Metabolic Imaging Biomarkers Research Articles

1H and 31P Magnetic Resonance Spectroscopic Metabolomic Imaging: Assessing Mitogen-Activated Protein Kinase Inhibition in Melanoma.

The MAPK signaling pathway with BRAF mutations has been shown to drive the pathogenesis of 40-60% of melanomas. Inhibitors of this pathway's BRAF and MEK components are currently used to treat these malignancies. However, responses to these treatments are not always successful. Therefore, identifying noninvasive biomarkers to predict treatment responses is essential for personalized medicine in melanoma. Using noninvasive 1H magnetic resonance spectroscopy (1H MRS), we previously showed that BRAF inhibition reduces lactate and alanine tumor levels in the early stages of effective therapy and could be considered as metabolic imaging biomarkers for drug response. The present work demonstrates that these metabolic changes observed by 1H MRS and those assessed by 31P MRS are also found in preclinical human melanoma models treated with MEK inhibitors. Apart from 1H and 31P MRS, additional supporting in vitro biochemical analyses are described. Our results indicate significant early metabolic correlations with response levels to MEK inhibition in the melanoma models and are consistent with our previous study of BRAF inhibition. Given these results, our study supports the potential clinical utility of noninvasive MRS to objectively image metabolic biomarkers for the early prediction of melanoma's response to MEK inhibition.

Correlating survival outcomes in patients with advanced prostate cancer with novel hyperpolarized 13C MRI metabolic imaging biomarkers.

e15059 Background: Hyperpolarized 13C (HP 13C) MRI is a novel molecular imaging approach that detects aberrant aerobic metabolism, namely elevated rates of pyruvate-to-lactate conversion (kPL), in patients with advanced malignancies. Higher kPL has been shown to correlate with higher tumor grade among patients with localized prostate cancer (PC). This research sought to evaluate the correlation between kPL and clinical outcome measures in patients with advanced PC. Methods: Patients with metastatic or locally advanced PC (castration sensitive or resistant) were prospectively enrolled at our institution and underwent HP 13C MRI of one or more target lesions identified on prior conventional imaging. Voxelwise kPL values were computed in MATLAB using an inputless two site exchange model. kPL,median was defined as the median kPL value per-patient across all target lesions; kPL,kurtosis measured the tailedness of the kPL distribution per-patient. We retrospectively analyzed progression free survival (PFS) and overall survival (OS) in subgroups divided by metabolic activity below versus above cut-point (kPL,median <0.017 s-1 and ≥ 0.017s-1, respectively). Survival statistics were calculated using the Cox PH model. Results: Sixteen patients (6 with castration-sensitive and 10 with castration-resistant PC) were accrued. With a median follow-up of 22.0 months from the date of MRI, the lower-kPL subgroup had significantly longer median PFS (11.2 vs 0.5 months; p<0.01) and OS (NR vs 18.4 months; p<0.05) compared to the higher-kPL subgroup. By comparison, baseline serum PSA (PFS: p=0.19, OS: p=0.41) and LDH (PFS: p=0.60, OS: p=0.34) did not demonstrate a significant association with clinical outcomes. There was a strong negative correlation between kPL,kurtosis and OS (r = -0.75), and moderate negative correlations between kPL,median and OS (r = -0.45) as well as kPL,max with both PFS (r = -0.48) and OS (r = -0.54). There was no significant kPL,median difference between castration-sensitive and resistant subgroups (0.015±0.011 vs 0.016±0.006 s-1, p>0.8). Conclusions: HP 13C MRI-derived non-invasive metabolic biomarker kPL,median significantly correlated with clinical outcome measures in a retrospective analysis of patients with advanced PC, outperforming established serological prognostic markers PSA and LDH. Limitations include our small sample size, retrospective design, and heterogeneous patient population. Nevertheless, these encouraging preliminary results support further investigation of HP 13C MRI as a prognostic and/or predictive PC biomarker in multi-center prospective imaging trials. [Table: see text]

Metabolic Imaging Biomarkers of Response to Signaling Inhibition Therapy in Melanoma.

Dabrafenib therapy for metastatic melanoma focuses on blocking growth-promoting signals produced by a hyperactive BRAF protein. We report the metabolic differences of four human melanoma cell lines with diverse responses to dabrafenib therapy (30 mg/kg; oral): WM3918 < WM9838BR < WM983B < DB-1. Our goal was to determine if metabolic changes produced by the altered signaling pathway due to BRAF mutations differ in the melanoma models and whether these differences correlate with response to treatment. We assessed metabolic changes in isolated cells using high-resolution proton magnetic resonance spectroscopy (1H MRS) and supplementary biochemical assays. We also noninvasively studied mouse xenografts using proton and phosphorus (1H/31P) MRS. We found consistent changes in lactate and alanine, either in isolated cells or mouse xenografts, correlating with their relative dabrafenib responsiveness. In xenografts, we also observed that a more significant response to dabrafenib correlated with higher bioenergetics (i.e., increased βNTP/Pi). Notably, our noninvasive assessment of the metabolic status of the human melanoma xenografts by 1H/31P MRS demonstrated early metabolite changes preceding therapy response (i.e., tumor shrinkage). Therefore, this noninvasive methodology could be translated to assess in vivo predictive metabolic biomarkers of response in melanoma patients under dabrafenib and probably other signaling inhibition therapies.

