BackgroundWhile several molecular markers of bladder cancer prognosis have been identified, the limited value of current prognostic markers has created the need for new molecular indicators of bladder cancer outcomes. The aim of this study was to identify genetic signatures associated with disease prognosis in bladder cancer.ResultsWe used 272 primary bladder cancer specimens for microarray analysis and real-time reverse transcriptase polymerase chain reaction (RT-PCR) analysis. Microarray gene expression analysis of randomly selected 165 primary bladder cancer specimens as an original cohort was carried out. Risk scores were applied to stratify prognosis-related gene classifiers. Prognosis-related gene classifiers were individually analyzed with tumor invasiveness (non-muscle invasive bladder cancer [NMIBC] and muscle invasive bladder cancer [MIBC]) and prognosis. We validated selected gene classifiers using RT-PCR in the original (165) and independent (107) cohorts. Ninety-seven genes related to disease progression among NMIBC patients were identified by microarray data analysis. Eight genes, a progression-related gene classifier in NMIBC, were selected for RT-PCR. The progression-related gene classifier in patients with NMIBC was closely correlated with progression in both original and independent cohorts. Furthermore, no patient with NMIBC in the good-prognosis signature group experienced cancer progression.ConclusionsWe identified progression-related gene classifier that has strong predictive value for determining disease outcome in NMIBC. This gene classifier could assist in selecting NMIBC patients who might benefit from more aggressive therapeutic intervention or surveillance.

We present a molecular signature that can predict, at diagnosis, the likelihood of bladder cancer progression and, possibly, lead to improvements in patient therapy.

Background Gene Expression database of Normal and Tumor tissues 2 (GENT2) is an updated version of GENT, which has provided a user-friendly search platform for gene expression patterns across different normal and tumor tissues compiled from public gene expression data sets. Results We refactored GENT2 with recent technologies such as Apache Lucene indexing for fast search and Google Web Toolkit (GWT) framework for a user-friendly web interface. Now, GENT2 contains more than 68,000 samples and has several new useful functions. First, GENT2 now provides gene expression across 72 different tissues compared to 57 in GENT. Second, with increasing importance of tumor subtypes, GENT2 provides an option to study the differential expression and its prognostic significance based on tumor subtypes. Third, whenever available, GENT2 provides prognostic information of a gene of interest. Fourth, GENT2 provides a meta-analysis of survival information to provide users more reliable prognostic value of a gene of interest. Conclusions In conclusion, with these significant improvements, GENT2 will continue to be a useful tool to a wide range of researchers. GENT2 is freely available at http://gent2.appex.kr . Electronic supplementary material The online version of this article (10.1186/s12920-019-0514-7) contains supplementary material, which is available to authorized users.

Colorectal cancer (CRC) patients frequently experience disease recurrence and distant metastasis. This study aimed to identify prognostic indicators, including individual responses to chemotherapy, in CRC patients. RNA-seq data was generated using 54 samples (normal colon, primary CRC, and liver metastases) from 18 CRC patients and genes associated with CRC aggressiveness were identified. A risk score based on these genes was developed and validated in four independent CRC patient cohorts (n = 1063). Diverse statistical methods were applied to validate the risk scoring system, including a generalized linear model likelihood ratio test, Kaplan-Meier curves, a log-rank test, and the Cox model. TREM1 and CTGF were identified as two activated regulators associated with CRC aggressiveness. A risk score based on 19 genes regulated by TREM1 or CTGF activation (TCA19) was a significant prognostic indicator. In multivariate and subset analyses based on pathological staging, TCA19 was an independent risk factor (HR = 1.894, 95% CI = 1.227-2.809, P = 0.002). Subset stratification in stage III patients revealed that TCA19 had prognostic potential and identified patients who would benefit from adjuvant chemotherapy, regardless of age. The TCA19 predictor represents a novel diagnostic tool for identifying high-risk CRC patients and possibly predicting the response to adjuvant chemotherapy.

Purpose: Previous study identified E2F1 as a key mediator of non-muscle-invasive bladder cancer (NMIBC) progression. The aim of this study was to identify the E2F1-related genes associated with poor prognosis and aggressive characteristics of bladder cancer.Experimental Design: Microarray analysis was performed to find E2F1-related genes associated with tumor progression and aggressiveness in the gene expression data from 165 primary patients with bladder cancer. The biologic activity of E2F1-related genes in tumor progression and aggressiveness was confirmed with experimental assays using bladder cancer cells and tumor xenograft assay.Results: The expression of E2F1 was significantly associated with EZH2 and SUZ12. The overexpression of E2F1, EZH2, and SUZ12 enhanced cancer progression including cell colony formation, migration, and invasiveness. Knockdown of these genes reduced motility, blocked invasion, and decreased tumor size in vivo. E2F1 bound the proximal EZH2 and SUZ12 promoter to activate transcription, suggesting that E2F1 and its downstream effectors, EZH2 and SUZ12, could be important mediators for the cancer progression. In addition, we confirmed an association between these genes and aggressive characteristics. Interestingly, the treatment of anticancer drugs to the cells overexpressing E2F1, EZH2, and SUZ12 induced the expression of CD44, KLF4, OCT4, and ABCG2 known as cancer stem cell (CSC)-related genes.Conclusions: The link between E2F1, EZH2, and/or SUZ12 revealed that E2f1 directly regulates transcription of the EZH2 and SUZ12 genes. The signature of E2F1--EZH2--SUZ12 shows a predictive value for prognosis in bladder tumors and the E2F1-EZH2-SUZ12-driven transcriptional events may regulate the cancer aggressiveness and chemo-resistance, which may provide opportunity for development of new treatment modalities. Clin Cancer Res; 21(23); 5391-403. Ó2015 AACR.

