Quantitative Metabolomics and Lipoprotein Analysis of PDAC Patients Suggests Serum Marker Categories for Pancreatic Function, Pancreatectomy, Cancer Metabolism, and Systemic Disturbances.

Pancreatic ductal adenocarcinoma (PDAC) is difficult to diagnose in the early stages and lacks reliable biomarkers. The scope of this project was to establish quantitative nuclear magnetic resonance (NMR) spectroscopy to comprehensively study blood serum alterations in PDAC patients. Serum samples from 34 PDAC patients obtained before and after pancreatectomy as well as 83 age- and sex-matched control samples from healthy donors were analyzed with in vitro diagnostics research (IVDr) proton NMR spectroscopy at 600 MHz. Uni- and multivariate statistics were applied to identify significant biofluid alterations. We identified 29 significantly changed metabolites and 98 lipoproteins when comparing serum from healthy controls with those of PDAC patients. The most prominent features were assigned to (i) markers of pancreatic function (e.g., glucose and blood triglycerides), (ii) markers related to surgery (e.g., ketone bodies and blood cholesterols), (iii) PDAC-associated markers (e.g., amino acids and creatine), and (iv) markers for systemic disturbances in PDAC (e.g., gut metabolites DMG, TMAO, DMSO2, and liver lipoproteins). Quantitative serum NMR spectroscopy is suited as a diagnostic tool to investigate PDAC. Remarkably, 2-hydroxybutyrate (2-HB) as a previously suggested marker for insulin resistance was found in extraordinarily high levels only after pancreatectomy, suggesting this metabolite is the strongest marker for pancreatic loss of function.

Stratification of ovarian cancer borderline from high-grade serous carcinoma patients by quantitative serum NMR spectroscopy of metabolites, lipoproteins, and inflammatory markers.

Background: Traditional diagnosis is based on histology or clinical-stage classification which provides no information on tumor metabolism and inflammation, which, however, are both hallmarks of cancer and are directly associated with prognosis and severity. This project was an exploratory approach to profile metabolites, lipoproteins, and inflammation parameters (glycoprotein A and glycoprotein B) of borderline ovarian tumor (BOT) and high-grade serous ovarian cancer (HGSOC) for identifying additional useful serum markers and stratifying ovarian cancer patients in the future. Methods: This project included 201 serum samples of which 50 were received from BOT and 151 from high-grade serous ovarian cancer (HGSOC), respectively. All the serum samples were validated and phenotyped by 1H-NMR-based metabolomics with in vitro diagnostics research (IVDr) standard operating procedures generating quantitative data on 38 metabolites, 112 lipoprotein parameters, and 5 inflammation markers. Uni- and multivariate statistics were applied to identify NMR-based alterations. Moreover, biomarker analysis was carried out with all NMR parameters and CA-125. Results: Ketone bodies, glutamate, 2-hydroxybutyrate, glucose, glycerol, and phenylalanine levels were significantly higher in HGSOC, while the same tumors showed significantly lower levels of alanine and histidine. Furthermore, alanine and histidine and formic acid decreased and increased, respectively, over the clinical stages. Inflammatory markers glycoproteins A and B (GlycA and GlycB) increased significantly over the clinical stages and were higher in HGSOC, alongside significant changes in lipoproteins. Lipoprotein subfractions of VLDLs, IDLs, and LDLs increased significantly in HGSOC and over the clinical stages, while total plasma apolipoprotein A1 and A2 and a subfraction of HDLs decreased significantly over the clinical stages. Additionally, LDL triglycerides significantly increased in advanced ovarian cancer. In biomarker analysis, glycoprotein inflammation biomarkers behaved in the same way as the established clinical biomarker CA-125. Moreover, CA-125/GlycA, CA-125/GlycB, and CA-125/Glycs are potential biomarkers for diagnosis, prognosis, and treatment response of epithelial ovarian cancer (EOC). Last, the quantitative inflammatory parameters clearly displayed unique patterns of metabolites, lipoproteins, and CA-125 in BOT and HGSOC with clinical stages I-IV. Conclusion: 1H-NMR-based metabolomics with commercial IVDr assays could detect and identify altered metabolites and lipoproteins relevant to EOC development and progression and show that inflammation (based on glycoproteins) increased along with malignancy. As inflammation is a hallmark of cancer, glycoproteins, thereof, are promising future serum biomarkers for the diagnosis, prognosis, and treatment response of EOC. This was supported by the definition and stratification of three different inflammatory serum classes which characterize specific alternations in metabolites, lipoproteins, and CA-125, implicating that future diagnosis could be refined not only by diagnosed histology and/or clinical stages but also by glycoprotein classes.

