Identification and validation of an immune-related gene-based prognostic index for bladder cancer
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ABSTRACT:
SUBMITTER: Tian Z
PROVIDER: S-EPMC7540134 | biostudies-literature | 2020 Jan
REPOSITORIES: biostudies-literature
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Project description:BackgroundThere has been no report of prognostic signature based on immune-related genes (IRGs). This study aimed to develop an IRG-based prognostic signature that could stratify patients with bladder cancer (BLCA).MethodsRNA-seq data along with clinical information on BLCA were retrieved from the Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO). Based on TCGA dataset, differentially expressed IRGs were identified via Wilcoxon test. Among these genes, prognostic IRGs were identified using univariate Cox regression analysis. Subsequently, we split TCGA dataset into the training (n = 284) and test datasets (n = 119). Based on the training dataset, we built a least absolute shrinkage and selection operator (LASSO) penalized Cox proportional hazards regression model with multiple prognostic IRGs. It was validated in the training dataset, test dataset, and external dataset GSE13507 (n = 165). Additionally, we accessed the six types of tumor-infiltrating immune cells from Tumor Immune Estimation Resource (TIMER) website and analyzed the difference between risk groups. Further, we constructed and validated a nomogram to tailor treatment for patients with BLCA.ResultsA set of 47 prognostic IRGs was identified. LASSO regression and identified seven BLCA-specific prognostic IRGs, i.e., RBP7, PDGFRA, AHNAK, OAS1, RAC3, EDNRA, and SH3BP2. We developed an IRG-based prognostic signature that stratify BLCA patients into two subgroups with statistically different survival outcomes [hazard ratio (HR) = 10, 95% confidence interval (CI) = 5.6-19, P < 0.001]. The ROC curve analysis showed acceptable discrimination with AUCs of 0.711, 0.754, and 0.772 at 1-, 3-, and 5-year follow-up respectively. The predictive performance was validated in the train set, test set, and external dataset GSE13507. Besides, the increased infiltration of CD4+ T cells, CD8+ T cells, macrophage, neutrophil, and dendritic cells in the high-risk group (as defined by the signature) indicated chronic inflammation may reduce the survival chances of BLCA patients. The nomogram demonstrated to be clinically-relevant and effective with accurate prediction and positive net benefit.ConclusionThe present immune-related signature can effectively classify BLCA patients into high-risk and low-risk groups in terms of survival rate, which may help select high-risk BLCA patients for more intensive treatment.
| S-EPMC7013035 | biostudies-literature
Project description:The prognosis of bladder cancer patients is strongly related to both the immune-infiltrating cells and the expression of lncRNAs. In this study, we analyzed the infiltration of immune cells in 403 bladder cancer samples obtained from TCGA by applying the ssGSEA to these samples, then dividing them into high/low immune cell infiltration groups. Based on these groupings, we found 404 differentially expressed immune infiltration-related lncRNAs, which were successively analyzed by univariate Cox regression, then Least Absolute Shrinkage and Selection Operator (LASSO), and finally stepwise multiple Cox regression. Then 12 differentially expressed immune infiltration-related lncRNAs were identified and used to construct a prognostic signature for bladder cancer. Subsequently, Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, and multivariate time-dependent ROC analyses (for 1, 3, 5 years) all revealed that this signature performed well in predicting overall survival and served as an independent prognostic factor for patients with bladder cancer. Finally, both TIMER and CIBESORT showed that this 12-lncRNA prognostic signature for bladder cancer was associated with the infiltration of immune cell subtypes. Besides, nomogram considered risk score and clinical characteristics was assembled and showed great performance. More importantly, we found our signature could well distinguish the drug response of patients with bladder cancer. High risk patients showed a better response to cisplatin, doxorubicin, and anti- CTLA4 immunotherapy, low risk patients showed a better response to methotrexate and anti-PD1 immunotherapy compared with each other.
