Shivanand Pudakalakatti1, Ashvin Jaiswal2, Prasanta Dutta1, Michael Curran2, and Pratip Bhattacharya1
1Department of cancer systems imaging, University of Texas M D Anderson Cancer Center, Houston, TX, United States, 2Department of Immunology, University of Texas M D Anderson Cancer Center, Houston, TX, United States
Synopsis
The cancer immunotherapy has brought new ray of hope in cancer patients
with its capability of curing cancer with less side effects. However not all
patients responds to therapy. In this study we have employed Nuclear Magnetic
Spectroscopy (NMR) and in vivo
hyperpolarized 1-13C pyruvate magnetic resonance spectroscopy (MRS)
to differentiate immunotherapy responding from immunotherapy resisting melanoma.
Purpose
Cancer immunotherapy is employed by blocking the two negative regulatory
proteins of T-cell activation known as cytotoxic T-lymphocyte associated
protein-4 (CTLA4) and programmed death-1 (PD1). The immunotherapy is successful
in treating cancer patients of melanoma however not all patients responds. The overarching
purpose of our study is to image immunotherapy responding and resistant
patients at metabolic level to distinguish.Methods
We have employed a two prong strategy to assess immunotherapy response;
a) in vitro high resolution Nuclear
Magnetic Resonance (NMR) spectroscopy and b) in vivo hyperpolarized 1-13C pyruvate magnetic resonance
spectroscopy (MRS) in live mice model1. The standard one dimensional (1D) 1H
NMR with water suppression sequence was used to acquire the data on a melanoma cell
line responsive to immunotherapy (B16/BL6 TMT) and a corresponding immunotherapy
resistant cell line (B16/BL6 3I F4). The data was processed in Topspin 3.1 and resonances
are identified using Chenomx, human metabolic database (HMDB), 2D [1H-1H]
TOCSY and 2D [1H-13C] HSQC2-3. All
the data were acquired on Bruker spectrometer operating at 600 MHz proton
resonance frequency equipped with triple resonance TXI (1H , 13C,
15N) cryogenically cooled probe. The dissolution DNP (Hypersense)
operating at 3T is employed to hyperpolarize 1-13C pyruvate. The 13C
magnetic resonance spectrum of hyperpolarized 1-13C pyruvate
acquired on intact, live immunocompetent mice models with melanoma tumor
implanted in flank at 7T Bruker MRI scanner.Results
The analysis of 1D 1H NMR revealed distinct difference in
metabolic activity in two different melanoma cell lines; immunotherapy
responsive and resistant (number of samples TMT= 8, 3I F4= 8). The metabolites lactate
(P = 0.03), alanine (P < 0.001) and phosphocholine (P < 0.001) were altered
significantly in the two individual cell lines (Figure 1). The real time dynamic hyperpolarized MRS on injection of
1-13C pyruvate reveals downregulation of conversion of pyruvate to
lactate in immunotherapy resistant mice compared to mice responding to immunotherapy
(Table I).Discussion
NMR data suggests upregulation of lactate and alanine in immunotherapy
resistant cell lines compared to immunotherapy responding ones. However,
phosphocholine is downregulated in immunotherapy resistant cell lines but upregulated
in responding ones. This shows that immunotherapy responding cells mainly
utilizes the end products of glycolysis to generate phospholipids leading to
increased phosphocholine synthesis and decreased lactate production2. There were four categories of mice used in the
dynamic metabolomics study 1) immunotherapy responding treated with
immunotherapy (anti PD-1 and anti-CTLA4); 2) immunotherapy responding untreated
3) immunotherapy resistant treated and 4) immunotherapy resistant untreated. The
hyperpolarized 1-13C pyruvate dynamics in melanoma bearing mice
suggests decreased ‘Warburg effect’ in immunotherapy responding mice compared to
untreated immunotherapy responding one. The same trend continued in immunotherapy
resistant treated and untreated category. However, immunotherapy resistant mice
treated with immunotherapy exhibited low Warburg effect. We are expanding this
study to validate this exciting preliminary results.Conclusion
1H NMR and hyperpolarized 13C MRS were successfully employed
to define the metabolic differences in immunotherapy responding and
non-responding cell lines and in vivo
animal models of melanoma. Altered concentrations of lactate, alanine and
phosphocholine were observed and studies are currently underway to understand
the mechanistic basis of this metabolic adaptation and employ these differences
are potential imaging biomarkers of immunotherapy resistance in the clinic. Acknowledgements
1) We would like to thank the department of cancer systems imaging, MD Anderson cancer center CCSG-funded NMR core facility (CA016672) and MRI facilities are highly acknowledged.
2) The research has been
funded in part by MD
Anderson Institutional Research Grants , MD Anderson Institutional
Startup, Brain
SPORE
Developmental
Research Award
and Koch Foundation.
References
1. Albers,
M. J.; Bok, R.; Chen, A. P.; Cunningham, C. H.; Zierhut, M. L.; Zhang, V. Y.;
Kohler, S. J.; Tropp, J.; Hurd, R. E.; Yen, Y.-F.; Nelson, S. J.; Vigneron, D.
B.; Kurhanewicz, J., Hyperpolarized (13)C Lactate, Pyruvate, and Alanine:
Noninvasive Biomarkers for Prostate Cancer Detection and Grading. Cancer research 2008, 68 (20), 8607-8615.
2. Armitage,
E. G.; Southam, A. D., Monitoring cancer prognosis, diagnosis and treatment
efficacy using metabolomics and lipidomics. Metabolomics
2016, 12 (9), 146.
3. Salzillo TC, Hu J, Nguyen L,
Pudakalakatti S, et al. (2016)
Interrogating metabolism in brain cancer
(Book Chapter). Mag Reson Imag Clin in North America 2016 4:687-703.