Bioinformatics prediction and experimental verification identify a cuproptosis-related gene signature as prognosis biomarkers of hepatocellular carcinoma
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ABSTRACT:
SUBMITTER: Wang W
PROVIDER: S-EPMC11231784 | biostudies-literature | 2024 Jun
REPOSITORIES: biostudies-literature
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Project description:Cuproptosis is a form of cell death caused by intracellular copper excess, which plays an important regulatory role in the development and progression of cancers, including hepatocellular carcinoma (HCC), a prevalent malignancy with high morbidity and mortality. This study aimed to create a cuproptosis associated long non-coding RNAs (CAlncRNAs)signature to predict HCC patient survival and immunotherapy response. Firstly, we identified 509 CAlncRNAs using Pearson correlation analysis in The Cancer Genome Atlas (TCGA) datasets, before the three CAlncRNAs (MKLN1-AS, FOXD2-AS1, LINC02870) with the most prognostic value were further screened. Then, we constructed a prognostic risk model for HCCwas using univariate and LASSO Cox regression analyses. Multivariate Cox regression analyses illustrated that this model was an independent prognostic factor for overall survival (OS) prediction, outperforming traditional clinicopathological factors. And the risk score not only could be prognostic factors independent of other factors but also suited for patients with diverse ages, stages, and grades. The 1-, 3-, and 5- years areas under the curves (AUC) values of the model were 0.759, 0.668 and 0.674 respectively. Pathway analyses showed that the high-risk groupenriched in immune-related pathways. Importantly, patients with higher risk scores exhibited higher mutation frequency, higher TMB scores, and lower TIDE scores. Besides, we screened for two chemical drugs (A-443654 and Pyrimethamine) with the greatest value for high-risk HCC patients. Finally, the abnormal high expression of the three CAlncRNAs were confirmed in HCC tissues and cells by Real Time Quantitative PCR (RT-qPCR). And proliferative, migratory and invasion abilities of HCC cell were restrained via silencing CAlncRNAs expression in vitro. In summary, we built a CAlncRNAs-based risk score model, which can be a candidate for HCC patients prognostic prediction and offer some useful information for immunotherapies.
| S-EPMC10322676 | biostudies-literature
Project description:BackgroundRhabdomyosarcoma (RMS) is a malignant soft-tissue tumour. In recent years, the tumour microenvironment (TME) has been reported to be associated with the development of tumours. However, the relationship between the occurrence and development of RMS and TME is unclear. The purpose of this study is to identify potential tumor microenvironment-related biomarkers in rhabdomyosarcoma and analyze their molecular mechanisms, diagnostic and prognostic significance.MethodsWe first applied bioinformatics method to analyse the tumour samples of 125 patients with rhabdomyosarcoma (RMS) from the Gene Expression Omnibus database (GEO). Differential genes (DEGs) that significantly correlate with TME and the clinical staging of tumors were extracted. Immunohistochemistry (IHC) was applied to validate the expression of mitotic arrest deficient 2 like 1 (MAD2L1) and cyclin B2 (CCNB2) in RMS tissue. Then, we used cell function and molecular biology techniques to study the influence of MAD2L1 and CCNB2 expression levels on the progression of RMS.ResultsBioinformatics results show that the RMS TME key genes were screened, and a TME-related tumour clinical staging model was constructed. The top 10 hub genes were screened through the establishment of a protein-protein interaction (PPI) network, and then Gene Expression Profiling Interactive Analysis (GEPIA) was conducted to measure the overall survival (OS) of the 10 hub genes in the sarcoma cases in The Cancer Genome Atlas (TCGA). Six DEGs of statistical significance were acquired. The relationship between these six differential genes and the clinical stage of RMS was analysed. Further analysis revealed that the OS of RMS patients with high expression of MAD2L1 and CCNB2 was worse and the expression of MAD2L1 and CCNB2 was related to the clinical stage of RMS patients. Gene set enrichment analysis (GSEA) revealed that the genes in MAD2L1 and CCNB2 groups with high expression were mainly related to the mechanism of tumour metastasis and recurrence. In the low-expression MAD2L1 and CCNB2 groups, the genes were enriched in the metabolic and immune pathways. Immunohistochemical results also confirmed that the expression levels of MAD2L1 (30/33, 87.5%) and CCNB2 (33/33, 100%) were remarkably higher in RMS group than in normal control group (0/11, 0%). Moreover, the expression of CCNB2 was related to tumour size. Downregulation of MAD2L1 and CCNB2 suppressed the growth, invasion, migration, and cell cycling of RMS cells and promoted their apoptosis. The CIBERSORT immune cell fraction analysis indicated that the expression levels of MAD2L1 and CCNB2 affected the immune status in the TME.ConclusionsThe expression levels of MAD2L1 and CCNB2 are potential indicators of TME status changes in RMS, which may help guide the prognosis of patients with RMS and the clinical staging of tumours.
