MP72-19 PLASMA GLYCOSAMINOGLYCAN SCORES IN RENAL CELL CARCINOMA

Abstract

You have accessJournal of UrologyKidney Cancer: Basic Research & Pathophysiology II1 Apr 2018MP72-19 PLASMA GLYCOSAMINOGLYCAN SCORES IN RENAL CELL CARCINOMA Kyle A. Blum, Francesco Gatto, Mazyar Ghannat, Alejandro Sanchez, Francesca Maccari, Fabio Galeotti, James Hsieh, Nicola Volpi, A. Ari Hakimi, and Jens Nielsen Kyle A. BlumKyle A. Blum More articles by this author , Francesco GattoFrancesco Gatto More articles by this author , Mazyar GhannatMazyar Ghannat More articles by this author , Alejandro SanchezAlejandro Sanchez More articles by this author , Francesca MaccariFrancesca Maccari More articles by this author , Fabio GaleottiFabio Galeotti More articles by this author , James HsiehJames Hsieh More articles by this author , Nicola VolpiNicola Volpi More articles by this author , A. Ari HakimiA. Ari Hakimi More articles by this author , and Jens NielsenJens Nielsen More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2018.02.2303AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Glycosaminoglycan (GAG) levels are measurably altered in the plasma of patients with clear cell renal cell carcinoma (ccRCC). GAG scores have been used to detect ccRCC in a cohort of patients with metastatic disease with 92.7% accuracy (Gatto et al, Cell Reports, 2016). However, it is unknown if GAG scores can detect RCC in earlier stages or non-ccRCC histologies. METHODS In this retrospective study, pre-operative plasma GAG levels from 162 RCC patients were compared to 19 healthy controls between 5/2011-2/2014. GAG scores were generated using 19 pre-specified properties and measured using capillary electrophoresis with laser induced fluorescence. GAG profile differences in RCC versus healthy controls were assessed using unsupervised clustering methods. A discovery set of 68 RCC vs. 19 healthy samples were first analyzed to update the historical GAG score. The new GAG score accuracy in RCC detection versus healthy subjects was validated using the remaining 94 RCC samples. RESULTS Median age was similar between RCC and healthy cohorts, 60 years (IQR: 52-67) vs. 55 years (IQR: 50-60), respectively. In the RCC cohort, 113 (70%) were ccRCC and 49 (30%) non-ccRCC. RCC stage included 86 (53%) pT1, 66 (41%) pT2-3, and 12 (7%) pT4. GAG profiles in RCC clustered separately from healthy volunteers (Figure 1A). In the first discovery set (n=68), the GAG score distinguished RCC from healthy subjects with an AUC equal to 0.999, 94.7% specificity and 100% sensitivity at an optimal cut-off equal to 0.87 (Figure 1B). In the validation set (n=94), the GAG score achieved an AUC equal to 0.994 (95% CI: 0.985 - 1) and 95.7% sensitivity (Figure 1B). GAG scores did not correlate with age or gender. GAG scores were elevated in all RCC samples compared to normal controls, irrespective and uncorrelated to stage, grade or histology. CONCLUSIONS Plasma GAG scores are measurably elevated in RCC compared to healthy individuals. It was possible to detect RCC irrespective of stage or histology with 95.7% sensitivity. GAG scores did not correlate with pathologic stage, grade, or histology. These findings suggest that GAG alterations occur early in tumor formation but are likely independent of progression. These findings warrant prospective validation to assess the clinical utility of pre-operative GAG scores as biomarkers for RCC. © 2018FiguresReferencesRelatedDetails Volume 199Issue 4SApril 2018Page: e959-e960 Advertisement Copyright & Permissions© 2018MetricsAuthor Information Kyle A. Blum More articles by this author Francesco Gatto More articles by this author Mazyar Ghannat More articles by this author Alejandro Sanchez More articles by this author Francesca Maccari More articles by this author Fabio Galeotti More articles by this author James Hsieh More articles by this author Nicola Volpi More articles by this author A. Ari Hakimi More articles by this author Jens Nielsen More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...