Magnetic resonance spectroscopy for the study of cns malignancies

GABA production induced by imipridones is a targetable and imageable metabolic alteration in diffuse midline gliomas

Diffuse midline gliomas (DMGs) are lethal primary brain tumors in children. The imipridones ONC201 and ONC206 induce mitochondrial dysfunction and have emerged as promising therapies for DMG patients. However, efficacy as monotherapy is limited, identifying a need for strategies that enhance response. Another hurdle is the lack of biomarkers that report on drug-target engagement at an early timepoint after treatment onset. Here, using 1 H-magnetic resonance spectroscopy, which is a non-invasive method of quantifying metabolite pool sizes, we show that accumulation of ψ-aminobutyric acid (GABA) is an early metabolic biomarker that can be detected within a week of ONC206 treatment, when anatomical alterations are absent, in mice bearing orthotopic xenografts. Mechanistically, imipridones activate the mitochondrial protease ClpP and upregulate the stress-responsive transcription factor ATF4. ATF4, in turn, upregulates glutamate decarboxylase, which synthesizes GABA, and downregulates ABAT , which degrades GABA, leading to GABA accumulation in DMG cells and tumors. Functionally, GABA secreted by imipridone-treated cells acts in an autocrine manner via the GABAB receptor to induce expression of superoxide dismutase (SOD1), which mitigates imipridone-induced oxidative stress and, thereby, curbs apoptosis. Importantly, blocking autocrine GABA signaling using the clinical stage GABAB receptor antagonist SGS-742 exacerbates oxidative stress and synergistically induces apoptosis in combination with imipridones in DMG cells and orthotopic tumor xenografts. Collectively, we identify GABA as a unique metabolic adaptation to imipridones that can be leveraged for non-invasive assessment of drug-target engagement and therapy. Clinical translation of our studies has the potential to enable precision metabolic therapy and imaging for DMG patients.

One Sentence Summary

Imipridones induce GABA accumulation in diffuse midline gliomas, an effect that can be leveraged for therapy and non-invasive imaging.

Systematic Review of Cerebrospinal Fluid Biomarker Discovery in Neuro-Oncology: A Roadmap to Standardization and Clinical Application

Effective diagnosis, prognostication, and management of CNS malignancies traditionally involves invasive brain biopsies that pose significant risk to the patient. Sampling and molecular profiling of cerebrospinal fluid (CSF) is a safer, rapid, and noninvasive alternative that offers a snapshot of the intracranial milieu while overcoming the challenge of sampling error that plagues conventional brain biopsy. Although numerous biomarkers have been identified, translational challenges remain, and standardization of protocols is necessary. Here, we systematically reviewed 141 studies (Medline, SCOPUS, and Biosis databases; between January 2000 and September 29, 2022) that molecularly profiled CSF from adults with brain malignancies including glioma, brain metastasis, and primary and secondary CNS lymphomas. We provide an overview of promising CSF biomarkers, propose CSF reporting guidelines, and discuss the various considerations that go into biomarker discovery, including the influence of blood-brain barrier disruption, cell of origin, and site of CSF acquisition (eg, lumbar and ventricular). We also performed a meta-analysis of proteomic data sets, identifying biomarkers in CNS malignancies and establishing a resource for the research community.

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.

Potential of in vitro nuclear magnetic resonance of biofluids and tissues in clinical research

Body fluids, cells, and tissues contain a wide variety of metabolites that consist of a mixture of various low-molecular-weight compounds, including amino acids, peptides, lipids, nucleic acids, and organic acids, which makes comprehensive analysis more difficult. Quantitative nuclear magnetic resonance (NMR) spectroscopy is a well-established analytical technique for analyzing the metabolic profiles of body fluids, cells, and tissues. It enables fast and comprehensive detection, characterization, a high level of experimental reproducibility, minimal sample preparation, and quantification of various endogenous metabolites. In recent times, NMR-based metabolomics has been appreciably utilized in diverse branches of medicine, including microbiology, toxicology, pathophysiology, pharmacology, nutritional intervention, and disease diagnosis/prognosis. In this review, the utility of NMR-based metabolomics in clinical studies is discussed. The significance of in vitro NMR-based metabolomics as an effective tool for detecting metabolites and their variations in different diseases are discussed, together with the possibility of identifying specific biomarkers that can contribute to early detection and diagnosis of disease.

Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response

Immunotherapy constitutes a paradigm shift in cancer treatment. Its FDA approval for several indications has yielded improved prognosis for cases where traditional therapy has shown limited efficiency. However, many patients still fail to benefit from this treatment modality, and the exact mechanisms responsible for tumor response are unknown. Noninvasive treatment monitoring is crucial for longitudinal tumor characterization and the early detection of non-responders. While various medical imaging techniques can provide a morphological picture of the lesion and its surrounding tissue, a molecular-oriented imaging approach holds the key to unraveling biological effects that occur much earlier in the immunotherapy timeline. Magnetic resonance imaging (MRI) is a highly versatile imaging modality, where the image contrast can be tailored to emphasize a particular biophysical property of interest using advanced engineering of the imaging pipeline. In this review, recent advances in molecular-MRI based cancer immunotherapy monitoring are described. Next, the presentation of the underlying physics, computational, and biological features are complemented by a critical analysis of the results obtained in preclinical and clinical studies. Finally, emerging artificial intelligence (AI)-based strategies to further distill, quantify, and interpret the image-based molecular MRI information are discussed in terms of perspectives for the future.

Advances in the intraoperative delineation of malignant glioma margin

Surgery plays a critical role in the treatment of malignant glioma. However, due to the infiltrative growth and brain shift, it is difficult for neurosurgeons to distinguish malignant glioma margins with the naked eye and with preoperative examinations. Therefore, several technologies were developed to determine precise tumor margins intraoperatively. Here, we introduced four intraoperative technologies to delineate malignant glioma margin, namely, magnetic resonance imaging, fluorescence-guided surgery, Raman histology, and mass spectrometry. By tracing their detecting principles and developments, we reviewed their advantages and disadvantages respectively and imagined future trends.

Imaging telomerase reverse transcriptase expression in oligodendrogliomas using hyperpolarized δ-[1-13C]-gluconolactone

Background

Telomere maintenance by telomerase reverse transcriptase (TERT) is essential for immortality in most cancers, including oligodendrogliomas. Agents that disrupt telomere maintenance such as the telomere uncapping agent 6-thio-2'-deoxyguanosine (6-thio-dG) are in clinical trials. We previously showed that TERT expression in oligodendrogliomas is associated with upregulation of glucose-6-phosphate dehydrogenase (G6PD), the rate-limiting enzyme of the pentose phosphate pathway (PPP). We also showed that hyperpolarized δ-[1-13C]-gluconolactone metabolism to 6-phosphogluconate (6-PG) can be used to probe the PPP in glioblastomas. The goal of this study was to determine whether hyperpolarized 13C imaging using δ-[1-13C]-gluconolactone can monitor TERT expression and response to 6-thio-dG in oligodendrogliomas.

Methods

We examined patient-derived oligodendroglioma cells and orthotopic tumors to assess the link between TERT and hyperpolarized δ-[1-13C]-gluconolactone metabolism. We performed in vivo imaging to assess the ability of hyperpolarized δ-[1-13C]-gluconolactone to report on TERT and response to 6-thio-dG in rats bearing orthotopic oligodendrogliomas in vivo.

Results

Doxycycline-inducible TERT silencing abrogated 6-PG production from hyperpolarized δ-[1-13C]-gluconolactone in oligodendroglioma cells, consistent with the loss of G6PD activity. Rescuing TERT expression by doxycycline removal restored G6PD activity and, concomitantly, 6-PG production. 6-PG production from hyperpolarized δ-[1-13C]-gluconolactone demarcated TERT-expressing tumor from surrounding TERT-negative normal brain in vivo. Importantly, 6-thio-dG abrogated 6-PG production at an early timepoint preceding MRI-detectable alterations in rats bearing orthotopic oligodendrogliomas in vivo.