| S-EPMC8626952 | biostudies-literature
Project description:BackgroundHepatocellular carcinoma (HCC) is a highly heterogeneous malignancy with poor overall prognosis. Cuproptosis, a recently proposed mode of copper-dependent cell death, plays a critical role in the malignant progression of various tumors; however, the expression and prognostic value of cuproptosis-related regulatory genes in HCC remain unclear.MethodsGenomic, genetic, and expression profiles of ten key cuproptosis-related regulatory genes were analyzed using The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) dataset and protein expression data from the Human Protein Atlas (HPA) database. Unsupervised clustering of HCC patients based on these ten key cuproptosis-related regulatory genes was used to identify different HCC subtypes and analyze the differences in clinical and immune characteristics among subtypes. Subsequently, univariate Cox and least absolute shrinkage and selection operator (LASSO) Cox analyses were used to establish a cuproptosis-related prognostic signature, and the accuracy of prognostic signature prediction was internally validated by Kaplan-Meier survival analysis and time-dependent receiver operating characteristic curve in TCGA training and testing cohorts. The prognostic signature was externally validated using TCGA-LIHC entire cohort and International Cancer Genome Consortium Liver Cancer (ICGC-LIRI) cohorts. Finally, the expression landscape of cuproptosis-related regulatory genes in prognostic signature was explored by quantitative real-time polymerase chain reaction (qRT-PCR), western blotting and immunohistochemistry (IHC) experiments.ResultsTen cuproptosis-related genes were differentially expressed in normal and HCC tissues. Unsupervised clustering identified two subtypes and HCC patients with these two subtypes had different clinical prognoses and immune characteristics, as well as different degrees of response to immunotherapy. Lipoyltransferase 1 (LIPT1), dihydrolipoamide s-acetyltransferase (DLAT), and cyclin dependent kinase inhibitor 2A (CDKN2A) were selected to construct a prognostic signature, which significantly distinguished HCC patients with different survival periods in the TCGA training and testing cohorts and was well validated in both the TCGA-LIHC entire cohort and ICGC-LIRI cohort. The risk score of the prognostic signature was confirmed to be an independent prognostic factor, and nomograms were generated to effectively predict the probability of HCC patient survival. The qRT-PCR, western blotting and IHC results also revealed a significant imbalance in the expression of these cuproptosis-related genes in HCC.ConclusionsThe classification and prognostic signature based on cuproptosis-related regulatory genes helps to explain the heterogeneity of HCC, which may contribute to the individualized treatment of patients with the disease.
| S-EPMC11009816 | biostudies-literature
Project description:Osteoarthritis (OA) is the one of most common joint diseases worldwide. Cuproptosis, which had been discovered lately, is a novel form of cell death induced by copper. Our purpose is to study the relationship between cuproptosis-related genes (CRGs) and inflammatory microenvironments in patients with OA and identify characteristic cuproptosis-related biomarkers. First, the combinatory analysis of OA transcriptome data from five datasets identified differentially expressed CRGs associated with OA. Then, we applied single-sample gene set enrichment analysis (ssGSEA) to evaluate immune-cell infiltration and immune-function levels in OA patients and normal controls, respectively. Hub CRGs for OA were mined based on the random forest (RF) model, and a nomogram prediction model was constructed based on them. In total, four differentially expressed CRGs were identified through bioinformatics analysis and confirmed by RT-qPCR. FDX1 and LIPT1 were expressed at a high level in OA, while DBT and DLST were expressed higher in the normal group. In total, 10 CRGs were found to be significantly correlated with immune landscape. Four hub CRGs were subsequently obtained by the RF analysis as potential biomarkers for OA. We constructed an OA predictive model based on these four CRGs (DBT, DLST, FDX1, and LIPT1).
