Prognostic and therapeutic model based on disulfidptosis-related genes for patients with clear cell renal cell carcinoma.

Disulfidptosis, a newly discovered mode of cell death caused by excessive accumulation of intracellular disulfide compounds, is closely associated with tumor development. This study focused on the relationship between disulfidptosis and clear cell renal cell carcinoma (ccRCC). Firstly, the characterizations of disulfidptosis-related genes (DRGs) in ccRCC were showed, which included number variation (CNV), single nucleotide variation (SNV), DNA methylation, mRNA expression and gene mutation.

ScRNA-seq revealed the tumor microenvironment heterogeneity related to the occurrence and metastasis in upper urinary tract urothelial carcinoma.

Metastasis is the greatest clinical challenge for UTUCs, which may have distinct molecular and cellular characteristics from earlier cancers. Herein, we provide single-cell transcriptome profiles of UTUC para cancer normal tissue, primary tumor lesions, and lymphatic metastases to explore possible mechanisms associated with UTUC occurrence and metastasis. From 28,315 cells obtained from normal and tumor tissues of 3 high-grade UTUC patients, we revealed the origin of UTUC tumor cells and the homology between metastatic and primary tumor cells.

Identification of a risk model for prognostic and therapeutic prediction in renal cell carcinoma based on infiltrating M0 cells.

The tumor microenvironment (TME) comprises immune-infiltrating cells that are closely linked to tumor development. By screening and analyzing genes associated with tumor-infiltrating M0 cells, we developed a risk model to provide therapeutic and prognostic guidance in clear cell renal cell carcinoma (ccRCC). First, the infiltration abundance of each immune cell type and its correlation with patient prognosis were analyzed.

T cell-mediated tumor killing based signature to predict the prognosis and immunotherapy for glioblastoma.

Despite the significant advancements in cancer treatment brought by immune checkpoint inhibitors (ICIs), their effectiveness in treating glioblastoma (GBM) remains highly dissatisfactory. Immunotherapy relies on the fundamental concept of T cell-mediated tumor killing (TTK). Nevertheless, additional investigation is required to explore its potential in prognostic prediction and regulation of tumor microenvironment (TME) in GBM.

miRNA-130a-3p/CPEB4 Axis Modulates Glioblastoma Growth and Progression.

Glioblastoma is the most frequent form of malignant brain tumor. Cytoplasmic polyadenylation element binding protein 4 (CPEB4) is overexpressed and involved in the tumorigenesis and metastasis of glioblastoma. miR-130a-3p has been revealed to be aberrantly expressed in tumors and has aroused wide attention.

A novel model based on disulfidptosis-related genes to predict prognosis and therapy of bladder urothelial carcinoma.

Purpose: Disulfidptosis is a novel type of cell death induced by disulphide stress that depends on the accumulation of cystine disulphide, causing cytotoxicity and triggering cell death. However, the direct prognostic effect and regulatory mechanism of disulfidptosis-related genes in bladder urothelial carcinoma (BLCA) remain unclear.

Methods: To explore the role of 10 disulfidptosis-related genes, the multiomic data of 10 genes were comprehensively analysed.

TGF-β based risk model to predict the prognosis and immune features in glioblastoma.

Background: Transforming growth factor-β (TGF-β) is a multifunctional cytokine with an important role in tissue development and tumorigenesis. TGF-β can inhibit the function of many immune cells, prevent T cells from penetrating into the tumor center, so that the tumor cells escape from immune surveillance and lead to low sensitivity to immunotherapy. However, its potential roles in predicting clinical prognosis and tumor microenvironment (TME) immune features need to be deeply investigated in glioblastoma (GBM).

Diagnostic markers and potential therapeutic agents for Sjögren's syndrome screened through multiple machine learning and molecular docking.

Primary Sjögren's syndrome (pSS) is a chronic inflammatory autoimmune disease, which mainly damages patients' exocrine glands. Sensitive early diagnostic indicators and effective treatments for pSS are lacking. Using machine learning methods to find diagnostic markers and effective therapeutic ways for pSS is of great significance.

Association between ABCB1 G2677T/A Polymorphism and Breast Cancer Risk: A Meta-Analysis.

Several studies have investigated the relationship between ABCB1 G2677T/A polymorphism and breast cancer susceptibility; however, the published results remain controversial. Thus, we conducted a meta-analysis to synthetically evaluate the association of this polymorphism with breast cancer risk. A computerized literature search was systematically carried out in PubMed, EMBASE, ScienceDirect, China National Knowledge Infrastructure and Wanfang Databases to identify the published case-control studies investigating the relationship between ABCB1 G2677T/A polymorphism and breast cancer risk.