MSACL 2018 US Abstract

Topic: Cannabinoids

A New Approach for Phytocannabinoids Comprehensive Metabolic Profiling: A Step Towards Understanding the Clinical Effects of Cannabis

Paula Berman (Presenter)
Technion - Israel Institute of Technology

Bio: Paula Berman is a post-doctoral fellow at the Technion - Israel Institute of Technology (advisor: Prof. Dedi Meiri). Her research involves development of chemical analysis methods for extraction, identification and isolation of phytocannabinoids in Cannabis for the purpose of metabolic profiling over 100 medical Cannabis strains prescribed to patients in Israel. This project is performed at the Laboratory of Cancer Biology and Cannabinoid Research which aims at forwarding the basic understanding of the cannabinoid mechanisms of action, and establish the optimal treatment strategy for cancer patients.

Authorship: Paula Berman (1), Kate Futoran (1), Dzmitry Mukha (1), Maya Benami (1), Tomer Shlomi (1,2), and David Meiri (1)
(1) Department of Biology, Technion-Israel Institute of Technology, Haifa 320003, Israel (2) Department of Computer Science, Technion-Israel Institute of Technology, Haifa 320003, Israel.

Short Abstract

Medical Cannabis today is prescribed to patients primarily by its content of (-)-Δ9-trans-tetrahydrocannabinol (Δ9-THC) and cannabidiol (CBD), regardless of the fact that the plant contains over 100 additional phytocannabinoids whose therapeutic effects and interplay have not yet been fully elucidated. In this study we suggest a new LC/MS/MS approach to identify phytocannabinoids from 10 different subclasses, and comprehensive profiling of the identified compounds in different medical Cannabis plants. This method is important for the successful medicalization and standardization of Cannabis, and critical when performing biological, medical and pharmacological-based research using medical Cannabis.

Long Abstract

Introduction

The number of people worldwide that are currently using physician-prescribed medical Cannabis is estimated at a few millions [1]. According to a recent review [2], out of more than 545 metabolic constituents identified from Cannabis [3], 144 have been isolated and identified as phytocannabinoids. These have been conventionally classified into 10 subclasses according to their chemical structures and one additional miscellaneous subclass. The concentration of phytocannabinoids in Cannabis depends on the plant's tissue type, age, variety, growth conditions (nutrition, humidity and light level), harvest time, storage conditions and processing method [4,5]. However, even though there is a great diversity in chemical constituents between Cannabis strains, most studies that profile phytocannabinoids from Cannabis plants report only the major phytocannabinoids in the extract, usually up to the eight most common components [6-12]. Recent studies [13,14] suggest that the relative proportions of each compound can influence the pharmacological effects of whole Cannabis extracts through a polypharmacological effect of different phytocannabinoids. It is therefore very important to derive accurate and comprehensive measurements of Cannabis phytocannabinoid contents.

In this study, we present an approach for comprehensive identification and quantification of phytocannabinoids in Cannabis using liquid chromatography mass spectrometry (LC-MS). In the identification process, phytocannabinoids were chromatographically separated by reversed phase ultra-high performance liquid chromatography (UHPLC) and detected via data-dependent MS/MS mode. As a result, an in-house spectral MS/MS library was established. According to the accurate masses and retention times of the identified phytocannabinoids we profiled numerous medical Cannabis strains by LC/MS and concluded that the Cannabis strains analyzed contain very different phytocannabinoid types, concentrations and ratios.

Methods

Identification of phytocannabinoids in this study was performed using 13 commercially available analytical standards and ethanolic extracts of medical Cannabis strains provided by local Israeli suppliers. We used the retention times and MS/MS fragmentation patterns of the available analyzed pentyl neutral phytocannabinoid standards as the reference for the identification of additional phytocannabinoid homologues for which analytical standards are not available. For the purpose of absolute quantification of phytocannabinoids in Cannabis extracts for which analytical standards were available, external calibrations were developed. Absolute concentrations for all other phytocannabinoids were calculated based on observed similarities in ionization efficiencies with the available analytical standards. Differential profiling of numerous medical Cannabis strains was performed by LC/MS according to the retention times and accurate masses of the identified phytocannabinoids in the spectral MS/MS library.

Chemical analysis methods were performed using a Thermo Scientific UHPLC system coupled with a Q Exactive™ Quadrupole-Orbitrap MS (Thermo Scientific, Bremen, Germany). The chromatographic separation was achieved using a Kinetex C18 core-shell column (2.6 μm, 150 mm × 2.1 mm i.d.) with a guard column (0.5 μm depth filter × 0.1 mm) (Phenomenex, Torrance, CA, USA) and a ternary A/B/C multistep gradient (solvent A: 0.1% acetic acid in Milli Q water, solvent B: 0.1% acetic acid in acetonitrile, and solvent C: methanol, all solvents were of LC/MS grade).

