Pyroptosis is defined as an inflammatory form of programmed cell death. Increasing studies have demonstrated that pyroptosis is closely related to tumor development and antitumor process. However, the role of pyroptosis in kidney renal papillary cell carcinoma (KIRP) remains obscure. In this study, we analyzed the expression of 52 pyroptosis-related genes (PRGs) in KIRP, of which 20 differentially expressed PRGs were identified between tumor and normal tissues. Consensus clustering analysis based on these PRGs was used to divided patients into two clusters, from which a significant difference in survival was found ( = 0.0041). The prognostic risk model based on six PRGs (, , , , , and ) was built using univariate Cox regression and LASSO-Cox regression analysis, with good performance in predicting one-, three-, and five-year overall survival. Kaplan-Meier survival analysis showed that the high-risk group had a poor survival outcome ( < 0.001) and risk score was an independent prognostic factor (HR: 2.655, 95% CI 1.192-5.911, = 0.016). Immune profiling revealed differences in immune cell infiltration between the two groups, and the infiltration of M2 macrophages was significantly upregulated in the tumor immune microenvironment, implying that tumor immunity participated in the KIRP progression. Finally, we identified two hub genes in tumor tissues ( and ), which were validated In conclusion, we conducted a comprehensive analysis of PRGs in KIRP and tried to provide a pyroptosis-related signature for predicting the prognosis.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8984942PMC
http://dx.doi.org/10.3389/fgene.2022.851384DOI Listing

Publication Analysis

Top Keywords

signature predicting
8
predicting prognosis
8
kidney renal
8
renal papillary
8
papillary cell
8
cell carcinoma
8
prgs kirp
8
based prgs
8
tumor
5
prgs
5

Similar Publications

Purpose: We aimed to identify the transcriptomic signatures of soft tissue sarcoma (STS) related to radioresistance and establish a model to predict radioresistance.

Materials And Methods: Nine STS cell lines were cultured. Adenosine triphosphate-based viability was determined 5 days after irradiation with 8 Gy of X-rays in a single fraction.

View Article and Find Full Text PDF

Endosomes play a pivotal role in cellular biology, orchestrating processes such as endocytosis, molecular trafficking, signal transduction, and recycling of cellular materials. This study aims to construct an endosome-related gene (ERG)-derived risk signature for breast cancer prognosis. Transcriptomic and clinical data were retrieved from The Cancer Genome Atlas and the University of California Santa Cruz databases to build and validate the model.

View Article and Find Full Text PDF

Growing evidence has demonstrated the association between necroptosis and tumorigenesis and immunotherapy. However, the influence of overall necroptosis related genes on prognosis and immune microenvironment of breast cancer is still unclear. In this study, We systematically analyzed the necroptosis related gene patterns and tumor microenvironment characteristics of 1294 breast cancer patients by clustering the gene expression of 22 necroptosis related genes.

View Article and Find Full Text PDF

Purpose: To detect the prognostic importance of liquid-liquid phase separation (LLPS) in lung adenocarcinoma.

Methods: The gene expression files, copy number variation data, and clinical data were downloaded from The Cancer Genome Atlas cohort. LLPS-related genes were acquired from the DrLLPS website.

View Article and Find Full Text PDF

Introduction: Molecular recognition features (MoRFs) are regions in protein sequences that undergo induced folding upon binding partner molecules. MoRFs are common in nature and can be predicted from sequences based on their distinctive sequence signatures.

Areas Covered: We overview twenty years of progress in the sequence-based prediction of MoRFs which resulted in the development of 25 predictors of MoRFs that interact with proteins, peptides and lipids.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!