DNA methylation patterns are associated with the development and prognosis of cancer. The aim of this study was to identify novel methylation markers for the prediction of patient outcomes using microarray analysis of DNA methylation and RNA expression patterns in samples from long-term follow-up patients with nonmuscle invasive bladder cancer (NMIBC). A total of 187 human bladder specimens were used for microarray array or pyrosequencing (PSQ) analyses: 6 normal controls (NC) and 181 NMIBC. Tumor-specific hypermethylated genes were selected from a data set comprising 24 matched microarray-based DNA methylation and gene expression profiles (6 controls and 18 NMIBC), and their clinical relevance was verified by quantitative PSQ analysis. The methylation status of Homeobox A9 (HOXA9), ISL LIM homeobox 1 (ISL1) and Aldehyde dehydrogenase 1 family, member A3 (ALDH1A3) was significantly associated with decreased gene expression levels and aggressive clinicopathological characteristics. Multivariate regression analyses showed that hypermethylation of these genes was an independent predictor of disease recurrence (HOXA9, ISL1 and ALDH1A3, either alone or in combination) and progression (ISL1 and ALDH1A3, either alone or in combination) (each p < 0.05). The results of this study suggest that these novel methylation markers are independent prognostic indicators in NMIBC patients, which may facilitate the assessment of disease recurrence and progression in NMIBC patients and inform clinical decision making regarding treatment.

Background: Although various molecular subtypes of bladder cancer (BC) have been investigated, most of these studies have focused on muscle-invasive BC (MIBC). A few studies have investigated non-muscle-invasive BC (NMIBC) or NMIBC and MIBC together, but none has classified progressive NMIBC or immune checkpoint inhibitor (ICI)-based therapeutic responses in early-stage BC patients. Methods: A total of 1,934 samples from seven patient cohorts were used. We performed unsupervised hierarchical clustering to stratify patients into distinct subgroups and constructed a classifier by applying SAM/ PAM algorithms. We then investigated the association between molecular subtypes and immunotherapy responsiveness using various statistical methods. Findings: We explored large-scale genomic datasets encompassing NMIBC and MIBC, redefining four distinct molecular subtypes, including a subgroup containing progressive NMIBC and MIBC with poor prognosis that would benefit from ICI treatment. This subgroup showed poor progression-free survival with the distinct features of high mutation load, activated cell cycle, and inhibited TGFb signalling. Importantly, we verified that BC patients with this subtype were significantly responsive to an anti-PD-L1 agent in the IMvigor210 cohort. Interpretation: Our results reveal an immunotherapeutic option for ICI treatment of highly progressive NMIBC and MIBC with poor prognosis.

Purpose: Although standard treatment with transurethral resection and intravesical therapy (IVT) is known to be effective to address the clinical behavior of non–muscle-invasive bladder cancer (NMIBC), many patients fail to respond to the treatment and frequently experience disease recurrence. Here, we aim to identify a prognostic molecular signature that predicts the NMIBC heterogeneity and response to IVT. Experimental Design: We analyzed the genomic profiles of 102 patients with NMIBC to identify a signature associated with disease recurrence. The validity of the signature was verified in three independent patient cohorts (n = 658). Various statistical methods, including a leave-one-out cross-validation and multivariate Cox regression analyses, were applied to identify a signature. We confirmed an association between the signature and tumor aggressiveness with experimental assays using bladder cancer cell lines. Results: Gene expression profiling in 102 patients with NMIBC identified a CCNB1 signature associated with disease recurrence, which was validated in another three independent cohorts of 658 patients. The CCNB1 signature was shown to be an independent risk factor by a multivariate analysis and subset stratification according to stage and grade [HR, 2.93; 95% confidence intervals (CI), 1.302–6.594; P = 0.009]. The subset analysis also revealed that the signature could identify patients who would benefit from IVT. Finally, gene network analyses and experimental assays indicated that NMIBC recurrence could be mediated by FOXM1–CCNB1–Fanconi anemia pathways. Conclusions: The CCNB1 signature represents a promising diagnostic tool to identify patients with NMIBC who have a high risk of recurrence and to predict response to IVT. Clin Cancer Res; 20(12); 3233–43. ©2014 AACR.