Objective To explore macrophage subpopulations in ischemic stroke (IS) by using single-cell RNA sequencing (scRNA-seq) data analysis and High-Dimensional Weighted Gene Co-Expression Network Analysis (hdWGCNA). Methods Based on single-cell sequencing data, transcriptomic information for different cell types was obtained, and macrophages were selected for subpopulation identification. hdWGCNA, cell-cell communication, and pseudotime trajectory analysis were used to explore the characteristics of macrophage subpopulations following IS. Key genes related to IS were identified using microarray data and validated for diagnostic potential through Receiver Operating Characteristic (ROC) analysis. Gene Set Enrichment Analysis (GSEA) was conducted to investigate the potential functions of these genes. Results The scRNA-seq data analysis revealed significant changes in macrophage subpopulation composition after IS. A specific macrophage subpopulation enriched in the stroke group was identified and designated as MCAO-specific macrophages (MSM). Pseudotime trajectory analysis indicated that MSM cells were in an intermediate stage of macrophage differentiation. Cell-cell communication analysis uncovered complex interactions between MSM cells and other cells, with the CCL6-CCR1 signaling axis potentially playing a crucial role in neuroinflammation. Two gene modules associated with MSM were identified via hdWGCNA, significantly enriched in pathways related to NOD-like receptors and antigen processing. By integrating differentially expressed MSM genes with conventional transcriptomic data, three IS-related hub genes were identified: Arg1, CLEC4D, and CLEC4E. Conclusion This study reveals the characteristics and functions of macrophage subpopulations following IS and identifies three hub genes with potential diagnostic value, providing novel insights into the pathological mechanisms of IS.
Macrophages/metabolism* ; Computational Biology/methods* ; Single-Cell Analysis/methods* ; Transcriptome ; Ischemic Stroke/metabolism* ; Animals ; Gene Regulatory Networks ; Gene Expression Profiling ; Humans ; Male

OBJECTIVE: To screen novel diagnostic marker or therapeutic target for multiple myeloma (MM). METHODS: Sel1L, SPAG4, KCNN3 and PARM1 were identified by bioinformatics method based on GEO database as high expression genes in MM. Their RNA and protein expression levels in bone marrow mononuclear cells from myeloma cell lines U266, NCI-H929, MM.1s, RPMI8226 and leukemia cell line THP1, as well as 31 MM patients were evaluated by RT-PCR and Western blot, respectively. Meanwhile, 5 samples of bone marrow from healthy donors for allogeneic hematopoietic stem cell transplantation were employed as controls. RESULTS: Compared with leukemia cell line THP1, the expression levels of KCNN3, PARM1 and Sel1L mRNA were significantly increased in myeloma cell lines U266, NCI-H929 and MM.1s, while PARM1 was further increased in myeloma cell lines 8226. Western blot showed that the 4 genes were all expressed in the 4 myeloma cell lines. Compared with healthy controls, the expression levels of Sel1L, SPAG4, KCNN3 and PARM1 mRNA were significantly higher in MM patients (all P < 0.05). Western blot showed that the 4 genes were all expressed in MM patients, and the protein expression level of Sel1L and KCNN3 were significantly different compared with healthy donors (all P < 0.01). CONCLUSION Sel1L, SPAG4, KCNN3 and PARM1 may be potential diagnostic markers and therapeutic targets for MM.
Humans ; Multiple Myeloma/genetics* ; Cell Line, Tumor ; Proteins/metabolism* ; Computational Biology ; RNA, Messenger/genetics*

OBJECTIVES: To identify potential molecular targets of quercetin in the treatment of clear cell renal carcinoma (ccRCC). METHODS: The therapeutic targets of quercetin were screened from multiple databases by network pharmacology analysis, and the targets significantly correlated with ccRCC were screened from 4907 plasma proteins using a Mendelian randomization method. The drug-disease network model was constructed to screen the potential key targets. The functions of these targets were evaluated via bioinformatics analysis, and the screened targets were verified in cultured ccRCC cells. RESULTS: Network pharmacology analysis combined with Mendelian randomization identified TP53 (OR=3.325, 95% CI: 1.805-6.124, P=0.0001), ARF4 (OR=0.173, 95% CI: 0.065-0.456, P=0.0003), and DPP4 (OR=0.463, 95% CI: 0.302-0.711, P=0.0004) as the core targets in quercetin treatment of ccRCC. Bioinformatics analysis showed that TP53 was highly expressed in ccRCC, and patients with high TP53 expressions had worse survival outcomes. Molecular docking studies showed that the binding energy between quercetin and TP53 was -5.83 kcal/mol. In cultured 786-O cells, CCK-8 assay and wound healing assay showed that treatment with quercetin significantly inhibited cell proliferation and migration. Quercetin treatment also strongly suppressed the expression of TP53 at both the mRNA and protein levels in 786-O cells as shown by RT-qPCR and Western blotting. CONCLUSIONS TP53 may be the key target of quercetin in the treatment of ccRCC, which sheds light on potential molecular mechanism that mediate the therapeutic effect of quercetin.
Humans ; Quercetin/pharmacology* ; Carcinoma, Renal Cell/genetics* ; Cell Proliferation/drug effects* ; Kidney Neoplasms/genetics* ; Cell Movement/drug effects* ; Tumor Suppressor Protein p53/metabolism* ; Cell Line, Tumor ; Computational Biology

