Dataset Information

Identification of time-to-peak on dynamic 18F-FET-PET as a prognostic marker specifically in IDH1/2 mutant diffuse astrocytoma.

ABSTRACT:

Background

Stratification of glioma according to isocitrate dehydrogenase 1/2 (IDH1/2) mutation and 1p/19q codeletion status has gained major importance in the new World Health Organization (WHO) classification. Parameters derived from uptake dynamics of 18F-fluoro-ethyl-tyrosine PET (18F-FET-PET) such as minimal time-to-peak (TTPmin) allow discrimination between different prognostic glioma subgroups, too. The present study is aimed at exploring whether TTPmin analysis provides prognostic information beyond the WHO classification.

Methods

Three hundred patients with newly diagnosed WHO 2007 grades II-IV gliomas with 18F-FET-PET imaging at diagnosis were grouped into 4 subgroups (IDH1/2 mut-1p/19q codel; IDH1/2 mut-1p/19q non-codel; IDH1/2 wildtype WHO grade II and III tumors; and glioblastoma). Clinical and imaging factors such as age, Karnofsky performance score, treatment, TTPmin, and maximal tumor-to-brain ratio (TBRmax) were analyzed with regard to progression-free and overall survival (PFS and OS) via univariate and multivariate regression analysis.

Results

PFS and OS were longest in the IDH1/2 mut-1p/19q codel subgroup, followed by IDH1/2 mut-1p/19q non-codel, IDH1/2 wildtype, and GBM (P < 0.001). Further, outcome stratified by TTPmin with a cutoff of 17.5 minutes revealed significantly longer PFS and OS in patients with TTPmin >17.5 minutes (P < 0.001 for PFS and OS). Lower TBRmax values or the absence of 18F-FET uptake was also associated with favorable outcome in the entire group. In the subgroup analyses, longer median TTPmin was associated with improved outcome specifically in the IDH1/2 mut-1p/19q non-codel group.

Conclusion

18F-FET-PET-derived dynamic analysis defines prognostically distinct subgroups of IDH1/2 mutant-1p/19q non-codel gliomas which cannot be distinguished as yet by molecular marker analysis.

SUBMITTER: Suchorska B

PROVIDER: S-EPMC5777500 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Publications

Identification of time-to-peak on dynamic 18F-FET-PET as a prognostic marker specifically in IDH1/2 mutant diffuse astrocytoma.

Suchorska Bogdana B Giese Armin A Biczok Annamaria A Unterrainer Marcus M Weller Michael M Drexler Mark M Bartenstein Peter P Schüller Ulrich U Tonn Jörg-Christian JC Albert Nathalie L NL

Neuro-oncology 20180101 2

<h4>Background</h4>Stratification of glioma according to isocitrate dehydrogenase 1/2 (IDH1/2) mutation and 1p/19q codeletion status has gained major importance in the new World Health Organization (WHO) classification. Parameters derived from uptake dynamics of 18F-fluoro-ethyl-tyrosine PET (18F-FET-PET) such as minimal time-to-peak (TTPmin) allow discrimination between different prognostic glioma subgroups, too. The present study is aimed at exploring whether TTPmin analysis provides prognosti ...[more]

PMID: 29016996

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Project description:IntroductionAim was to develop a full automatic clustering approach of the time-activity curves (TAC) from dynamic 18F-FET PET and evaluate its association with IDH1 mutation status and survival in patients with gliomas.MethodsThirty-seven patients (mean age: 45±13 y) with newly diagnosed gliomas and dynamic 18F-FET PET before any histopathologic investigation or treatment were retrospectively included. Each dynamic 18F-FET PET was realigned to the first image and spatially normalized in the Montreal Neurological Institute template. A tumor mask was semi-automatically generated from Z-score maps. Each brain tumor voxel was clustered in one of the 3 following centroids using dynamic time warping and k-means clustering (centroid #1: slowly increasing slope; centroid #2: rapidly increasing followed by slowly decreasing slope; and centroid #3: rapidly increasing followed by rapidly decreasing slope). The percentage of each dynamic 18F-FET TAC within tumors and other conventional 18F-FET PET parameters (maximum and mean tumor-to-brain ratios [TBRmax and TBRmean], time-to-peak [TTP] and slope) was compared between wild-type and IDH1 mutant tumors. Their prognostic value was assessed in terms of progression free-survival (PFS) and overall survival (OS) by Kaplan-Meier estimates.ResultsTwenty patients were IDH1 wild-type and 17 IDH1 mutant. Higher percentage of centroid #1 and centroid #3 within tumors were positively (P = 0.016) and negatively (P = 0.01) correlated with IDH1 mutated status. Also, TBRmax, TBRmean, TTP, and slope discriminated significantly between tumors with and without IDH1 mutation (P range 0.01 to 0.04). Progression occurred in 22 patients (59%) at a median of 13.1 months (7.6-37.6 months) and 13 patients (35%) died from tumor progression. Patients with a percentage of centroid #1 > 90% had a longer survival compared with those with a percentage of centroid #1 < 90% (P = 0.003 for PFS and P = 0.028 for OS). This remained significant after stratification on IDH1 mutation status (P = 0.029 for PFS and P = 0.034 for OS). Compared to other conventional 18F-FET PET parameters, TTP and slope were associated with PFS and OS (P range 0.009 to 0.04).ConclusionsBased on dynamic 18F-FET PET acquisition, we developed a full automatic clustering approach of TAC which appears to be a valuable noninvasive diagnostic and prognostic marker in patients with gliomas.

