A transcriptome study of p53-pathway related prognostic gene signature set in bladder cancer
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SUBMITTER: Khan S
PROVIDER: S-EPMC10590981 | biostudies-literature | 2023 Oct
REPOSITORIES: biostudies-literature
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Project description:BackgroundFerroptosis is a newly found non-apoptotic forms of cell death that plays an important role in tumors. However, the prognostic value of ferroptosis-related genes (FRG) in bladder cancer (BLCA) have not been well examined.MethodsFRG data and clinical information were collected from The Cancer Genome Atlas (TCGA). Then, significantly different FRGs were investigated by functional enrichment analyses. The prognostic FRG signature was identified by univariate cox regression and least absolute shrinkage and selection operator (LASSO) analysis, which was validated in TCGA cohort and Gene Expression Omnibus (GEO) cohort. Subsequently, the nomogram integrating risk scores and clinical parameters were established and evaluated. Additionally, Gene Set Enrichment Analyses (GSEA) was performed to explore the potential molecular mechanisms underlying our prognostic FRG signature. Finally, the expression of three key FRGs was verified in clinical specimens.ResultsThirty-two significantly different FRGs were identified from TCGA-BLCA cohort. Enrichment analyses showed that these genes were mainly related to the ferroptosis. Seven genes (TFRC, G6PD, SLC38A1, ZEB1, SCD, SRC, and PRDX6) were then identified to develop a prognostic signature. The Kaplan-Meier analysis confirmed the predictive value of the signature for overall survival (OS) in both TCGA and GEO cohort. A nomogram integrating age and risk scores was established and demonstrated high predictive accuracy, which was validated through calibration curves and receiver operating characteristic (ROC) curve [area under the curve (AUC) = 0.690]. GSEA showed that molecular alteration in the high- or low-risk group was closely associated with ferroptosis. Finally, experimental results confirmed the expression of SCD, SRC, and PRDX6 in BLCA.ConclusionHerein, we identified a novel FRG prognostic signature that maybe involved in BLCA. It showed high values in predicting OS, and targeting these FRGs may be an alternative for BLCA treatment. Further experimental studies are warranted to uncover the mechanisms that these FRGs mediate BLCA progression.
| S-EPMC8455063 | biostudies-literature
Project description:BackgroundBladder cancer (BC) is a molecular heterogeneous malignant tumor; the treatment strategies for advanced-stage patients were limited. Therefore, it is vital for improving the clinical outcome of BC patients to identify key biomarkers affecting prognosis. Ferroptosis is a newly discovered programmed cell death and plays a crucial role in the occurrence and progression of tumors. Ferroptosis-related genes (FRGs) can be promising candidate biomarkers in BC. The objective of our study was to construct a prognostic model to improve the prognosis prediction of BC.MethodsThe mRNA expression profiles and corresponding clinical data of bladder urothelial carcinoma (BLCA) patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. FRGs were identified by downloading data from FerrDb. Differential analysis was performed to identify differentially expressed genes (DEGs) related to ferroptosis. Univariate and multivariate Cox regression analyses were conducted to establish a prognostic model in the TCGA cohort. BLCA patients from the GEO cohort were used for validation. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and single-sample gene set enrichment analysis (ssGSEA) were used to explore underlying mechanisms.ResultsNine genes (ALB, BID, FADS2, FANCD2, IFNG, MIOX, PLIN4, SCD, and SLC2A3) were identified to construct a prognostic model. Patients were classified into high-risk and low-risk groups according to the signature-based risk score. Receiver operating characteristic (ROC) and Kaplan-Meier (K-M) survival analysis confirmed the superior predictive performance of the novel survival model based on the nine-FRG signature. Multivariate Cox regression analyses showed that risk score was an independent risk factor associated with overall survival (OS). GO and KEGG enrichment analysis indicated that apart from ferroptosis-related pathways, immune-related pathways were significantly enriched. ssGSEA analysis indicated that the immune status was different between the two risk groups.ConclusionThe results of our study indicated that a novel prognostic model based on the nine-FRG signature can be used for prognostic prediction in BC patients. FRGs are potential prognostic biomarkers and therapeutic targets.