OBJECTIVES: This study aimed to explore the biological functions and clinical value of mothers against decapentaplegic homolog (SMAD) 7 in head and neck squamous cell carcinoma (HNSCC) through bioinformatics analysis and basic experiments. METHODS: The expression of SMAD7 in HNSCC in public databases was studied. Western blot was used to detect the expression of SMAD7 in HNSCC cell lines and normal epithelial cells. The SMAD7 highly expressed HNSCC cell line HSC-4 was silenced, and CCK-8, Transwell assays, and cell scratch experiments were conducted to study the effect of SMAD7 on the biological functions of HSC-4 cells. HNSCC expression profile data were obtained from UCSC xena, and genes related to SMAD7 were selected for gene ontology and Kyoto encyclopedia of genes and genomes gene enrichment analysis, construction of a co-expression gene interaction network, and screening of related cell signaling pathways. Western blot was used to detect the expression changes of proteins in the related cell signaling pathways in HNSCC cells with silenced SMAD7. cBioPortal was utilized to analyze the mutation rate of the SMAD7 gene, and the MethSurv database was used to analyze the methylation level of the SMAD7 gene and its correlation with prognosis. The receiver operating characteristic curve was used to assess the diagnostic value of SMAD7 for HNSCC. TIMER2.0 was used to analyze the correlation between SMAD7 expression and immune cell infiltration. RESULTS: SMAD7 was highly expressed in HNSCC tumor tissues and some cell lines. Silencing the expression of SMAD7 can significantly inhibit the proliferation, migration, and invasion of cancer cells. Silencing SMAD7 can induce the downregulation of vascular cell adhesion molecule 1 (VCAM-1). The bioinformatics analysis showed that the mutation rate of the SMAD7 gene and the methylation level were significantly correlated with the prognosis of patients with HNSCC. The expression of SMAD7 was related to the level of immune cell infiltration in HNSCC. CONCLUSIONS SMAD7 promotes the proliferation, migration, and invasion of HNSCC cells by regulating the expression of VCAM-1. It may be a potential tumor biomarker and therapeutic target for HNSCC.
Humans ; Smad7 Protein/metabolism* ; Prognosis ; Squamous Cell Carcinoma of Head and Neck ; Head and Neck Neoplasms/pathology* ; Cell Line, Tumor ; Cell Movement ; Cell Proliferation ; Signal Transduction ; Gene Expression Regulation, Neoplastic ; Gene Silencing ; Computational Biology

The metabolic reactions in cells, whether spontaneous or enzyme-catalyzed, form a highly complex metabolic network closely related to cellular physiological metabolic activities. The reconstruction of cellular physiological metabolic network models aids in systematically elucidating the relationship between genotype and growth phenotype, providing important computational biology tools for precisely characterizing cellular physiological metabolic activities and green biomanufacturing. This paper systematically introduces the latest research progress in different types of cellular physiological metabolic network models, including genome-scale metabolic models (GEMs), kinetic models, and enzyme-constrained genome-scale metabolic models (ecGEMs). Additionally, our paper discusses the advancements in the automated construction of GEMs and strategies for condition-specific GEM modeling. Considering artificial intelligence offers new opportunities for the high-precision construction of cellular physiological metabolic network models, our paper summarizes the applications of artificial intelligence in the development of kinetic models and enzyme-constrained models. In summary, the high-quality reconstruction of the aforementioned cellular physiological metabolic network models will provide robust computational support for future research in quantitative synthetic biology and systems biology.
Metabolic Networks and Pathways/physiology* ; Models, Biological ; Artificial Intelligence ; Systems Biology ; Kinetics ; Cell Physiological Phenomena ; Computational Biology ; Synthetic Biology ; Humans

How to improve the performance of circulating tumor DNA (ctDNA) signal acquisition and the accuracy to authenticate ultra low-frequency mutation are major challenges of minimal residual disease (MRD) detection in solid tumors. In this study, we developed a new MRD bioinformatics algorithm, namely multi-variant joint confidence analysis (MinerVa), and tested this algorithm both in contrived ctDNA standards and plasma DNA samples of patients with early non-small cell lung cancer (NSCLC). Our results showed that the specificity of multi-variant tracking of MinerVa algorithm ranged from 99.62% to 99.70%, and when tracking 30 variants, variant signals could be detected as low as 6.3 × 10 ^-5 variant abundance. Furthermore, in a cohort of 27 NSCLC patients, the specificity of ctDNA-MRD for recurrence monitoring was 100%, and the sensitivity was 78.6%. These findings indicate that the MinerVa algorithm can efficiently capture ctDNA signals in blood samples and exhibit high accuracy in MRD detection.
Humans ; Carcinoma, Non-Small-Cell Lung/genetics* ; Lung Neoplasms/genetics* ; Neoplasm, Residual/pathology* ; Biomarkers, Tumor/genetics* ; Computational Biology

