5
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Metabolic consequences of perioperative oral carbohydrates in breast cancer patients — an explorative study

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          The metabolic consequences of preoperative carbohydrate load in breast cancer patients are not known. The present explorative study investigated the systemic and tumor metabolic changes after preoperative per-oral carbohydrate load and their influence on tumor characteristics and survival.

          Methods

          The study setting was on university hospital level with primary and secondary care functions in south-west Norway. Serum and tumor tissue were sampled from a population-based cohort of 60 patients with operable breast cancer who were randomized to either per-oral carbohydrate load (preOp™; n = 25) or standard pre-operative fasting ( n = 35) before surgery. Magnetic resonance (MR) metabolomics was performed on serum samples from all patients and high-resolution magic angle spinning (HR-MAS) MR analysis on 13 tumor samples available from the fasting group and 16 tumor samples from the carbohydrate group.

          Results

          Fourteen of 28 metabolites were differently expressed between fasting and carbohydrate groups. Partial least squares discriminant analysis showed a significant difference in the metabolic profile between the fasting and carbohydrate groups, compatible with the endocrine effects of insulin (i.e., increased serum-lactate and pyruvate and decreased ketone bodies and amino acids in the carbohydrate group). Among ER-positive tumors ( n = 18), glutathione was significantly elevated in the carbohydrate group compared to the fasting group ( p = 0.002), with a positive correlation between preoperative S-insulin levels and the glutathione content in tumors ( r = 0.680; p = 0.002). In all tumors ( n = 29), glutamate was increased in tumors with high proliferation (t-test; p = 0.009), independent of intervention group. Moreover, there was a positive correlation between tumor size and proliferation markers in the carbohydrate group only. Patients with ER-positive / T2 tumors and high tumor glutathione (≥1.09), high S-lactate (≥56.9), and high S-pyruvate (≥12.5) had inferior clinical outcomes regarding relapse-free survival, breast cancer-specific survival, and overall survival. Moreover, Integrated Pathway Analysis (IPA) in serum revealed activation of five major anabolic metabolic networks contributing to proliferation and growth.

          Conclusions

          Preoperative carbohydrate load increases systemic levels of lactate and pyruvate and tumor levels of glutathione and glutamate in ER-positive patients. These biological changes may contribute to the inferior clinical outcomes observed in luminal T2 breast cancer patients.

          Trial of registration

          ClinicalTrials.gov; NCT03886389. Retrospectively registered March 22, 2019.

          Related collections

          Most cited references57

          • Record: found
          • Abstract: found
          • Article: not found

          Lactate Metabolism in Human Lung Tumors

          Cancer cells consume glucose and secrete lactate in culture. It is unknown whether lactate contributes to energy metabolism in living tumors. We previously reported that human non-small cell lung cancers (NSCLC) oxidize glucose in the tricarboxylic acid (TCA) cycle. Here we show that lactate is also a TCA cycle carbon source for NSCLC. In human NSCLC, evidence of lactate utilization was most apparent in tumors with high 18 fluorodeoxyglucose uptake and aggressive oncological behavior. Infusing human NSCLC patients with 13 C-lactate revealed extensive labeling of TCA cycle metabolites. In mice, deleting monocarboxylate transporter-1 (MCT1) from tumor cells eliminated lactate-dependent metabolite labeling, confirming tumor-cell autonomous lactate uptake. Strikingly, directly comparing lactate and glucose metabolism in vivo indicated that lactate's contribution to the TCA cycle predominates. The data indicate that tumors, including bona fide human NSCLC, can use lactate as a fuel in vivo. Human non-small cell lung cancer preferentially utilizes lactate over glucose to fuel TCA cycle and sustain tumor metabolism in vivo.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            MetaboAnalyst 2.0—a comprehensive server for metabolomic data analysis

            First released in 2009, MetaboAnalyst (www.metaboanalyst.ca) was a relatively simple web server designed to facilitate metabolomic data processing and statistical analysis. With continuing advances in metabolomics along with constant user feedback, it became clear that a substantial upgrade to the original server was necessary. MetaboAnalyst 2.0, which is the successor to MetaboAnalyst, represents just such an upgrade. MetaboAnalyst 2.0 now contains dozens of new features and functions including new procedures for data filtering, data editing and data normalization. It also supports multi-group data analysis, two-factor analysis as well as time-series data analysis. These new functions have also been supplemented with: (i) a quality-control module that allows users to evaluate their data quality before conducting any analysis, (ii) a functional enrichment analysis module that allows users to identify biologically meaningful patterns using metabolite set enrichment analysis and (iii) a metabolic pathway analysis module that allows users to perform pathway analysis and visualization for 15 different model organisms. In developing MetaboAnalyst 2.0 we have also substantially improved its graphical presentation tools. All images are now generated using anti-aliasing and are available over a range of resolutions, sizes and formats (PNG, TIFF, PDF, PostScript, or SVG). To improve its performance, MetaboAnalyst 2.0 is now hosted on a much more powerful server with substantially modified code to take advantage the server’s multi-core CPUs for computationally intensive tasks. MetaboAnalyst 2.0 also maintains a collection of 50 or more FAQs and more than a dozen tutorials compiled from user queries and requests. A downloadable version of MetaboAnalyst 2.0, along detailed instructions for local installation is now available as well.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Fasting, Circadian Rhythms, and Time-Restricted Feeding in Healthy Lifespan.

