Upregulation of IFNɣ-mediated chemokines dominate the immune transcriptome of muscle-invasive urothelial carcinoma

Tumor inflammation is prognostically significant in high-grade muscle-invasive bladder cancer (MIBC). However, the underlying mechanisms remain elusive. To identify inflammation-associated immune gene expression patterns, we performed transcriptomic profiling of 40 MIBC archival tumors using the NanoString nCounter Human v.1.1 PanCancer Panel. Findings were validated using the TCGA MIBC dataset. Unsupervised and supervised clustering identified a distinctive immune-related gene expression profile for inflammation, characterized by significant upregulation of 149 genes, particularly chemokines, a subset of which also had potential prognostic utility. Some of the most enriched biological processes were lymphocyte activation and proliferation, leukocyte adhesion and migration, antigen processing and presentation and cellular response to IFN-γ. Upregulation of numerous IFN-γ-inducible chemokines, class II MHC molecules and immune checkpoint genes was detected as part of the complex immune response to MIBC. Further, B-cell markers linked to tertiary lymphoid structures were upregulated, which in turn is predictive of tumor response to immunotherapy and favorable outcome. Our findings of both an overall activated immune profıle and immunosuppressive microenvironment provide novel insights into the complex immune milieu of MIBC with inflammation and supports its clinical significance for predicting prognosis and immunotherapeutic responsiveness, which warrants further investigation. This may open novel opportunities to identify mechanisms for developing new immunotherapeutic strategies

Epigenetic Analysis of the Kallikrein Gene Family and Associated Pathways as a Novel Panel of Prostate Cancer Biomarkers

Aberrant epigenetic landscape is a hallmark of prostate cancer (PCa), one of the most common cancers among men worldwide. Currently, improved understanding of the molecular mechanisms driving PCa pathogenesis as well as biomarkers for improved diagnosis, prognosis and treatment of the disease are needed. Kallikrein related peptidases (KLKs) have emerged as important cancer biomarkers. However, the mechanisms leading to their deregulation in PCa are poorly understood. This thesis characterized the clinical impact of epigenetic mechanisms that regulate KLKs and associated genes contributing to PCa pathogenesis. Utilizing genome-wide DNA methylation profiling and quantitative MethyLight technology, novel tumor-specific hypermethylation of KLK6 and KLK10 was identified in PCa. KLK10 DNA methylation was associated with pathological stage and longer time to biochemical recurrence in two independent cohorts of PCa patients. KLK6 hypermethylation was observed in normal-appearing prostate tissue adjacent to PCa, which could be indicative of the epigenetic field effect. Through the use of qPCR microRNA arrays a signature of 42 upregulated microRNAs predicted to target KLKs was identified in association with Gleason score (GS)8 vs. GS6, but no signature was found in correlation with biochemical recurrence. Among these, the association of increased miR-137 with increasing GS was established in an independent cohort. Notably, expression of miR-137, predicted to target KLK10, was inversely correlated to KLK10 hypermethylation. The emerging independent clinical significance of clinicopathologic entities such as intraductal carcinoma (IDC) and carcinoma with cribriform architecture in PCa prognosis was further explored by investigating DNA hypermethylation alterations of selected candidate genes including KLK10 in association with these clinicopathologic entities. Although KLK10 methylation did not correlate with either IDC or cribriform architecture, the previously discovered methylation of APC, RASSF1A and TBX15 was significantly linked to these features in PCa. Further, the presence of large cribriform architecture or HOXD3 hypermethylation was a strong independent predictor of biochemical recurrence. Thus, this thesis presents a panel of methylated genes that demonstrated promising prognostic performance and investigated their role in the etiology of PCa. Accordingly, a novel multiplex MethyLight assay was developed for simultaneous analysis of three methylated genes with potential applications in research and clinical settings.Ph.D.2017-06-08 00:00:0

Measuring Kinetic Isotope Effects in Enzyme Reactions Using Time-Resolved Electrospray Mass Spectrometry

Kinetic isotope effect (KIE) measurements are a powerful tool for studying enzyme mechanisms; they can provide insights into microscopic catalytic processes and even structural constraints for transition states. However, KIEs have not come into widespread use in enzymology, due in large part to the requirement for prohibitively cumbersome experimental procedures and daunting analytical frameworks. In this work, we introduce time-resolved electrospray ionization mass spectrometry (TRESI-MS) as a straightforward, precise, and inexpensive method for measuring KIEs. Neither radioisotopes nor large amounts of material are needed and kinetic measurements for isotopically “labeled” and “unlabeled” species are acquired simultaneously in a single “competitive” assay. The approach is demonstrated first using a relatively large isotope effect associated with yeast alcohol dehydrogenase (YADH) catalyzed oxidation of ethanol. The measured macroscopic KIE of 2.19 ± 0.05 is consistent with comparable measurements in the literature but cannot be interpreted in a way that provides insights into isotope effects in individual microscopic steps. To demonstrate the ability of TRESI-MS to directly measure intrinsic KIEs and to characterize the precision of the technique, we measure a much smaller ¹²C/¹³C KIE associated specifically with presteady state acylation of chymotrypsin during hydrolysis of an ester substrate