| S-EPMC8378228 | biostudies-literature
Project description:BackgroundCellular senescence plays crucial role in the progression of tumors. However, the expression patterns and clinical significance of cellular senescence-related genes in bladder cancer (BCa) are still not clearly clarified. This study aimed to establish a prognosis model based on senescence-related genes in BCa.MethodsThe transcriptional profile data and clinical information of BCa were downloaded from TCGA and GEO databases. The least absolute shrinkage and selection operator (LASSO), univariate and multivariate Cox regression analyses were performed to develop a prognostic model in the TCGA cohort. The GSE13507 cohort were used for validation. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and single-sample gene set enrichment analysis (ssGSEA) were performed to investigate underlying mechanisms.ResultsA six-gene signature (CBX7, EPHA3, STK40, TGFB1I1, SREBF1, MYC) was constructed in the TCGA databases. Patients were classified into high risk and low risk group in terms of the median risk score. Survival analysis revealed that patients in the higher risk group presented significantly worse prognosis. Receiver operating characteristic (ROC) curve analysis verified the moderate predictive power of the risk model based on the six senescence-related genes signature. Further analysis indicated that the clinicopathological features analysis were significantly different between the two risk groups. As expected, the signature presented prognostic significance in the GSE13507 cohort. Functional analysis indicated that immune-related pathways activity, immune cell infiltration and immune-related function were different between two risk groups. In addition, risk score were positively correlated with multiple immunotherapy biomarkers.ConclusionOur study revealed that a novel model based on senescence-related genes could serve as a reliable predictor of survival for patients with BCa.
| S-EPMC9727082 | biostudies-literature
Project description:Bladder cancer (BC), as a genitourinary system tumor, is a highly prevalent tumor type. Ferroptosis is an iron-dependent oxidative cell death mechanism that is becoming increasingly recognized as a promising avenue for cancer therapy. However, further determination of the prospective prognostic value of ferroptosis for BC and investigation of the underlying mechanisms is required. The mRNA expression profiles and associated clinical data were downloaded from public databases such as The Cancer Genome Atlas, Gene Expression Omnibus and the IMvigor210 database. To construct a predictive formula, the least absolute shrinkage and selection operator Cox regression algorithm was used. In addition, a prognostic multigene signature was constructed using previously selected ferroptosis-related genes (FRGs). A total of 28 FRGs were differentially expressed between tumor and normal samples with |log2 fold change| >1 and adjusted P<0.05. A prognostic model was then established and it was validated in the GEO cohort using six genes: Glutamate-cysteine ligase modifier subunit, crystallin α-B, transferrin receptor, zinc finger E-box binding homeobox 1, squalene epoxidase and glucose-6-phosphate dehydrogenase (G6PD). Numerous important pathways involved in the development of the immune system and cancer were indicated to be significantly different between the two risk groups. In addition, it was discovered that G6PD expression subgroups that were associated with immunotherapy response in patients with BC had similar prognostic features to risk score subgroups. In the present study, a gene signature with a prognostic value for ferroptosis in BC was successfully developed and the potential value of G6PD was identified for future research.
| S-EPMC9353228 | biostudies-literature
Project description:BackgroundBladder cancer (BC) is the ninth most common malignant tumor. We constructed a risk signature using immune-related gene pairs (IRGPs) to predict the prognosis of BC patients.MethodsThe mRNA transcriptome, simple nucleotide variation and clinical data of BC patients were downloaded from The Cancer Genome Atlas (TCGA) database (TCGA-BLCA). The mRNA transcriptome and clinical data were also extracted from Gene Expression Omnibus (GEO) datasets (GSE31684). A risk signature was built based on the IRGPs. The ability of the signature to predict prognosis was analyzed with survival curves and Cox regression. The relationships between immunological parameters [immune cell infiltration, immune checkpoints, tumor microenvironment (TME) and tumor mutation burden (TMB)] and the risk score were investigated. Finally, gene set enrichment analysis (GSEA) was used to explore molecular mechanisms underlying the risk score.ResultsThe risk signature utilized 30 selected IRGPs. The prognosis of the high-risk group was significantly worse than that of the low-risk group. We used the GSE31684 dataset to validate the signature. Close relationships were found between the risk score and immunological parameters. Finally, GSEA showed that gene sets related to the extracellular matrix (ECM), stromal cells and epithelial-mesenchymal transition (EMT) were enriched in the high-risk group. In the low-risk group, we found a number of immune-related pathways in the enriched pathways and biofunctions.ConclusionsWe used a new tool, IRGPs, to build a risk signature to predict the prognosis of BC. By evaluating immune parameters and molecular mechanisms, we gained a better understanding of the mechanisms underlying the risk signature. This signature can also be used as a tool to predict the effect of immunotherapy in patients with BC.