| S-EPMC9855951 | biostudies-literature
Project description:BackgroundGuanine nucleotide binding (G) protein subunit γ 4 (GNG4) is closely related to the malignant progression and poor prognosis of various tumours. However, its role and mechanism in osteosarcoma remain unclear. This study aimed to elucidate the biological role and prognostic value of GNG4 in osteosarcoma.MethodsOsteosarcoma samples in the GSE12865, GSE14359, GSE162454 and TARGET datasets were selected as the test cohorts. The expression level of GNG4 between normal and osteosarcoma was identified in GSE12865 and GSE14359. Based on the osteosarcoma single-cell RNA sequencing (scRNA-seq) dataset GSE162454, differential expression of GNG4 among cell subsets was identified at the single-cell level. As the external validation cohort, 58 osteosarcoma specimens from the First Affiliated Hospital of Guangxi Medical University were collected. Patients with osteosarcoma were divided into high- and low-GNG4 groups. The biological function of GNG4 was annotated using Gene Ontology, gene set enrichment analysis, gene expression correlation analysis and immune infiltration analysis. Kaplan-Meier survival analysis was conducted and receiver operating characteristic (ROC) curves were calculated to determine the reliability of GNG4 in predicting prognostic significance and diagnostic value. Functional in vitro experiments were performed to explore the function of GNG4 in osteosarcoma cells.ResultsGNG4 was generally highly expressed in osteosarcoma. As an independent risk factor, high GNG4 was negatively correlated with both overall survival and event-free survival. Furthermore, GNG4 was a good diagnostic marker for osteosarcoma, with an area under the receiver operating characteristic curve (AUC) of more than 0.9. Functional analysis suggested that GNG4 may promote the occurrence of osteosarcoma by regulating ossification, B-cell activation, the cell cycle and the proportion of memory B cells. In in vitro experiments, silencing of GNG4 inhibited the viability, proliferation and invasion of osteosarcoma cells.ConclusionThrough bioinformatics analysis and experimental verification, high expression of GNG4 in osteosarcoma was identified as an oncogene and reliable biomarker for poor prognosis. This study helps to elucidate the significant potential of GNG4 in carcinogenesis and molecular targeted therapy for osteosarcoma.
| S-EPMC9950737 | biostudies-literature
Project description:BackgroundsAlcoholic hepatitis (AH) is a major health problem worldwide. There is increasing evidence that immune cells, iron metabolism and copper metabolism play important roles in the development of AH. We aimed to explore biomarkers that are co-associated with M1 macrophages, ferroptosis and cuproptosis in AH patients.MethodsGSE28619 and GSE103580 datasets were integrated, CIBERSORT algorithm was used to analyze the infiltration of 22 types of immune cells and GSVA algorithm was used to calculate ferroptosis and cuproptosis scores. Using the "WGCNA" R package, we established a gene co-expression network and analyzed the correlation between M1 macrophages, ferroptosis and cuproptosis scores and module characteristic genes. Subsequently, candidate genes were screened by WGCNA and differential expression gene analysis. The LASSO-SVM analysis was used to identify biomarkers co-associated with M1 macrophages, ferroptosis and cuproptosis. Finally, we validated these potential biomarkers using GEO datasets (GSE155907, GSE142530 and GSE97234) and a mouse model of AH.ResultsThe infiltration level of M1 macrophages was significantly increased in AH patients. Ferroptosis and cuproptosis scores were also increased in AH patients. In addition, M1 macrophages, ferroptosis and cuproptosis were positively correlated with each other. Combining bioinformatics analysis with a mouse model of AH, we found that ALDOA, COL3A1, LUM, THBS2 and TIMP1 may be potential biomarkers co-associated with M1 macrophages, ferroptosis and cuproptosis in AH patients.ConclusionWe identified 5 potential biomarkers that are promising new targets for the treatment and diagnosis of AH patients.
