Identification of a novel cuproptosis-related gene signature and integrative analyses in patients with lower-grade gliomas

Abstract

BackgroundCuproptosis is a newly discovered unique non-apoptotic programmed cell death distinguished from known death mechanisms like ferroptosis, pyroptosis, and necroptosis. However, the prognostic value of cuproptosis and the correlation between cuproptosis and the tumor microenvironment (TME) in lower-grade gliomas (LGGs) remain unknown.MethodsIn this study, we systematically investigated the genetic and transcriptional variation, prognostic value, and expression patterns of cuproptosis-related genes (CRGs). The CRG score was applied to quantify the cuproptosis subtypes. We then evaluated their values in the TME, prognostic prediction, and therapeutic responses in LGG. Lastly, we collected five paired LGG and matched normal adjacent tissue samples from Sun Yat-sen University Cancer Center (SYSUCC) to verify the expression of signature genes by quantitative real-time PCR (qRT-PCR) and Western blotting (WB).ResultsTwo distinct cuproptosis-related clusters were identified using consensus unsupervised clustering analysis. The correlation between multilayer CRG alterations with clinical characteristics, prognosis, and TME cell infiltration were observed. Then, a well-performed cuproptosis-related risk model (CRG score) was developed to predict LGG patients’ prognosis, which was evaluated and validated in two external cohorts. We classified patients into high- and low-risk groups according to the CRG score and found that patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group (P<0.001). A high CRG score implies higher TME scores, more significant TME cell infiltration, and increased mutation burden. Meanwhile, the CRG score was significantly correlated with the cancer stem cell index, chemoradiotherapy sensitivity–related genes and immune checkpoint genes, and chemotherapeutic sensitivity, indicating the association with CRGs and treatment responses. Univariate and multivariate Cox regression analyses revealed that the CRG score was an independent prognostic predictor for LGG patients. Subsequently, a highly accurate predictive model was established for facilitating the clinical application of the CRG score, showing good predictive ability and calibration. Additionally, crucial CRGs were further validated by qRT-PCR and WB.ConclusionCollectively, we demonstrated a comprehensive overview of CRG profiles in LGG and established a novel risk model for LGG patients’ therapy status and prognosis. Our findings highlight the potential clinical implications of CRGs, suggesting that cuproptosis may be the potential therapeutic target for patients with LGG.

Cuproptosis: mechanisms and links with cancers

“…Dihydrolipoamide Branched Chain Transacylase E2(DBT) catalyzed α-keto acid to acyl-CoA, which is thought to be associated with protective effects in both LUAD and cervical cancer(CC) patients [ 159 , 164 ]. Cytochrome c oxidase assembly factor 19(COX19) was involved in SCO1-dependent signaling essential for copper homeostasis [ 185 ], which was thought to be a risk factor in both gliomas and low-grade gliomas [ 140 , 142 ]. Pituitary tumor-transforming gene 1 protein(PTTG1), a key regulator of the p53/TP53 pathway and DNA repair, has been considered as a risk factor in studies of HCC by different investigators [ 133 , 135 ].…”

Identification and Validation of Cuproptosis Related Genes and Signature Markers in Bronchopulmonary Dysplasia Disease using Bioinformatics Analysis and Machine Learning

“…The expression matrix of BPD disease genes was obtained using perl language script, and the expression of copper death genes in the matrix was extracted from the corrected data to obtain the expression matrix of 19 CRGs (Bao et al, 2022). Based on the CRGs expression matrix, the "limma" package (Ritchie et al, 2015) was used to analyze the correlation between differential expression and CRGs between the experimental and control groups.…”

Iron-Sulfur Clusters: A Key Factor of Regulated Cell Death in Cancer

“…Iron-sulfur cluster proteins play a key role in cuproptosis and their homeostasis is involved in cuproptosis-dependent cancer therapy. Several recent studies have shown that cuproptosis-associated genes, including iron-sulfur clusters, are potential predictors of diagnostic, prognostic, and therapeutic response in some cancers and are associated with tumor microenvironment, immune response and immunotherapy [143][144][145][146][147].…”