Identifying the mRNAs associated with Bladder cancer recurrence

The therapeutic potential of brazilin in bladder cancer: inhibition of DNA topoisomerase I and tumor growth suppression

This study aims to investigate the therapeutic effects of brazilin in the treatment of bladder cancer through the inhibition of DNA topoisomerase I (Topo 1) and to explore its underlying mechanisms. In vitro experiments were conducted using bladder cancer T24 cell line and in vivo experiments were performed using a bladder cancer mouse model. The effects of brazilin on cell proliferation, apoptosis, and DNA damage were evaluated. RT-qPCR and Western Blot analyses were used to assess the expression of Topo 1 mRNA and protein after treatment with brazilin. Additionally, tumor growth inhibition and potential side effects were evaluated in the animal model. Brazilin significantly inhibited bladder cancer cell proliferation and induced apoptosis and DNA damage in vitro. The expression of Topo 1 was downregulated at both the mRNA and protein levels, suggesting that brazilin exerts its effects by inhibiting Topo 1 activity. In vivo, brazilin markedly suppressed tumor growth in the bladder cancer mouse model, with no significant toxic effects observed. Brazilin shows potential as a therapeutic agent for bladder cancer by inhibiting Topo 1 activity, leading to suppressed tumor growth and cellular damage.  This study provides experimental evidence supporting the potential use of brazilin as a novel anticancer drug for bladder cancer treatment.

Identification of Biomarkers in Intracranial Aneurysm and Their Immune Infiltration Characteristics

BACKGROUND

Intracranial aneurysm (IA), known as the intracranial "unscheduled bomb," is one of the most dangerous cerebrovascular diseases, with unclear pathogenesis. This study aimed to show the mechanisms and identify the new biological targets by applying bioinformatics analysis.

METHODS

Expression profiling for control superficial temporal artery and IA walls in GSE26969 and GSE75436 datasets were downloaded. By executing the LIMMA package in R software, the differentially expressed genes (DEGs) were filtered, and the functional enrichments were consequently performed. Further cross-linking with the 2483 immune-related genes (IRGs) from the ImmPort database, the differentially expressed IRGs were identified. Based on them, the least absolute shrinkage and selection operator logistic regression and support vector machine-recursive feature elimination algorithms were used to screen the biomarkers, which were validated in the GSE54083 datasets. The CIBERSORT algorithm was applied to evaluate the infiltration of immune cells in tissues.

RESULTS

A total of 668 DEGs were obtained, and the functional enrichment suggested that they were closely related to the immune process. After intersecting them with the IRGs, 90 differentially expressed IRGs emerged, and ADIPOQ and ESM1 were identified as the biomarkers. Besides, we found that the infiltrated immune cells, such as the mast cells resting, might be associated with them.

CONCLUSIONS

We explored the contributing factors involving IA, which may generate a better understanding of the complex interactions among them and inspire a promising strategy for clinical works.

Association of Elevated Expression Levels of COL4A1 in Stromal Cells with an Immunosuppressive Tumor Microenvironment in Low-Grade Glioma, Pancreatic Adenocarcinoma, Skin Cutaneous Melanoma, and Stomach Adenocarcinoma

Aberrant expression of collagen type IV alpha chain 1 (COL4A1) can influence tumor cell behavior. To examine the association of COL4A1 expression in the tumor microenvironment (TME) with tumor progression, we performed bioinformatics analyses of The Cancer Genome Atlas RNA sequencing and RNA microarray datasets available in public databases and identified upregulated COL4A1 expression in most examined tumor types compared to their normal counterparts. The elevated expression of COL4A1 was correlated with low survival rates of patients with low-grade glioma, pancreatic adenocarcinoma, skin cutaneous melanoma, and stomach adenocarcinoma, thus suggesting its potential use as a biomarker for the poor prognosis of these tumors. However, COL4A1 was mostly expressed in adjacent stromal cells, such as cancer-associated fibroblasts (CAFs) and endothelial cells. Additionally, COL4A1 expression was highly correlated with the signatures of CAFs and endothelial cells in all four tumor types. The expression of marker genes for the infiltration of pro-tumoral immune cells, such as Treg, M2, and TAM, and those of immunosuppressive cytokines exhibited very strong positive correlations with COL4A1 expression. Collectively, our data suggest that COL4A1 overexpression in stromal cells may be a potential regulator of tumor-supporting TME composition associated with poor prognosis.

