A novel risk score based on a combined signature of 10 immune system genes to predict bladder cancer prognosis

Tang, Yunliang; Hu, Yangyang; Wang, Jiao; Zeng, Zhenguo

doi:10.1016/j.intimp.2020.106851

Cited by 12 publications

(10 citation statements)

References 39 publications

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“…but its expression and function in BC are still unclear. Recently, some studies have used databases to analyze the prognostic relevance of Rac3 in BC [23][24][25][26][27], but strict inclusion criteria were in place for the patients with BC in this study, and the number of patients we analyzed was different. We first performed Kaplan-Meier survival analysis, followed by univariate and multivariate Cox analysis.…”

Section: Discussionmentioning

confidence: 99%

“…We first performed Kaplan-Meier survival analysis, followed by univariate and multivariate Cox analysis. Qiu et al [ 23 ] and Liu et al [ 24 ] screened only prognostic immune-related genes with univariate Cox analysis, while Na et al [ 25 ] and Tang et al [ 26 ] used prognostic immune-related genes for multivariate Cox analysis. However, we used Rac3 and clinicopathological variables for multivariate Cox analysis.…”

Section: Discussionmentioning

confidence: 99%

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Rac3 Expression and its Clinicopathological Significance in Patients With Bladder Cancer

Chen¹,

Nie²,

Cao³

et al. 2021

Pathol. Oncol. Res.

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Background: Ras-related C3 botulinum toxin substrate 3 (Rac3) is overexpressed in malignancies and promotes tumor progression. However, the correlations between Rac3 expression and the clinicopathological characteristics and prognoses of patients with bladder cancer (BC) remain unclear.Methods: Data from The Cancer Genome Atlas (TCGA) were used to analyze Rac3 expression in BC and normal bladder tissues and validated using the Oncomine database, quantitative real-time PCR (qRT-PCR) and western blot. The Kaplan-Meier method was used to analyze the relationship between Rac3 expression and the prognosis of patients with BC. Cox univariate and multivariate analyses of BC patients overall survival (OS) were performed. Signaling pathways that potentially mediate Rac3 activity in BC were then analyzed by gene set enrichment analysis (GSEA).Results: The Rac3 expression in BC tissues was significantly higher than that in normal bladder tissues. Rac3 expression was significantly correlated with grade and stage. Overexpression of Rac3 was associated with a poor prognosis. GSEA showed that the cell cycle, DNA replication, p53 signaling pathway and mismatch repair were differentially enriched in the high Rac3 expression phenotype. The qRT-PCR and western blot results confirmed that the Rac3 expression in BC tissues was higher than that in normal bladder tissues.Conclusion: Rac3 is highly expressed in BC, which is related to the advanced clinicopathological variables and adverse prognosis of patients with BC. These results provide a new therapeutic target for BC.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Rac3 Expression and its Clinicopathological Significance in Patients With Bladder Cancer

Chen¹,

Nie²,

Cao³

et al. 2021

Pathol. Oncol. Res.

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“…Depending on the training set, Cox proportion hazard regression models were used to screen potential prognostic factors and estimate their weights [ 19 , 20 ]. Univariable Cox regression analysis was performed to explore the potential predictors [ 21 ].…”

Section: Methodsmentioning

confidence: 99%

An easy-to-operate web-based calculator for predicting the progression of chronic kidney disease

Wang

Fang

et al. 2021

J Transl Med

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Background This study aimed to establish and validate an easy-to-operate novel scoring system based on simple and readily available clinical indices for predicting the progression of chronic kidney disease (CKD). Methods We retrospectively evaluated 1045 eligible CKD patients from a publicly available database. Factors included in the model were determined by univariate and multiple Cox proportional hazard analyses based on the training set. Results Independent prognostic factors including etiology, hemoglobin level, creatinine level, proteinuria, and urinary protein/creatinine ratio were determined and contained in the model. The model showed good calibration and discrimination. The area under the curve (AUC) values generated to predict 1-, 2-, and 3-year progression-free survival in the training set were 0.947, 0.931, and 0.939, respectively. In the validation set, the model still revealed excellent calibration and discrimination, and the AUC values generated to predict 1-, 2-, and 3-year progression-free survival were 0.948, 0.933, and 0.915, respectively. In addition, decision curve analysis demonstrated that the model was clinically beneficial. Moreover, to visualize the prediction results, we established a web-based calculator (https://ncutool.shinyapps.io/CKDprogression/). Conclusion An easy-to-operate model based on five relevant factors was developed and validated as a conventional tool to assist doctors with clinical decision-making and personalized treatment.

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“…Fractions of 22 human immune cell subsets in LUAD samples were calculated with Cell-type Identification by Estimating Relative Subsets of RNA Transcripts 6 , which is a computational program for characterizing immune cell compositions based on gene expression profiles (Tang et al, 2020). The proportion of each infiltrating immune cell was calculated based on the absolute mode between the low-and high-risk groups.…”

Section: Immune Infiltration Analysismentioning

confidence: 99%

An Aging-Related Gene Signature-Based Model for Risk Stratification and Prognosis Prediction in Lung Adenocarcinoma

Chen

2021

Front. Cell Dev. Biol.

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Aging is an inevitable time-dependent process associated with a gradual decline in many physiological functions. Importantly, some studies have supported that aging may be involved in the development of lung adenocarcinoma (LUAD). However, no studies have described an aging-related gene (ARG)-based prognosis signature for LUAD. Accordingly, in this study, we analyzed ARG expression data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). After LASSO and Cox regression analyses, a six ARG-based signature (APOC3, EPOR, H2AFX, MXD1, PLCG2, and YWHAZ) was constructed using TCGA dataset that significantly stratified cases into high- and low-risk groups in terms of overall survival (OS). Cox regression analysis indicated that the ARG signature was an independent prognostic factor in LUAD. A nomogram based on the ARG signature and clinicopathological factors was developed in TCGA cohort and validated in the GEO dataset. Moreover, to visualize the prediction results, we established a web-based calculator yurong.shinyapps.io/ARGs_LUAD/. Calibration plots showed good consistency between the prediction of the nomogram and actual observations. Receiver operating characteristic curve and decision curve analyses indicated that the ARG nomogram had better OS prediction and clinical net benefit than the staging system. Taken together, these results established a genetic signature for LUAD based on ARGs, which may promote individualized treatment and provide promising novel molecular markers for immunotherapy.

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A novel risk score based on a combined signature of 10 immune system genes to predict bladder cancer prognosis

Cited by 12 publications

References 39 publications

Rac3 Expression and its Clinicopathological Significance in Patients With Bladder Cancer

Rac3 Expression and its Clinicopathological Significance in Patients With Bladder Cancer

An easy-to-operate web-based calculator for predicting the progression of chronic kidney disease

An Aging-Related Gene Signature-Based Model for Risk Stratification and Prognosis Prediction in Lung Adenocarcinoma

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