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Integrative Pathway Analysis of Metabolic Signature in Bladder Cancer: a Linkage to the Cancer Genome Atlas Project and Prediction of Survival

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Integrative Pathway Analysis of Metabolic Signature in Bladder Cancer: a Linkage to the Cancer Genome Atlas Project and Prediction of Survival Integrative Pathway Analysis of Metabolic Signature in Bladder Cancer: A Linkage to The Cancer Genome Atlas Project and Prediction of Survival Friedrich-Carl von Rundstedt,* Kimal Rajapakshe,* Jing Ma, James M. Arnold, Jie Gohlke, Vasanta Putluri, Rashmi Krishnapuram, D. Badrajee Piyarathna, Yair Lotan, Daniel Godde,€ Stephan Roth, Stephan Storkel,€ Jonathan M. Levitt, George Michailidis, Arun Sreekumar, Seth P. Lerner, Cristian Coarfa† and Nagireddy Putluri† From the Scott Department of Urology (FCvR, JML, SPL), Department of Molecular and Cell Biology, Alkek Center for Molecular Discovery (KR, JMA, JG, RK, DBP, AS, CC, NP), Verna and Marrs McLean Department of Biochemistry (AS), Advanced Technology Core (VP, DBP, AS, NP) and Department of Pathology and Immunology (JML), Baylor College of Medicine, Houston and Department of Urology, University of Texas Southwestern Medical Center (YL), Dallas, Texas, Departments of Urology (FCvR, SR) and Pathology Helios Klinikum (DG, SS), Witten-Herdecke University, Wuppertal, Germany, and Department of Statistics, University of Michigan (JM, GM), Ann Arbor, Michigan Purpose: We used targeted mass spectrometry to study the metabolic fingerprint of urothelial cancer and determine whether the biochemical pathway analysis Abbreviations and Acronyms gene signature would have a predictive value in independent cohorts of patients ¼ with bladder cancer. BCa bladder cancer Materials and Methods: Pathologically evaluated, bladder derived tissues, including benign adjacent tissue from 14 patients and bladder cancer from 46, were analyzed by liquid chromatography based targeted mass spectrometry. Differen- tial metabolites associated with tumor samples in comparison to benign tissue were identified by adjusting the p values for multiple testing at a false discovery rate threshold of 15%. Enrichment of pathways and processes associated with the metabolic signature were determined using the GO (Gene Ontology) Database and MSigDB (Molecular Signature Database). Integration of metabolite alterations with transcriptome data from TCGA (The Cancer Genome Atlas) was done to identify the molecular signature of 30 metabolic genes. Available outcome data from TCGA portal were used to determine the association with survival. Results: We identified 145 metabolites, of which analysis revealed 31 differential metabolites when comparing benign and tumor tissue samples. Using the KEGG Accepted for publication January 7, 2016. No direct or indirect commercial incentive associated with publishing this article. The corresponding author certifies that, when applicable, a statement(s) has been included in the manuscript documenting institutional review board, ethics committee or ethical review board study approval; principles of Helsinki Declaration were followed in lieu of formal ethics committee approval; institutional animal care and use committee approval; all human subjects provided written informed consent with gua- rantees of confidentiality; IRB approved protocol number; animal approved project number. Supported by a grant from the German Research Foundation (FCvR), T32 fellowship T32CA174647 (JG), Dan L. Duncan Cancer Center (NP), American Cancer Society (ACS) Research Scholar Award 127430-RSG-15-105-01-CNE (NP), CPRIT Metabolomics and Proteomic Core Facility Support Award RP120092 (NP and AS), R21-CA185516-01 (AS), U01CA179674-01A1 (AS), a Pilot Grant from Alkek Center for Molecular Discovery (CC), Alkek Center for Molecular Discovery funds, Mass Spectrometry Center of Excellence by Agilent and the Baylor College of Medicine Shared Resources Metabolomics, Pathology and Histology Core with National Institutes of Health funding (NCI P30-CA125123). * Equal study contribution. † Correspondence: Department of Molecular and Cell Biology, Alkek Center for Molecular Discovery, Baylor College of Medicine, 1 Baylor Pl., Houston, Texas 77030 (telephone: 713-798-3139; e-mail: [email protected] or [email protected] [bioinformatics]). See Editorial on page 1645. 0022-5347/16/1956-1911/0 http://dx.doi.org/10.1016/j.juro.2016.01.039 THE JOURNAL OF UROLOGY® Vol. 195, 1911-1919, June 2016 www.jurology.com j 1911 Ó 2016 by AMERICAN UROLOGICAL ASSOCIATION EDUCATION AND RESEARCH,INC. Printed in U.S.A. Open access under CC BY license. 