3034 Background: Non-invasive liquid biopsies promise to enable early cancer detection and improve patient outcomes. However, virtually all liquid biopsies rely on genomic biomarkers, with limited sensitivity to early-stage tumors and poor detection of cancers shedding little cell-free DNA, like genitourinary or brain tumors. Here, we explored the use of plasma and urine glycosaminoglycan (GAGs) profiles, or GAGomes, as biomarkers reflective of tumor metabolism to serve as an alternative pan-cancer liquid biopsy. Methods: In this case-control study, we enrolled retrospective and prospective cohorts from Sweden and Italy. Included cases were treatment-naïve early-stage/low-grade cancers or metastatic/high-grade cancers across 14 histological types. Included controls were healthy 22-78 y/o adults with no history of cancer. We measured GAGomes – encompassing 17 chondroitin sulfate (CS), heparan sulfate (HS), and hyaluronate (HA) disaccharides - using a standardized UHPLC-MS/MS-based kit in a central blind laboratory. We tested the top GAGome features different in cancer using Bayesian estimation. These were used to design one plasma and one urine GAG score for the binary classification of cancer vs. control in a discovery set. We computed the area-under-the-curve (AUC), and sensitivity at 98% specificity of each GAG score in the validation set. A subset analysis was performed in early-stage/low-grade cancers only. In the subset of cases with survival records, we used multivariable Cox regression to estimate the hazard ratio (HR) for overall survival (OS) on each GAG score adjusted for cancer type, age, and gender. Results: GAGomes were measured in 753 plasma samples (460 cancers across 14 types, median age = 66 y/o, 51% female vs. 293 healthy adults, median age = 58 y/o, 57% female) and 559 urine samples (219 cancers across 5 types, median age = 69 y/o, 23% female vs. 340 healthy adults, median age = 56 y/o, 60% female). In the discovery set, the urine GAG score had an AUC = 0.80 (95% CI: 0.74-0.85, 124 cancers across 5 types vs. 184 controls) while the plasma GAG score had an AUC = 0.82 (95% CI: 0.78-0.86, 153 cancers across 14 types vs. 282 controls). In the validation set, the urine GAG score had an AUC = 0.78 (95% CI: 0.71-0.84, 95 cancers across 5 types vs. 156 controls) with 35% sensitivity at 98% specificity. The plasma GAG score had an AUC = 0.84 (95% CI: 0.79-0.88, 178 cancers across 14 types vs. 140 controls) with 41% sensitivity at 98% specificity. In the subset of early-stage/low-grade cancers, the AUC was 0.78 and 0.72 in plasma and urine, respectively. The plasma and urine GAG scores were independent predictors of OS regardless of cancer type (HR = 1.39, p = 0.005 in plasma [ N = 283, 11 types, 67 deaths, median follow-up 17 months] and HR = 1.53, p = 0.016 in urine [ N = 161, 4 types, 32 deaths, median follow-up 15 months]). Conclusions: GAGomes were sensitive non-invasive metabolic biomarkers for any-stage cancer, including genitourinary and brain tumors.
A wearable electrochemical sensing system for non-invasive monitoring of lithium drug in bipolar disorder