Development and Validation of a Three-Gene-Based Prognostic Model for Predicting the Overall Survival of Head and Neck Squamous Cell Carcinoma Through Bioinformatics Analysis

Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancer worldwide and seriously threats public health safety. Despite the improvement of diagnostic and treatment methods, the overall survival for advanced patients has not improved yet. This study aimed to sort out prognosis-related molecular biomarkers for HNSCC and establish a prognostic model to stratify the risk hazards and predicate the prognosis for these patients, providing a theoretical basis for the formulation of individual treatment plans. We firstly identified differentially expressed genes (DEGs) between HNSCC tissues and normal tissues via joint analysis based on GEO databases. Then a total of 11 hub genes were selected for single-gene prognostic analysis to identify the prognostic genes. Later, the clinical information and transcription information of HNSCC were downloaded from the TCGA database. With the application of least absolute shrinkage and selection operator (LASSO) algorithm analyses for the prognostic genes on the TCGA cohort, a prognostic model consisting of three genes (COL4A1, PLAU and ITGA5) was successfully established and the survival analyses showed that the prognostic model possessed a robust performance in the overall survival prediction. Afterward, the univariate and multivariate regression analysis indicated that the prognostic model could be an independent prognostic factor. Finally, the predicative efficiency of this model was well confirmed in an independent external HNSCC cohort.

The Highly Expressed IFIT1 in Nasopharyngeal Carcinoma Enhances Proliferation, Migration, and Invasion of Nasopharyngeal Carcinoma Cells

In this study, we aimed to identify potential targets modulating the progression of nasopharyngeal carcinoma (NPC) using integrated bioinformatics analysis and functional assays. Differentially expressed genes (DEGs) between NPC and normal tissues samples were obtained from publicly availably microarray datasets (GSE68799, GSE34573, and GSE53819) in the Gene Expression Omnibus (GEO) database. The bioinformatics analysis identified 49 common DEGs from three GEO datasets, which were mainly enriched in cytokine/chemokine pathways and extracellular matrix organization pathway. Further protein-protein interaction network analysis identified 11 hub genes from the 49 DEGs. The 11 hub genes were significantly up-regulated in the NPC tissues when compared to normal tissues by analyzing the Oncomine database. The 8 hub genes including COL5A1, COL7A1, COL22A1, CXCL11, IFI44L, IFIT1, RSAD2, and USP18 were significantly up-regulated in the NPC tissues when compared to normal tissues by using the Oncomine database. Further validation studies showed that IFIT1 was up-regulated in the NPC cells. Knockdown of IFI1T1 suppressed the proliferation, migration, and invasion of NPC cells; while IFIT1 overexpression promoted the proliferation, migration, and invasion of NPC cells. In conclusion, a total of 49 DEGs and 11 hub genes in NPC using the integrated bioinformatics analysis. IFIT1 was up-regulated in the NPC cells lines, and IFIT1 may act as an oncogene by promoting NPC cell proliferation, migration, and invasion.

Identification of a Hypoxia-Related Signature for Predicting Prognosis and the Immune Microenvironment in Bladder Cancer

Accumulating evidence indicates that hypoxia is highly associated with bladder cancer genesis, progression, and immune microenvironment. Nevertheless, few studies have identified the role of hypoxia-related genes as a prognostic signature in bladder cancer. This study aimed to establish a hypoxia-related signature with high accuracy for prognosis and immune microenvironment prediction in bladder cancer. We obtained expression profiles and clinical information from Gene Expression Omnibus and The Cancer Genome Atlas. Then the univariate Cox regression, random survival forest algorithm, and multivariate Cox regression analysis were conducted to identify the core genes and four hypoxia-related genes (ANXA2, GALK1, COL5A1, and HS3ST1) were selected to construct the signature. Kaplan-Meier survival analysis demonstrated that patients with a low-risk score had a higher disease-specific survival rate (p < 0.0001). The areas under the curve of the signature were 0.829 at 1 year, 0.869 at 3 years, and 0.848 at 5 years, respectively. Additionally, we found this hypoxia-related signature was highly correlated with tumor immune microenvironment and had the potential to predict the efficacy of immunotherapy. In summary, our study developed a hypoxia-related signature, which had high accuracy for prognosis prediction and the potential to guide the immunotherapy for bladder cancer patients.