Sunny Guin1, Courtney Pollard1, Yuanbin Ru1, Carolyn Ritterson Lew1, Jason E Duex1, Garrett Dancik1, Charles Owens1, Andrea Spencer1, Scott Knight1, Heather Holemon1, Sounak Gupta1, Donna Hansel1, Marc Hellerstein1, Pawel Lorkiewicz1, Andrew N Lane1, Teresa W-M Fan1, Dan Theodorescu2. 1. Affiliations of authors: Department of Surgery (SGui, CP, YR, CRL, JED, GD, CO, DT) and Department of Pharmacology (SGui, CP, YR, CRL, JED, GD, CO, DT), University of Colorado, Denver, CO; Sigma-Aldrich Research Biotech, Saint Louis, MO (AS, SK, HH); Department of Pathology, Cleveland Clinic, Cleveland, OH (SGup, DH); Department of Nutritional Sciences and Toxicology, University of California at Berkeley, Berkeley, CA (MH); Department of Medicine, University of California at San Francisco, San Francisco, CA (MH); Center for Regulatory and Environmental Analytical Metabolomics, Department of Chemistry, University of Louisville, Louisville, KY (PL); Graduate Center of Toxicology, Biopharm Complex, University of Kentucky, Lexington, KY (ANL, TW-MF); University of Colorado Comprehensive Cancer Center, Denver, CO (DT). Present affiliations: Department of Biomedical Informatics, Windber Research Institute, Windber, PA (YR); Mathematics and Computer Science Department, Eastern Connecticut State University, Willimantic, CT (GD). 2. Affiliations of authors: Department of Surgery (SGui, CP, YR, CRL, JED, GD, CO, DT) and Department of Pharmacology (SGui, CP, YR, CRL, JED, GD, CO, DT), University of Colorado, Denver, CO; Sigma-Aldrich Research Biotech, Saint Louis, MO (AS, SK, HH); Department of Pathology, Cleveland Clinic, Cleveland, OH (SGup, DH); Department of Nutritional Sciences and Toxicology, University of California at Berkeley, Berkeley, CA (MH); Department of Medicine, University of California at San Francisco, San Francisco, CA (MH); Center for Regulatory and Environmental Analytical Metabolomics, Department of Chemistry, University of Louisville, Louisville, KY (PL); Graduate Center of Toxicology, Biopharm Complex, University of Kentucky, Lexington, KY (ANL, TW-MF); University of Colorado Comprehensive Cancer Center, Denver, CO (DT). Present affiliations: Department of Biomedical Informatics, Windber Research Institute, Windber, PA (YR); Mathematics and Computer Science Department, Eastern Connecticut State University, Willimantic, CT (GD). dan.theodorescu@ucdenver.edu.
Abstract
BACKGROUND: Bladder cancer is the most common malignancy of the urinary system, yet our molecular understanding of this disease is incomplete, hampering therapeutic advances. METHODS: Here we used a genome-wide functional short-hairpin RNA (shRNA) screen to identify suppressors of in vivo bladder tumor xenograft growth (n = 50) using bladder cancer UMUC3 cells. Next-generation sequencing was used to identify the most frequently occurring shRNAs in tumors. Genes so identified were studied in 561 patients with bladder cancer for their association with stratification of clinical outcome by Kaplan-Meier analysis. The best prognostic marker was studied to determine its mechanism in tumor suppression using anchorage-dependent and -independent growth, xenograft (n = 20), and metabolomic assays. Statistical significance was determined using two-sided Student t test and repeated-measures statistical analysis. RESULTS: We identified the glycogen debranching enzyme AGL as a prognostic indicator of patient survival (P = .04) and as a novel regulator of bladder cancer anchorage-dependent (P < .001), anchorage-independent (mean ± standard deviation, 180 ± 23.1 colonies vs 20±9.5 in control, P < .001), and xenograft growth (P < .001). Rescue experiments using catalytically dead AGL variants revealed that this effect is independent of AGL enzymatic functions. We demonstrated that reduced AGL enhances tumor growth by increasing glycine synthesis through increased expression of serine hydroxymethyltransferase 2. CONCLUSIONS: Using an in vivo RNA interference screen, we discovered that AGL, a glycogen debranching enzyme, has a biologically and statistically significant role in suppressing human cancer growth.
BACKGROUND:Bladder cancer is the most common malignancy of the urinary system, yet our molecular understanding of this disease is incomplete, hampering therapeutic advances. METHODS: Here we used a genome-wide functional short-hairpin RNA (shRNA) screen to identify suppressors of in vivo bladder tumor xenograft growth (n = 50) using bladder cancer UMUC3 cells. Next-generation sequencing was used to identify the most frequently occurring shRNAs in tumors. Genes so identified were studied in 561 patients with bladder cancer for their association with stratification of clinical outcome by Kaplan-Meier analysis. The best prognostic marker was studied to determine its mechanism in tumor suppression using anchorage-dependent and -independent growth, xenograft (n = 20), and metabolomic assays. Statistical significance was determined using two-sided Student t test and repeated-measures statistical analysis. RESULTS: We identified the glycogen debranching enzyme AGL as a prognostic indicator of patient survival (P = .04) and as a novel regulator of bladder cancer anchorage-dependent (P < .001), anchorage-independent (mean ± standard deviation, 180 ± 23.1 colonies vs 20±9.5 in control, P < .001), and xenograft growth (P < .001). Rescue experiments using catalytically dead AGL variants revealed that this effect is independent of AGL enzymatic functions. We demonstrated that reduced AGL enhances tumor growth by increasing glycine synthesis through increased expression of serine hydroxymethyltransferase 2. CONCLUSIONS: Using an in vivo RNA interference screen, we discovered that AGL, a glycogen debranching enzyme, has a biologically and statistically significant role in suppressing humancancer growth.
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