Conclusions

These results indicate that hyperpolarized δ-[1-13C]-gluconolactone reports on TERT expression and early response to therapy in oligodendrogliomas. Our studies identify a novel agent for imaging tumor proliferation and treatment response in oligodendroglioma patients.

Radiomic study on preoperative multi-modal magnetic resonance images identifies IDH-mutant TERT promoter-mutant gliomas

OBJECTIVES

Gliomas with comutations of isocitrate dehydrogenase (IDH) genes and telomerase reverse transcriptase (TERT) gene promoter (IDHmut pTERTmut) show distinct biological features and respond to first-line treatment differently in comparison with other gliomas. This study aimed to characterize the IDHmut pTERTmut gliomas in multimodal MRI using the radiomic method and establish a precise diagnostic model identifying this group of gliomas.

METHODS

A total of 140 patients with untreated primary gliomas were admitted between 2016 and 2020 to West China Hospital as a discovery cohort, including 22 IDHmut pTERTmut patients. Thirty-four additional cases from a different hospital were included in the study as an independent validation cohort. A total of 3654 radiomic features were extracted from the preoperative multimodal MRI images (T1c, FLAIR, and ADC maps) and filtered in a data-driven approach. The discovery cohort was split into training and test sets by a 4:1 ratio. A diagnostic model (multilayer perceptron classifier) for detecting the IDHmut pTERTmut gliomas was trained using an automatic machine-learning algorithm named tree-based pipeline optimization tool (TPOT). The most critical radiomic features in the model were identified and visualized.

RESULTS

The model achieved an area under the receiver-operating curve (AUROC) of 0.971 (95% CI, 0.902-1.000), the sensitivity of 0.833 (95% CI, 0.333-1.000), and the specificity of 0.966 (95% CI, 0.931-1.000) in the test set. The area under the precision-recall curve (AUCPR) was 0.754 (95% CI, 0.572-0.833) and the F1 score was 0.833 (95% CI, 0.500-1.000). In the independent validation set, the model reached 0.952 AUROC, 0.714 sensitivity, 0.963 specificity, 0.841 AUCPR, and 0.769 F1 score. MR radiomic features of the IDHmut pTERTmut gliomas represented homogenous low-complexity texture in three modalities.

CONCLUSIONS

An accurate diagnostic model was constructed for detecting IDHmut pTERTmut gliomas using multimodal radiomic features. The most important features were associated with the homogenous simple texture of IDHmut pTERTmut gliomas in MRI images transformed using Laplacian of Gaussian and wavelet filters.

Deuterium Metabolic Imaging Reports on TERT Expression and Early Response to Therapy in Cancer

PURPOSE

Telomere maintenance is a hallmark of cancer. Most tumors maintain telomere length via reactivation of telomerase reverse transcriptase (TERT) expression. Identifying clinically translatable imaging biomarkers of TERT can enable noninvasive assessment of tumor proliferation and response to therapy.

EXPERIMENTAL DESIGN

We used RNAi, doxycycline-inducible expression systems, and pharmacologic inhibitors to mechanistically delineate the association between TERT and metabolism in preclinical patient-derived tumor models. Deuterium magnetic resonance spectroscopy (2H-MRS), which is a novel, translational metabolic imaging modality, was used for imaging TERT in cells and tumor-bearing mice in vivo.

RESULTS

Our results indicate that TERT expression is associated with elevated NADH in multiple cancers, including glioblastoma, oligodendroglioma, melanoma, neuroblastoma, and hepatocellular carcinoma. Mechanistically, TERT acts via the metabolic regulator FOXO1 to upregulate nicotinamide phosphoribosyl transferase, which is the key enzyme for NAD+ biosynthesis, and the glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase, which converts NAD+ to NADH. Because NADH is essential for pyruvate flux to lactate, we show that 2H-MRS-based assessment of lactate production from [U-2H]-pyruvate reports on TERT expression in preclinical tumor models in vivo, including at clinical field strength (3T). Importantly, [U-2H]-pyruvate reports on early response to therapy in mice bearing orthotopic patient-derived gliomas at early timepoints before radiographic alterations can be visualized by MRI.

