Analysis of cuproptosis-related genes in prognosis and immune infiltration in grade 4 diffuse gliomas
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SUBMITTER: Liu H
PROVIDER: S-EPMC11021980 | biostudies-literature | 2024 Apr
REPOSITORIES: biostudies-literature
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Project description:Although angiogenesis critically influences the progression of solid tumors, its contribution to highly malignant, grade 4 diffuse gliomas remains unclear. After analyzing 506 angiogenesis-related genes differentially expressed in grade 4 diffuse gliomas via LASSO and univariate and multivariate COX regression analyses, we constructed a nomogram based on COL22A1, IGFBP2, and MPO that accurately predicted patient survival. The nomogram's performance was validated in an external patient cohort, and a risk score based on the formula COL22A1*0.148+IGFBP2*0.234+MPO*0.145 was used to distinguish high-risk from low-risk patients. Based on differentially expressed genes among risk groups, functional enrichment and drug sensitivity analyses were conducted, and the association between COL22A1, IGFBP2, and MPO expression and infiltrating immune cells and immune checkpoint genes was investigated. We next focused on COL22A1, and verified its overexpression in both glioma cell lines and clinical samples. A pro-oncogenic role for COL22A1, evidenced by impaired proliferation, migration, and invasion capacities, was evidenced upon shRNA-mediated COL22A1 silencing in glioma U87 and LN18 cells. In summary, we present a novel nomogram based on the angiogenesis-related genes COL22A1, IGFBP2, and MPO that allows survival prediction in patients with grade 4 diffuse gliomas. Furthermore, our cellular assays support a pro-oncogenic role for COL22A1 in these tumors.
| S-EPMC10564429 | biostudies-literature
Project description:Skin cutaneous melanoma (SKCM, hereafter referred to as melanoma) is the most lethal skin cancer with increasing incidence. Regulated cell death plays an important role in tumorigenesis and serves as an important target for almost all treatment strategies. Cuproptosis is the most recently identified copper-dependent regulated cell death form that relies on mitochondria respiration. However, its role in tumorigenesis remains unknown. The correlation of cuproptosis-related genes with tumor prognosis is far to be understood, either. In the present study, we explored the correlation between cuproptosis-related genes with the prognosis of melanoma by accessing and analyzing a public database and found 11 out 12 genes were upregulated in melanoma tissues and three genes (LIPT1, PDHA1, and SLC31A1) have predictive value for the prognosis. The subgroup of melanoma patients with higher cuproptosis-related gene expression showed longer overall survival than those with lower gene expression. We chose LIPT1 for further exploration. LIPT1 expression was increased in melanoma biopsies and was an independent favorable prognostic indicator for melanoma patients. Moreover, LIPT1 expression was positively correlated with PD-L1 expression and negatively associated with Treg cell infiltration. The melanoma patients with higher LIPT1 expression showed longer overall survival than those with lower LIPT1 expression after receiving immunotherapy, indicating the prognostic predictive value of LIPT1. Finally, a pan-cancer analysis indicated that LIPT1 was differentially expressed in diverse cancers as compared to normal tissues and correlated with the expression of multiple immune checkpoints, especially PD-L1. It could serve as a favorable prognosis indicator in some cancer types. In conclusion, our study demonstrated the prognostic value of cuproptosis-related genes, especially LIPT1, in melanoma, and revealed the correlation between LIPT1 expression and immune infiltration in melanoma, thus providing new clues on the prognostic assessment of melanoma patients and providing a new target for the immunotherapy of melanoma.
| S-EPMC9273972 | biostudies-literature
Project description:BackgroundEvidence has revealed a connection between cuproptosis and the inhibition of tumor angiogenesis. While the efficacy of a model based on cuproptosis-related genes (CRGs) in predicting the prognosis of peripheral organ tumors has been demonstrated, the impact of CRGs on the prognosis and the immunological landscape of gliomas remains unexplored.MethodsWe screened CRGs to construct a novel scoring tool and developed a prognostic model for gliomas within the various cohorts. Afterward, a comprehensive exploration of the relationship between the CRG risk signature and the immunological landscape of gliomas was undertaken from multiple perspectives.ResultsFive genes (NLRP3, ATP7B, SLC31A1, FDX1, and GCSH) were identified to build a CRG scoring system. The nomogram, based on CRG risk and other signatures, demonstrated a superior predictive performance (AUC of 0.89, 0.92, and 0.93 at 1, 2, and 3 years, respectively) in the training cohort. Furthermore, the CRG score was closely associated with various aspects of the immune landscape in gliomas, including immune cell infiltration, tumor mutations, tumor immune dysfunction and exclusion, immune checkpoints, cytotoxic T lymphocyte and immune exhaustion-related markers, as well as cancer signaling pathway biomarkers and cytokines.ConclusionThe CRG risk signature may serve as a robust biomarker for predicting the prognosis and the potential viability of immunotherapy responses. Moreover, the key candidate CRGs might be promising targets to explore the underlying biological background and novel therapeutic interventions in gliomas.