NIMG-34. QUANTIFICATION OF GLYCOLYTIC FLUX REDUCTION IN RECURRENT GLIOBLASTOMA AFTER EGFR INHIBITION USING MOLECULAR MR-PET

Abstract In recently published work, we demonstrated that acute inhibition of the EGFR – the most frequently altered oncogene in GBM – can rapidly reduce glycolysis in a subset of GBM. To quantify this effect, we propose a new combination metabolic MR-PET imaging biomarker that combines 18F-FDG PET, DSC perfusion MRI, diffusion MRI, and pH- and oxygen-sensitive amine CEST-SAGE-EPI. Specifically, this “glycolytic index” or GI, can be defined as elevated glucose uptake (18F-FDG standard uptake value), elevated tumor acidity (MTRasym@3ppm), and lower oxygen utilization (relative cerebral metabolic rate of oxygen, rCMRO2, defined as R2’ x rCBF/rCBV from oxygen-sensitive SAGE-EPI and DSC perfusion), normalized to cell density (using ADC from diffusion MRI). In the current study, we explored the use of Tagrisso® (Osimertinib or AZD9291), which has very high brain to plasma ratios (&amp;gt; 1) and has proven effective in CNS metastasis of EGFR mutant lung cancer, as a potential treatment for EGFR amplified recurrent GBM. We have conducted a clinical trial (NCT03732352) to determine whether we observe similar metabolic imaging changes in EGFR mutated or amplified recurrent glioblastoma patients after treatment with osimertinib. Consistent with prior in vitro and in vivo results, treated patients exhibited a reduced glycolytic flux as indicated by reduction in 18F-FDG PET uptake (-3% change in SUV), tumor acidity (-19% change in MTRasym@3ppm) on pH-weighted CEST MRI, and glycolytic index (GI) (-25% change) in EGFR amplified recurrent GBM within 24 hours of treatment. Preliminary data suggests early change in GI correlates with and predicts both PFS (Pearson correlation, R2=0.3463, P=0.0441; Log-rank, P=0.0467) and OS (R2=0.6368, P=0.0019; Log-rank, P=0.0192). These preliminary data establish the scientific premise that a “glycolytic index” created using 18F-FDG PET, DSC perfusion, diffusion MRI, and pH- and oxygen-weighted amine CEST-SAGE-EPI may be an important tool for quantifying and visualizing glycolytic flux in GBM.

The effect of transmit B1 inhomogeneity on hyperpolarized [1-13 C]-pyruvate metabolic MR imaging biomarkers.

A specialized Helmholtz-style 13 C volume transmit "clamshell" coil is currently being utilized for 13 C excitation in pre-clinical and clinical hyperpolarized 13 C MRI studies aimed at probing the metabolic activity of tumors in various target anatomy. Due to the widespread use of this 13 C clamshell coil design, it is important that the effects of the 13 C clamshell coil B1 + profile on HP signal evolution and quantification are well understood. The goal of this study was to characterize the B1 + field of the 13 C clamshell coil and assess the impact of inhomogeneities on semi-quantitative and quantitative hyperpolarized MR imaging biomarkers of metabolism. The B1 + field of the 13 C clamshell coil was mapped by hand using a network analyzer equipped with an S-parameter test set. Pharmacokinetic models were used to simulate signal evolution as a function of position-dependent local excitation angles, for various nominal excitation angles, which were assumed to be accurately calibrated at the isocenter. These signals were then quantified according to the normalized lactate ratio (nLac) and the apparent rate constant for the conversion of pyruvate to lactate (kPL ). The percent difference between these metabolic imaging biomarker maps and the reference value observed at the isocenter of the clamshell coil was calculated to estimate the potential for error due to position within the clamshell coil. Finally, regions were identified within the clamshell coil where deviations in B1 + field inhomogeneity or imaging biomarker errors imparted by the B1 + field were within ±10% of the value at the isocenter. The B1 + field maps show that a limited volume encompassed by a region measuring approximately 12.9×11.5×13.4cm (X-direction, Y-direction, Z-direction) centered in the 13 C clamshell coil will produce deviations in the B1 + field within ±10% of that at the isocenter. For the metabolic imaging biomarkers that we evaluated, the case when the pyruvate excitation angle (θP ) and lactate excitation angle (θL ) were equal to 10° produced the largest volumetric region with deviations within ±10% of the value at the isocenter. Higher excitation angles yielded higher signal and SNR, but the size of the region in which uniform measurements could be collected near the isocenter of the coil was reduced at higher excitation angles. The tradeoff between the size of the homogenous region at the isocenter and signal intensity must be weighed carefully depending on the particular imaging application. This work identifies regions and optimal excitation angles (θP and θL ) within the 13 C clamshell coil where deviations in B1 + field inhomogeneity or imaging biomarker errors imparted by the B1 + field were within ±10% of the respective value at the isocenter, and thus where excitation angles are reproducible and well-calibrated. Semi-quantitative and quantitative metabolic imaging biomarkers can vary with position in the clamshell coil as a result of B1 + field inhomogeneity, necessitating care in patient positioning and the selection of an excitation angle set that balances reproducibility and SNR performance over the target imaging volume.