CONCLUSIONS

Elevated NADH is a metabolic consequence of TERT expression in cancer. Importantly, [U-2H]-pyruvate reports on early response to therapy, prior to anatomic alterations, thereby providing clinicians with a novel tool for assessment of tumor burden and treatment response in cancer.

Liquid biopsies to occult brain metastasis

Brain metastasis (BrM) is a major problem associated with cancer-related mortality, and currently, no specific biomarkers are available in clinical settings for early detection. Liquid biopsy is widely accepted as a non-invasive method for diagnosing cancer and other diseases. We have reviewed the evidence that shows how the molecular alterations are involved in BrM, majorly from breast cancer (BC), lung cancer (LC), and melanoma, with an inception in how they can be employed for biomarker development. We discussed genetic and epigenetic changes that influence cancer cells to breach the blood-brain barrier (BBB) and help to establish metastatic lesions in the uniquely distinct brain microenvironment. Keeping abreast with the recent breakthroughs in the context of various biomolecules detections and identifications, the circulating tumor cells (CTC), cell-free nucleotides, non-coding RNAs, secretory proteins, and metabolites can be pursued in human body fluids such as blood, serum, cerebrospinal fluid (CSF), and urine to obtain potential candidates for biomarker development. The liquid biopsy-based biomarkers can overlay with current imaging techniques to amplify the signal viable for improving the early detection and treatments of occult BrM.

Noise-immune Extreme Ensemble Learning for Early Diagnosis of Neuropsychiatric Systemic Lupus Erythematosus

Early diagnosis is currently the most effective way of saving the life of patients with neuropsychiatric systemic lupus erythematosus (NPSLE). However, it is rather difficult to detect this terrible disease at the early stage, due to the subtle and elusive symptomatic signals. Recent studies show that the ¹H-MRS (proton magnetic resonance spectroscopy) imaging technique can capture more information reflecting the early appearance of this disease than conventional magnetic resonance imaging techniques. 1H-MRS data, however, also presents more noises that can bring serious diagnosis bias. We hence proposed a noise-immune extreme ensemble learning technique for effectively leveraging 1H-MRS data for advancing the early diagnosis of NPSLE. Our main results are that 1) by developing generalized maximum correntropy criterion in the kernel extreme learning setting, many types of non-Gaussian noises can be distinguished, and 2) weighted recursive feature elimination, using maximal information coefficient to weight feature's importance, helps to further alleviate the bad impact of noises on the diagnosis performance. The proposed method is assessed on a publicly available dataset with 97.5% accuracy, 95.8% sensitivity, and 99.9% specificity, which well demonstrates its efficacy.

Epigenetic MRI: Noninvasive imaging of DNA methylation in the brain

Dynamic epigenetic activity is a fundamental mechanism underpinning how the brain changes its function during development and aging and in response to environmental and disease stimuli. We developed a technology called epigenetic MRI (eMRI) that enables noninvasive imaging of DNA methylation in the brain, a major epigenetic mechanism. eMRI reveals strong regional differences in global DNA methylation in pig brains, a model with stronger resemblance to human brains than are rodents. Given the noninvasive nature of eMRI, our results pave the way for a DNA-methylation imaging paradigm for living human brains. We expect eMRI to enable many studies to unravel the molecular control of brain function and disease.

Both neuronal and genetic mechanisms regulate brain function. While there are excellent methods to study neuronal activity in vivo, there are no nondestructive methods to measure global gene expression in living brains. Here, we present a method, epigenetic MRI (eMRI), that overcomes this limitation via direct imaging of DNA methylation, a major gene-expression regulator. eMRI exploits the methionine metabolic pathways for DNA methylation to label genomic DNA through ¹³C-enriched diets. A ¹³C magnetic resonance spectroscopic imaging method then maps the spatial distribution of labeled DNA. We validated eMRI using pigs, whose brains have stronger similarity to humans in volume and anatomy than rodents, and confirmed efficient ¹³C-labeling of brain DNA. We also discovered strong regional differences in global DNA methylation. Just as functional MRI measurements of regional neuronal activity have had a transformational effect on neuroscience, we expect that the eMRI signal, both as a measure of regional epigenetic activity and as a possible surrogate for regional gene expression, will enable many new investigations of human brain function, behavior, and disease.