| S-EPMC10117880 | biostudies-literature
Project description:Immune checkpoint genes (ICGs), the foundation of immunotherapy, are involved in the incidence and progression of hepatocellular carcinoma (HCC). Cuproptosis is characterized by copper-induced cell death, and this novel cell death pathway has piqued the interest of researchers in recent years. It is worth noting that there is little information available in the literature to determine the relationship between cuproptosis and anti-tumor immunity. We identified 39 cuproptosis-related ICGs using ICGs co-expressed with cuproptosis-related genes. A prognostic risk signature was constructed using the Cox regression and the least absolute shrinkage and selection operator analysis methods. The signature was built using the Cancer Genome Atlas (TCGA)-Liver Hepatocellular Carcinoma database. The TCGA and International Cancer Genome Consortium cohorts were classified into two groups; the low- and high-risk groups were determined using a prognostic signature comprised of five genes. The multivariate Cox regression analysis revealed that the signature could independently predict overall survival. Furthermore, the level of immune infiltration analysis revealed the robustness of the prognostic signature-immune cell infiltration relationship observed for Tregs, macrophages, helper T cells, and naive B cells. Both groups showed significant differences in immune checkpoint expression levels. The gene enrichment analysis was used for characterization, and the results revealed that enriching various pathways such as PI3K-AKT-mTOR signaling, glycolysis, Wnt/beta-catenin signaling, and unfolded protein response could potentially influence the prognosis of patients with HCC and the level of immune infiltration. The sensitivity of the two groups of patients to various drug-targeted therapy methods and immunotherapy was analyzed. In conclusion, the findings presented here lay the foundation for developing individualized treatment methods for HCC patients. The findings also revealed that studying the cuproptosis-based pathway can aid in the prognosis of HCC patients. It is also possible that cuproptosis contributes to developing anti-tumor immunity in patients.
| S-EPMC9579294 | biostudies-literature
Project description:Purpose: Targeting cuproptosis is considered as a promising therapeutic strategy for the prevention of tumors. However, the potential role of cuproptosis and its related genes in clear cell renal cell carcinoma (ccRCC) remains elusive. The present study aims to explore the sensitivity of ccRCC to cuproptosis and its underlying mechanism. Methods: Cuproptosis differential genes (CDGs) were extracted using the GSE53757 and GSE66272 datasets. A comprehensive analysis of the role of CDGs was conducted through multiple public databases and experiments. Results: It was found that cuproptosis inducer elesclomol significantly induced cell death in 786-O and A498 cells. FDX and DLAT exhibited significantly low expression, which were independent prognostic factors for poor survival, and had a strong positive correlation in ccRCC patients. Functional analysis of differentially expressed genes positively or negatively correlated with both FDX1 and DLAT indicated that acetyl-CoA biosynthetic process and acetyl-CoA metabolic process were remarkably affected. In ccRCC patients, the methylation levels and sites of FDX1 and DLAT genes were dramatically correlated with overall survival (OS). The expressions of FDX1 and DLAT were closely related to immune infiltration and immune checkpoints. Docking results indicated that mitotane, adicicol and dihydrolipoic acid might be potential drug targets for FDX1 and DLAT. Conclusions: Overall, the present study demonstrates the sensitivity of ccRCC to cuproptosis, and targeting the combination of FDX1 and DLAT may be a novel therapeutic strategy to induce cuproptosis in ccRCC.