18FDG positron emission tomography mining for metabolic imaging biomarkers of radiation-induced xerostomia in patients with oropharyngeal cancer

PurposeHead and neck cancers radiotherapy (RT) is associated with inevitable injury to parotid glands and subsequent xerostomia. We investigated the utility of SUV derived from 18FDG-PET to develop metabolic imaging biomarkers (MIBs) of RT-related parotid injury. MethodsData for oropharyngeal cancer (OPC) patients treated with RT at our institution between 2005 and 2015 with available planning computed tomography (CT), dose grid, pre- & first post-RT 18FDG-PET-CT scans, and physician-reported xerostomia assessment at 3–6 months post-RT (Xero 3–6 ms) per CTCAE, was retrieved, following an IRB approval. A CT-CT deformable image co-registration followed by voxel-by-voxel resampling of pre & post-RT 18FDG activity and dose grid were performed. Ipsilateral (Ipsi) and contralateral (contra) parotid glands were sub-segmented based on the received dose in 5 Gy increments, i.e. 0–5 Gy, 5–10 Gy sub-volumes, etc. Median and dose-weighted SUV were extracted from whole parotid volumes and sub-volumes on pre- & post-RT PET scans, using in-house code that runs on MATLAB. Wilcoxon signed-rank and Kruskal-Wallis tests were used to test differences pre- and post-RT. Results432 parotid glands, belonging to 108 OPC patients treated with RT, were sub-segmented & analyzed. Xero 3–6 ms was reported as: non-severe (78.7%) and severe (21.3%). SUV- median values were significantly reduced post-RT, irrespective of laterality (p = 0.02). A similar pattern was observed in parotid sub-volumes, especially ipsi parotid gland sub-volumes receiving doses 10–50 Gy (p < 0.05). Kruskal-Wallis test showed a significantly higher mean RT dose in the contra parotid in the patients with more severe Xero 3-6mo (p = 0.03). Multiple logistic regression showed a combined clinical-dosimetric-metabolic imaging model could predict the severity of Xero 3-6mo; AUC = 0.78 (95%CI: 0.66–0.85; p < 0.0001). ConclusionWe sought to quantify pre- and post-RT 18FDG-PET metrics of parotid glands in patients with OPC. Temporal dynamics of PET-derived metrics can potentially serve as MIBs of RT-related xerostomia in concert with clinical and dosimetric variables.

Evolutionary dynamics at the tumor edge reveal metabolic imaging biomarkers

Human cancers are biologically and morphologically heterogeneous. A variety of clonal populations emerge within these neoplasms and their interaction leads to complex spatiotemporal dynamics during tumor growth. We studied the reshaping of metabolic activity in human cancers by means of continuous and discrete mathematical models and matched the results to positron emission tomography (PET) imaging data. Our models revealed that the location of increasingly active proliferative cellular spots progressively drifted from the center of the tumor to the periphery, as a result of the competition between gradually more aggressive phenotypes. This computational finding led to the development of a metric, normalized distance from 18F-fluorodeoxyglucose (18F-FDG) hotspot to centroid (NHOC), based on the separation from the location of the activity (proliferation) hotspot to the tumor centroid. The NHOC metric can be computed for patients using 18F-FDG PET-computed tomography (PET/CT) images where the voxel of maximum uptake (standardized uptake value [SUV]max) is taken as the activity hotspot. Two datasets of 18F-FDG PET/CT images were collected, one from 61 breast cancer patients and another from 161 non-small-cell lung cancer patients. In both cohorts, survival analyses were carried out for the NHOC and for other classical PET/CT-based biomarkers, finding that the former had a high prognostic value, outperforming the latter. In summary, our work offers additional insights into the evolutionary mechanisms behind tumor progression, provides a different PET/CT-based biomarker, and reveals that an activity hotspot closer to the tumor periphery is associated to a worst patient outcome.

Identification and validation of Alzheimer’s disease‐related metabolic pattern in patients with pathologically confirmed Alzheimer’s disease

AbstractBackgroundAlzheimer’s disease (AD) is marked by accumulation of Aβ and tau protein causing neurodegeneration in the brain. AD represents a pathological and clinical continuum, ranging from mild cognitive impairment (MCI) to dementia. A specific metabolic imaging biomarker of AD ‐ Alzheimer’s disease‐related pattern (ADRP) has been previously identified from 2‐[18F]fluorodeoxyglucose positron emission tomography (2‐[18F]FDG‐PET) scans of clinically diagnosed AD patients, using scaled subprofile model based on principal component analysis (SSM/PCA) 1–3. However the clinical diagnosis may be wrong in substantial number of cases 4. We aimed to identify ADRP on patients with Alzheimer’s pathological changes in cerebrospinal (CSF) fluid and to validate it in an independent group of AD and other dementia patients and compare it to the original ADRP 1.Method2‐[18F]FDG‐PET scans from 20 AD1 and 20 normal controls (NC1) were used for pattern identification. Additional 110 scans were analyzed for validation: 68 from AD patients (37 AD2, 13 atypical clinical presentation AD (atAD), 18 MCI), 21 with frontotemporal dementia (FTD), 8 non‐AD MCI and 13 NC2 (Table 1). AD was defined with CSF biomarkers as: Aβ42 &lt; 815 pg/ml, pTau &gt; 60 pg/ml, tTau &gt; 400 pg/ml. Topographic profile rating algorithm was used to prospectively calculate ADRP Z‐scores from subjects scans3. Mini‐mental state examination (MMSE) was performed in all patients.ResultsADRP was identified and voxel weights were found to be stable by bootstrap resampling, Figure 1. Pattern’s expression was significantly higher in AD1 than NC1 (p&lt;0.001) and it strongly correlated (r=‐0.70) with MMSE. Pattern’s expression was also higher in AD2 than NC2 (p&lt;0.001), MCI vs. NC2 (p&lt;0.001), MCI vs. non‐AD MCI (p=0.02) and AD2 vs. FTD (p=0.02), Figure 2. Newly identified pattern moderately correlated (r=0.52) with the original one 1.ConclusionsWe identified ADRP on a cohort of pathologically confirmed AD patients, which was not done before. ADRP has shown to be a reliable metabolic biomarker of AD related neurodegeneration.