| S-EPMC11220998 | biostudies-literature
Project description:IntroductionBreast cancer (BC) has been ranking first in incidence and the leading cause of death among female cancers worldwide based on the latest report. Regulated cell death (RCD) plays a significant role in tumor initiation and provides an important target of cancer treatment. Cuproptosis, a novel form of RCD, is ignited by mitochondrial stress, particularly the lipoylated mitochondrial enzymes aggregation. However, the role of cuproptosis-related genes (CRGs) in tumor generation and progression remains unclear.MethodsIn this study, the mRNA expression data of CRGs in BC and normal breast tissue were extracted from TCGA database, and protein expression patterns of these CRGs were analyzed using UALCAN. The prognostic values of CRGs in BC were explored by using KaplanMeier plotter and Cox regression analysis. Genetic mutations profiles were evaluated using the cBioPortal database. Meanwhile, we utilized CIBERSORT and TIMER 2.0 database to perform the correlation analysis between CRGs and immune cell infiltration.ResultsOur results indicated that CRGs expression is significantly different in BC and normal breast tissues. Then we found that upregulated PDHA1 expression was associated with worse endpoint of BC. Moreover, we also performed immune infiltration analysis of CRGs, and demonstrated that PDHA1 expression was closely related to the infiltration levels of CD4+ memory T cell, macrophage M0 and M1 cell and mast cell in BC.ConclusionsOur results demonstrated the prognostic and immunogenetic values of PDHA1 in BC. Therefore, PDHA1 can be an independent prognostic biomarker and potential target for immunotherapy of BC.
| S-EPMC9742524 | biostudies-literature
Project description:Osteosarcoma (OS) is one of the most prevalent primary bone tumors at all ages of human development. The objective of our study was to develop a model of Cuproptosis-Related Genes (CRGs) for predicting prognosis in OS patients. All datasets of OS patients were obtained from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database and Gene Expression Omnibus (GEO) database. We obtained the gene set (81 CRGs) related to cuproptosis by accessing the database and previous literature. All the CRGs were analyzed by univariate COX regression, least absolute shrinkage and selection operator (LASSO) COX regression analysis to screen for CRGs associated with prognosis in OS patients. Then these CRGs were used to construct a prognostic signature, which was further verified by independent cohort (GSE21257) and clinical correlation analysis. Afterward, to identify underlying mechanisms, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used for the high-risk group by using the GSEA method. The association between the prognostic signature and 28 types of immune infiltrating cells in the tumor microenvironment was assessed. Ultimately, Lipoic Acid Synthetase (LIAS) (HR=0.632, P=0.004), Lipoyltransferase 1 (LIPT1) (HR=0.524, P=0.011), BCL2 Like 1 (BCL2L1/BCL-XL) (HR=0.593, P=0.022), and Pyruvate Dehydrogenase Kinase 1 (PDK1) (HR=0.662, P=0.025) were identified. Subsequently, they were used to calculate the risk score and build a prognostic model. In the training cohort, risk score (HR=1.878, P=0.003) could be considered as an independent prognostic factor, and OS patients with high-risk scores showed lower survival rates. Biological pathways related to substance metabolism and transport were enriched. There were significant differences in immune infiltrating cells in the tumor microenvironment. All in all, The CRGs signature is related to the tumor immune microenvironment and could be used as a credible predictor of the prognostic status in OS patients.
