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  • 1
    Online Resource
    Online Resource
    Identification of lipid metabolism-related biomarkers for diagnosis and molecular classification of atherosclerosis
    Springer Science and Business Media LLC ; 2023
    In:  Lipids in Health and Disease Vol. 22, No. 1 ( 2023-07-06)
    Details
    In: Lipids in Health and Disease, Springer Science and Business Media LLC, Vol. 22, No. 1 ( 2023-07-06)
    Abstract: Atherosclerosis is now the main cause of cardiac-cerebral vascular diseases around the world. Disturbances in lipid metabolism have an essential role in the development and progression of atherosclerosis. Thus, we aimed to investigate lipid metabolism-related molecular clusters and develop a diagnostic model for atherosclerosis. Methods First, we used the GSE100927 and GSE43292 datasets to screen differentially expressed lipid metabolism-related genes (LMRGs). Subsequent enrichment analysis of these key genes was performed using the Metascape database. Using 101 atherosclerosis samples, we investigated the LMRG-based molecular clusters and the corresponding immune cell infiltration. After that, a diagnostic model for atherosclerosis was constructed using the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression. Finally, a series of bioinformatics techniques, including CIBERSORT, gene set variation analysis, and single-cell data analysis, were used to analyze the potential mechanisms of the model genes in atherosclerosis. Results A total of 29 LMRGs were found to be differentially expressed between atherosclerosis and normal samples. Functional and DisGeNET enrichment analyses indicated that 29 LMRGs are primarily engaged in cholesterol and lipid metabolism, the PPAR signaling pathway, and regulation of the inflammatory response and are also closely associated with atherosclerotic lesions. Two LMRG-related molecular clusters with significant biological functional differences are defined in atherosclerosis. A three-gene diagnostic model containing ADCY7, SCD, and CD36 was subsequently constructed. Receiver operating characteristic curves, decision curves, and an external validation dataset showed that our model exhibits good predictive performance. In addition, three model genes were found to be closely associated with immune cell infiltration, especially macrophage infiltration. Conclusions Our study comprehensively highlighted the intricate association between lipid metabolism and atherosclerosis and created a three-gene model for future clinical diagnosis.
    Type of Medium: Online Resource
    ISSN: 1476-511X
    URL: Article
    DOI: 10.1186/s12944-023-01864-6
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2091381-3
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  • 2
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    Table_3.xlsx
    Frontiers Media SA ; 2023
    In:  Frontiers in Cardiovascular Medicine Vol. 9 ( 2023-1-6)
    Details
    In: Frontiers in Cardiovascular Medicine, Frontiers Media SA, Vol. 9 ( 2023-1-6)
    Abstract: Coronary artery disease (CAD) is a complex illness with unknown pathophysiology. Peripheral biomarkers are a non-invasive method required to track the onset and progression of CAD and have unbeatable benefits in terms of early identification, prognostic assessment, and categorization of the diagnosis. This study aimed to identify and validate the diagnostic and therapeutic potential of differentially expressed immune-related genes (DE-IRGs) in CAD, which will aid in improving our knowledge on the etiology of CAD and in forming genetic predictions. Methods First, we searched coronary heart disease in the Gene Expression Omnibus (GEO) database and identified GSE20680 (CAD = 87, Normal = 52) as the trial set and GSE20681 (CAD = 99, Normal = 99) as the validation set. Functional enrichment analysis using protein-protein interactions (PPIs), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) was carried out on the identified differentially expressed genes. Optimal feature genes (OFGs) were generated using the support vector machine recursive feature elimination algorithm and the least absolute shrinkage and selection operator (LASSO) algorithm. Furthermore, immune infiltration in CAD patients and healthy controls was compared using CIBERSORT, and the relationship between immune cells and OFGs was examined. In addition, we constructed potential targeted drugs for this model through the Drug-Gene Interaction database (DGIdb) database. Finally, we verify the expression of S100A8-dominated OFGs in the GSE20681 dataset to confirm the universality of our study. Results We identified the ten best OFGs for CAD from the DE-IRGs. Functional enrichment analysis showed that these marker genes are crucial for receptor-ligand activity, signaling receptor activator activity, and positive control of the response to stimuli from the outside world. Additionally, CIBERSORT revealed that S100A8 could be connected to alterations in the immune microenvironment in CAD patients. Furthermore, with the help of DGIdb and Cytoscape, a total of 64 medicines that target five marker genes were subsequently discovered. Finally, we verified the expression of the OFGs genes in the GSE20681 dataset between CAD patients and normal patients and found that there was also a significant difference in the expression of S100A8. Conclusion We created a 10-gene immune-related prognostic model for CAD and confirmed its validity. The model can identify potential biomarkers for CAD prediction and more accurately gauge the progression of the disease.
