Continuous saline bladder irrigation for two hours following transurethral resection of bladder tumors in patients with non-muscle invasive bladder cancer does not prevent recurrence or progression compared with intravesical Mitomycin-C.

BackgroundIntravesical Mitomycin-C (MMC) following transurethral resection of bladder tumor (TURBT), while efficacious, is associated with side effects and poor utilization. Continuous saline bladder irrigation (CSBI) has been examined as an alternative. In this study we sought to compare the rates of recurrence and/or progression in patients with NMIBC who were treated with either MMC or CSBI after TURBT.MethodsWe retrospectively reviewed records of patients with NMIBC at our institution in 2012-2015. Perioperative use of MMC (40 mg in 20 mL), CSBI (two hours), or neither were recorded. Primary outcome was time to recurrence or progression. Descriptive statistics, chi-squared analysis, Kaplan-Meier survival analysis, and Cox multivariable regression analyses were performed.Results205 patients met inclusion criteria. Forty-five (22.0%) patients received CSBI, 71 (34.6%) received MMC, and 89 (43.4%) received no perioperative therapy. On survival analysis, MMC was associated with improved DFS compared with CSBI (p = 0.001) and no treatment (p = 0.0009). On multivariable analysis, high risk disease was associated with increased risk of recurrence or progression (HR 2.77, 95% CI: 1.28-6.01), whereas adjuvant therapy (HR 0.35, 95% CI: 0.20-0.59) and MMC (HR 0.43, 95% CI: 0.25-0.75) were associated with decreased risk.ConclusionsPostoperative MMC was associated with improved DFS compared with CSBI and no treatment. The DFS benefit seen with CSBI in other studies may be limited to patients receiving prolonged irrigation. New intravesical agents being evaluated may consider saline as a control given our data demonstrating that short-term CSBI is not superior to TURBT alone

Shed urinary ALCAM is an independent prognostic biomarker of three-year overall survival after cystectomy in patients with bladder cancer.

Proteins involved in tumor cell migration can potentially serve as markers of invasive disease. Activated Leukocyte Cell Adhesion Molecule (ALCAM) promotes adhesion, while shedding of its extracellular domain is associated with migration. We hypothesized that shed ALCAM in biofluids could be predictive of progressive disease. ALCAM expression in tumor (n = 198) and shedding in biofluids (n = 120) were measured in two separate VUMC bladder cancer cystectomy cohorts by immunofluorescence and enzyme-linked immunosorbent assay, respectively. The primary outcome measure was accuracy of predicting 3-year overall survival (OS) with shed ALCAM compared to standard clinical indicators alone, assessed by multivariable Cox regression and concordance-indices. Validation was performed by internal bootstrap, a cohort from a second institution (n = 64), and treatment of missing data with multiple-imputation. While ALCAM mRNA expression was unchanged, histological detection of ALCAM decreased with increasing stage (P = 0.004). Importantly, urine ALCAM was elevated 17.0-fold (P < 0.0001) above non-cancer controls, correlated positively with tumor stage (P = 0.018), was an independent predictor of OS after adjusting for age, tumor stage, lymph-node status, and hematuria (HR, 1.46; 95% CI, 1.03-2.06; P = 0.002), and improved prediction of OS by 3.3% (concordance-index, 78.5% vs. 75.2%). Urine ALCAM remained an independent predictor of OS after accounting for treatment with Bacillus Calmette-Guerin, carcinoma in situ, lymph-node dissection, lymphovascular invasion, urine creatinine, and adjuvant chemotherapy (HR, 1.10; 95% CI, 1.02-1.19; P = 0.011). In conclusion, shed ALCAM may be a novel prognostic biomarker in bladder cancer, although prospective validation studies are warranted. These findings demonstrate that markers reporting on cell motility can act as prognostic indicators

Clinical proteomics for precision medicine: the bladder cancer case

Precision medicine can improve patient management by guiding therapeutic decision based on molecular characteristics. The concept has been extensively addressed through the application of –omics based approaches. Proteomics attract high interest, as proteins reflect a “real-time” dynamic molecular phenotype. Focusing on proteomics applications for personalized medicine, a literature search was conducted to cover: a) disease prevention, b) monitoring/ prediction of treatment response, c) stratification to guide intervention and d) identification of drug targets. The review indicates the potential of proteomics for personalized medicine by also highlighting multiple challenges to be addressed prior to actual implementation. In oncology, particularly bladder cancer, application of precision medicine appears especially promising. The high heterogeneity and recurrence rates together with the limited treatment options, suggests that earlier and more efficient intervention, continuous monitoring and the development of alternative therapies could be accomplished by applying proteomics-guided personalized approaches. This notion is backed by studies presenting biomarkers that are of value in patient stratification and prognosis, and by recent studies demonstrating the identification of promising therapeutic targets. Herein, we aim to present an approach whereby combining the knowledge on biomarkers and therapeutic targets in bladder cancer could serve as basis towards proteomics- guided personalized patient management