Results

Overall a spectral MS/MS library of 67 identified phytocannabinoids from 10 different phytocannabinoid subclasses was established. Among these, 13 were identified with high confidence based on chemical standards from seven subclasses (type I) and 40 more were identified according to the characterized phytocannabinoid subclasses (type II). Another 14 phytocannabinoids were identified via their chromatographic and spectral similarities between the remaining 3 subclasses and their precursors (type III). An additional 27 phytocannabinoids whose absolute identification could not be determined with certainty at the time of submission were also added to the spectral library for the purpose of quantification. The phytocannabinoids in this last group were attributed as potential phytocannabinoids by accurate mass and fragmentation patterns typical to the ones presented for the identified phytocannabinoids in this research. In total, our spectral MS/MS library currently consists of 94 phytocannabinoids.

In order to examine the variation in the amounts and ratios of phytocannabinoids in medical Cannabis plants, 36 of the most commonly used Cannabis plants were chosen from over a hundred available strains prescribed to patients in Israel. Among the analyzed samples, not a single extract shared the same phytocannabinoid chemical profile in regard to types, quantities, or ratios. An additional four genetically identical plants intended for clinical trials were grown in differing conditions and portrayed substantially different phytocannabinoid chemical profiles.

Conclusions & Discussion

The developed MS/MS spectral library in this research can be directly employed by other experts with access to similar instrumental configurations for putative identification of unknown peaks in Cannabis extracts, as generally performed using public/commercial spectral libraries. Moreover, one could develop in-house MS/MS spectral libraries following the chromatographic and MS characteristics suggested in this research for phytocannabinoid identification.

In terms of reliable quantification of absolute concentrations using LC/MS, analytical standards are needed since ionization efficiencies (IEs) of components with different chemical structures are difficult to predict. Herein lies the difficulty with phytocannabinoid quantification, as commercial standards for most phytocannabinoids found in the plant are not available. In the presented work, absolute concentrations for each phytocannabinoid should be regarded with different levels of confidence. For type I phytocannabinoids, for which analytical standards were available, external calibration curves were developed for quantification and compared to the widely accepted standard addition method for the same sample. No statistical difference was observed for the two methods of quantification (p = 0.13). For all other phytocannabinoids, concentrations were extrapolated by comparing IEs of the type I phytocannabinoids.

The results in this study highlight the great need for accurate analysis of phytocannabinoid compositions before and throughout medical Cannabis clinical trials, treatments, or experiments. This is particularly important when prescribing Cannabis as a medication in terms of both therapeutic potential and side effects. Therefore, the exploration and identification of as many Cannabis components as possible is critical for exploiting the full potential of this unique plant and its derivatives.

The suggested approach in this research can be applied as a straightforward analytical method to robustly detect a wide range of phytocannabinoids in Cannabis, with a high potential for successful transfer into other laboratories. Our proposed method aims to advance the development and standardization of Cannabis-based medicines and to dramatically improve our fundamental understanding of how to determine optimal Cannabis treatments for specific patients.


References & Acknowledgements:

Acknowledgements

We thank The Evelyn Gruss Lipper Charitable Foundation for financial support of this work. P.B. was supported in part at the Technion by a fellowship from the Lady Davis Foundation, and by the Levi Eshkol fellowship of the Israel Ministry of Science.

References

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2. Hanuš LO, Meyer SM, Muñoz E, Taglialatela-Scafati O, Appendino G (2016) Phytocannabinoids: a unified critical inventory. Nat Prod Rep 33:1357–1392.

3. ElSohly M, Gul W (2014) Constituents of Cannabis Sativa. Handbook of Cannabis, ed Pertwee R (Oxford University Press, New York), pp 3–22.

4. Turner SE, Williams CM, Iversen L, Whalley BJ (2017). Molecular Pharmacology of Phytocannabinoids. Phytocannabinoids, eds Kinghorn AD, Falk H, Gibbons S, Kobayashi J (Springer International Publishing, Switzerland), pp 61–101.

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9. Giese MW, Lewis MA, Giese L, Smith KM (2015) Method for the analysis of cannabinoids and terpenes in Cannabis J AOAC Int 98:1503–1522.

10. Hazekamp A, Tejkalová K, Papadimitriou S (2016) Cannabis: from cultivar to chemovar II—a metabolomics approach to Cannabis classification. Cannabis Cannabinoid Res 1:202–215.

11. Aizpurua-Olaizola O, et al. (2016) Evolution of the cannabinoid and terpene content during the growth of Cannabis sativa plants from different chemotypes. J Nat Prod 79:324–331.

12. Vergara D, et al. (2017) Compromised external validity: Federally produced Cannabis does not reflect legal markets. Sci Rep 7:46528.

13. Turner SE, Williams CM, Iversen L, Whalley BJ (2017). Molecular Pharmacology of Phytocannabinoids. Phytocannabinoids, eds Kinghorn AD, Falk H, Gibbons S, Kobayashi J (Springer International Publishing, Switzerland), pp 61–101.

14. Morales P, Hurst DP, Reggio PH (2017). Molecular Targets of the Phytocannabinoids: A Complex Picture. Phytocannabinoids, eds Kinghorn AD, Falk H, Gibbons S, Kobayashi J (Springer International Publishing, Switzerland), pp 103-131.


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