Lipoprotein and metabolite associations to breast cancer risk in the HUNT2 study.

BACKGROUND: The aim of this study was to gain an increased understanding of the aetiology of breast cancer, by investigating possible associations between serum lipoprotein subfractions and metabolites and the long-term risk of developing the disease. METHODS: From a cohort of 65,200 participants within the Trøndelag Health Study (HUNT study), we identified all women who developed breast cancer within a 22-year follow-up period. Using nuclear magnetic resonance (NMR) spectroscopy, 28 metabolites and 89 lipoprotein subfractions were quantified from prediagnostic serum samples of future breast cancer patients and matching controls (n = 1199 case-control pairs). RESULTS: Among premenopausal women (554 cases) 14 lipoprotein subfractions were associated with long-term breast cancer risk. In specific, different subfractions of VLDL particles (in particular VLDL-2, VLDL-3 and VLDL-4) were inversely associated with breast cancer. In addition, inverse associations were detected for total serum triglyceride levels and HDL-4 triglycerides. No significant association was found in postmenopausal women. CONCLUSIONS: We identified several associations between lipoprotein subfractions and long-term risk of breast cancer in premenopausal women. Inverse associations between several VLDL subfractions and breast cancer risk were found, revealing an altered metabolism in the endogenous lipid pathway many years prior to a breast cancer diagnosis.

Identification of neurodegeneration indicators and disease progression in metachromatic leukodystrophy using quantitative NMR-based urinary metabolomics.

Metachromatic leukodystrophy (MLD) is a lysosomal storage disease caused by a deficiency of the arylsulfatase A (ARSA). ARSA deficiency leads to an accumulation of sulfatides primarily in the nervous system ultimately causing demyelination. With evolving therapeutic options, there is an increasing need for indicators to evaluate disease progression. Here, we report targeted metabolic urine profiling of 56 MLD patients including longitudinal sampling, using 1H (proton) nuclear magnetic resonance (NMR) spectroscopy. 1H-NMR urine spectra of 119 MLD samples and 323 healthy controls were analyzed by an in vitro diagnostics research (IVDr) tool, covering up to 50 endogenous and 100 disease-related metabolites on a 600-MHz IVDr NMR spectrometer. Quantitative data reports were analyzed regarding age of onset, clinical course, and therapeutic intervention. The NMR data reveal metabolome changes consistent with a multiorgan affection in MLD patients in comparison to controls. In the MLD cohort, N-acetylaspartate (NAA) excretion in urine is elevated. Early onset MLD forms show a different metabolic profile suggesting a metabolic shift toward ketogenesis in comparison to late onset MLD and controls. In samples of juvenile MLD patients who stabilize clinically after hematopoietic stem cell transplantation (HSCT), the macrophage activation marker neopterin is elevated. We were able to identify different metabolic patterns reflecting variable organ disturbances in MLD, including brain and energy metabolism and inflammatory processes. We suggest NAA in urine as a quantitative biomarker for neurodegeneration. Intriguingly, elevated neopterin after HSCT supports the hypothesis that competent donor macrophages are crucial for favorable outcome.

1H NMR-Based Urine Metabolomics Reveals Signs of Enhanced Carbon and Nitrogen Recycling in Prostate Cancer.

Prostate cancer is the second most common tumor and the fifth cause of cancer-related death among men worldwide. PC cells exhibit profound signaling and metabolic reprogramming that account for the acquisition of aggressive features. Although the metabolic understanding of this disease has increased in recent years, the analysis of such alterations through noninvasive methodologies in biofluids remains limited. Here, we used NMR-based metabolomics on a large cohort of urine samples (more than 650) from PC and benign prostate hyperplasia (BPH) patients to investigate the molecular basis of this disease. Multivariate analysis failed to distinguish between the two classes, highlighting the modest impact of prostate alterations on urine composition and the multifactorial nature of PC. However, univariate analysis of urine metabolites unveiled significant changes, discriminating PC from BPH. Metabolites with altered abundance in urine from PC patients revealed changes in pathways related to cancer biology, including glycolysis and the urea cycle. We found out that metabolites from such pathways were diminished in the urine from PC individuals, strongly supporting the notion that PC reduces nitrogen and carbon waste in order to maximize their usage in anabolic processes that support cancer cell growth.