| S-EPMC9582135 | biostudies-literature
Project description:BackgroundCuproptosis is a recently discovered form of nonapoptotic programmed cell death. However, no research on cuproptosis in the context of adrenocortical carcinoma has been conducted, and the prognostic value of assessing cuproptosis remains unclear.MethodsIn this study, we established comprehensive models to assess gene expression changes, mutation status, and prognosis prediction and developed a prognostic nomogram for cuproptosis-related genes. Using data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Genotype-Tissue Expression (GTEx) databases, an analysis of 11 cuproptosis-related genes was performed. Additionally, a risk scoring method and nomogram were used to assess the relationships among cuproptosis-associated genes, transcript expression, clinical characteristics, and prognosis. The connections among tumors, immune checkpoints, and immune infiltration were also analyzed.ResultsThe patterns observed in patients with adrenocortical carcinoma who were assessed using cuproptosis-associated risk scores provide useful information for understanding gene mutations, clinical outcomes, immune cell infiltration, and immune checkpoint analysis results. FDX1, LIPT1, MTF1, COX11, CYP2D6, DLAT, ATP7Band CDKN2A were differentially expressed in patients with adrenocortical carcinoma and normal controls. In addition, higher risk scores were significantly associated with poor overall survival and progression-free interval. The nomogram model subsequently developed to facilitate the clinical application of the analysis showed good predictive and calibration capabilities. GSE10927 and GSE33371 were used for independent cohort validation. Moreover, CDKN2A, FDX1, and other cuproptosis-related genes were significantly associated with immune infiltration and checkpoints.ConclusionWe confirmed that our model had excellent predictive ability in patients with adrenocortical carcinoma. Therefore, an in-depth evaluation of patients using cuproptosis-related risk scores is clinically essential and can assist in therapy in the future.
| S-EPMC10767392 | biostudies-literature
Project description:BackgroundImmune infiltration plays an important role in the course of ischemic stroke (IS) progression. Cuproptosis is a newly discovered form of programmed cell death. To date, no studies on the mechanisms by which cuproptosis-related genes regulate immune infiltration in IS have been reported.MethodsIS-related microarray datasets were retrieved from the Gene Expression Omnibus (GEO) database and standardized. Immune infiltration was extracted and quantified based on the processed gene expression matrix. The differences between the IS group and the normal group as well as the correlation between the infiltrating immune cells and their functions were analyzed. The cuproptosis-related DEGs most related to immunity were screened out, and the risk model was constructed. Finally, Gene Ontology (GO) function, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and drug target were performed using the Enrichr website database. miRNAs were predicted using FunRich software. Finally, cuproptosis-related differentially expressed genes (DEGs) in IS samples were typed, and Gene Set Variation Analysis (GSVA) was used to analyze the differences in biological functions among the different types.ResultsSeven Cuproptosis-related DEGs were obtained by merging the GSE16561 and GSE37587 datasets. Correlation analysis of the immune cells showed that NLRP3, NFE2L2, ATP7A, LIPT1, GLS, and MTF1 were significantly correlated with immune cells. Subsequently, these six genes were included in the risk study, and the risk prediction model was constructed to calculate the total score to analyze the risk probability of the IS group. KEGG analysis showed that the genes were mainly enriched in the following two pathways: D-glutamine and D-glutamate metabolism; and lipids and atherosclerosis. Drug target prediction found that DMBA CTD 00007046 and Lithocholate TTD 00009000 were predicted to have potential therapeutic effects of candidate molecules. GSVA showed that the TGF-β signaling pathway and autophagy regulation pathways were upregulated in the subgroup with high expression of cuproptosis-related DEGs.ConclusionsNLRP3, NFE2L2, ATP7A, LIPT1, GLS and MTF1 may serve as predictors of cuproptosis and play an important role in the pathogenesis of immune infiltration in IS.
| S-EPMC9933552 | biostudies-literature
Project description:DLAT has been recognized as a cuproptosis-related gene that is crucial for cuproptosis in earlier research. The study is to look at how DLAT affects individuals with low-grade glioma's prognosis and immune infiltration. The Genotype-Tissue Expression (GTEx) database and the TCGA database were used in this work to download RNAseq data in TPM format. DLAT was found to be overexpressed in LGG by comparing DLAT expression levels between LGG and normal brain tissue, and the expression of DLAT was verified by immunohistochemistry and semi-quantitative analysis. Then, the functional enrichment analysis revealed that the biological functional pathways and possible signal transduction pathways involved were primarily focused on extracellular matrix organization, transmembrane transporter complex, ion channel complex, channel activity, neuroactive ligand-receptor interaction, complement and coagulation cascades, and channel activity. The level of immune cell infiltration by plasmacytoid dendritic cells and CD8 T cells was subsequently evaluated using single-sample gene set enrichment analysis, which showed that high DLAT expression was inversely connected with that level of infiltration. The link between the methylation and mRNA transcription of DLAT was then further investigated via the MethSurv database, and the results showed that DLAT's hypomethylation status was linked to a poor outcome. Finally, by evaluating the prognostic value of DLAT using the Cox regression analysis and Kaplan-Meier technique, a column line graph was created to forecast the overall survival (OS) rate at 1, 3, and 5 years after LGG identification. The aforementioned results demonstrated that high DLAT expression significantly decreased OS and DSS, and that overexpression of DLAT in LGG was significantly linked with WHO grade, IDH status, primary therapy outcome, overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) events. DLAT was discovered as a separate predictive sign of OS in the end. DLAT might thus represent a brand-new predictive biomarker.