| S-EPMC8876923 | biostudies-literature
Project description:Purpose: Autophagy is a major catabolic system by which eukaryotic cells undergo self-degradation of damaged, defective, or unwanted intracellular components. An abnormal autophagic level is implicated in the pathogenesis of multiple diseases, including cancers. The aim of this study is to explore the prognostic value of autophagy in bladder cancer (BC), which is a major cause of cancer-related death globally. Patients and methods: First, 27 differentially expressed autophagy-related genes (ARGs) were identified in BC patients based on The Cancer Genome Atlas (TCGA) database. Functional enrichment analyses hinted that autophagy may act in a tumor-suppressive role in the initiation of BC. Then, the Cox proportional hazard regression model were employed to identify three key prognostic ARGs (JUN, MYC, and ITGA3), which were related with overall survival (OS) significantly in BC. The three genes represented important clinical significance and prognostic value in BC. Then a prognostic index (PI) was constructed. Results: The PI was constructed based on the three genes, and significantly stratified BC patients into high- and low-risk groups in terms of OS (HR=1.610, 95% CI=1.200-2.160, P=0.002). PI remained as an independent prognostic factor in multivariate analyses (HR=2.355, 95% CI=1.483-3.739, P<0.001). When integrated with clinical characteristics of age and stage, an autophagy-clinical prognostic index (ACPI) was finally validated, which had improved performance in predicting OS of BC patients (HR=2.669, 95% CI=1.986-3.587, P<0.001). The ACPI was confirmed in datasets of GSE13507 (HR=7.389, 95% CI=3.645-14.980, P<0.001) and GSE31684 (HR=1.665, 95% CI=0.872-3.179, P=0.122). Conclusion: This study provides a potential prognostic signature for predicting prognosis of BC patients and molecular insights of autophagy in BC.
| S-EPMC6526186 | biostudies-literature
Project description:Bladder cancer is one of the most common cancers worldwide. The immune response and immune cell infiltration play crucial roles in tumour progression. Immunotherapy has delivered breakthrough achievements in the past decade in bladder cancer. Differentially expressed genes and immune-related genes (DEIRGs) were identified by using the edgeR package. Gene ontology annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed for functional enrichment analysis of DEIRGs. Survival-associated IRGs were identified by univariate Cox regression analysis. A prognostic model was established by univariate COX regression analysis, and verified by a validation prognostic model based on the GEO database. Patients were divided into high-risk and low-risk groups based on the median risk score value for immune cell infiltration and clinicopathological analyses. A regulatory network of survival-associated IRGs and potential transcription factors was constructed to investigate the potential regulatory mechanisms of survival-associated IRGs. Nomogram and ROC curve to verify the accuracy of the model. Quantitative real-time PCR was performed to validate the expression of relevant key genes in the prognostic model. A total of 259 differentially expressed IRGs were identified in the present study. KEGG pathway analysis of IRGs showed that the "cytokine-cytokine receptor interaction" pathway was the most significantly enriched pathway. Thirteen survival-associated IRGs were selected to establish a prognostic index for bladder cancer. In both TCGA prognostic model and GEO validation model, patients with high riskscore had worse prognosis compared to low riskscore group. A high infiltration level of macrophages was observed in high-risk patients. OGN, ELN, ANXA6, ILK and TGFB3 were identified as hub survival-associated IRGs in the network. EBF1, WWTR1, GATA6, MYH11, and MEF2C were involved in the transcriptional regulation of these survival-associated hub IRGs. The present study identified several survival-associated IRGs of clinical significance and established a prognostic index for bladder cancer outcome evaluation for the first time.
| S-EPMC7661532 | biostudies-literature
Project description:Background and Objective: Bladder cancer is the most common tumor in the urinary system, with a higher incidence in men than in women and a high recurrence rate. However, the mechanism of recurrence is still unclear, and it is urgent to clarify the pathophysiological mechanism of bladder cancer. To provide theoretical basis for the development of new therapies, investigating the effect of tumor microenvironment on the prognosis of bladder cancer is necessary. Methods: We applied the Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE) algorithm to the downloaded TCGA (The Cancer Genome Atlas) transcriptome data to obtain the immune scores and stromal scores of each sample, and then divided the samples into two groups: high and low immune scores (or high and low stromal scores), and found that some differential genes were associated with poor prognosis of patients. We then performed protein-protein interaction (PPI) network analysis to explore the relationship between these differentially expressed genes. Moreover, we also performed (Gene Ontology) GO and (Kyoto Encyclopedia of Genes and Genomes) KEGG analyses to explore the potential functions of differentially expressed genes. Finally, our results were validated in an independent dataset. Results: We identified 136 tumor microenvironment-related genes associated with poor prognosis of bladder cancer. GO annotation and KEGG pathway enrichment analysis found that these genes are mainly involved in extracellular matrix, Focal adhesion and phosphatidylinositol 3 kinase-protein kinaseB (PI3k-Akt) signaling pathway. Next, PPI network analysis revealed some hub genes including Versican (VCAN), Thrombospondin 1 (THBS1) and Thrombospondin 1 (THBS2). Finally, 27 genes were further verified in the independent data set. Conclusions: We found 27 tumor microenvironment-related genes of bladder cancer, which are associated with poor prognosis of bladder cancer. These genes may inspire researchers to develop new treatments for bladder cancer.