    Type of Medium: Online Resource
    ISSN: 2297-055X
    URL: Article
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    DOI: 10.3389/fcvm.2022.1055422
    DOI: 10.3389/fcvm.2022.1055422.s001
    DOI: 10.3389/fcvm.2022.1055422.s002
    DOI: 10.3389/fcvm.2022.1055422.s003
    DOI: 10.3389/fcvm.2022.1055422.s004
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2781496-8
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  • 3
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    Network pharmacology prediction and molecular docking-based strategy to discover the potential pharmacological mechanism of action of Wang Bu Liu Xing (Semen vaccariae) for colorectal cancer
    AME Publishing Company ; 2023
    In:  Journal of Gastrointestinal Oncology Vol. 14, No. 2 ( 2023-4), p. 504-515
    Details
    In: Journal of Gastrointestinal Oncology, AME Publishing Company, Vol. 14, No. 2 ( 2023-4), p. 504-515
    Type of Medium: Online Resource
    ISSN: 2078-6891 , 2219-679X
    URL: Journal
    URL: Article
    DOI: 10.21037/jgo
    DOI: 10.21037/jgo-23-83
    Language: Unknown
    Publisher: AME Publishing Company
    Publication Date: 2023
    detail.hit.zdb_id: 2594644-4
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  • 4
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    Table_1.docx
    Frontiers Media SA ; 2024
    In:  Frontiers in Nutrition Vol. 10 ( 2024-1-8)
    Details
    In: Frontiers in Nutrition, Frontiers Media SA, Vol. 10 ( 2024-1-8)
    Abstract: Numerous studies have reported sarcopenia to be associated with unfavorable outcomes in patients who have undergone pancreatectomy. Therefore, in this meta-analysis, we examined the relationship between sarcopenia and survival after pancreatic surgery. Methods PubMed, Embase, and Cochrane Library were searched for studies that examined the association between sarcopenia and survival after pancreatic surgery from the inception of the database until June 1, 2023. Hazard ratio (HR) for overall survival (OS) and/or progression-free survival (PFS) of sarcopenia and pancreatic surgery were extracted from the selected studies and random or fixed-effect models were used to summarize the data according to the heterogeneity. Publication bias was assessed using Egger’s linear regression test and a funnel plot. Results Sixteen studies met the inclusion criteria. For 13 aggregated univariate and 16 multivariate estimates, sarcopenia was associated with decreased OS (univariate analysis: HR 1.69, 95% CI 1.48–1.93; multivariate analysis: HR 1.69; 95% CI 1.39–2.05, I 2 = 77.4%). Furthermore, sarcopenia was significantly associated with poor PFS of pancreatic resection (Change to univariate analysis: HR 1.74, 95% CI 1.47–2.05; multivariate analysis: HR 1.54; 95% CI 1.23–1.93, I 2 = 63%). Conclusion Sarcopenia may be a significant prognostic factor for a shortened survival following pancreatectomy since it is linked to an elevated risk of mortality. Further studies are required to understand how sarcopenia affects long-term results after pancreatic resection. Systematic review registrationRegistration ID: CRD42023438208 https://www.crd.york.ac.uk/PROSPERO/#recordDetails .