Differential Diagnosis of Parkinsonism with Deep Metabolic Imaging Biomarker – An Artificial Intelligence-Aided Multi-Cohort FDG PET Study

Background: The clinical presentation of early idiopathic Parkinson’s disease (IPD) substantially overlaps with that of atypical parkinsonian syndromes such as multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) has proven useful in assisting in the differential diagnosis of these parkinsonian syndromes. The aim of this study was to develop a metabolic imaging biomarker based on deep learning to support the differential diagnosis of parkinsonism. Methods: In addition to 863 non-parkinsonian subjects, a total of 1275 parkinsonian patients were accessed who underwent FDG PET imaging, clinical evaluation, and follow-up, yielding clinically possible, definite, or confirmative diagnoses of IPD, MSA, and PSP. A 3D deep convolutional neural network was developed to extract a deep metabolic imaging (DMI) biomarker. The accuracy of the DMI biomarker was evaluated with a cross-validation and a blind test. The robustness of the DMI biomarker was assessed on patients with longitudinal follow-up. The functional basis of DMI biomarker was further investigated based on the saliency map of the obtained deep neural network. Findings: The proposed DMI biomarker achieved an area under the receiver operating characteristic curve of 0·986 for the differential diagnosis of IPD, 0·997 for MSA, and 0·982 for PSP in the cross-validation. In the blind test, the DMI biomarker resulted in sensitivities of 98·1%, 88·5%, and 84·5%, as well as specificities of 90·0%, 99·2%, and 97·8% for IPD, MSA, and PSP respectively. The integration of demographic information and clinical assessments to DMI biomarker resulted in slight improvements. Saliencies for the DMI biomarker were found in several parkinsonism-related regions such as midbrain, putamen, and cerebellum. Interpretation: The DMI biomarker based on deep learning shows potential to provide accurate differential diagnosis for parkinsonism on FDG PET. The functional regions behind the DMI biomarker are consistent with known parkinsonian pathology. Funding Statement: The work was supported by grants from the National Natural Science Foundation of China (No. 81771483, 81671239, 81361120393, 81401135, 81971641, 81902282, 91949118, 81771372), from the Ministry of Science and Technology of China (2016YFC1306504), Shanghai Municipal Science and Technology Major Project (No. 2017SHZDZX01, 2018SHZDZX03) and ZJ Lab, Shanghai Sailing Program (No. 18YF1403100). It was also supported by Swiss National Science Foundation (No. 188350) and Siemens Healthineers. Declaration of Interests: W.H.O is Hertie Senior Research Professor, supported by the Charitable Hertie Foundation, Frankfurt/Main, Germany. A.R. and K.S. received research support from Siemens Healthineer. Other authors report no financial interests or potential conflicts of interest regarding the subject matter of the manuscript. Ethics Approval Statement: All procedures performed in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. All the data were from Parkinson's Disease Database and Samples Bank in Huashan Hospital. Ethics permission was obtained from the Institutional Review Board of Huashan Hospital and written consent was obtained from each subject after detailed explanation of the procedures.

Early Detection of Pancreatic Intraepithelial Neoplasias (PanINs) in Transgenic Mouse Model by Hyperpolarized 13C Metabolic Magnetic Resonance Spectroscopy.

