Lipid biomarkers of glioma cell growth arrest and cell death detected by 1 H magic angle spinning MRS

Tracking Therapy Response in Glioblastoma Using 1D Convolutional Neural Networks

BACKGROUND

Glioblastoma (GB) is a malignant brain tumour that is challenging to treat, often relapsing even after aggressive therapy. Evaluating therapy response relies on magnetic resonance imaging (MRI) following the Response Assessment in Neuro-Oncology (RANO) criteria. However, early assessment is hindered by phenomena such as pseudoprogression and pseudoresponse. Magnetic resonance spectroscopy (MRS/MRSI) provides metabolomics information but is underutilised due to a lack of familiarity and standardisation.

METHODS

This study explores the potential of spectroscopic imaging (MRSI) in combination with several machine learning approaches, including one-dimensional convolutional neural networks (1D-CNNs), to improve therapy response assessment. Preclinical GB (GL261-bearing mice) were studied for method optimisation and validation.

RESULTS

The proposed 1D-CNN models successfully identify different regions of tumours sampled by MRSI, i.e., normal brain (N), control/unresponsive tumour (T), and tumour responding to treatment (R). Class activation maps using Grad-CAM enabled the study of the key areas relevant to the models, providing model explainability. The generated colour-coded maps showing the N, T and R regions were highly accurate (according to Dice scores) when compared against ground truth and outperformed our previous method.

CONCLUSIONS

The proposed methodology may provide new and better opportunities for therapy response assessment, potentially providing earlier hints of tumour relapsing stages.

Establishing Imaging Biomarkers of Host Immune System Efficacy during Glioblastoma Therapy Response: Challenges, Obstacles and Future Perspectives

This hypothesis proposal addresses three major questions: (1) Why do we need imaging biomarkers for assessing the efficacy of immune system participation in glioblastoma therapy response? (2) Why are they not available yet? and (3) How can we produce them? We summarize the literature data supporting the claim that the immune system is behind the efficacy of most successful glioblastoma therapies but, unfortunately, there are no current short-term imaging biomarkers of its activity. We also discuss how using an immunocompetent murine model of glioblastoma, allowing the cure of mice and the generation of immune memory, provides a suitable framework for glioblastoma therapy response biomarker studies. Both magnetic resonance imaging and magnetic resonance-based metabolomic data (i.e., magnetic resonance spectroscopic imaging) can provide non-invasive assessments of such a system. A predictor based in nosological images, generated from magnetic resonance spectroscopic imaging analyses and their oscillatory patterns, should be translational to clinics. We also review hurdles that may explain why such an oscillatory biomarker was not reported in previous imaging glioblastoma work. Single shot explorations that neglect short-term oscillatory behavior derived from immune system attack on tumors may mislead actual response extent detection. Finally, we consider improvements required to properly predict immune system-mediated early response (1–2 weeks) to therapy. The sensible use of improved biomarkers may enable translatable evidence-based therapeutic protocols, with the possibility of extending preclinical results to human patients.

NMR spectroscopy of a single mammalian early stage embryo

The resolving power, chemical sensitivity and non-invasive nature of NMR have made it an established technique for in vivo studies of large organisms both for research and clinical applications. NMR would clearly be beneficial for analysis of entities at the microscopic scale of about 1 nL (the nanoliter scale), typical of early development of mammalian embryos, microtissues and organoids: the scale where the building blocks of complex organisms could be observed. However, the handling of such small samples (about 100 µm) and sensitivity issues have prevented a widespread adoption of NMR. In this article we show how these limitations can be overcome to obtain NMR spectra of a mammalian embryo in its early stage. To achieve this we employ ultra-compact micro-chip technologies in combination with 3D-printed micro-structures. Such device is packaged for use as plug & play sensor and it shows sufficient sensitivity to resolve NMR signals from individual bovine pre-implantation embryos. The embryos in this study are obtained through In Vitro Fertilization (IVF) techniques, transported cryopreserved to the NMR laboratory, and measured shortly after thawing. In less than 1 h these spherical samples of just 130-190 µm produce distinct spectral peaks, largely originating from lipids contained inside them. We further observe how the spectra vary from one sample to another despite their optical and morphological similarities, suggesting that the method can further develop into a non-invasive embryo assay for selection prior to embryo transfer.