| S-EPMC6883806 | biostudies-literature
Project description:BackgroundLung cancer is the most common malignant tumor in the world, and its prognosis is still not optimistic. The aim of this study was to establish an immune-related gene (IRG) prognostic index (IRGPI) for lung adenocarcinoma (LUAD) based on IRGs, and to explore the prognosis, molecular and immune features, and response to immune checkpoint inhibitor (ICI) therapy in IRGPI-classified different subgroups of LUAD.MethodsBased on the LUAD transcriptome RNA-sequencing data in TCGA database, the differentially expressed genes (DEGs) were selected. Subsequently, DEGs were intersected with IRGs to obtain differentially expressed immune-related genes (DEIRGs). Weighted gene co-expression network analysis (WGCNA) identified hub genes in DEIRGs. Finally, univariate and multivariate Cox regression analyses were used to build an IRGPI model. Subsequently, TCGA patients were divided into high- and low-risk groups, and the survival of patients in different groups was further analyzed. Besides, we validated the molecular and immune characteristics, relationship with immune checkpoints, angiogenesis-related genes, and immune subtypes distribution in different subgroups. Meanwhile, we further validated the response to ICI therapy in different subgroups.ResultsThe IRGPI was constructed based on 13 DEIRGs. Compared with the low-risk group, overall survival (OS) was lower in the high-risk group, and the high-risk score was independently associated with poorer OS. Besides, the high-risk score was associated with cell cycle pathway, high mutation rate of TP53 and KRAS, high infiltration of M0 macrophages, and immunosuppressive state, and these patients had poorer prognosis but the TIDE score of the high-risk group was lower than that of the other group, which means that the high-risk group could benefit more from ICI treatment. In contrast, the low-risk score was related to low mutation rate of TP53 and KRAS, high infiltration of plasma cells, and immunoactive state, and these patients had better prognosis but the low-risk group less benefit from ICI treatment based on the results of TIDE score.ConclusionsIRGPI is a prospective biomarker based on IRGs that can distinguish high- and low-risk groups to predict patient prognosis, help characterize the tumor immune microenvironment, and evaluate the benefit of ICI therapy in LUAD.
| S-EPMC10713328 | biostudies-literature
Project description:Compelling evidence indicates that immune function is correlated with the prognosis of bladder cancer (BC). Here, we aimed to develop a clinically translatable immune-related gene pairs (IRGPs) prognostic signature to estimate the overall survival (OS) of bladder cancer. From the 251 prognostic-related IRGPs, 37 prognostic-related IRGPs were identified using LASSO regression. We identified IRGPs with the potential to be prognostic markers. The established risk scores divided BC patients into high and low risk score groups, and the survival analysis showed that risk score was related to OS in the TCGA-training set (p < 0.001; HR = 7.5 [5.3, 10]). ROC curve analysis showed that the AUC for the 1-year, 3-year, and 5-year follow-up was 0.820, 0.883, and 0.879, respectively. The model was verified in the TCGA-testing set and external dataset GSE13507. Multivariate analysis showed that risk score was an independent prognostic predictor in patients with BC. In addition, significant differences were found in gene mutations, copy number variations, and gene expression levels in patients with BC between the high and low risk score groups. Gene set enrichment analysis showed that, in the high-risk score group, multiple immune-related pathways were inhibited, and multiple mesenchymal phenotype-related pathways were activated. Immune infiltration analysis revealed that immune cells associated with poor prognosis of BC were upregulated in the high-risk score group, whereas immune cells associated with a better prognosis of BC were downregulated in the high-risk score group. Other immunoregulatory genes were also differentially expressed between high and low risk score groups. A 37 IRGPs-based risk score signature is presented in this study. This signature can efficiently classify BC patients into high and low risk score groups. This signature can be exploited to select high-risk BC patients for more targeted treatment.
