A costimulatory molecule-related signature in regard to evaluation of prognosis and immune features for clear cell renal cell carcinoma

Abstract

Costimulatory molecules have been proven to enhance antitumor immune responses, but their roles in clear cell renal cell carcinoma (ccRCC) remain unexplored. In this study, we aimed to explore the gene expression profiles of costimulatory molecule genes in ccRCC and construct a prognostic signature to improve treatment decision-making and clinical outcomes. We performed the first comprehensive analysis of costimulatory molecules in patients with ccRCC and identified 13 costimulatory molecule genes with prognostic values and diagnostic values. Consensus clustering analysis based on these 13 costimulatory molecular genes showed different distribution patterns and prognostic differences for the two clusters identified. Then, a costimulatory molecule-related signature was constructed based on these 13 costimulatory molecular genes, and validated in an external dataset, showing good performance for predicting a patient’s prognosis. The signature was an independent risk factor for ccRCC patients and was significantly correlated with patients’ clinical factors, which could be used as a complement for clinical factors. In addition, the signature was associated with the tumor immune microenvironment and the response to immunotherapy. Patients identified as high-risk based on our signature exhibited a high mutation frequency, a high level of immune cell infiltration, and an immunosuppressive microenvironment. High-risk patients tended to have high cytolytic activity scores and immunophenoscore of CTLA4 and PD1/PD-L1/PD-L2 blocker than low-risk patients, suggesting these patients may be more suitable for immunotherapy. Therefore, our signature could provide clinicians with prognosis predictions and help guide treatment for ccRCC patients.

Costimulatory molecule‐related lncRNA model as a potential prognostic biomarker in non‐small cell lung cancer

“…A recent study identified a high‐risk model to predict prognosis in LUAD patients based on costimulatory molecule signature genes from the cancer genome atlas (TCGA) and Gene Expression Omnibus profiles 12 . In addition, a prognosis‐related signature was developed for clear cell renal cell carcinoma, which included 13 costimulatory molecular genes from the TCGA database 9 . However, these studies only focused on costimulatory molecular genes.…”

“…Killer T cells are activated after the creation of a signal if a major histocompatibility complex on antigen‐presenting cell is distinguished by T cell receptors, followed by dispensing some costimulatory molecules to a second signal. 9 Costimulatory molecules are crucial in the activation of T cells. 10 The costimulatory molecules family consists of 61 cell‐surface molecules that regulate the T cell activation and tolerance.…”

Identification and validation a costimulatory molecule gene signature to predict the prognosis and immunotherapy response for hepatocellular carcinoma

“…There were no significantly differences in clinical characteristics between two sets (Table 1 ). Furthermore, a total of sixty costimulatory molecules genes (CMGs) were collected from prior reviews [ 21 , 22 ].…”

GPX4 is a potential biomarker and is associated with the diagnosis and treatment of diffuse large B lymphoma and B cell immune infiltration

“…In order to evaluate the prognostic role of GPX4 in DLBCL, we used R 4.2.1 to conduct Lasso Cox regional analysis on GSE10846 and GSE181063 to obtain GPX4 prognostic risk model data, and conducted univariate analysis [27]. Then the prognosis of DLBCL patients after treatment was evaluated by analyzing the high and low expression of GPX4 with KM curve, and then veri ed in TCGA dataset to evaluate the potential ability of GPX4 as a prognostic marker of DLBCL.…”