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Prognostic and Immunological Significance of NMNAT1 in Colorectal and Pan-Cancer Contexts.
INTRODUCTION: Nicotinamide plays a critical role in the prevention and treatment of tumors, and its metabolism is closely associated with tumor progression. The aim of this study was to understand the prognostic and immunological significance of nicotinamide metabolism-related genes in pan-cancer. METHODS: We downloaded The Cancer Genome Atlas and Genotype Tissue Expression pan-cancer datasets for NMNAT1 from the UCSC database. We analyzed the differential expression, prognosis, genetic alterations, DNA methylation, immune infiltration, and co-expression with RNA modification-related genes and immune checkpoint-related genes. Genes with expression patterns similar to NMNAT1 were identified using the GEPIA library. The GSCA database was used to investigate the correlation between gene expression and drug sensitivity, as assessed by GDSC and CTRP. The CancerSEA database was employed to examine the association of NMNAT1 expression at the single-cell level across different tumors and its relation to 14 functional states. Immunohistochemistry was performed to assess the clinical significance of NMNAT1 expression. RESULTS: NMNAT1 exhibited differential expression across 25 tumor types, including colorectal cancer (CRC), and its expression was significantly associated with the prognosis of 11 tumors. Furthermore, NMNAT1 expression correlated significantly with clinicopathological features. NMNAT1 was strongly associated with immune cells, RNA modification-related genes, and immune checkpoint-related genes in most tumors, affecting immune responses. The expression of NMNAT1 also correlated with sensitivity and resistance to several drugs. Single-cell analysis revealed that NMNAT1 is involved in the progression of retinoblastoma, uveal melanoma, and CRC. Immunohistochemical analysis confirmed that NMNAT1 expression is an independent prognostic factor in patients with CRC. CONCLUSION: NMNAT1 is a crucial prognostic and immune marker gene for nicotinamide metabolism, particularly in CRC. It has potential as a clinical biomarker and a therapeutic target for cancer treatment.
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Unified integration of spatial transcriptomics across platforms with LLOKI.
Spatial transcriptomics (ST) has transformed our understanding of tissue architecture and cellular interactions, but integrating ST data across platforms remains challenging due to differences in gene panels, data sparsity, and technical variability. Here, we introduce LLOKI, a novel framework for integrating imaging-based ST data from diverse platforms without requiring shared gene panels. LLOKI addresses ST integration through two key alignment tasks: feature alignment across technologies and batch alignment across data sets. Optimal transport-guided feature propagation adjusts data sparsity to match scRNA-seq references through graph-based imputation, enabling single-cell foundation models such as scGPT to generate unified features. Batch alignment then refines scGPT-transformed embeddings, mitigating batch effects while preserving biological variability. Evaluations on mouse brain samples from five different technologies demonstrate that LLOKI outperforms existing methods and is effective for cross-technology spatial gene program identification, and tissue slice alignment. Applying LLOKI to five ovarian cancer data sets, we identify an integrated gene program indicative of tumor-infiltrating T cells across gene panels. Together, LLOKI provides a robust foundation for cross-platform ST studies, with the potential to scale to large atlas data sets, enabling deeper insights into cellular organization and tissue environments.
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Expression and clinical significance of FANCI gene in pan-cancer: a comprehensive analysis based on multi-omics data.
INTRODUCTION: The FANCI gene, an essential element of the Fanconi anemia pathway, has been associated with a variety of cancer types. This investigation seeks to clarify the expression profiles, prognostic relevance, and diagnostic capabilities of FANCI across multiple malignancies, along with its links to immune cell infiltration, genetic alterations, protein-protein interactions, and functional roles. METHODS: By utilizing data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases, we conducted a comprehensive analysis of FANCI mRNA expression using R software and visualized the results with the ggplot2 package. Prognostic and diagnostic evaluations were conducted using Xiantao tools to produce survival and receiver operating characteristic (ROC) curves. The examination of genetic variation was facilitated through cBioPortal, while DNA methylation and mRNA modifications were analyzed utilizing UALCAN and SangerBox 3.0. Correlations with immune responses were assessed via the EPIC platform and SangerBox 3.0. Additionally, we constructed protein-protein interaction networks employing the STRING database and Cytoscape software. Functional enrichment analyses encompassed Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). The CancerSEA database was also utilized for single-cell level investigation of FANCI's association with the functional states of cancer. RESULTS: Our findings reveal that FANCI is significantly upregulated in the majority of tumor types when compared to normal tissues, with increased protein levels observed in several cancers, including colorectal adenocarcinoma (COAD) and pancreatic adenocarcinoma (PAAD). Elevated FANCI expression is associated with unfavorable prognoses in cancers such as adrenocortical carcinoma (ACC) and liver hepatocellular carcinoma (LIHC). Methylation assessments demonstrated a robust inverse correlation between FANCI promoter methylation and its expression in LIHC. Moreover, FANCI expression was found to be connected to immune cell infiltration and tumor mutation burden in select cancers. DISCUSSION: In summary, FANCI presents as a promising biomarker for cancer prognosis and diagnosis, with potential implications for therapeutic interventions. Subsequent investigations should concentrate on elucidating the mechanistic functions of FANCI in cancer development and assessing its viability as a therapeutic target.
