Dataset Information

Identification of a prognostic gene signature based on an immunogenomic landscape analysis of bladder cancer.

ABSTRACT: Cancer immune plays a critical role in cancer progression. Tumour immunology and immunotherapy are one of the exciting areas in bladder cancer research. In this study, we aimed to develop an immune-related gene signature to improve the prognostic prediction of bladder cancer. Firstly, we identified 392 differentially expressed immune-related genes (IRGs) based on TCGA and ImmPort databases. Functional enrichment analysis revealed that these genes were enriched in inflammatory and immune-related pathways, including in 'regulation of signaling receptor activity', 'cytokine-cytokine receptor interaction' and 'GPCR ligand binding'. Then, we separated all samples in TCGA data set into the training cohort and the testing cohort in a ratio of 3:1 randomly. Data set GSE13507 was set as the validation cohort. We constructed a prognostic six-IRG signature with LASSO Cox regression in the training cohort, including AHNAK, OAS1, APOBEC3H, SCG2, CTSE and KIR2DS4. Six IRGs reflected the microenvironment of bladder cancer, especially immune cell infiltration. The prognostic value of six-IRG signature was further validated in the testing cohort and the validation cohort. The results of multivariable Cox regression and subgroup analysis revealed that six-IRG signature was a clinically independent prognostic factor for bladder cancer patients. Further, we constructed a nomogram based on six-IRG signature and other clinicopathological risk factors, and it performed well in predict patients' survival. Finally, we found six-IRG signature showed significant difference in different molecular subtypes of bladder cancer. In conclusions, our research provided a novel immune-related gene signature to estimate prognosis for patients' survival with bladder cancer.

SUBMITTER: Luo Y

PROVIDER: S-EPMC7701570 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of a prognostic gene signature based on an immunogenomic landscape analysis of bladder cancer.

Luo Yongwen Y Chen Liang L Zhou Qiang Q Xiong Yaoyi Y Wang Gang G Liu Xuefeng X Xiao Yu Y Ju Lingao L Wang Xinghuan X

Journal of cellular and molecular medicine 20201013 22

Cancer immune plays a critical role in cancer progression. Tumour immunology and immunotherapy are one of the exciting areas in bladder cancer research. In this study, we aimed to develop an immune-related gene signature to improve the prognostic prediction of bladder cancer. Firstly, we identified 392 differentially expressed immune-related genes (IRGs) based on TCGA and ImmPort databases. Functional enrichment analysis revealed that these genes were enriched in inflammatory and immune-related ...[more]

PMID: 33048468

Similar Datasets

Project description:Acute myeloid leukemia (AML) is a hematopoietic malignancy characterized by highly heterogeneous molecular lesions and cytogenetic abnormalities. Immune disorders in AML and impaired immune cell function have been found to be associated with abnormal karyotypes in AML patients. Immunotherapy has become an alternative therapeutic method that can improve the outcomes of AML patients. For solid tumors, the expression patterns of genes associated with the immune microenvironment provide valuable prognostic information. However, the prognostic roles of immune genes in AML have not been studied as yet. In this study, we identified 136 immune-related genes associated with overall survival in AML patients through a univariate Cox regression analysis using data from TCGA-AML and GTEx datasets. Next, we selected 24 hub genes from among the 136 genes based on the PPI network analysis. The 24 immune-related hub genes further underwent multivariate Cox regression analysis and LASSO regression analysis. Finally, a 6 immune-related gene signature was constructed to predict the prognosis of AML patients. The function of the hub IRGs and the relationships between hub IRGs and transcriptional factors were investigated. We found that higher levels of expression of CSK, MMP7, PSMA7, PDCD1, IKBKG, and ISG15 were associated with an unfavorable prognosis of AML patients. Meanwhile, patients in the TCGA-AML datasets were divided into a high risk score group and a low risk score group, based on the median risk score value. Patients in the high risk group tended to show poorer prognosis [P = 0.00019, HR = 1.89 (1.26-2.83)]. The area under the curve (AUC) was 0.6643. Multivariate Cox Regression assay confirmed that the 6 IRG signature was an independent prognostic factor for AML. The prognostic role of the immune related-gene signature was further validated using an independent AML dataset, GSE37642. In addition, patients in the high risk score group in the TCGA dataset were found to be of an advanced age, IDH mutation, and M5 FAB category. These results suggested that the proposed immune related-gene signature may serve as a potential prognostic tool for AML patients.

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.

Dataset Information

Identification of a prognostic gene signature based on an immunogenomic landscape analysis of bladder cancer.

Publications

Identification of a prognostic gene signature based on an immunogenomic landscape analysis of bladder cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets