Biomolecular self-assembly provides a facile way to synthesize functional nanomaterials. Due to the unique structure and functions of biomolecules, the created biological nanomaterials via biomolecular self-assembly have a wide range of applications, from materials science to biomedical engineering, tissue engineering, nanotechnology, and analytical science. In this review, we present recent advances in the synthesis of biological nanomaterials by controlling the biomolecular self-assembly from adjusting internal interactions and external stimulations. The self-assembly mechanisms of biomolecules (DNA, protein, peptide, virus, enzyme, metabolites, lipid, cholesterol, and others) related to various internal interactions, including hydrogen bonds, electrostatic interactions, hydrophobic interactions, π–π stacking, DNA base pairing, and ligand–receptor binding, are discussed by analyzing some recent studies. In addition, some strategies for promoting biomolecular self-assembly via external stimulations, such as adjusting the solution conditions (pH, temperature, ionic strength), adding organics, nanoparticles, or enzymes, and applying external light stimulation to the self-assembly systems, are demonstrated. We hope that this overview will be helpful for readers to understand the self-assembly mechanisms and strategies of biomolecules and to design and develop new biological nanostructures or nanomaterials for desired applications.
ObjectiveTo evaluate whether pretreatment albumin−globulin ratio (AGR) can be used as a biomarker for predicting the prognosis of patients with urothelial carcinoma (UC).MethodsWe systematically searched PubMed, Web of Science, China National Knowledge Infrastructure (CNKI), Google Scholar and Cochrane Library; the search time was up to May 2022. Stata 16.0 was used for data processing and statistical analysis.ResultsWe identified 12 studies with 5,727 patients from 317 unique citations during the meta-analysis. Our results suggested that a low AGR before treatment was significantly associated with poor overall survival (OS) [hazard ratio (HR) = 1.99, 95% confidence interval (CI) = 1.45-2.75, P < 0.001], cancer-specific survival (CSS) [HR=2.01, 95% CI = 1.50-2.69, P < 0.001] and recurrence-free survival (RFS) [HR=1.39, 95% CI = 1.12-1.72, P = 0.002]. Furthermore, we defined different subgroups according to ethnicity, cancer type, cut-off value, sample size and stage. Similar prognostic outcomes for OS and CSS were observed in most subgroups. However, for subgroup of stage, the low pretreatment AGR only predicted the poor survival of patients with non-metastatic UC.ConclusionOur meta-analysis revealed that the AGR before treatment could be used as a predictive biomarker to indicate the prognosis of UC patients during clinical practice, especially in patients with non-metastatic UC.
BackgroundNumerous clinical studies have reported an association between the pretreatment albumin to globulin ratio (AGR) and survival outcomes of urological cancers. However, these conclusions remain controversial. Therefore, we performed a meta-analysis to explore the prognostic value of the AGR in urinary system tumors.MethodsWe retrieved eligible studies published up to June 2022 through a comprehensive search of multiple databases. Pooled hazard ratios (HRs) with 95% confidence intervals (CI) for overall survival (OS), cancer-specific survival (CSS), recurrence-free survival (RFS), progression-free survival (PFS), and biochemical recurrence-free survival (BRFS) were used to evaluated the predictive effect of the AGR before treatment in urinary system tumors. Heterogeneity test, random-effects models, fixed-effects models and sensitivity tests were used for analyses.ResultsA total of 21 studies with 18,269 patients were enrolled in our meta-analysis. We found that patients with urinary system cancer with low AGR prior to treatment had poor OS [HR = 1.93, 95% CI (1.56–2.39), p < 0.001], CSS [HR = 2.22, 95% CI (1.67–2.96), p < 0.001], RFS [HR = 1.69, 95% CI (1.29–2.22), p < 0.001], and PFS [HR = 1.29, 95% CI (0.54–3.07), p < 0.001]. For prostate cancer (PCa), a low pretreatment AGR was associated with poor BRFS [HR = 1.46, 95% CI (1.28–1.67), p < 0.001]. Also, a subgroup analysis, stratified by ethnicity, cancer type, cutoff value, sample size and publication year, was conducted. The results showed that worse OS and CSS were significantly associated with these factors.ConclusionOur meta-analysis revealed that the AGR before treatment could be used as a non-invasive predictive biomarker to evaluate the prognosis of urological cancer patients in clinical practice.
LncRNA TYMSOS plays an important role in cancers; However, its impact on prostate cancer (PCa) is still unclear. Thus, we analyzed the relationship between TYMSOS expression and PCa using the data from The Cancer Genome Atlas (TCGA) TCGA and Genotype Tissue-Expression (GTEx). Wilcoxon rank serum test and logistic regression were used to compare TYMSOS expression in PCa and normal tissues, and evaluated its correlation with clinicopathological features. Receiver operating characteristic (ROC) curves was used to evaluate the prediction accuracy of TYMSOS. Correlation between TYMSOS expression and prognosis was evaluated using Kaplan-Meier analysis and Cox regression. Gene Set Enrichment Analysis (GSEA), Gene Set Variation Analysis (GSVA) and ImmuCellAI platform were performed to determine biological function, signal pathways, and immune cell infiltration for TYMSOS in PCa. By analyzing the online data, we found that TYMSOS was highly expressed in PCa and associated with T stage , Gleason score, age, and primary therapy outcome. The results of ROC curve showed that TYMSOS has a significant diagnostic ability. Furthermore, Kaplan-Meier analyses suggested that TYMSOS plays an important role in progression-free survival (PFS). Increased TYMSOS expression was an independent risk factor correlated with PFS in PCa patients. GSEA and GSVA indicated that TYMSOS was involved in cell cycles, neurodegenerative diseases, oxidative phosphorylation, spliceosomes, and adaptive immune system pathways. Additionally, TYMSOS expression was also associated with immune cell infiltrates and tumor mutational burden in PCa. The functional experiments were further conducted, and we verified that TYMSOS played an oncogenic role in regulating PCa aggressiveness. Specifically, silencing of TYMSOS suppressed cell proliferation, division and epithelial-mesenchymal transition (EMT), whereas promoted cell apoptosis in the PCa cells, and conversely, TYMSOS overexpression had opposite effects. In summary, our study revealed that TYMSOS could be a biomarker and therapeutic targets in PCa and a participant in tumor-immune cell infiltration.
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