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Transcript and protein signatures derived from shared molecular interactions across cancers are associated with mortality.
BACKGROUND: Characterization of shared cancer mechanisms have been proposed to improve therapy strategies and prognosis. Here, we aimed to identify shared cell-cell interactions (CCIs) within the tumor microenvironment across multiple solid cancers and assess their association with cancer mortality. METHODS: CCIs of each cancer were identified by NicheNet analysis of single-cell RNA sequencing data from breast, colon, liver, lung, and ovarian cancers. These CCIs were used to construct a shared multi-cellular tumor model (shared-MCTM) representing common CCIs across cancers. A gene signature was identified from the shared-MCTM and tested on the mRNA and protein level in two large independent cohorts: The Cancer Genome Atlas (TCGA, 9185 tumor samples and 727 controls across 22 cancers) and UK biobank (UKBB, 10,384 cancer patients and 5063 controls with proteomics data across 17 cancers). Cox proportional hazards models were used to evaluate the association of the signature with 10-year all-cause mortality, including sex-specific analysis. RESULTS: A shared-MCTM was derived from five individual cancers. A shared gene signature was extracted from this shared-MCTM and the most prominent regulatory cell type, matrix cancer-associated fibroblast (mCAF). The signature exhibited significant expression changes in multiple cancers compared to controls at both mRNA and protein levels in two independent cohorts. Importantly, it was significantly associated with mortality in cancer patients in both cohorts. The highest hazard ratios were observed for brain cancer in TCGA (HR [95%CI] = 6.90[4.64-10.25]) and ovarian cancer in UKBB (5.53[2.08-8.80]). Sex-specific analysis revealed distinct risks, with a higher mortality risk associated with the protein signature score in males (2.41[1.97-2.96]) compared to females (1.84[1.44-2.37]). CONCLUSION: We identified a gene signature from a comprehensive shared-MCTM representing common CCIs across different cancers and revealed the regulatory role of mCAF in the tumor microenvironment. The pathogenic relevance of the gene signature was supported by differential expression and association with mortality on both mRNA and protein levels in two independent cohorts.
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Chromosome-level genome assembly and single-cell analysis unveil molecular mechanisms of arm regeneration in the ophiuroid Ophiura sarsii vadicola.
BACKGROUND: Ophiuroids, belonging to Ophiuroidea in Echinodermata, possess remarkable regenerative capacities in their arms, relying on cellular recruitment and de-differentiation. However, limited high-quality genomic resources have hindered the investigation of the underlying molecular mechanisms of ophiuroid regeneration. RESULTS: Here, we report a chromosome-level genome of Ophiura sarsii vadicola, 259.28 Mbp in length with a scaffold N50 length of 66.91 Mbp. We then perform bulk and single-cell RNA sequencing analysis to investigate gene expression and cellular dynamics during arm regeneration. We identify five distinct cellular clusters involved in the arm regeneration and infer the dynamic transformations from sensory stimulation to injury response, wound healing, and tissue regeneration. We find that progenitor cells derived from connective tissue cells differentiate into muscle, cartilage, endothelial, and epithelial cells. Pseudotime analysis indicates that muscle differentiation occurs early in the regeneration process. CONCLUSIONS: Our genomic resource and single-cell atlas shed light on the mechanisms of organ regeneration in ophiuroids.
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KNOX1 Transcription Factors in Plants with a Special Focus on Horticultural Crops: A Review.