Imaging of cancer lipid metabolism in response to therapy

Lipids represent a diverse array of molecules essential to the cell's structure, defense, energy, and communication. Lipid metabolism can often become dysregulated during tumor development. During cancer therapy, targeted inhibition of cell proliferation can likewise cause widespread and drastic changes in lipid composition. Molecular imaging techniques have been developed to monitor altered lipid profiles as a biomarker for cancer diagnosis and treatment response. For decades, MRS has been the dominant non-invasive technique for studying lipid metabolite levels. Recent insights into the oncogenic transformations driving changes in lipid metabolism have revealed new mechanisms and signaling molecules that can be exploited using optical imaging, mass spectrometry imaging, and positron emission tomography. These novel imaging modalities have provided researchers with a diverse toolbox to examine changes in lipids in response to a wide array of anticancer strategies including chemotherapy, radiation therapy, signal transduction inhibitors, gene therapy, immunotherapy, or a combination of these strategies. The understanding of lipid metabolism in response to cancer therapy continues to evolve as each therapeutic method emerges, and this review seeks to summarize the current field and areas of unmet needs.

Ex vivo metabolite profiling of paediatric central nervous system tumours reveals prognostic markers

Brain tumours are the most common cause of cancer death in children. Molecular studies have greatly improved our understanding of these tumours but tumour metabolism is underexplored. Metabolites measured in vivo have been reported as prognostic biomarkers of these tumours but analysis of surgically resected tumour tissue allows a more extensive set of metabolites to be measured aiding biomarker discovery and providing validation of in vivo findings. In this study, metabolites were quantified across a range of paediatric brain tumours using 1H-High-Resolution Magic Angle Spinning nuclear magnetic resonance spectroscopy (HR-MAS) and their prognostic potential investigated. HR-MAS was performed on pre-treatment frozen tumour tissue from a single centre. Univariate and multivariate Cox regression was used to examine the ability of metabolites to predict survival. The models were cross validated using C-indices and further validated by splitting the cohort into two. Higher concentrations of glutamine were predictive of a longer overall survival, whilst higher concentrations of lipids were predictive of a shorter overall survival. These metabolites were predictive independent of diagnosis, as demonstrated in multivariate Cox regression models. Whilst accurate quantification of metabolites such as glutamine in vivo is challenging, metabolites show promise as prognostic markers due to development of optimised detection methods and increasing use of 3 T clinical scanners.

Microbial Lipid Alternatives to Plant Lipids

Lipids are in high demand in food production, nutritional supplements, detergents, lubricants, and biofuels. Different oil seeds produced from plants are conventionally extracted to yield lipids. With increasing population and reduced availability of cultivable land, conventional methods of producing lipids alone will not satisfy increasing demand. Lipids produced using different microbial sources are considered as sustainable alternative to plant derived lipids. Various microorganisms belonging to the genera of algae, bacteria, yeast, fungi, or marine-derived microorganisms such as thraustochytrids possess the ability to accumulate lipids in their cells. A variety of microbial production technologies are being used to cultivate these organisms under specific conditions using agricultural residues as carbon source to be cost competitive with plant derived lipids. Microbial oils, also known as single cell oils, have many advantages when compared with plant derived lipids, such as shorter life cycle, less labor required, season and climate independence, no use of arable land and ease of scale-up. In this chapter we compare the lipids derived from plants and different microorganisms. We also highlight various analytical techniques that are being used to characterize the lipids produced in oleaginous organisms and their applications in various processes.