| S-EPMC8281685 | biostudies-literature
Project description:AbstractBladder cancer (BC) is one of the most common malignancies worldwide. Several biomarkers related to the prognosis of patients with BC have previously been identified. However, these prognostic models use only one gene and are thus not reliable or accurate enough. The purpose of our study was to develop an innovative gene signature that has greater prognostic value in BC. So, in this study, we performed mRNA expression profiling of glycolysis-related genes in BC (n = 407) cohorts by mining data from The Cancer Genome Atlas (TCGA) database. The glycolysis-related gene sets were confirmed using the Gene Set Enrichment Analysis (GSEA). Using Cox regression analysis, a risk score staging model was built based on the genes that were determined to be significantly associated with BC outcome. Eventually, the system of risk score was structured to predict a patient's survival, and we identified four genes (CHPF, AK3, GALK1, and NUP188) that were associated with the outcomes of BC patients. According to the above-mentioned gene signature, patients were divided into two risk subgroups. The analysis showed that our constructed risk model was independent of clinical features and that the risk score was a highly powerful tool for predicting the overall survival (OS) of BC patients. Taking together, we identified a gene signature associated with glycolysis that could effectively predict the prognosis of BC patients. Our findings offer a new perspective for the clinical research and treatment of BC.
| S-EPMC7837905 | biostudies-literature
Project description:Survival rates for highly invasive bladder cancer (BC) patients have been very low, with a 5-year survival rate of 6%. Accurate prediction of tumor progression and survival is important for diagnosis and therapeutic decisions for BC patients. Our study aims to develop an autophagy-related-gene (ARG) signature that helps to predict the survival of BC patients. RNA-seq data of 403 BC patients were retrieved from The Cancer Genome Atlas Urothelial Bladder Carcinoma (TCGA-BLCA) database. Univariate Cox regression analysis was performed to identify overall survival (OS)-related ARGs. The Lasso Cox regression model was applied to establish an ARG signature in the TCGA training cohort (N = 203). The performance of the 11-gene ARG signature was further evaluated in a training cohort and an independent validation cohort (N = 200) using Kaplan-Meier OS curve analysis, receiver operating characteristic (ROC) analysis, as well as univariate and multivariate Cox regression analysis. Our study identified an 11-gene ARG signature that is significantly associated with OS, including APOL1, ATG4B, BAG1, CASP3, DRAM1, ITGA3, KLHL24, P4HB, PRKCD, ULK2, and WDR45. The ARGs-derived high-risk bladder cancer patients exhibited significantly poor OS in both training and validation cohorts. The prognostic model showed good predictive efficacy, with the area under the ROC curve (AUCs) for 1-year, 3-year, and 5-year overall survival of 0.702 (0.695), 0.744 (0.640), and 0.794 (0.658) in the training and validation cohorts, respectively. A prognostic nomogram, which included the ARGs-derived risk factor, age and stage for eventual clinical translation, was established. We identified a novel ARG signature for risk-stratification and robust prediction of overall survival for BC patients.