Class I KNOX1 (KNOTTED1-like homeobox 1) transcription factors integrate gibberellin (GA), cytokinin (CK), and auxin (IAA) signaling to maintain shoot apical meristem identity and coordinate plant organogenesis. This review examines the structural conservation, evolutionary dynamics, and regulatory architecture of KNOX1 genes across horticultural crops, drawing essential mechanistic context from model species. We synthesize KNOX1 functions in six agronomic domains, including plant architecture and branching, leaf morphogenesis and ornamental traits, floral development and sex determination, fruit formation and quality, storage organ specification, and abiotic stress resilience. Particular attention is given to recent breakthroughs in cucurbit inferior ovary development, tomato chloroplast patterning, and potato tuber morphogenesis. We identify critical bottlenecks constraining translation, including fragmented regulatory networks, recalcitrant transformation systems in woody perennials, uneven taxonomic coverage favoring annual vegetables over ornamentals and medicinal species, and a near-complete absence of multi-environment field validation. We propose four strategic priorities to bridge this gap: (i) construction of spatiotemporal expression atlases using single-cell and spatial transcriptomics; (ii) tissue-specific and promoter-engineered CRISPR/Cas9 editing to circumvent pleiotropic penalties; (iii) cross-species comparative evo-devo analysis of lineage-specific innovations (compound leaves, inferior ovaries, tubers); and (iv) integrated field trials assessing genotype-by-environment interactions and trait stability. This framework aims to accelerate KNOX1-directed molecular design breeding in horticultural crops.
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Single-cell and bulk RNA sequencing analysis of B cell marker genes in TNBC TME landscape and immunotherapy.
OBJECTIVE: This study amied to investigate the prognostic characteristics of triple negative breast cancer (TNBC) patients by analyzing B cell marker genes based on single-cell and bulk RNA sequencing. METHODS: Utilizing single-cell sequencing data from TNBC patients, we examined tumor-associated B cell marker genes. Transcriptomic data from The Cancer Genome Atlas (TCGA) database were used as the foundation for predictive modeling. Independent validation set was conducted using the GSE58812 dataset. Immune cell infiltration into the tumor was assessed through various, including XCELL, TIMER, QUANTISEQ, CIBERSORT, CIBERSORT-ABS, and ssGSEA. The TIDE score was utilized to predict immunotherapy outcomes. Additional investigations were conducted on the immune checkpoint blockade gene, tumor mutational load, and the GSEA enrichment analysis. RESULTS: Our analysis encompassed 22,106 cells and 20,556 genes in cancerous tissue samples from four TNBC patients, resulting in the identification of 116 B cell marker genes. A B cell marker gene score (BCMG score) involving nine B cell marker genes (ZBP1, SEL1L3, CCND2, TNFRSF13C, HSPA6, PLPP5, CXCR4, GZMB, and CCDC50) was developed using TCGA transcriptomic data, revealing statistically significant differences in survival analysis (P<0.05). Functional analysis demonstrated that marker genes were predominantly associated with immune-related pathways. Notably, substantial differences between the higher and lower- BCMG score groups were observed in terms of immune cell infiltration, immune cell activity, tumor mutational burden, TIDE score, and the expression of immune checkpoint blockade genes. CONCLUSION: This study has established a robust model based on B-cell marker genes in TNBC, which holds significant potential for predicting prognosis and response to immunotherapy in TNBC patients.
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UBE2L3, a susceptibility gene that plays oncogenic role in hepatitis B-related hepatocellular carcinoma.
Previously, we identified UBE2L3 as a susceptibility gene for chronic hepatitis B virus (HBV) infection through genome-wide association study. Here, we analysed the association between genetic variants of UBE2L3 and the susceptibility to HBV-related hepatocellular carcinoma (HCC) and further explored its role in HCC. This case-control study included 1344 subjects who cleared HBV, 1560 HBV carriers and 1057 HBV-related HCC patients. Two single nucleotide polymorphisms (SNPs) were genotyped, including rs2266959 and rs4821116. Logistic regression analysis was performed to compute the odds ratio (OR) and 95% confidence interval (CI). We further analysed the expression of UBE2L3 and its association with pathological features based on The Cancer Genome Atlas (TCGA) data and our tissue microarray. Proliferation and migration assays were performed in hepatoma cell lines with or without UBE2L3 knockdown. Further RNA-seq analysis was performed to explore the underlying oncogenic mechanism. The variant genotypes of rs4821116 in UBE2L3 were associated with decreased risk for HCC and chronic HBV infection. Moreover, based on both TCGA and our tissue microarray data, higher levels of UBE2L3 expression were correlated with higher tumour grade, advanced tumour stage and poor survival. In vitro analysis revealed that UBE2L3 may promote hepatocyte proliferation and migration. RNA-seq analysis showed that UBE2L3 was inversely correlated with CDKN2B, a negative regulator of cell cycle, and CLDN1, loss of which may promote cancer metastasis. In conclusion, UBE2L3 may also be a susceptibility gene in HBV-related HCC, and it may promote HCC proliferation and migration by negatively regulating CDKN2B and CLDN1.