While pancreatic cancer (PC) survival rates have recently shown modest improvement, the disease remains largely incurable. Early detection of pancreatic cancer may result in improved outcomes and therefore, methods for early detection of cancer, even premalignant lesions, may provide more favorable outcomes. Pancreatic intraepithelial neoplasias (PanINs) have been identified as premalignant precursor lesions to pancreatic cancer. However, conventional imaging methods used for screening high-risk populations do not have the sensitivity to detect PanINs. Here, we have employed hyperpolarized metabolic imaging in vivo and nuclear magnetic resonance (1H-NMR) metabolomics ex vivo to identify and understand metabolic changes, towards enabling detection of early PanINs and progression to advanced PanINs lesions that precede pancreatic cancer formation. Progression of disease from tissue containing predominantly low-grade PanINs to tissue with high-grade PanINs showed a decreasing alanine/lactate ratio from high-resolution NMR metabolomics ex vivo. Hyperpolarized magnetic resonance spectroscopy (HP-MRS) allows over 10,000-fold sensitivity enhancement relative to conventional magnetic resonance. Real-time HP-MRS was employed to measure non-invasively changes of alanine and lactate metabolites with disease progression and in control mice in vivo, following injection of hyperpolarized [1-13C] pyruvate. The alanine-to-lactate signal intensity ratio was found to decrease as the disease progressed from low-grade PanINs to high-grade PanINs. The biochemical changes of alanine transaminase (ALT) and lactate dehydrogenase (LDH) enzyme activity were assessed. These results demonstrate that there are significant alterations of ALT and LDH activities during the transformation from early to advanced PanINs lesions. Furthermore, we demonstrate that real-time conversion kinetic rate constants (kPA and kPL) can be used as metabolic imaging biomarkers of pancreatic premalignant lesions. Findings from this emerging HP-MRS technique can be translated to the clinic for detection of pancreatic premalignant lesion in high-risk populations.

Investigating the origin of pH-sensitive magnetization transfer ratio asymmetry MRI contrast during the acute stroke: Correction of T1 change reveals the dominant amide proton transfer MRI signal.

Amide proton transfer (APT) MRI is promising to serve as a surrogate metabolic imaging biomarker of acute stroke. Although the magnetization transfer ratio asymmetry (MTRasym ) has been used commonly, the origin of pH-weighted MRI effect remains an area of investigation, including contributions from APT, semisolid MT contrast asymmetry, and nuclear Overhauser enhancement effects. Our study aimed to determine the origin of pH-weighted MTRasym contrast following acute stroke. Multiparametric MRI, including T1 , T2 , diffusion and Z-spectrum, were performed in rats after middle cerebral artery occlusion. We analyzed the conventional Z-spectrum and the apparent exchange spectrum , being the difference between the relaxation-scaled inverse Z-spectrum and the intrinsic spinlock relaxation rate . The ischemia-induced change was calculated as the spectral difference between the diffusion lesion and the contralateral normal area. The conventional Z-spectrum signal change at -3.5 ppm dominates that at +3.5 ppm (-1.16 ± 0.39% vs. 0.76 ± 0.26%, P < .01) following acute stroke. In comparison, the magnitude of ΔRex change at 3.5 ppm becomes significantly larger than that at -3.5 ppm (-2.80 ± 0.40% vs. -0.94 ± 0.80%, P < .001), with their SNR being 7.0 and 1.2, respectively. We extended the magnetization transfer and relaxation normalized APT concept to the apparent exchange-dependent relaxation image, documenting an enhanced pH contrast between the ischemic lesion and the intact tissue, over that of MTRasym . Our study shows that after the relaxation-effect correction, the APT effect is the dominant contributing factor to pH-weighted MTRasym following acute stroke.

Demonstration of magnetization transfer and relaxation normalized pH-specific pulse-amide proton transfer imaging in an animal model of acute stroke.

pH-weighted amide proton transfer (APT) MRI is promising to serve as a new surrogate metabolic imaging biomarker for refined ischemic tissue demarcation. APT MRI with pulse-RF irradiation (pulse-APT) is an alternative to the routine continuous wave (CW-) APT MRI that overcomes the RF duty cycle limit. Our study aimed to generalize the recently developed pH-specific magnetization transfer and relaxation-normalized APT (MRAPT) analysis to pulse-APT MRI in acute stroke imaging. Multiparametric MRI, including CW- and pulse-APT MRI scans, were performed following middle cerebral artery occlusion in rats. We calculated pH-sensitive MTRasym and pH-specific MRAPT contrast between the ipsilateral diffusion lesion and contralateral normal area. An inversion pulse of 10 to 15 ms maximizes the pH-sensitive MRI contrast for pulse-APT MRI. The contrast-to-noise ratio of pH-specific MRAPT effect between the contralateral normal area and ischemic lesion from both methods are comparable (3.25 ± 0.65 vs. 3.59 ± 0.40, P > .05). pH determined from both methods were in good agreement, with their difference within 0.1. Pulse-APT MRI provides highly pH-specific mapping for acute stroke imaging.

Glycine by MR spectroscopy is an imaging biomarker of glioma aggressiveness.