| S-EPMC11219321 | biostudies-literature
Project description:BACKGROUNDLower-grade gliomas (LGGs) vary widely in terms of the patient's overall survival (OS). There is no current, valid method that could exactly predict the survival. The effects of intratumoral immune infiltration on clinical outcome have been widely reported. Thus, we aim to develop an immune infiltration signature to predict the survival of LGG patients.METHODSWe analyzed 1216 LGGs from 5 public data sets, including 2 RNA sequencing data sets and 3 microarray data sets. Least absolute shrinkage and selection operator (LASSO) Cox regression was used to select an immune infiltration signature and build a risk score. The performance of the risk score was assessed in the training set (329 patients), internal validation set (140 patients), and 4 external validation sets (405, 118, 88, and 136 patients).RESULTSAn immune infiltration signature consisting of 20 immune metagenes was used to generate a risk score. The performance of the risk score was thoroughly verified in the training and validation sets. Additionally, we found that the risk score was positively correlated with the expression levels of TGF-β and PD-L1, which were important targets of combination immunotherapy. Furthermore, a nomogram incorporating the risk score, patient's age, and tumor grade was developed to predict the OS, and it performed well in all the training and validation sets (C-index: 0.873, 0.881, 0.781, 0.765, 0.721, and 0.753).CONCLUSIONThe risk score based on the immune infiltration signature has reliable prognostic and predictive value for patients with LGGs and is a potential biomarker for the cotargeting immunotherapy.FUNDINGThis work was supported by The National Natural Science Foundation of China (grant nos. 81472370 and 81672506), the Natural Science Foundation of Beijing (grant no. J180005), the National High Technology Research and Development Program of China (863 Program, grant no. 2014AA020610), and the National Basic Research Program of China (973 Program, grant no. 2014CB542006).
| S-EPMC7205440 | biostudies-literature
Project description:BackgroundBeing among the most common malignancies worldwide, hepatocellular carcinoma (HCC) accounting for the third cause of cancer mortality. The regulation of cell death is the most crucial step in tumor progression and has become a crucial target for nearly all therapeutic options. Cuproptosis, a copper-induced cell death, was recently reported in Science. However, its primary function in carcinogenesis is still unclear.MethodsCuproptosis-related lncRNAs significantly associated with overall survival (OS) were screened by stepwise univariate Cox regression. The signature of cuproptosis-related lncRNAs for HCC prognosis was constructed by the LASSO algorithm and multivariate Cox regression. Further Kaplan-Meier analysis, proportional hazards model, and ROC analysis were performed. Functional annotation was performed using gene set enrichment analysis (GSEA). The relationship between prognostic cuproptosis-related lncRNAs and HCC prognosis was further explored by GEPIA( http://gepia.cancer-pku.cn/ ) online analysis tool. Finally, we used the ESTIMATE and XCELL algorithms to estimate stromal and immune cells in tumor tissue and cast each sample to infer the underlying mechanism of cuproptosis-related lncRNAs in the tumor immune microenvironment (TIME) of HCC patients.ResultsFour cuproptosis-related lncRNAs were used to construct a prognostic lncRNA signature, which was an independent factor in predicting OS in HCC patients. Kaplan-Meier curves showed significant differences in survival rates between risk subgroups (p = 0.002). At the same time, we found that the expression levels of most immune checkpoint genes increased with increasing risk scores. Tumorigenesis and immunological-related pathways were primarily enhanced in the high-risk group, as determined by GSEA. The results of drug sensitivity analysis showed that compared with patients in the high-risk group, the IC50 values of erlotinib and lapatinib were lower in patients in the low-risk group, while the opposite was true for sunitinib, paclitaxel, gemcitabine, and imatinib. We also found that elevated AL133243.2 expression was significantly associated with worse OS and disease-free survival (DFS), more advanced T stage and higher tumor grade, and reduced immune cell infiltration, suggesting that HCC patients with low AL133243.2 expression in tumor tissues may have a better response to immunotherapy.ConclusionCollectively, the cuproptosis-associated lncRNA signature can serve as an independent predictor to guide individual treatment strategies. Furthermore, AL133243.2 is a promising marker for predicting immunotherapy response in HCC patients. This data may facilitate further exploration of more effective immunotherapy strategies for HCC.
| S-EPMC9811804 | biostudies-literature