A six-gene prognostic model predicts overall survival in bladder cancer patients

Abstract

Background The fatality and recurrence rates of bladder cancer (BC) have progressively increased. DNA methylation is an influential regulator associated with gene transcription in the pathogenesis of BC. We describe a comprehensive epigenetic study performed to analyse DNA methylation-driven genes in BC. Methods Data related to DNA methylation, the gene transcriptome and survival in BC were downloaded from The Cancer Genome Atlas (TCGA). MethylMix was used to detect BC-specific hyper-/hypo-methylated genes. Metascape was used to carry out gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. A least absolute shrinkage and selection operator (LASSO)-penalized Cox regression was conducted to identify the characteristic dimension decrease and distinguish prognosis-related methylation-driven genes. Subsequently, we developed a six-gene risk evaluation model and a novel prognosis-related nomogram to predict overall survival (OS). A survival analysis was carried out to explore the individual prognostic significance of the six genes. Results In total, 167 methylation-driven genes were identified. Based on the LASSO Cox regression, six genes, i.e., ARHGDIB, LINC00526, IDH2, ARL14, GSTM2, and LURAP1, were selected for the development of a risk evaluation model. The Kaplan–Meier curve indicated that patients in the low-risk group had considerably better OS (P = 1.679e−05). The area under the curve (AUC) of this model was 0.698 at 3 years of OS. The verification performed in subgroups demonstrated the validity of the model. Then, we designed an OS-associated nomogram that included the risk score and clinical factors. The concordance index of the nomogram was 0.694. The methylation levels of IDH2 and ARL14 were appreciably related to the survival results. In addition, the methylation and gene expression-matched survival analysis revealed that ARHGDIB and ARL14 could be used as independent prognostic indicators. Among the six genes, 6 methylation sites in ARHGDIB, 3 in GSTM2, 1 in ARL14, 2 in LINC00526 and 2 in LURAP1 were meaningfully associated with BC prognosis. In addition, several abnormal methylated sites were identified as linked to gene expression. Conclusion We discovered differential methylation in BC patients with better and worse survival and provided a risk evaluation model by merging six gene markers with clinical characteristics.

Development and verification of immune-related long non-coding RNA prognostic signature in bladder cancer

“…The ROC curve analysis, C-index, calibration curves, and DCA con rmed the model's predictive power. Compared to models based on other sequencing data, the prognostic model constructed by immune-related lncRNAs presented better e cacy according to ROC curve method [23][24][25][26].…”

A robust eleven-genes prognostic model can predict overall survival in bladder cancer patients based on five cohorts

“…Bladder cancer is a heterogeneous disease with a high incidence and recurrence rate, but there is no robust predictive tool to guide clinical treatment [5]. Some recent studies have also constructed a new model for bladder cancer, such as DNA methylation-driven genes related model [23] and immune genes related model [24]. These models prefer to take a kind of gene set to build the model, rather than the whole genome into the screening.…”

The Role of ARF Family Proteins and Their Regulators and Effectors in Cancer Progression: A Therapeutic Perspective

“…A recent study reported that ARL14 silencing in lung cancer cells blocks ERK1/2 and p28 signaling and upregulates the cell death inducing DFFA-like effector C (CIDEC), leading to cell cycle arrest (Guo et al, 2019). Also, hypermethylation of ARL14 was found to be correlated with a poor prognosis of bladder cancer patients (Wang L. et al, 2019).…”