In vivo metabolic profiling of glioma-initiating cells using proton magnetic resonance spectroscopy at 14.1 Tesla

The STEMRI trial: Magnetic resonance spectroscopy imaging can define tumor areas enriched in glioblastoma stem-like cells

Despite maximally safe resection of the magnetic resonance imaging (MRI)-defined contrast-enhanced (CE) central tumor area and chemoradiotherapy, most patients with glioblastoma (GBM) relapse within a year in peritumoral FLAIR regions. Magnetic resonance spectroscopy imaging (MRSI) can discriminate metabolic tumor areas with higher recurrence potential as CNI+ regions (choline/N-acetyl-aspartate index >2) can predict relapse sites. As relapses are mainly imputed to glioblastoma stem-like cells (GSCs), CNI+ areas might be GSC enriched. In this prospective trial, 16 patients with GBM underwent MRSI/MRI before surgery/chemoradiotherapy to investigate GSC content in CNI-/+ biopsies from CE/FLAIR. Biopsy and derived-GSC characterization revealed a FLAIR/CNI+ sample enrichment in GSC and in gene signatures related to stemness, DNA repair, adhesion/migration, and mitochondrial bioenergetics. FLAIR/CNI+ samples generate GSC-enriched neurospheres faster than FLAIR/CNI-. Parameters assessing biopsy GSC content and time-to-neurosphere formation in FLAIR/CNI+ were associated with worse patient outcome. Preoperative MRI/MRSI would certainly allow better resection and targeting of FLAIR/CNI+ areas, as their GSC enrichment can predict worse outcomes.

Lipid Alterations in Glioma: A Systematic Review

Gliomas are highly lethal tumours characterised by heterogeneous molecular features, producing various metabolic phenotypes leading to therapeutic resistance. Lipid metabolism reprogramming is predominant and has contributed to the metabolic plasticity in glioma. This systematic review aims to discover lipids alteration and their biological roles in glioma and the identification of potential lipids biomarker. This systematic review was conducted using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Extensive research articles search for the last 10 years, from 2011 to 2021, were conducted using four electronic databases, including PubMed, Web of Science, CINAHL and ScienceDirect. A total of 158 research articles were included in this study. All studies reported significant lipid alteration between glioma and control groups, impacting glioma cell growth, proliferation, drug resistance, patients' survival and metastasis. Different lipids demonstrated different biological roles, either beneficial or detrimental effects on glioma. Notably, prostaglandin (PGE2), triacylglycerol (TG), phosphatidylcholine (PC), and sphingosine-1-phosphate play significant roles in glioma development. Conversely, the most prominent anti-carcinogenic lipids include docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and vitamin D3 have been reported to have detrimental effects on glioma cells. Furthermore, high lipid signals were detected at 0.9 and 1.3 ppm in high-grade glioma relative to low-grade glioma. This evidence shows that lipid metabolisms were significantly dysregulated in glioma. Concurrent with this knowledge, the discovery of specific lipid classes altered in glioma will accelerate the development of potential lipid biomarkers and enhance future glioma therapeutics.

7T HR FID-MRSI Compared to Amino Acid PET: Glutamine and Glycine as Promising Biomarkers in Brain Tumors

Simple Summary

Magnetic resonance spectroscopic imaging is an imaging method that can map the distribution of multiple biochemicals in the human brain in one scan. Using stronger magnetic fields, such as 7 Tesla, allows for higher resolution images and more biochemical maps. To test these results, we compared it to positron emission tomography, the established clinical standard for metabolic imaging. This comparison mainly looked at the overlap between regions with increased signal between both methods. We found that the molecules glutamine and glycine, only mappable at 7 Tesla, corresponded better to positron emission tomography than the commonly used choline.

Abstract

(1) Background: Recent developments in 7T magnetic resonance spectroscopic imaging (MRSI) made the acquisition of high-resolution metabolic images in clinically feasible measurement times possible. The amino acids glutamine (Gln) and glycine (Gly) were identified as potential neuro-oncological markers of importance. For the first time, we compared 7T MRSI to amino acid PET in a cohort of glioma patients. (2) Methods: In 24 patients, we co-registered 7T MRSI and routine PET and compared hotspot volumes of interest (VOI). We evaluated dice similarity coefficients (DSC), volume, center of intensity distance (CoI), median and threshold values for VOIs of PET and ratios of total choline (tCho), Gln, Gly, myo-inositol (Ins) to total N-acetylaspartate (tNAA) or total creatine (tCr). (3) Results: We found that Gln and Gly ratios generally resulted in a higher correspondence to PET than tCho. Using cutoffs of 1.6-times median values of a control region, DSCs to PET were 0.53 ± 0.36 for tCho/tNAA, 0.66 ± 0.40 for Gln/tNAA, 0.57 ± 0.36 for Gly/tNAA, and 0.38 ± 0.31 for Ins/tNAA. (4) Conclusions: Our 7T MRSI data corresponded better to PET than previous studies at lower fields. Our results for Gln and Gly highlight the importance of future research (e.g., using Gln PET tracers) into the role of both amino acids.