Response of Cisplatin Resistant Skov-3 Cells to [Pt(O,O'-Acac)(γ-Acac)(DMS)] Treatment Revealed by a Metabolomic ¹H-NMR Study

The novel [Pt(O,O′-acac)(γ-acac)(DMS)], Ptac2S, Pt(II) complex has recently gained increasing attention as a potential anticancer agent for its pharmacological activity shown in different tumor cell lines, studied both in vitro and in vivo. The mechanism of action of Ptac2S, operating on non-genomic targets, is known to be very different from that of cis-[PtCl₂(NH₃)₂], cisplatin, targeting nucleic acids. In this work, we evaluated the cytotoxicity of Ptac2S on the cisplatin resistant Epithelial Ovarian Carcinoma (EOC), SKOV-3 cells, by the MTT assay. A ¹H-NMR metabolomic approach coupled with multivariate statistical analysis was used for the first time for Ptac2S to figure out the biological mechanisms of action of the complex. The metabolic variations of intracellular metabolites and the composition of the corresponding extracellular culture media were compared to those of cisplatin (cells were treated at the IC₅₀ doses of both drugs). The reported comparative metabolomic analysis revealed a very different metabolic profile between Ptac2S and cisplatin treated samples, thus confirming the different mechanism of action of Ptac2S also in the Epithelial Ovarian Carcinoma (EOC), SKOV-3 cells line. In particular, higher levels of pyruvate were observed in Ptac2S treated, with respect to cisplatin treated, cells (in both aqueous and culture media). In addition, a very different lipid expression resulted after the exposure to the two drugs (Ptac2S and cisplatin). These results suggest a possible explanation for the Ptac2S ability to circumvent cisplatin resistance in SKOV-3 cells.

Analytical Techniques in Lipidomics: State of the Art

Current studies related to lipid identification and determination, or lipidomics in biological samples, are one of the most important issues in modern bioanalytical chemistry. There are many articles dedicated to specific analytical strategies used in lipidomics in various kinds of biological samples. However, in such literature, there is a lack of articles dedicated to a comprehensive review of the actual analytical methodologies used in lipidomics. The aim of this article is to characterize the lipidomics methods used in modern bioanalysis according to the methodological point of view: (1) chromatography/separation methods, (2) spectroscopic methods and (3) mass spectrometry and also hyphenated methods. In the first part, we discussed thin layer chromatography (TLC), high-pressure liquid chromatography (HPLC), gas chromatography (GC) and capillary electrophoresis (CE). The second part includes spectroscopic techniques such as Raman spectroscopy (RS), Fourier transform infrared spectroscopy (FT-IR) and nuclear magnetic resonance (NMR). The third part is a synthetic review of mass spectrometry, matrix-assisted laser desorption/ionization (MALDI), hyphenated methods, which include liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and also multidimensional techniques. Other aspects are the possibilities of the application of the described methods in lipidomics studies. Due to the fact that the exploration of new methods of lipidomics analysis and their applications in clinical and medical studies are still challenging for researchers working in life science, we hope that this review article will be very useful for readers.

Assessment of alterations in X-ray irradiation-induced DNA damage of glioma cells by using proton nuclear magnetic resonance spectroscopy