Treatment of non-muscle invasive bladder cancer with Bacillus Calmette–Guerin (BCG): Biological markers and simulation studies

AbstractIntravesical Bacillus Calmette–Guerin (BCG) vaccine is the preferred first line treatment for non-muscle invasive bladder carcinoma (NMIBC) in order to prevent recurrence and progression of cancer. There is ongoing need for the rational selection of i) BCG dose, ii) frequency of BCG administration along with iii) synergistic adjuvant therapy and iv) a reliable set of biochemical markers relevant to tumor response. In this review we evaluate cellular and molecular markers pertinent to the immunological response triggered by the BCG instillation and respective mathematical models of the treatment. Specific examples of markers include diverse immune cells, genetic polymorphisms, miRNAs, epigenetics, immunohistochemistry and molecular biology ‘beacons’ as exemplified by cell surface proteins, cytokines, signaling proteins and enzymes. We identified tumor associated macrophages (TAMs), human leukocyte antigen (HLA) class I, a combination of Ki-67/CK20, IL-2, IL-8 and IL-6/IL-10 ratio as the most promising markers for both pre-BCG and post-BCG treatment suitable for the simulation studies.The intricate and patient-specific nature of these data warrants the use of powerful multi-parametral mathematical methods in combination with molecular/cellular biology insight and clinical input

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Joint Parametric Modeling and Estimation of Time to Cancer Recurrence and Disease Stage at Recurrence.

A clinical trial with bladder cancer patients who went through surgery and were followed up for tumor recurrence was used as motivation for this research. The surgery was conducted on patients with an early bladder cancer stage. During the follow-up, patients were evaluated for cancer recurrence at 3 months, 6 months, 9 months, and at about 5 year visits unless they had cancer recurrence in between visits or died prior to a scheduled visit. One of the main objectives of the study was to evaluate the time to cancer recurrence. At the time of cancer recurrence, the disease stage was also evaluated. The stage of the cancer at recurrence significantly impacts future treatment and quality of life. Therefore, modeling and analyzing the time to cancer recurrence and the stage at recurrence jointly makes more sense than an analysis based on the time to recurrence alone. In our research, we describe a model for the joint distribution of time to recurrence and cancer stage at recurrence that accounts for the recurrence caused by the cancer cells surviving treatment or surgery, and for the recurrence caused by spontaneous carcinogenesis. First, we proceeded with a continuous follow-up assumption using stochastic models of cancer recurrence. Then we extend the approach to allow for a discrete follow-up process. We provide methods for full maximum likelihood estimation based on the EM algorithm. The methods are illustrated through modeling and estimation of data from a clinical trial in patients with bladder cancer described above. Simulations are used to assess the sensitivity of the methods. An added benefit of such modeling is that it permits using the cancer stage at recurrence to provide adjusted estimates for the time to recurrence distribution and allows for more powerful inference.Ph.D.StatisticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91378/1/olgavm_1.pd

Optimal Management of High-Risk T1G3 Bladder Cancer: A Decision Analysis

Using a Markov model, Shabbir Alibhai and colleagues develop a decision analysis comparing cystectomy with conservative treatment for high-risk superficial bladder cancer depending on patient age, comorbid conditions, and preferences

MicroRNA expression profile identifies high grade, non-muscle-invasive bladder tumors at elevated risk to progress to an invasive phenotype

Abstract: The objective of this study was to identify a panel of microRNAs (miRNAs) differentially expressed in high-grade non-muscle invasive (NMI; TaG3–T1G3) urothelial carcinoma that progress to muscle-invasive disease compared to those that remain non-muscle invasive, whether recurrence happens or not. Eighty-nine high-grade NMI urothelial carcinoma lesions were identified and total RNA was extracted from paraffin-embedded tissue. Patients were categorized as either having a non-muscle invasive lesion with no evidence of progression over a 3-year period or as having a similar lesion showing progression to muscle invasion over the same period. In addition, comparison of miRNA expression levels between patients with and without prior intravesical therapy was performed. Total RNA was pooled for microarray analysis in each group (non-progressors and progressors), and qRT-PCR of individual samples validated differential expression between non-progressive and progressive lesions. MiR-32-5p, -224-5p, and -412-3p were associated with cancer-specific survival. Downregulation of miR-203a-3p and miR-205-5p were significantly linked to progression in non-muscle invasive bladder tumors. These miRNAs include those implicated in epithelial mesenchymal transition, previously identified as members of a panel characterizing transition from the non-invasive to invasive phenotype in bladder tumors. Furthermore, we were able to identify specific miRNAs that are linked to postoperative outcome in patients with high grade NMI urothelial carcinoma of the bladder (UCB) that progressed to muscle-invasive (MI) disease