1912 INTEGRATIVE PATHWAY ANALYSIS OF METABOLIC SIGNATURE IN BLADDER CANCER (Kyoto Encyclopedia of Genes and Genomes) Database we identified a total of 174 genes that correlated with the altered metabolic pathways involved. By integrating these genes with the transcriptomic data from the corresponding TCGA data set we identified a metabolic signature consisting of 30 genes. The signature was significant in its prediction of survival in 95 patients with a low signature score vs 282 with a high signature score (p ¼ 0.0458). Conclusions: Targeted mass spectrometry of bladder cancer is highly sensitive for detecting metabolic alterations. Applying transcriptome data allows for integration into larger data sets and identification of relevant metabolic pathways in bladder cancer progression. Key Words: urinary bladder neoplasms, urothelium, metabolomics, mass spectrometry, metabolic networks and pathways UROTHELIAL BCa is the second most prevalent uro- cancergenome.nih.gov/) has provided us with novel logical malignancy and the fourth most common insights into molecular subgroups and potential cause of cancer in men in the United States.1 targets for targeted therapies.6 We have asked the Because most patients present with nonmuscle question of whether we could define a metabolic invasive BCa at the time of diagnosis, this cancer gene signature associated with progression and can be managed by bladder sparing approaches. survival by integrating metabolomic pathway anal- Conversely most patients who present with gross ysis based on a validated targeted mass spectrom- hematuria will have muscle invasive disease. The etry platform with TCGA transcriptome profiles. biological processes that are associated with tumor Our report provides insight into metabolic path- progression are poorly understood. ways that are potentially associated with tumori- While radical cystectomy offers excellent survival genesis and tumor progression. rates for organ confined disease, the outcome is inferior in patients with advanced disease as well as those who undergo delayed cystectomy for non- PATIENTS AND METHODS muscle invasive BCa.2 A significant limitation in the management of advanced disease is the inability Bladder Tumor Metabolomic Profiling A total of 60 pathologically verified tissues, including to predict the patients who are most likely to benign adjacent tissue from 14 patients and BCa from 46 respond to systemic chemotherapy. A wide spec- (table 1), were obtained from the tumor banks of the trum of urinary and molecular markers has been participating institutions (Baylor College of Medicine, evaluated but none have been shown to predict the University of Texas Southwestern Medical Center and 3 natural history of BCa in the clinical setting. University of Witten-Herdecke). All samples were de- Physicians currently rely predominantly on histo- identified and included in study under an institutional logical grade and primary tumor stage from initial review board approved protocol (H-35808). bladder tumor resection as well as cross-sectional Flash frozen, macrodissected tumor samples as well imaging to assess the risk of disease progression as adjacent noncancerous tissues were reviewed by a in individual patients. Unlike other tumors BCa is closely linked to environmental carcinogens, including tobacco, Table 1. Clinical characteristics of 60 patients polyaromatic hydrocarbons, aniline, benzidine, No. Pts (%) naphthylamine and multiple other compounds.4 Our Pathological stage: group has previously performed unbiased meta- Ta 1 (2) bolic profiling of bladder derived tissues and was T1 1 (2) able to report the accumulation of aromatic com- T2 12 (19) 5 T3 23 (37) pounds and xenobiotic compounds in tumors. In T4 9 (14) this context elevated levels of SAM (S-adenosyl Normal 14 (22) methionine) were indicative of increased methyl- Grade:* High 44 (96) ation potential in these tumors. Notably the latter Missing 2 (4) contributes to the decreased expression of enzymes Lymph node metastasis: in the cytochrome driven phase I metabolic path- Present 21 (45) Absent 25 (53) way, which could potentially lead to alterations in Neoadjuvant chemotherapy: precarcinogen metabolism in bladder tissues. Present 6 (13) A recently published, comprehensive molecular Absent 40 (85) analysis of urothelial BCa from TCGA (http:// *No low grade BCa. INTEGRATIVE PATHWAY ANALYSIS OF METABOLIC SIGNATURE IN BLADDER CANCER 1913 Figure 1. Overview of strategy used to profile and characterize BCa metabolome genitourinary pathologist. Of 46 tumor samples 44 were overview of the metabolomic profiling and the associated muscle invasive bladder tumors and 21 patients were data analysis strategy used in this study. The chro- found to have lymph node metastasis at the time of tissue matographic separation of metabolites and analysis by collection. Tissue was retrieved at transurethral tumor mass spectrometry were monitored for drifts using in- resection or cystectomy. All patients ultimately under- ternal standards and biological replicates of pooled went radical cystectomy and pathological tumor stage was extract of mouse liver and were found to be highly available for all. Six of the 46 patients received neo- reproducible. adjuvant chemotherapy. Tissues were analyzed by liquid
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