A novel method to measure T1 -relaxation times of macromolecules and quantification of the macromolecular resonances

PURPOSE

Macromolecular peaks underlying metabolite spectra influence the quantification of metabolites. Therefore, it is important to understand the extent of contribution from macromolecules (MMs) in metabolite quantification. However, to model MMs more accurately in spectral fitting, differences in T₁ relaxation times among individual MM peaks must be considered. Characterization of T₁ -relaxation times for all individual MM peaks using a single inversion recovery technique is difficult due to eventual contributions from metabolites. On the contrary, a double inversion recovery (DIR) technique provided flexibility to acquire MM spectra spanning a range of longitudinal magnetizations with minimal metabolite influence. Thus, a novel method to determine T₁ -relaxation times of individual MM peaks is reported in this work.

METHODS

Extensive Bloch simulations were performed to determine inversion time combinations for a DIR technique that yielded adequate MM signal with varying longitudinal magnetizations while minimizing metabolite contributions. MM spectra were acquired using DIR-metabolite-cycled semi-LASER sequence. LCModel concentrations were fitted to the DIR signal equation to calculate T₁ -relaxation times.

RESULTS

T₁ -relaxation times of MMs range from 204 to 510 ms and 253 to 564 ms in gray- and white-matter rich voxels respectively at 9.4T. Additionally, concentrations of 13 MM peaks are reported.

CONCLUSION

A novel DIR method is reported in this work to calculate T₁ -relaxation times of MMs in the human brain. T₁ -relaxation times and relaxation time corrected concentrations of individual MMs are reported in gray- and white-matter rich voxels for the first time at 9.4T.

Early detection of human glioma sphere xenografts in mouse brain using diffusion MRI at 14.1 T

Glioma models have provided important insights into human brain cancers. Among the investigative tools, MRI has allowed their characterization and diagnosis. In this study, we investigated whether diffusion MRI might be a useful technique for early detection and characterization of slow-growing and diffuse infiltrative gliomas, such as the proposed new models, LN-2669GS and LN-2540GS glioma sphere xenografts. Tumours grown in these models are not visible in conventional T₂ -weighted or contrast-enhanced T₁ -weighted MRI at 14.1 T. Diffusion-weighted imaging and diffusion tensor imaging protocols were optimized for contrast by exploring long diffusion times sensitive for probing the microstructural alterations induced in the normal brain by the slow infiltration of glioma sphere cells. Compared with T₂ -weighted images, tumours were properly identified in their early stage of growth using diffusion MRI, and confirmed by localized proton MR spectroscopy as well as immunohistochemistry. The first evidence of tumour presence was revealed for both glioma sphere xenograft models three months after tumour implantation, while no necrosis, oedema or haemorrhage were detected either by MRI or by histology. Moreover, different values of diffusion indices, such as mean diffusivity and fractional anisotropy, were obtained in tumours grown from LN-2669GS and LN-2540GS glioma sphere lines. These observations highlighted diverse tumour microstructures for both xenograft models, which were reflected in histology. This study demonstrates the ability of diffusion MRI techniques to identify and investigate early stages of slow-growing, invasive tumours in the mouse brain, thus providing a potential imaging biomarker for early detection of tumours in humans.

Characterization of the response of taurine protons to PRESS at 9.4 T for Resolving choline and Determining taurine T2

Point-resolved spectroscopy (PRESS), characterized by two TEs (TE1 and TE2 ), can be employed to perform animal magnetic resonance spectroscopy (MRS) studies at 9.4 T. Taurine (Tau) and choline (Cho) are relevant metabolites that can be measured by MRS. In this work, the response of the J-coupled protons of Tau as a function of PRESS TE1 and TE2 was characterized at 9.4 T to achieve two objectives. The first was to determine two TE1 and TE2 combinations that could be used to obtain T2 -corrected measures of Tau (3.42 ppm) that were minimally influenced by J coupling. The second was to exploit the Tau J coupling to find a timing combination that minimized the 3.25-ppm Tau signal to enable the Cho (3.22 ppm) resonance to be resolved from the overlapping Tau signal. The response of Tau protons was investigated both numerically and experimentally. It was numerically determined that the timings {TE1 , TE2 } = {17 ms, 10 ms} and {TE1 , TE2 } = {80 ms, 70 ms} yielded similar 3.42-ppm Tau resonance areas (5% difference), rendering them suitable for Tau T2 determination. {TE1 , TE2 } = {25 ms, 50 ms} was found to yield minimal 3.25-ppm Tau signal, reducing its interference with Cho. The efficacy of the timings was demonstrated on phantom solutions and in vivo in four Sprague Dawley rats. LCModel was employed to analyse the in vivo spectra and Tau T2 values were estimated by fitting the Tau peak areas obtained with {TE1 , TE2 } = {17 ms, 10 ms} and {TE1 , TE2 } = {80 ms, 70 ms} to a monoexponentially decaying function. An average Tau T2 of 106 ms (standard deviation, 12 ms) was obtained. LCModel analysis of rat spectra obtained with {TE1 , TE2 } = {25 ms, 50 ms} demonstrated negligible levels of Tau signal, compared with that obtained with short TE.

