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May 1, 2012 (Vol. 32, No. 9)

Metabolomics Continues Auspicious Climb

  • Hormone-Resistant Breast Cancer

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    Scientists at Georgetown University have shown that breast cancer cells can functionally coordinate cell-survival and cell-proliferation mechanisms, while maintaining a certain degree of cellular metabolism.

    To grow, cells need energy, and energy is a product of cellular metabolism. For nearly a century, it was thought that the uncoupling of glycolysis from the mitochondria, leading to the inefficient but rapid metabolism of glucose and the formation of lactic acid (the Warburg effect), was the major and only metabolism driving force for unchecked proliferation and tumorigenesis of cancer cells. Other aspects of metabolism were often overlooked.

    “I think we understand now that cellular metabolism is a lot more than just metabolizing glucose,” said Robert Clarke, Ph.D., professor of oncology and physiology and biophysics at Georgetown University. Dr. Clarke, in collaboration with the Waters Center for Innovation at Georgetown University (led by Albert J. Fornace, Jr., M.D.), obtained the metabolomic profile of hormone-sensitive and -resistant breast cancer cells through the use of UPLC-MS.

    Although glucose is important, they showed that breast cancer cells, through a rather complex and not yet completely understood process, can functionally coordinate cell-survival and cell-proliferation mechanisms, while maintaining a certain degree of cellular metabolism. This is at least partly accomplished through the upregulation of important pro-survival mechanisms; including the unfolded protein response; an important regulator of endoplasmic reticulum stress and initiator of autophagy.

    Normally, during a stressful situation, a cell may enter a state of quiescence and undergo autophagy, a process by which a cell can recycle organelles in order to maintain enough energy to survive during a stressful situation or, if the stress is too great, undergo apoptosis. By integrating cell-survival mechanisms and cellular metabolism advanced ER+ hormone-resistant breast cancer cells can maintain a low level of autophagy to adapt and resist hormone/chemotherapy treatment.

    This adaptation allows cells to reallocate important metabolites recovered from organelle degradation and provide enough energy to also promote proliferation. With further research, we can gain a better understanding of the underlying causes of hormone-resistant breast cancer, with the overall goal of developing effective diagnostic, prognostic, and therapeutic tools.

  • NMR

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    Over the last two decades, NMR has established itself as a major tool for metabolomics analysis. It is especially adept at testing biological fluids. [Bruker BioSpin]

    Historically, nuclear magnetic resonance spectroscopy (NMR) has been used for structural elucidation of pure molecular compounds. However, in the last two decades, NMR has established itself as a major tool for metabolomics analysis. Since the integral of an NMR signal is directly proportional to the molar concentration throughout the dynamic range of a sample, “the simultaneous quantification of highly concentrated compounds and lower concentrated compounds is possible without the need for specific reference standards or calibration curves,” according to Lea Heintz of Bruker BioSpin.

    For this reason, combined with high reproducibility, standardized protocols, low sample manipulation, and the production of a large subset of data, NMR is adept at testing biological fluids.

    Bruker BioSpin is presently involved in a project for the screening of inborn errors of metabolism in newborn children from Turkey, based on their urine NMR profiles. More than 20 clinics are participating to the project that is coordinated by INFAI, a specialist in the transfer of advanced analytical technology into medical diagnostics. The construction of statistical models for the detection of deviations from normality, as well as automatic quantification methods for indicative metabolites are under development at Bruker BioSpin.

    Bruker BioSpin also recently installed high-resolution magic angle spinning NMR (HRMAS-NMR) systems into several research hospitals; these systems can rapidly analyze tissue biopsies. The main objective for HRMAS-NMR is to establish a rapid and effective clinical method to assess tumor grade and other important aspects of cancer during surgery.

  • Combined NMR and Mass Spec

    There is increasing interest in combining NMR and MS as a means to improve data sensitivity and to fully elucidate the complex metabolome within a given biological sample. NMR and MS are two of the main analytical assays in metabolomic research.

    Aalim Weljie, Ph.D., research assistant professor, department of pharmacology, University of Pennsylvania, maintains that combined NMR/MS has great promise for cancer biomarker discovery in the realms of diagnosis, prognosis, and treatment.

    For example, according to Dr. Weljie, in 10–15% of the cases, it is difficult to discern between benign and malignant pancreatic lesions. Using combined NMR and MS to measure the levels of nearly 250 separate metabolites in the patient’s blood, Dr. Weljie and other researchers at the University of Calgary were able to rapidly determine the malignancy of a lesion, while avoiding unnecessary surgery in patients with benign lesions. There are, however, certain limitations that must be addressed before NMR/MS data integration can be completely utilized.

    When performing NMR and MS on a single biological fluid, ultimately “we are,” noted Dr. Weljie, “splitting up information content, processing, and introducing a lot of background noise and error and then trying to reintegrate the data…It’s like taking a complex item, with multiple pieces, out of an IKEA box and trying to repackage it perfectly into another box.”

    It’s not easy. Due to the wide range of possible physiochemical properties, a biologically pure sample is immediately biased with the initial extraction of the metabolites. Further NMR and MS platform specific biases are then introduced into the sample.

    By improving the workflow between the initial splitting of the sample, they improved endpoint data integration, proving that a streamlined approach to combined NMR/MS can be achieved, leading to a very strong, robust and precise metabolomic toolset.

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