    Type of Medium: Online Resource
    ISSN: 2296-861X
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fnut.2023.1315097
    DOI: 10.3389/fnut.2023.1315097.s001
    DOI: 10.3389/fnut.2023.1315097.s002
    DOI: 10.3389/fnut.2023.1315097.s003
    DOI: 10.3389/fnut.2023.1315097.s004
    DOI: 10.3389/fnut.2023.1315097.s005
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2024
    detail.hit.zdb_id: 2776676-7
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  • 5
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    Identification and immunological characterization of lipid metabolism-related molecular clusters in nonalcoholic fatty liver disease
    Springer Science and Business Media LLC ; 2023
    In:  Lipids in Health and Disease Vol. 22, No. 1 ( 2023-08-09)
    Details
    In: Lipids in Health and Disease, Springer Science and Business Media LLC, Vol. 22, No. 1 ( 2023-08-09)
    Abstract: Nonalcoholic fatty liver disease (NAFLD) is now the major contributor to chronic liver disease. Disorders of lipid metabolism are a major element in the emergence of NAFLD. This research intended to explore lipid metabolism-related clusters in NAFLD and establish a prediction biomarker. Methods The expression mode of lipid metabolism-related genes (LMRGs) and immune characteristics in NAFLD were examined. The “ConsensusClusterPlus” package was utilized to investigate the lipid metabolism-related subgroup. The WGCNA was utilized to determine hub genes and perform functional enrichment analysis. After that, a model was constructed by machine learning techniques. To validate the predictive effectiveness, receiver operating characteristic curves, nomograms, decision curve analysis (DCA), and test sets were used. Lastly, gene set variation analysis (GSVA) was utilized to investigate the biological role of biomarkers in NAFLD. Results Dysregulated LMRGs and immunological responses were identified between NAFLD and normal samples. Two LMRG-related clusters were identified in NAFLD. Immune infiltration analysis revealed that C2 had much more immune infiltration. GSVA also showed that these two subtypes have distinctly different biological features. Thirty cluster-specific genes were identified by two WGCNAs. Functional enrichment analysis indicated that cluster-specific genes are primarily engaged in adipogenesis, signalling by interleukins, and the JAK-STAT signalling pathway. Comparing several models, the random forest model exhibited good discrimination performance. Importantly, the final five-gene random forest model showed excellent predictive power in two test sets. In addition, the nomogram and DCA confirmed the precision of the model for NAFLD prediction. GSVA revealed that model genes were down-regulated in several immune and inflammatory-related routes. This suggests that these genes may inhibit the progression of NAFLD by inhibiting these pathways. Conclusions This research thoroughly emphasized the complex relationship between LMRGs and NAFLD and established a five-gene biomarker to evaluate the risk of the lipid metabolism phenotype and the pathologic results of NAFLD.
    Type of Medium: Online Resource
    ISSN: 1476-511X
    URL: Article
    DOI: 10.1186/s12944-023-01878-0
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2091381-3
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  • 6
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    Image8.JPEG
    Frontiers Media SA ; 2022
    In:  Frontiers in Genetics Vol. 13 ( 2022-9-12)
    Details
    In: Frontiers in Genetics, Frontiers Media SA, Vol. 13 ( 2022-9-12)
    Abstract: Both cuproptosis and necroptosis are typical cell death processes that serve essential regulatory roles in the onset and progression of malignancies, including low-grade glioma (LGG). Nonetheless, there remains a paucity of research on cuproptosis and necroptosis-related gene (CNRG) prognostic signature in patients with LGG. We acquired patient data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) and captured CNRGs from the well-recognized literature. Firstly, we comprehensively summarized the pan-cancer landscape of CNRGs from the perspective of expression traits, prognostic values, mutation profiles, and pathway regulation. Then, we devised a technique for predicting the clinical efficacy of immunotherapy for LGG patients. Non-negative matrix factorization (NMF) defined by CNRGs with prognostic values was performed to generate molecular subtypes (i.e., C1 and C2). C1 subtype is characterized by poor prognosis in terms of disease-specific survival (DSS), progression-free survival (PFS), and overall survival (OS), more patients with G3 and tumour recurrence, high abundance of immunocyte infiltration, high expression of immune checkpoints, and poor response to immunotherapy. LASSO-SVM-random Forest analysis was performed to aid in developing a novel and robust CNRG-based prognostic signature. LGG patients in the TCGA and GEO databases were categorized into the training and test cohorts, respectively. A five-gene signature, including SQSTM1, ZBP1, PLK1, CFLAR, and FADD, for predicting OS of LGG patients was constructed and its predictive reliability was confirmed in both training and test cohorts. In both the training and the test datasets (cohorts), higher risk scores were linked to a lower OS rate. The time-dependent ROC curve proved that the risk score had outstanding prediction efficiency for LGG patients in the training and test cohorts. Univariate and multivariate Cox regression analyses showed the CNRG-based prognostic signature independently functioned as a risk factor for OS in LGG patients. Furthermore, we developed a highly reliable nomogram to facilitate the clinical practice of the CNRG-based prognostic signature (AUC & gt; 0.9). Collectively, our results gave a promising understanding of cuproptosis and necroptosis in LGG, as well as a tailored prediction tool for prognosis and immunotherapeutic responses in patients.