High-grade gliomas likely remodel the metabolic machinery to meet the increased demands for amino acids and nucleotides during rapid cell proliferation. Glycine, a non-essential amino acid and intermediate of nucleotide biosynthesis, may increase with proliferation. Non-invasive measurement of glycine by magnetic resonance spectroscopy (MRS) was evaluated as an imaging biomarker for assessment of tumor aggressiveness. We measured glycine, 2-hydroxyglutarate (2HG), and other tumor-related metabolites in 35 glioma patients using an MRS sequence tailored for co-detection of glycine and 2HG in gadolinium-enhancing and non-enhancing tumor regions on 3T MRI. Glycine and 2HG concentrations as measured by MRS were correlated with tumor cell proliferation (MIB-1 labeling index), expression of mitochondrial serine hydroxymethyltransferase (SHMT2), and glycine decarboxylase (GLDC) enzymes, and patient overall survival. Elevated glycine was strongly associated with presence of gadolinium enhancement, indicating more rapidly proliferative disease. Glycine concentration was positively correlated with MIB-1, and levels higher than 2.5 mM showed significant association with shorter patient survival, irrespective of isocitrate dehydrogenase status. Concentration of 2HG did not correlate with MIB-1 index. A high glycine/2HG concentration ratio, >2.5, was strongly associated with shorter survival (P < 0.0001). GLDC and SHMT2 expression were detectable in all tumors with glycine concentration, demonstrating an inverse correlation with GLDC. The data suggest that aggressive gliomas reprogram glycine-mediated one-carbon metabolism to meet the biosynthetic demands for rapid cell proliferation. MRS evaluation of glycine provides a non-invasive metabolic imaging biomarker that is predictive of tumor progression and clinical outcome. 1. Glycine and 2-hydroxyglutarate in glioma patients are precisely co-detected using MRS at 3T.2. Tumors with elevated glycine proliferate and progress rapidly.3. A high glycine/2HG ratio is predictive of shortened patient survival.

MR-detectable metabolic biomarkers of response to mutant IDH inhibition in low-grade glioma.

Mutations in isocitrate dehydrogenase 1 (IDH1mut) are reported in 70-90% of low-grade gliomas and secondary glioblastomas. IDH1mut catalyzes the reduction of α-ketoglutarate (α-KG) to 2-hydroxyglutarate (2-HG), an oncometabolite which drives tumorigenesis. Inhibition of IDH1mut is therefore an emerging therapeutic approach, and inhibitors such as AG-120 and AG-881 have shown promising results in phase 1 and 2 clinical studies. However, detection of response to these therapies prior to changes in tumor growth can be challenging. The goal of this study was to identify non-invasive clinically translatable metabolic imaging biomarkers of IDH1mut inhibition that can serve to assess response.Methods: IDH1mut inhibition was confirmed using an enzyme assay and 1H- and 13C- magnetic resonance spectroscopy (MRS) were used to investigate the metabolic effects of AG-120 and AG-881 on two genetically engineered IDH1mut-expressing cell lines, NHAIDH1mut and U87IDH1mut.Results: 1H-MRS indicated a significant decrease in steady-state 2-HG following treatment, as expected. This was accompanied by a significant 1H-MRS-detectable increase in glutamate. However, other metabolites previously linked to 2-HG were not altered. 13C-MRS also showed that the steady-state changes in glutamate were associated with a modulation in the flux of glutamine to both glutamate and 2-HG. Finally, hyperpolarized 13C-MRS was used to show that the flux of α-KG to both glutamate and 2-HG was modulated by treatment.Conclusion: In this study, we identified potential 1H- and 13C-MRS-detectable biomarkers of response to IDH1mut inhibition in gliomas. Although further studies are needed to evaluate the utility of these biomarkers in vivo, we expect that in addition to a 1H-MRS-detectable drop in 2-HG, a 1H-MRS-detectable increase in glutamate, as well as a hyperpolarized 13C-MRS-detectable change in [1-13C] α-KG flux, could serve as metabolic imaging biomarkers of response to treatment.

EXTH-20. HYPERPOLARIZED [2-13C] PYRUVATE TO [5-13C] GLUTAMATE AS BIOMARKERS OF IDH1 MUTANT GLIOMA RESPONSE TO TEMOZOLOMIDE THERAPY

Abstract Low-grade gliomas, driven by mutations in the cytosolic isocitrate dehydrogenase 1 (IDH1) gene, are less aggressive than primary glioblastoma, but nonetheless always recur and ultimately lead to patient death. The treatment of IDH1 mutant patients with Temozolomide (TMZ) improves survival, but there remains a need for complementary imaging methods to assess response to therapy at an early time point. The goal of this study was, therefore, to determine the value of magnetic resonance spectroscopy (MRS)-based metabolic imaging biomarkers for detection of response to treatment. To this end we investigated NHA and U87 cells expressing IDH1 R132H mutant gene (NHAIDHmut and U87IDHmut) and first used 1H MRS combined with chemometrics to examined the metabolic alterations that occurred following treatment with the IC50 value of TMZ. We observed a significant increase in 2-hydroxyglutarate (2-HG), glutamate, and glutamine, and metabolic pathway analysis showed tricarboxylic acid (TCA) cycle and pyruvate metabolism to be significantly altered pathways following TMZ treatment compared to DMSO control. To confirm changes in TCA cycle flux and to assess the metabolic pathways contributing to the increase in 2-HG and glutamate/glutamine, cells were then labelled with [1-13C] glucose and [3-13C] glutamine. Our data indicated that both glucose flux via the TCA to glutamate and 2HG, and the contribution of glutamine to glutamate and 2HG were increased following TMZ treatment. Finally, we used hyperpolarized 13C-MRS to dynamically probe the metabolism of hyperpolarized [2-13C] pyruvate and its conversion to hyperpolarized [5-13C] glutamate via the TCA cycle. Consistent with our previous findings, we observed that hyperpolarized [5-13C] glutamate synthesis was significantly higher in TMZ-treated cells compared to controls. Collectively, our findings identify 1H MRS-detectable elevation of 2-HG and glutamate/glutamine as well as hyperpolarized 13C-MRS-detectable [5-13C] glutamate production from [2-13C] pyruvate as potentially translatable metabolic biomarkers of response to TMZ therapy in mutant IDH1 glioma.

