May 1, 2012 (Vol. 32, No. 9)
Jeffery Herman, Ph.D.
Aberrant biochemical and metabolite signaling plays an important role in the development and progression of diseased tissue. This concept has been studied by the science community for decades. However, with relatively recent advances in analytical technology and bioinformatics as well as the development of the Human Metabolome Database (HMDB), metabolomics has become an invaluable field of research.
At the “International Conference and Exhibition on Metabolomics & Systems Biology” held recently in San Francisco, researchers and industry leaders discussed how the underlying cellular biochemical/metabolite fingerprint in response to a specific disease state, toxin exposure, or pharmaceutical compound is useful in clinical diagnosis and biomarker discovery and in understanding disease development and progression.
Developed by BASF, MetaMap® Tox is a database that helps identify in vivo systemic effects of a tested compound, including targeted organs, mechanism of action, and adverse events. Based on 28-day systemic rat toxicity studies, MetaMap Tox is composed of differential plasma metabolite profiles of rats after exposure to a large variety of chemical toxins and pharmaceutical compounds.
“Using the reference data, we have developed more than 110 patterns of metabolite changes, which are specific and predictive for certain toxicological modes of action,” said Hennicke Kamp, Ph.D., group leader, department of experimental toxicology and ecology at BASF.
With MetaMap Tox, a potential drug candidate can be compared to a similar reference compound using statistical correlation algorithms, which allow for the creation of a toxicity and mechanism of action profile.
“MetaMap Tox, in the context of early pre-clinical safety enablement in pharmaceutical development,” continued Dr. Kamp, has been independently validated “by an industry consortium (Drug Safety Executive Council) of 12 leading biopharmaceutical companies.”
By allowing for quick and accurate decisions on the safety and efficacy of compounds during early and preclinical toxicological studies, this technology may prove invaluable for high-throughput drug candidate screening, added Dr. Kamp. Furthermore, by comparing a lead compound to a variety of molecular derivatives, the rapid identification of the most optimal molecular structure with the best efficacy and safety profiles might be streamlined.
Targeted Tandem Mass Spectrometry
Biocrates Life Sciences focuses on targeted metabolomics, an important approach for the accurate quantification of known metabolites within a biological sample. Originally used for the clinical screening of inherent metabolic disorders from dried blood-spots of newborn children, Biocrates has developed a tandem mass spectrometry (MS/MS) platform, which allows for the identification, quantification, and mapping of more than 800 metabolites to specific cellular pathways.
Based on “flow injection analysis and high-performance liquid chromatography MS/MS,” according to Guido Dallmann, Ph.D., director, customer method development, biomarker and funding, at Biocrates, the MetaDisIDQ® Kit is a new generation “multiparamatic” diagnostic assay designed for the “comprehensive assessment of a person’s metabolic state” and the early determination of pathophysiological events with regards to a specific disease.
With the use of isotopically labeled internal standards, MetaDisIDQ is designed to quantify a diverse range of 181 metabolites involved in major metabolic pathways, from a small amount of human serum (10 µL).
In animal and clinical studies, the value of this kit has been demonstrated with its ability to detect changes in metabolites that are commonly associated with the development of metabolic syndrome, type 2 diabetes, and diabetic nephropathy, according to Dr. Dallmann. Data generated with the MetaDisIDQ kit correlates strongly with routine chemical analyses of common metabolites including glucose and creatinine, he added.
Biocrates has also developed the MS/MS-based AbsoluteIDQ® kits, which are an “easy-to-use” biomarker analysis tool for laboratory research. The kit, which functions on MS machines from a variety of vendors, allows for the quantification of 150-180 metabolites.
The SteroIDQ® kit is a high-throughput standardized MS/MS diagnostic assay, validated in human serum, for the rapid and accurate clinical determination of 16 known steroids. Initially focusing on the analysis of steroid ranges in premenopausal women, for the potential development of optimized hormone replacement therapy, the SteroIDQ Kit is expected to have a wide clinical application, according to the company.
Hormone-Resistant Breast Cancer
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.
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.