Glioma is one of the most common types of brain tumors. DNA damage is closely associated with glioma cell apoptosis induced by X-ray irradiation. Alterations of metabolites in glioma can be detected noninvasively by proton nuclear magnetic resonance (1H NMR) spectroscopy. To noninvasively explore the micro mechanism in X-ray irradiation-induced apoptosis, the relationship between metabolites and DNA damage in glioma cells was investigated. Three glioma cell lines (C6, U87 and U251) were randomly designated as control (0Gy) and treatment groups (1, 5, 10, 15Gy). After X-ray exposure, each group was separated into four parts: (i) to detect metabolites by 1H NMR spectroscopy; (ii) to make cell colonies; (iii) to detect cell cycle distribution and apoptosis rate by flow cytometry; and (iv) to measure DNA damage by comet assay. The metabolite ratios of lactate/creatine and succinate/creatine decreased (lactate/creatine: C6, 22.17-66.27%; U87, 15.93-44.56%; U251, 26.27-74.48%. succinate/creatine: C6, 14.41-48.35%; U87, 22.03-70.62%; U251, 17.33-60.06%) and choline/creatine increased (C6, 52.22-389.68%; U87, 56.15-82.36%; U251, 31.87-278.62%) in the treatment groups compared with the control group (each P<0.05), which linearly depended on DNA damage. An increasing dose of X-ray irradiation increased numbers of apoptotic cells (P<0.01), and the DNA damage parameters were dose-dependent (P<0.05). The colony-forming rate declined (P<0.01) and the percentage of cells at G1 stage increased when exposed to 1Gy X-ray (three cell lines, P<0.05). Metabolite alterations detected by 1H NMR spectroscopy can be used to determine DNA damage induced by X-ray irradiation. 1H NMR spectroscopy is a noninvasive method to predict DNA damage of glioma cell at the micro level.

MRSI-based molecular imaging of therapy response to temozolomide in preclinical glioblastoma using source analysis

Characterization of glioblastoma (GB) response to treatment is a key factor for improving patients' survival and prognosis. MRI and magnetic resonance spectroscopic imaging (MRSI) provide morphologic and metabolic profiles of GB but usually fail to produce unequivocal biomarkers of response. The purpose of this work is to provide proof of concept of the ability of a semi-supervised signal source extraction methodology to produce images with robust recognition of response to temozolomide (TMZ) in a preclinical GB model. A total of 38 female C57BL/6 mice were used in this study. The semi-supervised methodology extracted the required sources from a training set consisting of MRSI grids from eight GL261 GBs treated with TMZ, and six control untreated GBs. Three different sources (normal brain parenchyma, actively proliferating GB and GB responding to treatment) were extracted and used for calculating nosologic maps representing the spatial response to treatment. These results were validated with an independent test set (7 control and 17 treated cases) and correlated with histopathology. Major differences between the responder and non-responder sources were mainly related to the resonances of mobile lipids (MLs) and polyunsaturated fatty acids in MLs (0.9, 1.3 and 2.8 ppm). Responding tumors showed significantly lower mitotic (3.3 ± 2.9 versus 14.1 ± 4.2 mitoses/field) and proliferation rates (29.8 ± 10.3 versus 57.8 ± 5.4%) than control untreated cases. The methodology described in this work is able to produce nosological images of response to TMZ in GL261 preclinical GBs and suitably correlates with the histopathological analysis of tumors. A similar strategy could be devised for monitoring response to treatment in patients. Copyright © 2016 John Wiley & Sons, Ltd.

Metabolic markers of MG-63 osteosarcoma cell line response to doxorubicin and methotrexate treatment: comparison to cisplatin

A high resolution magic angle spinning NMR metabolomics study of the effects of doxorubicin (DOX), methotrexate (MTX) and cisplatin (cDDP) on MG-63 cells is presented and unveils the cellular metabolic adaptations to these drugs, often used together in clinical protocols. Although cDDP-treated cells were confirmed to undergo extensive membrane degradation accompanied by increased neutral lipids, DOX- and MTX-treated cells showed no lipids increase and different phospholipid signatures, which suggests that (i) DOX induces significant membrane degradation, decreased membrane synthesis, and apparent inhibition of de novo lipid synthesis, and (ii) MTX induces decreased membrane synthesis, while no membrane disruption or de novo lipid synthesis seem to occur. Nucleotide signatures were in apparent agreement with the different drug action mechanisms, a link having been found between UDP-GlcNAc and the active pathways of membrane degradation and energy metabolism, for cDDP and DOX, with a relation to oxidative state and DNA degradation, for cDDP. Correlation studies unveiled drug-specific antioxidative signatures, which pinpointed m- and s-inositols, taurine, glutamate/glutamine, and possibly creatine as important in glutathione metabolism. These results illustrate the ability of NMR metabolomics to measure cellular responses to different drugs, a first step toward understanding drug synergism and the definition of new biomarkers of drug efficacy.