Magnetic Resonance (MR) Metabolic Imaging in Glioma

This review is focused on describing the use of magnetic resonance (MR) spectroscopy for metabolic imaging of brain tumors. We will first review the MR metabolic imaging findings generated from preclinical models, focusing primarily on in vivo studies, and will then describe the use of metabolic imaging in the clinical setting. We will address relatively well-established (1) H MRS approaches, as well as (31) P MRS, (13) C MRS and emerging hyperpolarized (13) C MRS methodologies, and will describe the use of metabolic imaging for understanding the basic biology of glioma as well as for improving the characterization and monitoring of brain tumors in the clinic.

OVCAR-3 spheroid-derived cells display distinct metabolic profiles

Introduction

Recently, multicellular spheroids were isolated from a well-established epithelial ovarian cancer cell line, OVCAR-3, and were propagated in vitro. These spheroid-derived cells displayed numerous hallmarks of cancer stem cells, which are chemo- and radioresistant cells thought to be a significant cause of cancer recurrence and resultant mortality. Gene set enrichment analysis of expression data from the OVCAR-3 cells and the spheroid-derived putative cancer stem cells identified several metabolic pathways enriched in differentially expressed genes. Before this, there had been little previous knowledge or investigation of systems-scale metabolic differences between cancer cells and cancer stem cells, and no knowledge of such differences in ovarian cancer stem cells.

Methods

To determine if there were substantial metabolic changes corresponding with these transcriptional differences, we used two-dimensional gas chromatography coupled to mass spectrometry to measure the metabolite profiles of the two cell lines.

Results

These two cell lines exhibited significant metabolic differences in both intracellular and extracellular metabolite measurements. Principal components analysis, an unsupervised dimensional reduction technique, showed complete separation between the two cell types based on their metabolite profiles. Pathway analysis of intracellular metabolomics data revealed close overlap with metabolic pathways identified from gene expression data, with four out of six pathways found enriched in gene-level analysis also enriched in metabolite-level analysis. Some of those pathways contained multiple metabolites that were individually statistically significantly different between the two cell lines, with one of the most broadly and consistently different pathways, arginine and proline metabolism, suggesting an interesting hypothesis about cancerous and stem-like metabolic phenotypes in this pair of cell lines.

Conclusions

Overall, we demonstrate for the first time that metabolism in an ovarian cancer stem cell line is distinct from that of more differentiated isogenic cancer cells, supporting the potential importance of metabolism in the differences between cancer cells and cancer stem cells.

¹H MRS characterization of neurochemical profiles in orthotopic mouse models of human brain tumors

Glioblastoma (GBM), the most common primary brain tumor, is resistant to currently available treatments. The development of mouse models of human GBM has provided a tool for studying mechanisms involved in tumor initiation and growth as well as a platform for preclinical investigation of new drugs. In this study we used (1) H MR spectroscopy to study the neurochemical profile of a human orthotopic tumor (HOT) mouse model of human GBM. The goal of this study was to evaluate differences in metabolite concentrations in the GBM HOT mice when compared with normal mouse brain in order to determine if MRS could reliably differentiate tumor from normal brain. A TE =19 ms PRESS sequence at 9.4 T was used for measuring metabolite levels in 12 GBM mice and 8 healthy mice. Levels for 12 metabolites and for lipids/macromolecules at 0.9 ppm and at 1.3 ppm were reliably detected in all mouse spectra. The tumors had significantly lower concentrations of total creatine, GABA, glutamate, total N-acetylaspartate, aspartate, lipids/macromolecules at 0.9 ppm, and lipids/macromolecules at 1.3 ppm than did the brains of normal mice. The concentrations of glycine and lactate, however, were significantly higher in tumors than in normal brain.

