantly advance our understanding of heterogeneous cellular processes and connect cell type to function. Here, we present Deterministic Barcoding in Tissue sequencing plus (DBiTplus), an integrative multi-modality spatial omics approach that combines sequencing-based spatial transcriptomics and image-based spatial protein profiling on the same tissue section to enable both single-cell resolution cell typing and genome-scale interrogation of biological pathways. DBiTplus begins with in situ reverse transcription for cDNA synthesis, microfluidic delivery of DNA oligos for spatial barcoding, retrieval of barcoded cDNA using RNaseH, an enzyme that selectively degrades RNA in an RNA-DNA hybrid, preserving the intact tissue section for high-plex protein imaging with CODEX. We developed computational pipelines to register data from two distinct modalities. Performing both DBiT-seq and CODEX on the same tissue slide enables accurate cell typing in each spatial transcriptome spot and subsequently image-guided decomposition to generate single-cell resolved spatial transcriptome atlases. DBiTplus was applied to mouse embryos with limited protein markers but still demonstrated excellent integration for single-cell transcriptome decomposition, to normal human lymph nodes with high-plex protein profiling to yield a single-cell spatial transcriptome map, and to human lymphoma FFPE tissue to explore the mechanisms of lymphomagenesis and progression. DBiTplusCODEX is a unified workflow including integrative experimental procedure and computational innovation for spatially resolved single-cell atlasing and exploration of biological pathways cell-by-cell at genome-scale.
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CCT5 as a candidate biomarker in bladder cancer: functional validation and mechanistic clues.
CCT5, a subunit of the chaperonin-containing TCP1 complex, has been implicated in the development of various malignancies. However, its role in bladder cancer remains undefined. This study investigated the functional contribution of CCT5 and its association with Hippo/YAP signaling. Using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), CCT5 expression and its prognostic significance were analyzed. Single-cell and spatial transcriptomics were employed to explore expression patterns and cellular heterogeneity. Functional assessments were conducted in vitro and in vivo using xenografts. To elucidate the underlying mechanisms, RNA-seq was integrated with Western blotting analysis. CCT5 was found to be upregulated in bladder cancer and correlated with poor prognosis and aggressive pathological features. Single-cell and spatial analyses revealed that CCT5 was enriched in malignant epithelial subpopulations with high CNV scores, activated oncogenic pathways, and extensive cell-cell interactions. Functionally, CCT5 promoted proliferation, migration, invasion, and G1/S transition while inhibiting apoptosis; its depletion reduced xenograft growth. At the signaling level, CCT5 knockdown enhanced phosphorylation of MST1, LATS1, and YAP, without significant changes in total protein levels, suggesting activation of Hippo/YAP signaling. These findings highlight CCT5 as an oncogenic factor in bladder cancer, potentially acting through the regulation of Hippo/YAP signaling, and propose its potential as a biomarker and therapeutic target in bladder cancer.
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Single-cell transcriptional profiling reveals developmental dynamics of longissimus dorsi muscle in adult and Juvenile bactrian camels.
INTRODUCTION: The longissimus dorsi muscle of Bactrian camels holds significant biological and economic value. However, the cellular heterogeneity, lineage differentiation patterns, and intercellular communication mechanisms underlying its skeletal muscle development remain unclear, which has hampered the advancement of precise regulation of camel meat quality traits and genetic improvement of the breed. Accordingly, there is an urgent need to elucidate the developmental regulatory mechanisms of this muscle tissue at the single-cell level. METHODS: In this study, longissimus dorsi muscle tissues from 4-day-old (juvenile) and 5-year-old (adult) Bactrian camels were selected as research subjects. Integrated single-nucleus RNA sequencing (snRNA-seq) was employed to obtain gene expression data, which was coupled with Monocle2 pseudotime analysis, CellChat-based intercellular communication dissection, Gene Ontology (GO) enrichment analysis, and C2C12 cell functional validation experiments to conduct a systematic investigation into the cellular characteristics and developmental mechanisms of the Bactrian camel longissimus dorsi muscle. RESULTS: A total of 14 cell clusters were identified, and the cellular composition of muscle tissues differed significantly between age groups-juvenile camel muscles were enriched with proliferative cell populations such as muscle satellite cells (MuSCs) and fibroblast-like progenitor cells (FAPs), while adult camel muscles were dominated by mature type IIX/IIA fast-twitch muscle fibers. Further analysis revealed that MuSCs exhibited bidirectional differentiation potential towards type I slow-twitch muscle fibers and type IIA/IIX fast-twitch muscle fibers, and the PCDH7 gene was found to promote myogenic differentiation. Additionally, four FAP subpopulations were characterized, among which the MME+ FAP subpopulation was closely associated with intramyocellular fat (IMF) deposition. DISCUSSION: This study, for the first time, constructed a single-cell atlas and intercellular communication network of the Bactrian camel longissimus dorsi muscle, uncovered the key regulatory mechanisms governing its skeletal muscle development, and identified functionally important regulatory targets such as PCDH7. These findings not only provide a theoretical basis for the precise improvement of camel meat quality but also laid the groundwork for in-depth investigations into the adaptive evolutionary mechanisms of camel skeletal muscle.