Molecular imaging coupled to pattern recognition distinguishes response to temozolomide in preclinical glioblastoma

Non-invasive monitoring of response to treatment of glioblastoma (GB) is nowadays carried out using MRI. MRS and MR spectroscopic imaging (MRSI) constitute promising tools for this undertaking. A temozolomide (TMZ) protocol was optimized for GL261 GB. Sixty-three mice were studied by MRI/MRS/MRSI. The spectroscopic information was used for the classification of control brain and untreated and responding GB, and validated against post-mortem immunostainings in selected animals. A classification system was developed, based on the MRSI-sampled metabolome of normal brain parenchyma, untreated and responding GB, with a 93% accuracy. Classification of an independent test set yielded a balanced error rate of 6% or less. Classifications correlated well both with tumor volume changes detected by MRI after two TMZ cycles and with the histopathological data: a significant decrease (p < 0.05) in the proliferation and mitotic rates and a 4.6-fold increase in the apoptotic rate. A surrogate response biomarker based on the linear combination of 12 spectral features has been found in the MRS/MRSI pattern of treated tumors, allowing the non-invasive classification of growing and responding GL261 GB. The methodology described can be applied to preclinical treatment efficacy studies to test new antitumoral drugs, and begets translational potential for early response detection in clinical studies.

Hippocampal and thalamic neuronal metabolism in a putative rat model of schizophrenia

The transcription factor early growth response protein 3 (EGR3) is involved in schizophrenia. We developed a putative rat model of schizophrenia by transfecting lentiviral particles carrying the Egr3 gene into bilateral hippocampal dentate gyrus. We assessed spatial working memory using the Morris water maze test, and neuronal metabolite levels in bilateral hippocampus and thalamus were determined by 3.0 T proton magnetic resonance spectroscopy. Choline content was significantly greater in the hippocampus after transfection, while N-acetylaspartate and the ratio of N-acetylaspartate to creatine/phosphocreatine in the thalamus were lower than in controls. This study is the first to report evaluation of brain metabolites using 3.0 T proton magnetic resonance spectroscopy in rats transfected with Egr3, and reveals metabolic abnormalities in the hippocampus and thalamus in this putative model of schizophrenia.

Metabolomics in cell culture--a strategy to study crucial metabolic pathways in cancer development and the response to treatment

Metabolomics is a comprehensive tool for monitoring processes within biological systems. Thus, metabolomics may be widely applied to the determination of diagnostic biomarkers for certain diseases or treatment outcomes. There is significant potential for metabolomics to be implemented in cancer research because cancer may modify metabolic pathways in the whole organism. However, not all biological questions can be answered solely by the examination of small molecule composition in biofluids; in particular, the study of cellular processes or preclinical drug testing requires ex vivo models. The major objective of this review was to summarise the current achievement in the field of metabolomics in cancer cell culture-focusing on the metabolic pathways regulated in different cancer cell lines-and progress that has been made in the area of drug screening and development by the implementation of metabolomics in cell lines.

Metabolic impact of anti-angiogenic agents on U87 glioma cells

BACKGROUND

Glioma cells not only secrete high levels of vascular endothelial growth factor (VEGF) but also express VEGF receptors (VEGFR), supporting the existence of an autocrine loop. The direct impact on glioma cells metabolism of drugs targeting the VEGF pathway, such as Bevacizumab (Bev) or VEGFR Tyrosine Kinase Inhibitor (TKI), is poorly known.

