Construction of 3D and 2D contrast-enhanced CT radiomics for prediction of CGB3 expression level and clinical prognosis in bladder cancer.

Objective: The purpose of this study was to construct a 3D and 2D contrast-enhanced computed tomography (CECT) radiomics model to predict CGB3 levels and assess its prognostic abilities in bladder cancer (Bca) patients.

Methods: Transcriptome data and CECT images of Bca patients were downloaded from The Cancer Imaging Archive (TCIA) and The Cancer Genome Atlas (TCGA) database. Clinical data of 43 cases from TCGA and TCIA were used for radiomics model evaluation.

Association of dietary carotenoid intake with the prevalence kidney stones among the general adult population.

Purpose: This study was to examine whether higher dietary carotenoid intake levels were associated with a lower prevalence of kidney stones.

Materials And Methods: This study analyzed data from 2007 to 2018 National Health and Nutrition Examination Survey (NHANES) project. Dietary carotenoid intake (α-carotene, β-carotene, β-cryptoxanthin, lycopene, and lutein/zeaxanthin) was assessed using two 24-h dietary recall interviews.

Advancements in the diagnosis and treatment of renal epithelioid angiomyolipoma: A narrative review.

Renal epithelioid angiomyolipoma (EAML) is a unique subtype of angiomyolipoma that contains a variety of cytoplasmic-rich, eosinophilic cytoplasm epithelioid cells in addition to mature adipocytes, hyaline thick-walled vessels, and smooth muscle-like spindle cells. In recent years, increasing evidence has shown that EAML is a potentially malignant tumor. Due to the lack of typical clinical manifestations and imaging features, it is difficult to diagnose before surgery, and the diagnosis mainly depends on postoperative histopathological examination.

Homologous Recombination Related Signatures Predict Prognosis and Immunotherapy Response in Metastatic Urothelial Carcinoma.

This study used homologous recombination (HR) related signatures to develop a clinical prediction model for screening immune checkpoint inhibitors (ICIs) advantaged populations and identify hub genes in advanced metastatic urothelial carcinoma. The single-sample gene enrichment analysis and weighted gene co-expression network analysis were applied to identify modules associated with immune response and HR in IMvigor210 cohort samples. The principal component analysis was utilized to determine the differences in HR-related module gene signature scores across different tissue subtypes and clinical variables.

The analysis of N6-methyladenosine regulators impacting the immune infiltration in clear cell renal cell carcinoma.

The tumor immune microenvironment (TIME) and N6-methyladenosine (m6A) are related to the progression of several types of cancer. Nevertheless, the impact of m6A on the TIME of clear cell renal cell carcinoma (ccRCC) remains unclear. This study used an unsupervised clustering algorithm to divide the samples into distinct subgroups.

A Bioinformatic Analysis of Immune-Related Prognostic Genes in Clear Cell Renal Cell Carcinoma Based on TCGA and GEO Databases.

Background: Clear cell renal cell carcinoma (ccRCC) is a commonly occurring tumor. Through a deeper understanding of the immune regulatory mechanisms in the tumor microenvironment, immunotherapy may serve as a potential treatment for cancer patients. This study aimed at identifying the survival-related immune cells and hub genes, which could be potential targets for immunotherapy in ccRCC.

Identification of potential biomarkers associated with immune infiltration in papillary renal cell carcinoma.

Background: Immunotherapeutic approaches have recently emerged as effective treatment regimens against various types of cancer. However, the immune-mediated mechanisms surrounding papillary renal cell carcinoma (pRCC) remain unclear. This study aimed to investigate the tumor microenvironment (TME) and identify the potential immune-related biomarkers for pRCC.

Construction of a novel mRNA-signature prediction model for prognosis of bladder cancer based on a statistical analysis.

Background: Bladder cancer (BC) is a common malignancy neoplasm diagnosed in advanced stages in most cases. It is crucial to screen ideal biomarkers and construct a more accurate prognostic model than conventional clinical parameters. The aim of this research was to develop and validate an mRNA-based signature for predicting the prognosis of patients with bladder cancer.

Identification of prognostic biomarkers associated with stromal cell infiltration in muscle-invasive bladder cancer by bioinformatics analyses.

Muscle-invasive bladder cancer (MIBC) is one of the common malignant tumors. Patients with MIBC still have high tumor recurrence and progression rates after surgery. Bioinformatics analysis of stromal infiltration-related genes in the tumor microenvironment (TME) of MIBC patients was performed in this study to determine the major stromal cells types and biomarkers for their progression and poor prognosis.