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Abstract Background At present, the extent and clinical relevance of epigenetic differences between upper tract urothelial carcinoma (UTUC) and urothelial carcinoma of the bladder (UCB) remain largely unknown. Here, we conducted a study to describe the global DNA methylation landscape of UTUC and UCB and to address the prognostic value of DNA methylation subtype and responses to the DNA methyltransferase inhibitor SGI-110 in urothelial carcinoma (UC). Methods Using whole-genome bisulfite sequencing (n = 49 samples), we analyzed epigenomic features and profiles of UTUC (n = 36) and UCB (n = 9). Next, we characterized potential links between DNA methylation, gene expression (n = 9 samples), and clinical outcomes. Then, we integrated an independent UTUC cohort (Fujii et al., n = 86) and UCB cohort (TCGA, n = 411) to validate the prognostic significance. Furthermore, we performed an integrative analysis of genome-wide DNA methylation and gene expression in two UC cell lines following transient DNA methyltransferase inhibitor SGI-110 treatment to identify potential epigenetic driver events that contribute to drug efficacy. Results We showed that UTUC and UCB have very similar DNA methylation profiles. Unsupervised DNA methylation classification identified two epi-clusters, Methy-High and Methy-Low, associated with distinct muscle-invasive statuses and patient outcomes. Methy-High samples were hypermethylated, immune-infiltrated, and enriched for exhausted T cells, with poor clinical outcome. SGI-110 inhibited the migration and invasion of Methy-High UC cell lines (UMUC-3 and T24) by upregulating multiple antitumor immune pathways. Conclusions DNA methylation subtypes pave the way for predicting patient prognosis in UC. Our results provide mechanistic rationale for evaluating SGI-110 in treating UC patients in the clinic.

Bladder cancer (BLCA) represents the ninth most common malignant tumor in the world and is characterized by high recurrence risk. Tumor microenvironment (TME) plays an important role in regulating the progression of BLCA. Immunotherapy, including Bacillus Calmette-Guerin (BCG) and programmed cell death protein 1 (PD-1)/programmed death ligand 1 (PD-L1), is closely associated with TME and is widely used for treating BLCA. But parts of BLCA patients have no response to these treatment ways, thus a better understanding of the complex TME of BLCA is still needed. We downloaded the gene expression profile and corresponding clinical information of 414 BLCA patients from the TCGA database. Via the ESTIMATE and CIBERSORT algorithm, we identified the two hub genes (CXCL12 and CD3E) and explored their correlations with immune infiltration. We found that BLCA patients with higher expression of CXCL12 and lower expression of CD3E had prolonged survival. Gene set enrichment analysis (GSEA) revealed that both CXCL12 and CD3E were enriched in immune-related pathways. We also discovered that stromal score and the level of CXCL12 were higher in luminal subtype, and immune score and the level of CD3E were higher in the basal subtype. Furtherly, we found that CXCL12 was associated with naive B cells, resting mast cell, M2 macrophages, follicular helper T cells, and dendritic cells. CD8+ T cells, CD4+ T cells, regulatory T cells (Tregs), and macrophages were correlated with CD3E. In conclusions, we found that CXCL12 and CD3E might serve as indicators of TME modulation in BLCA. Therapy targeting CXCL12 and CD3E had the potential as novel therapeutic strategy.

RNA-binding proteins (RBPs) are a kind of gene regulatory factor that presents a significant biological effect in the initiation and development of various tumors, including bladder cancer (BLCA). However, the RBP-based prognosis signature for BLCA has not been investigated. In this study, we attempted to develop an RBP-based classifier to predict overall survival (OS) for BLCA based on transcriptome analysis. We extracted data of BLCA patients from The Cancer Genome Atlas database (TCGA) and UCSC Xena. Finally, a total of 398 cases without missing clinical data were enrolled and six RBPs (FLNA, HSPG2, AHNAK, FASTKD3, POU5F1, and PCSK9) associated with OS of BLCA were identified through univariate and multivariate Cox regression analysis. Online analyses and immunohistochemistry validated the prognostic value and expression of six RBPs. Risk scores were calculated to divide patients into high-risk and low-risk level, and patients in the high-risk group tended to have a poor prognosis. In addition, the receiver operating characteristic (ROC) curve analysis was performed to assess the prognostic value of RBPs, and the area under the curve (AUC) values were 0.711 and 0.706, respectively, in the training set and validating set. The findings were further validated in an external validation set. Subsequently, the 6-RBP-based signature and pathological stage were used to construct the nomogram to predict the 3- and 5-years OS of BLCA patients. Also, this 6-RBP-based signature was highly related to recurrence-free survival of BLCA. Weighted co-expression network analysis (WGCNA) combined with functional enrichment analysis contributed to study the potential pathways of six RBPs, including keratinocyte differentiation, RHO GTPases activate PNKs, epithelial tube morphogenesis, establishment or maintenance of cell polarity, and so on. In summary, the 6-RBP-based signature holds the potentiality to serve as a novel prognostic predictor of OS for BLCA.

Prolyl 4-hydroxylase, beta polypeptide (P4HB) protein is an endoplasmic reticulum (ER) molecular chaperone protein and has been reported to be overexpressed in multiple tumor types. However, the role of P4HB in bladder cancer (BLCA) has not yet been elucidated. The aim of the present study was to investigate the prognostic value of P4HB and the association between clinicopathological characteristics and P4HB in BLCA. P4HB expression levels were assessed through The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and validated by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and western blot analysis in BLCA tissues and cells. A total of 69 pairs of tumor and normal samples were used to analyze the expression of P4HB via immunohistochemical staining. A co-expression network and functional enrichment analyses were conducted to investigate the biological function of P4HB in BLCA. The protein-protein interaction (PPI) network was constructed by Search Tool for the Retrieval of Interacting Genes. The results showed that P4HB was highly [ABSTRACT FROM AUTHOR]