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Pan-cancer analysis of the role of α2C-adrenergic receptor (ADRA2C) in human tumors and validation in glioblastoma multiforme models.
Background: Several studies have reported the relationship between α2C-adrenergic receptor (ADRA2C) and both neoplastic and non-neoplastic diseases. However, a comprehensive pan-cancer analysis is currently lacking. Methods: Utilizing the RNA sequencing (RNA-seq) datasets from The Cancer Genome Atlas (TCGA) database, the roles of ADRA2C in human pan-cancer were analyzed through a variety of bioinformatics approaches, including R programming language and single-cell sequencing data analysis, et al. Besides, cell migration assay and immunochemistry were employed to further validate the role of ADRA2C in glioblastoma multiforme (GBM) cell lines and GBM mouse model. Results: A total of 33 cancer types were involved in this study. It was revealed that the expression level of ADRA2C varied across different clinical stages in patients with breast invasive carcinoma (BRCA), esophageal adenocarcinoma (ESCA), kidney renal papillary cell carcinoma (KIRP) and lung squamous cell carcinoma (LUSC). Meanwhile, it was found that ADRA2C may play roles in prognosis of adrenocortical carcinoma (ACC), glioblastoma multiforme and lower grade glioma (GBM-LGG), and uveal melanoma (UVM). Functional enrichment analysis suggested that ADRA2C expression level was highly correlated with neuronal system-related pathways. Moreover, ADRA2C may be a promising diagnostic marker for cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), cholangiocarcinoma (CHOL), GBM, GBMLGG, kidney chromophobe (KICH), and KIRP. Additionally, ADRA2C expression level was correlated with the levels of several infiltrating cells and immune checkpoint genes. Besides, the single-cell sequencing data analysis indicated that ADRA2C played a role in multiple tumor development processes in GBM, retinoblastoma (RB), and UVM. Finally, in vitro and in vivo experiments confirmed that the expression level of ADRA2C may be associated with glioma cell migration, apoptosis, and invasion. Conclusion: ADRA2C exhibited to play a notable role in several cancer types, suggesting that ADRA2C could serve as a promising biomarker or target for cancer diagnosis, prognosis, and treatment, particularly for GBM.
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A Single-Nucleus Resolution Atlas of Transcriptome and Chromatin Accessibility for Peanut (Arachis Hypogaea L.) Leaves.
The peanut is an important worldwide cash-crop for edible oil and protein. However, the kinetic mechanisms that determine gene expression and chromatin accessibility during leaf development in peanut represented allotetraploid leguminous crops are poorly understood at single-cell resolution. Here, a single-nucleus atlas of peanut leaves is developed by simultaneously profiling the transcriptome and chromatin accessibility in the same individual-cell using fluorescence-activated sorted single-nuclei. In total, 5930 cells with 50 890 expressed genes are classified into 18 cell-clusters, and 5315 chromatin fragments are enriched with 26 083 target genes in the chromatin accessible landscape. The developmental trajectory analysis reveals the involvement of the ethylene-AP2 module in leaf cell differentiation, and cell-cycle analysis demonstrated that genome replication featured in distinct cell-types with circadian rhythms transcription factors (TFs). Furthermore, dual-omics illustrates that the fatty acid pathway modulates epidermal-guard cells differentiation and providescritical TFs interaction networks for understanding mesophyll development, and the cytokinin module (LHY/LOG) that regulates vascular growth. Additionally, an AT-hook protein AhAHL11 is identified that promotes leaf area expansion by modulating the auxin content increase. In summary, the simultaneous profiling of transcription and chromatin accessibility landscapes using snRNA/ATAC-seq provides novel biological insights into the dynamic processes of peanut leaf cell development at the cellular level.