Humans ; Immunoblastic Lymphadenopathy/pathology* ; Lymphoma, T-Cell, Peripheral/pathology* ; Molecular Biology

Objective To investigate the role and mechanism of circ_0092315 in the proliferation and invasion of papillary thyroid carcinoma cells. Methods The expression of circ_0092315 in papillary thyroid carcinoma cells was examined by real-time fluorescence quantitative PCR.The proliferation and invasion of TPC-1 cells was assessed by CCK-8 and Transwell assays.The protein level of high mobility group A2 (HMGA2) was determined by Western blotting.The regulatory relationship of circ_0092315,microRNA-1256 (miR-1256),and HMGA2 was explored by bioinformatics tools,dual-luciferase reporter assay,real-time fluorescence quantitative PCR,and Western blotting. ++++Results circ_0092315 was overexpressed in papillary thyroid carcinoma cells (all P<0.001).circ_0092315 promoted the proliferation and invasion of TPC-1 cells (all P<0.001).The transfection of si-circ_0092315 up-regulated the expression of miR-1256 (P<0.001),and miR-1256 inhibitor up-regulated the protein level of HMGA2 (P<0.001). ++++Conclusion circ_0092315 is overexpressed in TPC-1 cells and it promotes the proliferation and invasion of TPC-1 cells by regulating the miR-1256/HMGA2 axis.
Humans ; Thyroid Cancer, Papillary/genetics* ; Computational Biology ; Thyroid Neoplasms/genetics* ; Cell Proliferation ; MicroRNAs/genetics*

Tunneling nanotube (TNT) is a newly discovered communication mode between animal cells in recent years, which have important physiological and pathological significance. However, the role of TNT in bone biology is still unclear. At present, there are many reports about tunneling nanotubes in bone marrow mesenchymal stem cells, osteoclast precursor cells, osteoblasts and immune cells. This review describes the research advances of TNT and its research progress in bone biology. It looks forward to the research direction of TNT in oral and maxillofacial bone development and bone biology, to provide new strategies for the maintenance of bone homeostasis and the treatment of bone diseases.
Animals ; Bone and Bones ; Nanotubes ; Osteoclasts ; Biology ; Cell Communication/physiology*

Objective: To investigate the clinicopathological features, molecular genetic features, differential diagnosis and prognosis of ELOC mutated renal cell carcinoma. Methods: From January 2015 to June 2022, 11 cases of renal cell carcinoma with clear-cell morphology, expression of CAⅨ and CK7 and no 3p deletion were collected. Two cases of ELOC mutant renal cell carcinoma were diagnosed using whole exome sequencing (WES). The clinical features, morphology, immunophenotype, FISH and WES results were analyzed. The relevant literature was reviewed. Results: The two patients were both male, aged 29 and 51 years, respectively. They were both found to have a renal mass by physical examination. The maximum diameters of the tumors were 3.5 cm and 2.0 cm, respectively. At the low magnification, the tumors were well-defined. The tumor cells showed a pushing border and were separated by thick fibrous bands, forming nodules. The tumor cells were arranged in a variety of patterns, including tubular, papillary, solid nest or alveolar. At high magnification, the tumor cells were large, with well-defined cell borders and clear cytoplasm or fine eosinophilic granules. CAⅨ was diffusely box-like positive in both cases. Case 1 was partially and moderately positive for CK7, strongly positive for CD10, diffusely and moderately positive for P504S, and weakly positive for 34βE12. In case 2, CK7 and CD10 were both partially, moderately positive and P504s were diffusely positive, but 34βE12 was negative. FISH results showed that both cases had no 3p deletion. ELOC c.235T>A (p.Y79N) mutation was identified using WES in case 1, while ELOC c.236_237inv (p.Y79C) mutation was identified in case 2. Conclusions: As a new clinical entity, ELOC mutated renal cell carcinoma may be underdiagnosed due to its overlap with clear cell renal cell carcinoma in morphology and immunophenotype. The diagnosis of renal cell carcinoma with ELOC mutation should be confirmed by morphology, immunohistochemistry, FISH and gene mutation detection. However, more additional cases are needed to explain its biological behavior and prognosis.
Humans ; Male ; Biomarkers, Tumor/genetics* ; Carcinoma, Renal Cell/pathology* ; Chromosome Aberrations ; Kidney Neoplasms/pathology* ; Molecular Biology ; Mutation ; Prognosis