| S-EPMC8146553 | biostudies-literature
Project description:Background: The immune microenvironment profoundly affects tumor prognosis and therapy. The present study aimed to reveal potential immune escape mechanisms and construct a novel prognostic signature via systematic bioinformatic analysis of the bladder cancer (BLCA) immune microenvironment. Patients and Methods: The transcriptomic data and clinicopathological information for patients with BLCA were obtained from The Cancer Genome Atlas (TCGA). Consensus clustering analysis based on the CIBERSORT and ESTIMATE algorithms was performed with patients with BLCA, which divided them into two clusters. Subsequently, the differentially expressed genes (DEGs) in the two were subjected to univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses to identify prognostic genes, which were used to construct a prognostic model. The predictive performance of the model was verified by receiver operating characteristic (ROC) and Kaplan-Meier (K-M) analyses. In addition, we analyzed the differentially altered immune cells, mutation burden, neoantigen load, and subclonal genome fraction between the two clusters to reveal the immune escape mechanism. Results: Based on the ESTIMATE and clustering analyses, patients with BLCA were classified into two heterogeneous clusters: ImmuneScoreH and ImmuneScoreL. Univariate Cox and LASSO regression analyses identified CD96 (HR = 0.83) and IBSP (HR = 1.09), which were used to construct a prognostic gene signature with significant predictive accuracy. Regarding potential immune escape mechanisms, ImmuneScoreH and ImmuneScoreL were characterized by inactivation of innate immune cell chemotaxis. In ImmuneScoreL, a low tumor antigen load might contribute to immune escape. ImmuneScoreH featured high expression of immune checkpoint molecules. Conclusion: CD96 and IBSP were considered prognostic factors for BLCA. Innate immune inactivation and a low tumor antigen load may be associated with immune escape mechanisms in both clusters. Our research complements the exploration of the immune microenvironment in BLCA.
| S-EPMC9133907 | biostudies-literature
Project description:Bladder cancer is known to be the most common malignant tumor in the urinary system and has a poor prognosis; thus, new targets for drug treatment are urgently needed. Pyroptosis is defined as programmed cell death in the inflammatory form mediated by the gasdermin protein. It has therapeutic potential due to the synergistic effect of radiotherapy and chemotherapy, can reverse chemotherapy resistance, is able to regulate the body environment to alter tumor metabolism, and may enhance the response rate of the immune checkpoint inhibitor. Accordingly, this study attempted to explore the role of pyroptosis in bladder cancer. A prognostic model based on five pyroptosis-related genes was constructed by conducting univariate Cox survival and LASSO regression analyses using The Cancer Genome Atlas (TCGA) cohort. Patients were divided into high- and low-risk groups according to the median risk score, with all five PRGs having downregulated expression in the high-risk group. The high-risk group was shown to have a worse prognosis than the low-risk group, and survival differences between the two groups were then validated in the Gene Expression Omnibus (GEO) cohort. Moreover, the ROC curves demonstrated the model's moderate predictive ability. The univariate and multivariate Cox regression analyses indicated that risk scores were found to serve as an independent prognosis factor for OS in bladder cancer patients. In addition, the high-risk group was observed to be associated with advanced N and TNM stages. A nomogram combining risk scores and clinical features was then established, with the ROC curve indicating that the AUC of TCGA training cohort in 3 and 5 years was 0.789 and 0.775, respectively. The calibration curve exhibited a high consistency between the actual survival rate and the predicted rate. Furthermore, the GO and KEGG analyses found that antigen processing and presentation of exogenous antigen, exogenous peptide antigen, and peptide antigen were enriched in the low-risk group. A higher abundance of tumor-infiltrating immune cells and additional active immune pathways were also noted in the low-risk group. In addition, immunotherapy biomarkers, including TMB, PD1, PD-L1, CTLA4, and LAG3, were shown to have higher levels in the low-risk group. Therefore, patients in the low-risk group may be potential responders to immune checkpoint inhibitors.
| S-EPMC9283834 | biostudies-literature
Project description:Pyroptosis is a kind of programmed cell death related to inflammation, which is closely related to cancer. The goal of this study is to establish and verify pyroptosis-related gene signature to predict the prognosis of patients with bladder cancer (BLCA) and explore its relationship with immunity. Somatic mutation, copy number variation, correlation, and expression of 33 pyroptosis-related genes were evaluated based on The Cancer Genome Atlas (TCGA) database. BLCA cases were divided into two clusters by consistent clustering and found that pyroptosis-related genes were related to the overall survival (OS) of BLCA. The least absolute shrinkage and selection operator (LASSO) Cox regression was used to construct the signature (including 7 pyroptosis-realated genes). Survival analysis curve and receiver operating characteristic curve (ROC) showed that this signature could predict the prognosis of BLCA patients. Univariate and multivariate Cox regression analysis showed the independent prognostic value of this model. Immune infiltration analysis showed that the six types of immune cells have significantly different infiltrations. The effect of immunotherapy is better in the low-risk group. In summary, our effort indicated the potential role of pyroptosis-related genes in BLCA and provided new perspectives on the prognosis of BLCA and new ideas for immunotherapy.
| S-EPMC9771655 | biostudies-literature