CBMT-41. IMAGING A HALLMARK OF CANCER: HYPERPOLARIZED 13C-MAGNETIC RESONANCE SPECTROSCOPY CAN NON-INVASIVELY MONITOR TERT EXPRESSION IN LOW-GRADE GLIOMAS IN VIVO

Abstract Telomerase reverse transcriptase (TERT) expression is a hallmark of cancer, including in primary glioblastomas and low-grade oligodendrogliomas. Since TERT is essential for glioma proliferation and is an attractive therapeutic target, metabolic imaging of TERT status can inform on tumor progression and response to therapy. To that end, the goal of this study was to identify non-invasive, translational, hyperpolarized 13C-magnetic resonance spectroscopy-detectable metabolic imaging biomarkers of TERT in low-grade oligodendrogliomas. Unbiased metabolomic analysis of immortalized normal human astrocytes without (NHAcontrol) and with TERT (NHAtert) indicated that TERT induced unique metabolic reprogramming. Notably, TERT increased NADPH and NADH levels. Glucose flux through the pentose phosphate pathway (PPP) is a major producer of NADPH. Non-invasive imaging of PPP flux using hyperpolarized [U-13C,U-2H]-glucose indicated that production of the PPP metabolite 6-phosphogluconate (6-PG) was elevated in NHAtert cells relative to NHAcontrol. Importantly, hyperpolarized [U-13C,U-2H]-glucose flux to 6-PG clearly differentiated tumor from normal brain in orthotopic NHAtert tumor xenografts. Next, we exploited the observation that TERT expression increased NADH, which is essential for the metabolism of hyperpolarized [1-13C]-alanine to lactate. Lactate production from hyperpolarized [1-13C]-alanine was higher in NHAtert cells relative to NHAcontrol. Importantly, hyperpolarized [1-13C]-alanine imaging in orthotopic NHAtert tumors revealed pronounced differences in lactate production between tumor tissue and normal brain. Mechanistically, TERT increased expression of glucose-6-phosphate dehydrogenase (G6PDH), the rate-limiting enzyme for 6-PG and NADPH production, and of nicotinamide phosphoribosyltransferase (NAMPT), a rate-limiting enzyme for NADH biosynthesis. Silencing TERT reversed G6PDH and NAMPT expression and normalized hyperpolarized [U-13C,U-2H]-glucose and [1-13C]-alanine metabolism, validating our imaging biomarkers. Finally, hyperpolarized [U-13C,U-2H]-glucose and [1-13C]-alanine could monitor TERT status in the clinically relevant, patient-derived BT54 oligodendroglioma model. In summary, we demonstrate, for the first time, non-invasive in vivo imaging of TERT status in gliomas that can enable longitudinal analysis of tumor burden and treatment response in the clinic.

Imaging endogenous macrophage iron deposits reveals a metabolic biomarker of polarized tumor macrophage infiltration and response to CSF1R breast cancer immunotherapy

Iron deposits are a phenotypic trait of tumor-associated macrophages (TAMs). Histological iron imaging and contrast-agent free magnetic resonance imaging (MRI) can detect these deposits, but their presence in human cancer, and correlation with immunotherapeutic response is largely untested. Here, primarily using these iron imaging approaches, we evaluated the spatial distribution of polarized macrophage populations containing high endogenous levels of iron in preclinical murine models and human breast cancer, and used them as metabolic biomarkers to correlate TAM infiltration with response to immunotherapy in preclinical trials. Macrophage-targeted inhibition of the colony stimulating factor 1 receptor (CSF1R) by immunotherapy was confirmed to inhibit macrophage accumulation and slow mammary tumor growth in mouse models while also reducing hemosiderin iron-laden TAM accumulation as measured by both iron histology and in vivo iron MRI (FeMRI). Spatial profiling of TAM iron deposit infiltration defined regions of maximal accumulation and response to the CSF1R inhibitor, and revealed differences between microenvironments of human cancer according to levels of polarized macrophage iron accumulation in stromal margins. We therefore demonstrate that iron deposition serves as an endogenous metabolic imaging biomarker of TAM infiltration in breast cancer that has high translational potential for evaluation of immunotherapeutic response.

18F]Fluorocholine and [18F]Fluoroacetate PET as Imaging Biomarkers to Assess Phosphatidylcholine and Mitochondrial Metabolism in Preclinical Models of TSC and LAM.