| S-EPMC11705067 | biostudies-literature
Project description:Increasing evidence indicates that peripheral blood vessels play a pivotal role in regulating tumor growth with the presence of new blood vessels facilitating tumor growth and metastasis. Nevertheless, the impact of specific molecule-mediated angiogenesis on the tumor immune microenvironment (TIME) and individual prognosis of uterine corpus endometrial carcinoma (UCEC) remains uncertain. The transcriptome information on 217 prognostic angiogenesis-related genes was integrated, and the angiogenesis patterns of 506 UCEC patients in The Cancer Genome Atlas (TCGA) cohort were comprehensively evaluated. We identified five angiogenic subtypes, namely, EC1, EC2, EC3, EC4, and EC5, which differed significantly in terms of prognosis, clinicopathological features, cancer hallmarks, genomic mutations, TIME patterns, and immunotherapy responses. Additionally, an angiogenesis-related prognostic risk score (APRS) was constructed to enable an individualized comprehensive evaluation. In multiple cohorts, APRS demonstrated a powerful predictive ability for the prognosis of UCEC patients. Likewise, APRS was confirmed to be associated with clinicopathological features, genomic mutations, cancer hallmarks, and TIME patterns in UCEC patients. The predictability of APRS for immune checkpoint inhibitor (ICI) therapy was also salient. Subsequently, the expression levels of four angiogenesis-related hub genes were verified by qRT-PCR, immunohistochemistry, and single-cell sequencing data analysis. The effects of four representative genes on angiogenesis were validated by Wound-Healing and Transwell assays, tube formation assay in vitro, and tumor xenograft model in vivo. This study proffered a new classification of UCEC patients based on angiogenesis. The established APRS may contribute to individualized prognosis prediction and immunotherapy selections that are better suited for UCEC patients.
| S-EPMC11190931 | biostudies-literature
Project description:BackgroundDiabetic kidney disease (DKD) is the leading cause of death in people with type 2 diabetes mellitus (T2DM). The main objective of this study is to find the potential biomarkers for DKD.Materials and methodsTwo datasets (GSE86300 and GSE184836) retrieved from Gene Expression Omnibus (GEO) database were used, combined with our RNA sequencing (RNA-seq) results of DKD mice (C57 BLKS-32w db/db) and non-diabetic (db/m) mice for further analysis. After processing the expression matrix of the three sets of data using R software "Limma", differential expression analysis was performed. The significantly differentially expressed genes (DEGs) (-logFC- > 1, p-value < 0.05) were visualized by heatmaps and volcano plots respectively. Next, the co-expression genes expressed in the three groups of DEGs were obtained by constructing a Venn diagram. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were further analyzed the related functions and enrichment pathways of these co-expression genes. Then, qRT-PCR was used to verify the expression levels of co-expression genes in the kidney of DKD and control mice. Finally, protein-protein interaction network (PPI), GO, KEGG analysis and Pearson correlation test were performed on the experimentally validated genes, in order to clarify the possible mechanism of them in DKD.ResultsOur RNA-seq results identified a total of 125 DEGs, including 59 up-regulated and 66 down-regulated DEGs. At the same time, 183 up-regulated and 153 down-regulated DEGs were obtained in GEO database GSE86300, and 76 up-regulated and 117 down-regulated DEGs were obtained in GSE184836. Venn diagram showed that 13 co-expression DEGs among the three groups of DEGs. GO analysis showed that biological processes (BP) were mainly enriched inresponse to stilbenoid, response to fatty acid, response to nutrient, positive regulation of macrophage derived foam cell differentiation, triglyceride metabolic process. KEGG pathway analysis showed that the three major enriched pathways were cholesterol metabolism, drug metabolism-cytochrome P450, PPAR signaling pathway. After qRT-PCR validation, we obtained 11 genes that were significant differentially expressed in the kidney tissues of DKD mice compared with control mice. (The mRNA expression levels of Aacs, Cpe, Cd36, Slc22a7, Slc1a4, Lpl, Cyp7b1, Akr1c14 and Apoh were declined, whereas Abcc4 and Gsta2 were elevated).ConclusionOur study, based on RNA-seq results, GEO databases and qRT-PCR, identified 11 significant dysregulated DEGs, which play an important role in lipid metabolism and the PPAR signaling pathway, which provide novel targets for diagnosis and treatment of DKD.
| S-EPMC9504448 | biostudies-literature