Ionizing radiations sustain glioblastoma cell dedifferentiation to a stem-like phenotype through survivin: possible involvement in radioresistance

Glioblastomas (GBM) are some bad prognosis brain tumors despite a conventional treatment associating surgical resection and subsequent radio-chemotherapy. Among these heterogeneous tumors, a subpopulation of chemo- and radioresistant GBM stem-like cells appears to be involved in the systematic GBM recurrence. Moreover, recent studies showed that differentiated tumor cells may have the ability to dedifferentiate and acquire a stem-like phenotype, a phenomenon also called plasticity, in response to microenvironment stresses such as hypoxia. We hypothesized that GBM cells could be subjected to a similar dedifferentiation process after ionizing radiations (IRs), then supporting the GBM rapid recurrence after radiotherapy. In the present study we demonstrated that subtoxic IR exposure of differentiated GBM cells isolated from patient resections potentiated the long-term reacquisition of stem-associated properties such as the ability to generate primary and secondary neurospheres, the expression of stemness markers and an increased tumorigenicity. We also identified during this process an upregulation of the anti-apoptotic protein survivin and we showed that its specific downregulation led to the blockade of the IR-induced plasticity. Altogether, these results demonstrated that irradiation could regulate GBM cell dedifferentiation via a survivin-dependent pathway. Targeting the mechanisms associated with IR-induced plasticity will likely contribute to the development of some innovating pharmacological strategies for an improved radiosensitization of these aggressive brain cancers.

Metabolic profiling of dividing cells in live rodent brain by proton magnetic resonance spectroscopy (1HMRS) and LCModel analysis

Rationale

Dividing cells can be detected in the live brain by positron emission tomography or optical imaging. Here we apply proton magnetic resonance spectroscopy (¹HMRS) and a widely used spectral fitting algorithm to characterize the effect of increased neurogenesis after electroconvulsive shock in the live rodent brain via spectral signatures representing mobile lipids resonating at ∼1.30 ppm. In addition, we also apply the same ¹HMRS methodology to metabolically profile glioblastomas with actively dividing cells growing in RCAS-PDGF mice.

Methods

¹HMRS metabolic profiles were acquired on a 9.4T MRI instrument in combination with LCModel spectral analysis of: 1) rat brains before and after ECS or sham treatments and 2) RCAS-PDGF mice with glioblastomas and wild-type controls. Quantified ¹HMRS data were compared to post-mortem histology.

Results

Dividing cells in the rat hippocampus increased ∼3-fold after ECS compared to sham treatment. Quantification of hippocampal metabolites revealed significant decreases in N-acetyl-aspartate but no evidence of an elevated signal at ∼1.3 ppm (Lip13a+Lip13b) in the ECS compared to the sham group. In RCAS-PDGF mice a high density (22%) of dividing cells characterized glioblastomas. Nile Red staining revealed a small fraction (3%) of dying cells with intracellular lipid droplets in the tumors of RCAS-PDGF mice. Concentrations of NAA were lower, whereas lactate and Lip13a+Lip13b were found to be significantly higher in glioblastomas of RCAS-PDGF mice, when compared to normal brain tissue in the control mice.

Conclusions

Metabolic profiling using ¹HMRS in combination with LCModel analysis did not reveal correlation between Lip13a+Lip13b spectral signatures and an increase in neurogenesis in adult rat hippocampus after ECS. However, increases in Lip13a+Lip13b were evident in glioblastomas suggesting that a higher density of actively dividing cells and/or the presence of lipid droplets is necessary for LCModel to reveal mobile lipids.

Quantification, self-renewal, and genetic tracing of FL1⁺ tumor-initiating cells in a large cohort of human gliomas

Evidence has emerged that the initiation and growth of gliomas is sustained by a subpopulation of cancer-initiating cells (CICs). Because of the difficulty of using markers to tag CICs in gliomas, we have previously exploited more robust phenotypic characteristics, including a specific morphology and intrincic autofluorescence, to identify and isolate a subpopulation of glioma CICs, called FL1(+). The objective of this study was to further validate our method in a large cohort of human glioma and a mouse model of glioma. Seventy-four human gliomas of all grades and the GFAP-V(12)HA-ras B8 mouse model were analyzed for in vitro self-renewal capacity and their content of FL1(+). Nonneoplastic brain tissue and embryonic mouse brain were used as control. Genetic traceability along passages was assessed with microsatellite analysis. We found that FL1(+) cells from low-grade gliomas and from control nonneoplasic brain tissue show a lower level of autofluorescence and undergo a restricted number of cell divisions before dying in culture. In contrast, we found that FL1(+) cells derived from many but not all high-grade gliomas acquire high levels of autofluorescence and can be propagated in long-term cultures. Moreover, FL1(+) cells show a remarkable traceability over time in vitro and in vivo. Our results show that FL1(+) cells can be found in all specimens of a large cohort of human gliomas of different grades and in a model of genetically induced mouse glioma as well as nonneoplastic brain. However, their self-renewal capacity is variable and seems to be dependent on the tumor grade.