Development of a Clinically Applicable NanoString-Based Gene Expression Classifier for Muscle-Invasive Bladder Cancer Molecular Stratification

Transcriptional profiling of muscle-invasive bladder cancer (MIBC) using RNA sequencing (RNA-seq) technology has demonstrated the existence of intrinsic basal and luminal molecular subtypes that vary in their prognosis and response to therapy. However, routine use of RNA-seq in a clinical setting is restricted by cost and technical difficulties. Herein, we provide a single-sample NanoString-based seven-gene (KRT5, KRT6C, SERPINB13, UPK1A, UPK2, UPK3A and KRT20) MIBC molecular classifier that assigns a luminal and basal molecular subtype. The classifier was developed in a series of 138 chemotherapy naïve MIBCs split into training (70%) and testing (30%) datasets. Further, we validated the previously published CK5/6 and GATA3 immunohistochemical classifier which showed high concordance of 96.9% with the NanoString-based gene expression classifier. Immunohistochemistry-based molecular subtypes significantly correlated with recurrence-free survival (RFS) and disease-specific survival (DSS) in univariable (p  =  0.006 and p  =  0.011, respectively) and multivariate cox regression analysis for DSS (p = 0.032). Used sequentially, the immunohistochemical- and NanoString-based classifiers provide faster turnaround time, lower cost per sample and simpler data analysis for ease of clinical implementation in routine diagnostics

Integrated analysis of epigenomic and genomic changes by DNA methylation dependent mechanisms provides potential novel biomarkers for prostate cancer

Epigenetic silencing mediated by CpG methylation is a common feature of many cancers. Characterizing aberrant DNA methylation changes associated with tumor progression may identify potential prognostic markers for prostate cancer (PCa). We treated two PCa cell lines, 22Rv1 and DU-145 with the demethylating agent 5-Aza 2’–deoxycitidine (DAC) and global methylation status was analyzed by performing methylation-sensitive restriction enzyme based differential methylation hybridization strategy followed by genome-wide CpG methylation array profiling. In addition, we examined gene expression changes using a custom microarray. Gene Set Enrichment Analysis (GSEA) identified the most significantly dysregulated pathways. In addition, we assessed methylation status of candidate genes that showed reduced CpG methylation and increased gene expression after DAC treatment, in Gleason score (GS) 8 vs. GS6 patients using three independent cohorts of patients; the publically available The Cancer Genome Atlas (TCGA) dataset, and two separate patient cohorts. Our analysis, by integrating methylation and gene expression in PCa cell lines, combined with patient tumor data, identified novel potential biomarkers for PCa patients. These markers may help elucidate the pathogenesis of PCa and represent potential prognostic markers for PCa patients

Epigenome-wide DNA methylation profiling identifies differential methylation biomarkers in high-grade bladder cancer

Epigenetic changes, including CpG island hypermethylation, occur frequently in bladder cancer (BC) and may be exploited for BC detection and distinction between high-grade (HG) and low-grade (LG) disease. Genome-wide methylation analysis was performed using Agilent Human CpG Island Microarrays to determine epigenetic differences between LG and HG cases. Pathway enrichment analysis and functional annotation determined that the most frequently methylated pathways in HG BC were enriched for anterior/posterior pattern specification, embryonic skeletal system development, neuron fate commitment, DNA binding, and transcription factor activity. We identified 990 probes comprising a 32-gene panel that completely distinguished LG from HG based on methylation. Selected genes from this panel, EOMES, GP5, PAX6, TCF4, and ZSCAN12, were selected for quantitative polymerase chain reaction-based validation by MethyLight in an independent series (n=84) of normal bladder samples and LG and HG cases. GP5 and ZSCAN12, two novel methylated genes in BC, were significantly hypermethylated in HG versus LG BC (P≤.03). We validated our data in a second independent cohort of LG and HG BC cases (n=42) from The Cancer Genome Atlas (TCGA). Probes representing our 32-gene panel were significantly differentially methylated in LG versus HG tumors (P≤.04). These results indicate the ability to distinguish normal tissue from cancer, as well as LG from HG, based on methylation and reveal important pathways dysregulated in HG BC. Our findings were corroborated using publicly available data sets from TCGA. Ultimately, the creation of a methylation panel, including GP5 and ZSCAN12, able to distinguish between disease phenotypes will improve disease management and patient outcomes