NMR-based metabolomics of biofluids in cancer

Author's accepted version (post-print).Available from 20/04/2019.acceptedVersio

DNA methylation changes in response to neoadjuvant chemotherapy are associated with breast cancer survival

Background: Locally advanced breast cancer is a heterogeneous disease with respect to response to neoadjuvant chemotherapy (NACT) and survival. It is currently not possible to accurately predict who will benefit from the specific types of NACT. DNA methylation is an epigenetic mechanism known to play an important role in regulating gene expression and may serve as a biomarker for treatment response and survival. We investigated the potential role of DNA methylation as a prognostic marker for long-term survival (> 5 years) after NACT in breast cancer. Methods: DNA methylation profiles of pre-treatment (n = 55) and post-treatment (n = 75) biopsies from 83 women with locally advanced breast cancer were investigated using the Illumina HumanMethylation450 BeadChip. The patients received neoadjuvant treatment with epirubicin and/or paclitaxel. Linear mixed models were used to associate DNA methylation to treatment response and survival based on clinical response to NACT (partial response or stable disease) and 5-year survival, respectively. LASSO regression was performed to identify a risk score based on the statistically significant methylation sites and Kaplan–Meier curve analysis was used to estimate survival probabilities using ten years of survival follow-up data. The risk score developed in our discovery cohort was validated in an independent validation cohort consisting of paired pre-treatment and post-treatment biopsies from 85 women with locally advanced breast cancer. Patients included in the validation cohort were treated with either doxorubicin or 5-FU and mitomycin NACT. Results: DNA methylation patterns changed from before to after NACT in 5-year survivors, while no significant changes were observed in non-survivors or related to treatment response. DNA methylation changes included an overall loss of methylation at CpG islands and gain of methylation in non-CpG islands, and these changes affected genes linked to transcription factor activity, cell adhesion and immune functions. A risk score was developed based on four methylation sites which successfully predicted long-term survival in our cohort (p = 0.0034) and in an independent validation cohort (p = 0.049). Conclusion: Our results demonstrate that DNA methylation patterns in breast tumors change in response to NACT. These changes in DNA methylation show potential as prognostic biomarkers for breast cancer survival.publishedVersio

Metabolic effects of ultraviolet radiation on the anterior part of the eye

Ultraviolet radiation (UV-R) is an environmental factor known to increase the risk of developing an irreversible opacification of the lens (cataract). Increased irradiance of UV-R to the earth because of depletion of stratospheric ozone is of current concern considering cataract formation. Detailed metabolic information from the cornea, lens and aqueous humour might give valuable knowledge on the biochcemical processes occurring in the eye after exposure to UV-R, and thereby a better understanding of the mechanisms by which UV-R induces cataractogenesis. The purpose of this thesis was to study metabolic effects of exposure to UV-R on the anterior part of the eye. Effects of UV-B (280-315 nm) and UV-A (315-400 nm) on the aqueous humour, cornea and the lens from animal models were investigated by 1H nuclear magnetic resonance (NMR) spectroscopy. Since the lens is composed of functionally distinct anatomical compartments, with different metabolic activity, biochemical changes in various compartments of the lens were analyzed. Application of NMR-based metabonomics was effective to analyze metabolic changes in the anterior part of the eye after exposure to UV-R. High-resolution (HR) magic angle spinning (MAS) 1H NMR spectroscopy provided high quality spectra from intact tissue of cornea and lens, and provided important information about metabolic alteration occurring in these tissues after exposure to UV-R. The results from this thesis show that in vivo UV-B radiation affects metabolism of the anterior compartments of the eye. Metabolic changes were observed in aqueous humour, cornea, lens and in the different compartments of the lens. The antioxidants, glutathione and ascorbate, several amino acids, high energetic phosphates, and compounds important for membrane building and osmoregulation were substantially altered after exposure to UV-B radiation. Several biochemical effects such as oxidation, membrane disruption, osmoregulatory problems, lipid peroxidation, problems with cellular signalling and impairment of growth and protein synthesis were suggested. After UV-A exposure, no observable metabolic alterations were found in the anterior part of the eye in the present animal models

Metabolic alterations in tissues and biofluids of patients with prostate cancer

Altered metabolism is one of the key molecular characteristics of prostate cancer (PCa) development, and a number of studies have searched for metabolic biomarkers in patient-derived samples. Reported metabolic changes in PCa tissue compared with normal tissue include reduced levels of citrate and spermine, elevated lipid synthesis and fatty acid oxidation, and higher levels of the amino acids alanine, glutamine, and glutamate. Recent studies have investigated the tumor microenvironment, such as reactive stroma, and so-called metabolic field effects. Furthermore, analysis of blood and urine samples reveals other, but significant, metabolic differences between patients with PCa and controls. Large-cohort studies show promising results for assessing future PCa risk from blood samples. In addition, metabolic profiling of extracellular vesicles from urine has gained interest as a noninvasive and more prostate-specific approach to diagnose PCa

The effect of sampling procedures and day-to-day variations in metabolomics studies of biofluids