MATERIAL AND METHODS

U87 cells were treated with Bev or SU1498, a selective VEGFR2 TKI. VEGFR expression was checked with FACS flow cytometry and Quantitative Real-Time PCR. VEGF secretion into the medium was assessed with an ELISA kit. Metabolomic studies on cells were performed using High Resolution Magic Angle Spinning Spectroscopy (HR-MAS).

RESULTS

U87 cells secreted VEGF and expressed low level of VEGFR2, but no detectable VEGFR1. Exposure to SU1498, but not Bev, significantly impacted cell proliferation and apoptosis. Metabolomic studies with HR MAS showed that Bev had no significant effect on cell metabolism, while SU1498 induced a marked increase in lipids and a decrease in glycerophosphocholine. Accordingly, accumulation of lipid droplets was seen in the cytoplasm of SU1498-treated U87 cells.

CONCLUSION

Although both drugs target the VEGF pathway, only SU1498 showed a clear impact on cell proliferation, cell morphology and metabolism. Bevacizumab is thus less likely to modify glioma cells phenotype due to a direct therapeutic pressure on the VEGF autocrine loop. In patients treated with VEGFR TKI, monitoring lipids with magnetic resonance spectroscopic (MRS) might be a valuable marker to assess drug cytotoxicity.

Monitoring response to cytostatic cisplatin in a HER2(+) ovary cancer model by MRI and in vitro and in vivo MR spectroscopy

Background:

Limited knowledge is available on alterations induced by cytostatic drugs on magnetic resonance spectroscopy (MRS) and imaging (MRI) parameters of human cancers, in absence of apoptosis or cytotoxicity. We here investigated the effects of a cytostatic cisplatin (CDDP) treatment on ¹H MRS and MRI of HER2-overexpressing epithelial ovarian cancer (EOC) cells and in vivo xenografts.

Methods:

High-resolution MRS analyses were performed on in vivo passaged SKOV3.ip cells and cell/tissue extracts (16.4 or 9.4 T). In vivo MRI/MRS quantitative analyses (4.7 T) were conducted on xenografts obtained by subcutaneous implantation of SKOV3.ip cells in SCID mice. The apparent diffusion coefficient (ADC) and metabolite levels were measured.

Results:

CDDP-induced cytostatic effects were associated with a metabolic shift of cancer cells towards accumulation of MRS-detected neutral lipids, whereas the total choline profile failed to be perturbed in both cultured cells and xenografts. In vivo MRI examinations showed delayed tumour growth in the CDDP-treated group, associated with early reduction of the ADC mean value.

Conclusion:

This study provides an integrated set of information on cancer metabolism and physiology for monitoring the response of an EOC model to a cytostatic chemotherapy, as a basis for improving the interpretation of non-invasive MR examinations of EOC patients.

Increased unsaturation of lipids in cytoplasmic lipid droplets in DAOY cancer cells in response to cisplatin treatment

Increases in ¹H nuclear magnetic resonance spectroscopy (NMR) visible lipids are a well-documented sign of treatment response in cancers. Lipids in cytoplasmic lipid droplets (LDs) are the main contributors to the NMR lipid signals. Two human primitive neuroectodermal tumour cell lines with different sensitivities to cisplatin treatment were studied. Increases in NMR visible saturated and unsaturated lipids in cisplatin treated DAOY cells were associated with the accumulation of LDs prior to DNA fragmentation due to apoptosis. An increase in unsaturated fatty acids (UFAs) was detected in isolated LDs from DAOY cells, in contrast to a slight decrease in UFAs in lipid extracts from whole cells. Oleic acid and linoleic acid were identified as the accumulating UFAs in LDs by heteronuclear single quantum coherence spectroscopy (HSQC). ¹H NMR lipids in non-responding PFSK-1 cells were unchanged by exposure to 10 μM cisplatin. These findings support the potential of NMR detectable UFAs to serve as a non-invasive marker of tumour cell response to treatment.