| S-EPMC8331311 | biostudies-literature
Project description:BackgroundThe depth of response to platinum in urothelial neoplasm tissues varies greatly. Biomarkers that have practical value in prognosis stratification are increasingly needed. Our study aimed to select a set of BC (bladder cancer)-related genes involved in both platinum resistance and survival, then use these genes to establish the prognostic model.Materials and methodsPlatinum resistance-related DEGs (differentially expressed genes) and tumorigenesis-related DEGs were identified. Ten most predictive co-DEGs were acquired followed by building a risk score model. Survival analysis and ROC (receiver operating characteristic) plot were used to evaluate the predictive accuracy. Combined with age and tumor stages, a nomogram was generated to create a graphical representation of survival rates at 1-, 3-, 5-, and 8-year in BC patients. The prognostic performance was validated in three independent BC datasets with platinum-based chemotherapy. The potential mechanism was explored by enrichment analysis.ResultsPPP2R2B, TSPAN7, ATAD3C, SYT15, SAPCD1, AKR1B1, TCHH, AKAP12, AGLN3, and IGF2 were selected for our prognostic model. Patients in high- and low-risk groups exhibited a significant survival difference with HR (hazard ratio) = 2.7 (p < 0.0001). The prognostic nomogram of predicting 3-year OS (overall survival) for BC patients could yield an AUC (area under the curve) of 0.819. In the external validation dataset, the risk score also has a robust predictive ability.ConclusionA prognostic model derived from platinum resistance-related genes was constructed, we confirmed its value in predicting platinum-based chemotherapy benefits and overall survival for BC patients. The model might assist in therapeutic decisions for bladder malignancy.
| S-EPMC9881817 | biostudies-literature
Project description:Immune-related genes (IRGs) have been identified as critical drivers of the initiation and progression of hepatocellular carcinoma (HCC). This study is aimed at constructing an IRG signature for HCC and validating its prognostic value in clinical application. The prognostic signature was developed by integrating multiple IRG expression data sets from TCGA and GEO databases. The IRGs were then combined with clinical features to validate the robustness of the prognostic signature through bioinformatics tools. A total of 1039 IRGs were identified in the 657 HCC samples. Subsequently, the IRGs were subjected to univariate Cox regression and LASSO Cox regression analyses in the training set to construct an IRG signature comprising nine immune-related gene pairs (IRGPs). Functional analyses revealed that the nine IRGPs were associated with tumor immune mechanisms, including cell proliferation, cell-mediated immunity, and tumorigenesis signal pathway. Concerning the overall survival rate, the IRGPs distinctly grouped the HCC samples into the high- and low-risk groups. Also, we found that the risk score based on nine IRGPs was related to clinical and pathologic factors and remained a valid independent prognostic signature after adjusting for tumor TNM, grade, and grade in multivariate Cox regression analyses. The prognostic value of the nine IRGPs was further validated by forest and nomogram plots, which revealed that it was superior to the tumor TNM, grade, and stage. Our findings suggest that the nine-IRGP signature can be effective in determining the disease outcomes of HCC patients.
| S-EPMC7081044 | biostudies-literature
Project description:PurposeWe aimed to construct an immune-related long noncoding ribonucleic acids (irlncRNA) signature to evaluate the prognosis of patients without specific expression level of these irlncRNA.MethodsThe raw transcriptome data were downloaded from The Cancer Genome Atlas (TCGA), irlncRNAs were filtered out using an online immune related gene database and coexpression analysis, differently expressed irlncRNA (DEirlncRNA) pairs were identified by univariate analysis. The areas under curve (AUC) were compared and the Akaike information criterion (AIC) values of receiver operating curve (ROC) was counted, the most optimal model was constructed to divide bladder cancer patients into high- and low-risk groups usingõ the cut-off point of ROC. Then, we evaluated them from multiple perspectives, such as survival time, clinic-pathological characteristics, immune-related cells infiltrating, chemotherapeutics efficacy and immune checkpoint inhibitors.Results14 DEirlncRNA pairs were included in this signature. Patients in high-risk groups demonstrated apparent shorter survival time, more aggressive clinic-pathological characteristics, different immune-related cells infiltrating status, lower chemotherapeutics efficacy.ConclusionThe irlncRNA signature demonstrated a promising prediction value for bladder cancer patients and was important in guiding clinical treatment.
| S-EPMC8311739 | biostudies-literature