Metabolomics analysis of biofluids is a feasible tool for disease characterization and monitoring due to its minimally invasive nature. To reduce unwanted variation in biobanks and clinical studies, it is important to determine the effect of external factors on metabolic profiles of biofluids. In this study we examined the effect of sample collection and sample processing procedures on NMR measured serum lipoproteins and small-molecule metabolites in serum and urine, using a cohort of men diagnosed with either prostate cancer or benign prostatic hyperplasia. We determined day-to-day reliability of metabolites by systematic sample collection at two different days, in both fasting and non-fasting conditions. Study participants received prostate massage the first day to assess the differences between urine with and without prostate secretions. Further, metabolic differences between first-void and mid-stream urine samples, and the effect of centrifugation of urine samples before storage were assessed. Our results show that day-to-day reliability is highly variable between metabolites in both serum and urine, while lipoprotein subfractions possess high reliability. Further, fasting status clearly influenced the metabolite concentrations, demonstrating the importance of keeping this condition constant within a study cohort. Day-to-day reliabilities were however comparable in fasting and non-fasting samples. Urine sampling procedures such as sampling of first-void or mid-stream urine, and centrifugation or not before sample storage, were shown to only have minimal effect on the overall metabolic profile, and is thus unlikely to constitute a confounder in clinical studies utilizing NMR derived metabolomics

Gene signatures ESC, MYC and ERG-fusion are early markers of a potentially dangerous subtype of prostate cancer

Background Good prognostic tools for predicting disease progression in early stage prostate cancer (PCa) are still missing. Detection of molecular subtypes, for instance by using microarray gene technology, can give new prognostic information which can assist personalized treatment planning. The detection of new subtypes with validation across additional and larger patient cohorts is important for bringing a potential prognostic tool into the clinic. Methods We used fresh frozen prostatectomy tissue of high molecular quality to further explore four molecular subtype signatures of PCa based on Gene Set Enrichment Analysis (GSEA) of 15 selected gene sets published in a previous study. For this analysis we used a statistical test of dependent correlations to compare reference signatures to signatures in new normal and PCa samples, and also explore signatures within and between sample subgroups in the new samples. Results An important finding was the consistent signatures observed for samples from the same patient independent of Gleason score. This proves that the signatures are robust and can surpass a normally high tumor heterogeneity within each patient. Our data did not distinguish between four different subtypes of PCa as previously published, but rather highlighted two groups of samples which could be related to good and poor prognosis based on survival data from the previous study.The poor prognosis group highlighted a set of samples characterized by enrichment of ESC, ERG-fusion and MYC + rich signatures in patients diagnosed with low Gleason score,. The other group consisted of PCa samples showing good prognosis as well as normal samples. Accounting for sample composition (the amount of benign structures such as stroma and epithelial cells in addition to the cancer component) was important to improve subtype assignments and should also be considered in future studies. Conclusion Our study validates a previous molecular subtyping of PCa in a new patient cohort, and identifies a subgroup of PCa samples highly interesting for detecting high risk PCa at an early stage. The importance of taking sample tissue composition into account when assigning subtype is emphasized. Keywords: Prostate cancer; Gleason; Subtypes; Microarray; GSE

Cholesterol synthesis pathway genes in prostate cancer are transcriptionally downregulated when tissue confounding is minimized

Background The relationship between cholesterol and prostate cancer has been extensively studied for decades, where high levels of cellular cholesterol are generally associated with cancer progression and less favorable outcomes. However, the role of in vivo cellular cholesterol synthesis in this process is unclear, and data on the transcriptional activity of cholesterol synthesis pathway genes in tissue from prostate cancer patients are inconsistent. Methods A common problem with cancer tissue data from patient cohorts is the presence of heterogeneous tissue which confounds molecular analysis of the samples. In this study we present a general method to minimize systematic confounding from stroma tissue in any prostate cancer cohort comparing prostate cancer and normal samples. In particular we use samples assessed by histopathology to identify genes enriched and depleted in prostate stroma. These genes are then used to assess stroma content in tissue samples from other prostate cancer cohorts where no histopathology is available. Differential expression analysis is performed by comparing cancer and normal samples where the average stroma content has been balanced between the sample groups. In total we analyzed seven patient cohorts with prostate cancer consisting of 1713 prostate cancer and 230 normal tissue samples. Results When stroma confounding was minimized, differential gene expression analysis over all cohorts showed robust and consistent downregulation of nearly all genes in the cholesterol synthesis pathway. Additional Gene Ontology analysis also identified cholesterol synthesis as the most significantly altered metabolic pathway in prostate cancer at the transcriptional level. Conclusion The surprising observation that cholesterol synthesis genes are downregulated in prostate cancer is important for our understanding of how prostate cancer cells regulate cholesterol levels in vivo. Moreover, we show that tissue heterogeneity explains the lack of consistency in previous expression analysis of cholesterol synthesis genes in prostate cancer.publishedVersion© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated

NMR-based metabolomics of biofluids in cancer

Metabolomics is the branch of “omics” technologies that involves high‐throughput identification and quantification of small‐molecule metabolites in the metabolome. NMR‐based spectroscopy of biofluids represents a potential method for non‐invasive characterization of cancer. While the metabolism of cancer cells is altered compared with normal non‐proliferating cells, the metabolome of several biofluids (e.g. blood and urine) reflects the metabolism of the entire organism. This review provides an update on the current status of NMR metabolomics analysis of biofluids with respect to: (i) cancer risk assessment; (ii) cancer detection; (iii) disease characterization and prognosis; and (iv) treatment monitoring. We conclude that many studies show impressive associations between biofluid metabolomics and cancer progression, and suggest that NMR metabolomics can be used to provide information with prognostic or predictive value. However, translation of these findings to clinical practice is currently hindered by a lack of validation, difficulties in biological interpretation, and non‐standardized analytical procedures