Project description:Astrocytomas are the most common subtype of brain tumors and no curative treatment exist. Longitudinal assessment of patients, usually via Magnetic Resonance Imaging (MRI), is crucial since tumor progression may occur earlier than clinical progression. MRI usually provides a means for monitoring the disease, but it only informs about the structural changes of the tumor, while molecular changes can occur as a treatment response without any MRI-visible change. Radiotherapy (RT) is routinely performed following surgery as part of the standard of care in astrocytomas, that can also include chemotherapy involving temozolomide. Monitoring the response to RT is a key factor for the management of patients. Herein, we provide plasma and tissue metabolic biomarkers of treatment response in a mouse model of astrocytoma that was subjected to radiotherapy. Plasma metabolic profiles acquired over time by Liquid Chromatography Mass Spectrometry (LC/MS) were subjected to multivariate empirical Bayes time-series analysis (MEBA) and Receiver Operating Characteristic (ROC) assessment including Random Forest as the classification strategy. These analyses revealed a variation of the plasma metabolome in those mice that underwent radiotherapy compared to controls; specifically, fumarate was the best discriminatory feature. Additionally, Nuclear Magnetic Resonance (NMR)-based 13C-tracing experiments were performed at end-point utilizing [U-13C]-Glutamine to investigate its fate in the tumor and contralateral tissues. Irradiated mice displayed lower levels of glycolytic metabolites (e.g. phosphoenolpyruvate) in tumor tissue, and a higher flux of glutamine towards succinate was observed in the radiation cohort. The plasma biomarkers provided herein could be validated in the clinic, thereby improving the assessment of brain tumor patients throughout radiotherapy. Moreover, the metabolic rewiring associated to radiotherapy in tumor tissue could lead to potential metabolic imaging approaches for monitoring treatment using blood draws.

Project description:Glioma is recognized to be a highly heterogeneous CNS malignancy, whose diverse cellular composition and cellular interactions have not been well characterized. To gain new clinical- and biological-insights into the genetically-bifurcated IDH1 mutant (mt) vs wildtype (wt) forms of glioma, we integrated data from protein, genomic and MR imaging from 20 treatment-naïve glioma cases and 16 recurrent GBM cases. Multiplexed immunofluorescence (MxIF) was used to generate single cell data for 43 protein markers representing all cancer hallmarks, Genomic sequencing (exome and RNA (normal and tumor) and magnetic resonance imaging (MRI) quantitative features (protocols were T1-post, FLAIR and ADC) from whole tumor, peritumoral edema and enhancing core vs equivalent normal region were also collected from patients. Based on MxIF analysis, 85,767 cells (glioma cases) and 56,304 cells (GBM cases) were used to generate cell-level data for 24 biomarkers. K-means clustering was used to generate 7 distinct groups of cells with divergent biomarker profiles and deconvolution was used to assign RNA data into three classes. Spatial and molecular heterogeneity metrics were generated for the cell data. All features were compared between IDH mt and IDHwt patients and were finally combined to provide a holistic/integrated comparison. Protein expression by hallmark was generally lower in the IDHmt vs wt patients. Molecular and spatial heterogeneity scores for angiogenesis and cell invasion also differed between IDHmt and wt gliomas irrespective of prior treatment and tumor grade; these differences also persisted in the MR imaging features of peritumoral edema and contrast enhancement volumes. A coherent picture of enhanced angiogenesis in IDHwt tumors was derived from multiple platforms (genomic, proteomic and imaging) and scales from individual proteins to cell clusters and heterogeneity, as well as bulk tumor RNA and imaging features. Longer overall survival for IDH1mt glioma patients may reflect mutation-driven alterations in cellular, molecular, and spatial heterogeneity which manifest in discernable radiological manifestations.

Dataset Information

Identification of time-to-peak on dynamic 18F-FET-PET as a prognostic marker specifically in IDH1/2 mutant diffuse astrocytoma.

Background

Methods

Results

Conclusion

Publications

Identification of time-to-peak on dynamic 18F-FET-PET as a prognostic marker specifically in IDH1/2 mutant diffuse astrocytoma.

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