Tuberous sclerosis complex (TSC) is an autosomal dominant disorder caused by inactivating mutations of the TSC1 or TSC2 gene, characterized by neurocognitive impairment and benign tumors of the brain, skin, heart, and kidneys. Lymphangioleiomyomatosis (LAM) is a diffuse proliferation of α-smooth muscle actin-positive cells associated with cystic destruction of the lung. LAM occurs almost exclusively in women, as a TSC manifestation or a sporadic disorder (TSC1/TSC2 somatic mutations). Biomarkers of whole-body tumor burden/activity and response to rapalogs or other therapies remain needed in TSC/LAM. These preclinical studies aimed to assess feasibility of [18F]fluorocholine (FCH) and [18F]fluoroacetate (FACE) as TSC/LAM metabolic imaging biomarkers. We previously reported that TSC2-deficient cells enhance phosphatidylcholine synthesis via the Kennedy pathway. Here, we show that TSC2-deficient cells exhibit rapid uptake of [18F]FCH in vivo and can be visualized by PET imaging in preclinical models of TSC/LAM, including subcutaneous tumors and pulmonary nodules. Treatment with rapamycin (72 hours) suppressed [18F]FCH standardized uptake value (SUV) by >50% in tumors. Interestingly, [18F]FCH-PET imaging of TSC2-deficient xenografts in ovariectomized mice also showed a significant decrease in tumor SUV. Finally, we found rapamycin-insensitive uptake of FACE by TSC2-deficient cells in vitro and in vivo, reflecting its mitochondrial accumulation via inhibition of aconitase, a TCA cycle enzyme. Preclinical models of TSC2 deficiency represent informative platforms to identify tracers of potential clinical interest. Our findings provide mechanistic evidence for testing the potential of [18F]FCH and [18F]FACE as metabolic imaging biomarkers for TSC and LAM proliferative lesions, and novel insights into the metabolic reprogramming of TSC tumors.

I122] Quantitative molecular imaging: Can we trust the SUV?

Metabolic activity can be measured using FDG PET/CT. Quantification of FDG PET/CT studies is often based on so-called standardised uptake values (SUV). SUVs or other metabolic parameters, such as metabolic volume and total lesion glycolysis can be used for metabolic phenotyping of the tumor. These quantitative metrics are affected by various sources of bias [1] . Factor influencing tracer uptake can be described as technical, imaging physics related or biological uncertainties. Effects of the above mentioned factors on SUV should be mitigated and/or harmonized as much as possible [2] . Harmonization of PET/CT examinations aims at making SUV reads as exchangeable (comparable) and reproducible as possible by harmonizing imaging procedures, image quality and quantitation and harmonizing data analysis methods and interpretation. The main challenge of harmonisation arises from differences in PET/CT imaging procedures and in technology across multiple sites and users. To this end the European Association of Nuclear Medicine published FDG PET/CT imaging guidelines [2] and started a multicentre accreditation program. Moreover, continuous monitoring of the FDG PET/CT data quality is warranted [3] . In this lecture the principles of metabolic imaging with PET, the mechanism of FDG uptake, various factors affecting FDG PET/CT tracer uptake and its quantification by SUV will be discussed. Moreover, the need for validation of simplified uptake metrics, such as SUV, against full kinetic analysis and use of FDG PET as quantitative metabolic imaging biomarker will be addressed. Finally, it will be shown that by standardisation of imaging procedures and by ongoing quality control of the PET/CT systems, FDG uptake can be reliably quantified.

Metabolic and Physiologic Imaging Biomarkers of the Tumor Microenvironment Predict Treatment Outcome with Radiation or a Hypoxia-Activated Prodrug in Mice.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by hypoxic niches that lead to treatment resistance. Therefore, studies of tumor oxygenation and metabolic profiling should contribute to improved treatment strategies. Here, we define two imaging biomarkers that predict differences in tumor response to therapy: (i) partial oxygen pressure (pO2), measured by EPR imaging; and (ii) [1-13C] pyruvate metabolism rate, measured by hyperpolarized 13C MRI. Three human PDAC xenografts with varying treatment sensitivity (Hs766t, MiaPaCa2, and Su.86.86) were grown in mice. The median pO2 of the mature Hs766t, MiaPaCa2, and Su.86.86 tumors was 9.1 ± 1.7, 11.1 ± 2.2, and 17.6 ± 2.6 mm Hg, and the rate of pyruvate-to-lactate conversion was 2.72 ± 0.48, 2.28 ± 0.26, and 1.98 ± 0.51 per minute, respectively (n = 6, each). These results are in agreement with steady-state data of matabolites quantified by mass spectroscopy and histologic analysis, indicating glycolytic and hypoxia profile in Hs766t, MiaPaca2, and Su.86.86 tumors. Fractionated radiotherapy (5 Gy × 5) resulted in a tumor growth delay of 16.7 ± 1.6 and 18.0 ± 2.7 days in MiaPaca2 and Su.86.86 tumors, respectively, compared with 6.3 ± 2.7 days in hypoxic Hs766t tumors. Treatment with gemcitabine, a first-line chemotherapeutic agent, or the hypoxia-activated prodrug TH-302 was more effective against Hs766t tumors (20.0 ± 3.5 and 25.0 ± 7.7 days increase in survival time, respectively) than MiaPaCa2 (2.7 ± 0.4 and 6.7 ± 0.7 days) and Su.86.86 (4.7 ± 0.6 and 0.7 ± 0.6 days) tumors. Collectively, these results demonstrate the ability of molecular imaging biomarkers to predict the response of PDAC to treatment with radiotherapy and TH-302.Significance: pO2 imaging data and clinically available metabolic imaging data provide useful insight into predicting the treatment efficacy of chemotherapy, radiation, and a hypoxia-activated prodrug as monotherapies and combination therapies in PDAC tumor xenograft models. Cancer Res; 78(14); 3783-92. ©2018 AACR.