ObjectiveThe mutation of the ‘telomerase reverse transcriptase gene promoter’ (TERTp) has been identified as an important factor for individual prognostication and tumorigenesis and will be implemented in upcoming glioma classifications. Uptake characteristics on dynamic 18F-FET PET have been shown to serve as additional imaging biomarker for prognosis. However, data on the correlation of TERTp-mutational status and amino acid uptake on dynamic 18F-FET PET are missing. Therefore, we aimed to analyze whether static and dynamic 18F-FET PET parameters are associated with the TERTp-mutational status in de-novo IDH-wildtype glioblastoma and whether a TERTp-mutation can be predicted by dynamic 18F-FET PET.MethodsPatients with de-novo IDH-wildtype glioblastoma, WHO grade IV, available TERTp-mutational status and dynamic 18F-FET PET scan prior to any therapy were included. Here, established clinical parameters maximal and mean tumor-to-background-ratios (TBRmax/TBRmean), the biological-tumor-volume (BTV) and minimal-time-to-peak (TTPmin) on dynamic PET were analyzed and correlated with the TERTp-mutational status.ResultsOne hundred IDH-wildtype glioblastoma patients were evaluated; 85/100 of the analyzed tumors showed a TERTp-mutation (C228T or C250T), 15/100 were classified as TERTp-wildtype. None of the static PET parameters was associated with the TERTp-mutational status (median TBRmax 3.41 vs. 3.32 (p=0.362), TBRmean 2.09 vs. 2.02 (p=0.349) and BTV 26.1 vs. 22.4 ml (p=0.377)). Also, the dynamic PET parameter TTPmin did not differ in both groups (12.5 vs. 12.5 min, p=0.411). Within the TERTp-mutant subgroups (i.e., C228T (n=23) & C250T (n=62)), the median TBRmax (3.33 vs. 3.69, p=0.095), TBRmean (2.08 vs. 2.09, p=0.352), BTV (25.4 vs. 30.0 ml, p=0.130) and TTPmin (12.5 vs. 12.5 min, p=0.190) were comparable, too.ConclusionUptake characteristics on dynamic 18F-FET PET are not associated with the TERTp-mutational status in glioblastoma However, as both, dynamic 18F-FET PET parameters as well as the TERTp-mutation status are well-known prognostic biomarkers, future studies should investigate the complementary and independent prognostic value of both factors in order to further stratify patients into risk groups.

The 18-kDa translocator protein (TSPO) is gaining recognition as a relevant target in glioblastoma imaging. However, data on the potential prognostic value of TSPO PET imaging in glioblastoma are lacking. Therefore, we investigated the association of TSPO PET imaging results with survival outcome in a homogeneous cohort of glioblastoma patients. Methods: Patients were included who had newly diagnosed, histologically confirmed isocitrate dehydrogenase (IDH)-wild-type glioblastoma with available TSPO PET before either normofractionated radiotherapy combined with temozolomide or hypofractionated radiotherapy. SUV max on TSPO PET, TSPO binding affinity status, tumor volumes on MRI, and further clinical data, such as O 6 -alkylguanine DNA methyltransferase (MGMT) and telomerase reverse transcriptase (TERT) gene promoter mutation status, were correlated with patient survival. Results: Forty-five patients (median age, 63.3 y) were included. Median SUV max was 2.2 (range, 1.0-4.7). A TSPO PET signal was associated with survival: High uptake intensity (SUV max . 2.2) was related to significantly shorter overall survival (OS; 8.3 vs. 17.8 mo, P 5 0.037). Besides SUV max , prognostic factors for OS were age (P 5 0.046), MGMT promoter methylation status (P 5 0.032), and T2-weighted MRI volume (P 5 0.031). In the multivariate survival analysis, SUV max in TSPO PET remained an independent prognostic factor for OS (P 5 0.023), with a hazard ratio of 2.212 (95% CI, for death in cases with a high TSPO PET signal (SUV max . 2.2). Conclusion: A high TSPO PET signal before radiotherapy is associated with significantly shorter survival in patients with newly diagnosed IDH-wild-type glioblastoma. TSPO PET seems to add prognostic insights beyond established clinical parameters and might serve as an informative tool as clinicians make survival predictions for patients with glioblastoma.

The purpose of this study was to evaluate the possibility of extracting relevant information from radiomic features even in apparently [18F]FET-negative gliomas. A total of 46 patients with a newly diagnosed, histologically verified glioma that was visually classified as [18F]FET-negative were included. Tumor volumes were defined using routine T2/FLAIR MRI data and applied to extract information from dynamic [18F]FET PET data, i.e., early and late tumor-to-background (TBR5–15, TBR20–40) and time-to-peak (TTP) images. Radiomic features of healthy background were calculated from the tumor volume of interest mirrored in the contralateral hemisphere. The ability to distinguish tumors from healthy tissue was assessed using the Wilcoxon test and logistic regression. A total of 5, 15, and 69% of features derived from TBR20–40, TBR5–15, and TTP images, respectively, were significantly different. A high number of significantly different TTP features was even found in isometabolic gliomas (after exclusion of photopenic gliomas) with visually normal [18F]FET uptake in static images. However, the differences did not reach satisfactory predictability for machine-learning-based identification of tumor tissue. In conclusion, radiomic features derived from dynamic [18F]FET PET data may extract additional information even in [18F]FET-negative gliomas, which should be investigated in larger cohorts and correlated with histological and outcome features in future studies.

7651 Background: Recent studies have examined potential predictive markers in NSCLC patients (pts) treated with EGFR tyrosine kinase inhibitors. However, few data are available on inter-relationships between different markers. Clinical and molecular markers were analyzed for patients from TRUST, an open label, non-randomized trial initiated to provide erlotinib access to pts with advanced NSCLC. Methods: 393 German pts (99% Caucasian) with stage IIIb/IV NSCLC were included. Markers/characteristics assessed were: EGFR (282 pts) and phosphorylated MAPK (pMAPK; 109 pts) using immunohistochemistry (IHC; positive status was defined as: ≥10% of tumor cells with any membrane staining for EGFR; and H-score ≥200 for pMAPK), EGFR gene copy number (135 pts) using fluorescence in-situ hybridization (FISH), EGFR mutations (86 pts), KRAS mutations (108 pts), tumor type (281 pts), smoking status (392 pts) and gender (393 pts). Results: EGFR FISH+ pts were likely to also be EGFR IHC+: 92.9% (26/28) of EGFR FISH+ pts were EGFR IHC+, and 92.6% of EGFR IHC- pts were also EGFR FISH- (p<0.1). pMAPK expression status was not related to other markers. 15.7% (17/108) pts had KRAS and 7.0% (6/86) had EGFR mutations; no pts had mutations in both genes, indicating that these mutations might be mutually exclusive. Both KRAS mutations and histology were associated with smoking status. 94.1% (16/17) pts with KRAS mutations and 91.6% (87/95) pts with squamous-cell carcinoma were smokers. In female pts, the occurrence of adenocarcinoma was significantly higher (73.6% vs 55.4% in males; p<0.001), possibly influenced by a lower incidence of smokers in this group (51.3% vs 92.2% in males; p<0.001). Conclusions: The availability of a large number of tumor samples from the TRUST study, and assessment of a broad range of markers allows investigation of relationships between various tumor/patient characteristics. Understanding these complex inter-relationships may shed light on the role of each marker. Specific combinations of markers may prove useful in predicting clinical benefit from erlotinib. As the study is ongoing, additional data will be available and presented. No significant financial relationships to disclose.

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