Deuterium magnetic resonance spectroscopy enables noninvasive metabolic imaging of tumor burden and response to therapy in low-grade gliomas

BACKGROUND

The alternative lengthening of telomeres (ALT) pathway is essential for tumor proliferation in astrocytomas. The goal of this study was to identify metabolic alterations linked to the ALT pathway that can be exploited for noninvasive magnetic resonance spectroscopy (MRS)-based imaging of astrocytomas in vivo.

METHODS

Genetic and pharmacological methods were used to dissect the association between the ALT pathway and glucose metabolism in genetically engineered and patient-derived astrocytoma models. 2H-MRS was used for noninvasive imaging of ALT-linked modulation of glycolytic flux in mice bearing orthotopic astrocytomas in vivo.

RESULTS

The ALT pathway was associated with higher activity of the rate-limiting glycolytic enzyme phosphofructokinase-1 and concomitantly elevated flux of glucose to lactate in astrocytoma cells. Silencing the ALT pathway or treating with the poly(ADP-ribose) polymerase inhibitor niraparib that induces telomeric fusion in ALT-dependent astrocytoma cells abrogated glycolytic flux. Importantly, this metabolic reprogramming could be non-invasively visualized by 2H-MRS. Lactate production from [6,6'-2H]-glucose was higher in ALT-dependent astrocytoma tumors relative to the normal brain in vivo. Furthermore, treatment of orthotopic astrocytoma-bearing mice with niraparib reduced lactate production from [6,6'-2H]-glucose at early timepoints when alterations in tumor volume could not be detected by anatomical imaging, pointing to the ability of [6,6'-2H]-glucose to report on pseudoprogression in vivo.

CONCLUSIONS

We have mechanistically linked the ALT pathway to elevated glycolytic flux and demonstrated the ability of [6,6'-2H]-glucose to non-invasively assess tumor burden and response to therapy in astrocytomas. Our findings point to a novel, clinically translatable method for metabolic imaging of astrocytoma patients.

Quantitative Assessment of Occipital Metabolic and Energetic Changes in Parkinson's Patients, Using In Vivo 31P MRS-Based Metabolic Imaging at 7T

Abnormal energy metabolism associated with mitochondrial dysfunction is thought to be a major contributor to the progression of neurodegenerative diseases such as Parkinson's disease (PD). Recent advancements in the field of magnetic resonance (MR) based metabolic imaging provide state-of-the-art technologies for non-invasively probing cerebral energy metabolism under various brain conditions. In this proof-of-principle clinical study, we employed quantitative ³¹P MR spectroscopy (MRS) imaging techniques to determine a constellation of metabolic and bioenergetic parameters, including cerebral adenosine triphosphate (ATP) and other phosphorous metabolite concentrations, intracellular pH and nicotinamide adenine dinucleotide (NAD) redox ratio, and ATP production rates in the occipital lobe of cognitive-normal PD patients, and then we compared them with age-sex matched healthy controls. Small but statistically significant differences in intracellular pH, NAD and ATP contents and ATPase enzyme activity between the two groups were detected, suggesting that subtle defects in energy metabolism and mitochondrial function are quantifiable before regional neurological deficits or pathogenesis begin to occur in these patients. Pilot data aiming to evaluate the bioenergetic effect of mitochondrial-protective bile acid, ursodeoxycholic acid (UDCA) were also obtained. These results collectively demonstrated that in vivo ³¹P MRS-based neuroimaging can non-invasively and quantitatively assess key metabolic-energetic metrics in the human brain. This provides an exciting opportunity to better understand neurodegenerative diseases, their progression and response to treatment.