    Type of Medium: Online Resource
    ISSN: 1664-8021
    URL: Article
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    DOI: 10.3389/fgene.2022.951239
    DOI: 10.3389/fgene.2022.951239.s001
    DOI: 10.3389/fgene.2022.951239.s002
    DOI: 10.3389/fgene.2022.951239.s003
    DOI: 10.3389/fgene.2022.951239.s004
    DOI: 10.3389/fgene.2022.951239.s005
    DOI: 10.3389/fgene.2022.951239.s006
    DOI: 10.3389/fgene.2022.951239.s007
    DOI: 10.3389/fgene.2022.951239.s008
    DOI: 10.3389/fgene.2022.951239.s009
    DOI: 10.3389/fgene.2022.951239.s010
    DOI: 10.3389/fgene.2022.951239.s011
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2606823-0
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  • 7
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    The combined signatures of the tumour microenvironment and nucleotide metabolism-related genes provide a prognostic and therapeutic biomarker for gastric cancer
    Springer Science and Business Media LLC ; 2023
    In:  Scientific Reports Vol. 13, No. 1 ( 2023-04-24)
    Details
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 13, No. 1 ( 2023-04-24)
    Abstract: The tumour microenvironment (TME) is vital to tumour development and influences the immunotherapy response. Abnormal nucleotide metabolism (NM) not only promotes tumour cell proliferation but also inhibits immune responses in the TME. Therefore, this study aimed to determine whether the combined signatures of NM and the TME could better predict the prognosis and treatment response in gastric cancer (GC). 97 NM-related genes and 22 TME cells were evaluated in TCGA-STAD samples, and predictive NM and TME characteristics were determined. Subsequent correlation analysis and single-cell data analysis illustrated a link between NM scores and TME cells. Thereafter, NM and TME characteristics were combined to construct an NM-TME classifier. Patients in the NMlow/TMEhigh group exhibited better clinical outcomes and treatment responses, which could be attributed to the differences in immune cell infiltration, immune checkpoint genes, tumour somatic mutations, immunophenoscore, immunotherapy response rate and proteomap. Additionally, the NMhigh/TMElow group benefited more from Imatinib, Midostaurin and Linsitinib, while patients in the NMlow/TMEhigh group benefited more from Paclitaxel, Methotrexate and Camptothecin. Finally, a highly reliable nomogram was developed. In conclusion, the NM-TME classifier demonstrated a pretreatment predictive value for prognosis and therapeutic responses, which may offer novel strategies for strategizing patients with optimal therapies.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    URL: Article
    DOI: 10.1038/s41598-023-33213-z
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2615211-3
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  • 8
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    Single-cell sequencing and bulk RNA sequencing reveal a cell differentiation-related multigene panel to predict the prognosis and immunotherapy response of hepatocellular carcinoma
    Ovid Technologies (Wolters Kluwer Health) ; 2023
    In:  Chinese Medical Journal Vol. 136, No. 4 ( 2023-02-1), p. 485-487
    Details
    In: Chinese Medical Journal, Ovid Technologies (Wolters Kluwer Health), Vol. 136, No. 4 ( 2023-02-1), p. 485-487
    Type of Medium: Online Resource
    ISSN: 0366-6999 , 2542-5641
    URL: Article
    DOI: 10.1097/CM9.0000000000002393
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2023
    detail.hit.zdb_id: 2108782-9
    SSG: 6,25
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