              Most animals alternate periods of feeding with periods of fasting often coinciding with sleep. Upon >24 hr of fasting, humans, rodents, and other mammals enter alternative metabolic phases, which rely less on glucose and more on ketone body-like carbon sources. Both intermittent and periodic fasting result in benefits ranging from the prevention to the enhanced treatment of diseases. Similarly, time-restricted feeding (TRF), in which food consumption is restricted to certain hours of the day, allows the daily fasting period to last >12 hr, thus imparting pleiotropic benefits. Understanding the mechanistic link between nutrients and the fasting benefits is leading to the identification of fasting-mimicking diets (FMDs) that achieve changes similar to those caused by fasting. Given the pleiotropic and sustained benefits of TRF and FMDs, both basic science and translational research are warranted to develop fasting-associated interventions into feasible, effective, and inexpensive treatments with the potential to improve healthspan.
                Bookmark

                Author and article information

                Contributors
                tonehl@yahoo.no
                marie.austdal@sus.no
                tone.f.bathen@ntnu.no
                anne.elin.varhaugvik@helse-mr.no
                skiv@sus.no
                guei@sus.no
                nina.gran.egeland@sus.no
                siri.lunde@sus.no
                lars.akslen@uib.no
                kristin.jonsdottir@sus.no
                jaem@sus.no
                hsoiland@gmail.com
                info@drjanbaak.com
                Journal
                BMC Cancer
                BMC Cancer
                BMC Cancer
                BioMed Central (London )
                1471-2407
                4 December 2019
                4 December 2019
                2019
                : 19
                : 1183
                Affiliations
                [1 ]ISNI 0000 0004 0627 2891, GRID grid.412835.9, Department of Breast & Endocrine Surgery, , Stavanger University Hospital, Helse Stavanger HF, ; P.O. Box 8100, N-4068 Stavanger, Norway
                [2 ]ISNI 0000 0004 1936 7443, GRID grid.7914.b, Centre for Cancer Biomarkers CCBIO, Department of Clinical Medicine, Faculty of Medicine and Dentistry, , University of Bergen, ; Jonas Lies vei 87, N-5012 Bergen, Norway
                [3 ]ISNI 0000 0004 0627 2891, GRID grid.412835.9, Department of Research, , Stavanger University Hospital, Helse Stavanger HF, ; P.O. Box 8100, N-4068 Stavanger, Norway
                [4 ]ISNI 0000 0004 0627 2891, GRID grid.412835.9, Department of Pathology, , Stavanger University Hospital, Helse Stavanger HF, ; P.O. Box 8100, N-4068 Stavanger, Norway
                [5 ]ISNI 0000 0001 1516 2393, GRID grid.5947.f, Department of Circulation and Medical Imaging, , Norwegian University of Science and Technology, ; Trondheim, Norway
                [6 ]Department of Pathology, Helse Møre og Romsdal, Ålesund, Norway
                [7 ]ISNI 0000 0001 2299 9255, GRID grid.18883.3a, Department of Chemistry, Bioscience and Environmental Technology, , University of Stavanger, ; P.O. Box 8600 Forus, N-4036 Stavanger, Norway
                [8 ]ISNI 0000 0004 1936 7443, GRID grid.7914.b, Department of Clinical Science, , University of Bergen, ; Jonas Lies vei 87, N-5012 Bergen, Norway
                [9 ]Dr. Med. Jan Baak AS, Risavegen 66, N-4056 Tananger, Norway
                Author information
                http://orcid.org/0000-0002-7829-8885
                Article
                6393
                10.1186/s12885-019-6393-7
                6894229
                31801490
                3de30e5d-62a0-463e-90b6-30c3bd2d78e7
                © The Author(s). 2019

                Open AccessThis 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.

                History
                : 6 September 2019
                : 21 November 2019
                Funding
                Funded by: Folke Hermansen Foundation
                Award ID: N-2012
                Award Recipient :
                Funded by: Marathon Oil
                Award ID: US-2009
                Award Recipient :
                Funded by: Inge Steensland Foundation
                Award ID: N-2011
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2019

                Oncology & Radiotherapy
                breast cancer,carbohydrate load,proliferation,insulin,insulin c-peptide,s-lactate,s-pyruvate,tumor glutamate,tumor glutathione,fasting state,ketonic bodies,clinical outcome

                Comments

                Comment on this article