EGFR TKI PET/CT in advanced stage non-small cell lung cancer patients

An overview of biomarker development is provided in chapter 2.PET tracer-based biomarkers can be used to monitor different biological or clinical metrics. A clinically important biomarker, especially in lung cancer, is the epidermal growth factor receptor (EGFR) abundance. In this chapter we give an overview of current EGFR-directed PET tracers to visualize the tumors’ EGFR binding capacity, and discuss the challenges and opportunities regarding their clinical application. One of the major challenges is the necessity of highly complex and invasive acquisition protocols for quantitative assessment of tracer uptake. Another important challenge for the current tracer developmental process is the rapidly changing treatment landscape. Development of a TKI-based PET tracer can be relatively long and with the current rate of change in treatment options, developed tracers should be brought quickly into clinical usage before they lose their clinical relevance. This chapter also highlights some opportunities. The total body PET scanner could greatly decrease the level of complexity of protocols. This would decrease the time needed for a tracer to be ready for clinical use, which in turn could improve the clinical relevance of EGFR-directed tracers. In chapter 3 we describe the process of quantification of 18F-afatinib. Ten NSCLC patients underwent dynamic PET scanning using 18F-afatinib. Three pharmacokinetic compartment models were assessed using both plasma-derived input functions and image-derived input functions: a single-tissue model (1T2K), a two-tissue reversible model (2T4K) and a two-tissue irreversible model (2T3K). The preferred model was the two-tissue irreversible model. This is consistent with in vitro data showing irreversible binding of afatinib to the EGF receptor. The relationship between 18F-afatinib tumor uptake, EGFR mutational status and response to treatment using afatinib was investigated in chapter 4. In this chapter we compared tracer uptake of EGFR wild type tumors with both EGFR common and uncommon tumors, hypothesizing that uncommon EGFR mutations behave similarly to common mutations. A significant difference was observed between tracer uptake of wild type tumors versus both common and uncommon mutations. Furthermore, a TBR60-90 value of >6 was shown to be predictive of response to treatment using afatinib. Chapter 5 focuses on the biodistribution and image quality of three generations of EGFR TKI PET tracers: 11C-erlotinib, 18F-afatinib and 11C-osimertinib based. The image quality derived from patients in a recently started clinical trial of the 11C-osimertinib derived tracer was remarkably different from the first two generation of TKI tracers. The tumor tissue showed a low tracer uptake compared to the surrounding lung tissue. To investigate this phenomenon, we (re-)analyzed data from three previously published prospective studies and one ongoing clinical trial. Image quality was also quantified for each tracer by calculating the tumor-to-lung contrast and background noise for each tracer. 11C-erlotinib and 18F-afatinib showed the best image quality based on both tumor-to-lung contrast and noise, whereas 11C-osimertinib showed an inverse tumor-to-lung contrast: lung tissue showed a higher level of tracer uptake when compared to tumor tissue. Differences in physicochemical, pharmacological and pharmacokinetic parameters of the three generation of TKI’s may explain the observed the differences in tumor-to-lung contrast. The results of the comparison that we conducted in chapter 5 lead to chapter 6. In this chapter we developed a physiologically-based pharmacokinetic (PBPK) model that accurately predicted tissue uptake for the three EGFR TKIs (erlotinib, afatinib and osimertinib) using physicochemical and drug specific properties. This model was validated using PET data as obtained and described in the previous chapter. Our model yielded an adequate prediction of tumor-to-lung contrast and whole-body distribution of the three EGFR TKIs

Radiolabeled EGFR TKI as predictive imaging biomarkers in NSCLC patients – an overview

Non-small cell lung cancer (NSCLC) has one of the highest cancer-related mortality rates worldwide. In a subgroup of NSCLC, tumor growth is driven by epidermal growth factor receptors (EGFR) that harbor an activating mutation. These patients are best treated with EGFR tyrosine kinase inhibitors (EGFR TKI). Identifying the EGFR mutational status on a tumor biopsy or a liquid biopsy using tumor DNA sequencing techniques is the current approach to predict tumor response on EGFR TKI therapy. However, due to difficulty in reaching tumor sites, and varying inter- and intralesional tumor heterogeneity, biopsies are not always possible or representative of all tumor lesions, highlighting the need for alternative biomarkers that predict tumor response. Positron emission tomography (PET) studies using EGFR TKI-based tracers have shown that EGFR mutational status could be identified, and that tracer uptake could potentially be used as a biomarker for tumor response. However, despite their likely predictive and monitoring value, the EGFR TKI-PET biomarkers are not yet qualified to be used in the routine clinical practice. In this review, we will discuss the currently investigated EGFR-directed PET biomarkers, elaborate on the typical biomarker development process, and describe how the advances, challenges, and opportunities of EGFR PET biomarkers relate to this process on their way to qualification for routine clinical practice

Relationship between Biodistribution and Tracer Kinetics of C-11-Erlotinib, F-18-Afatinib and C-11-Osimertinib and Image Quality Evaluation Using Pharmacokinetic/Pharmacodynamic Analysis in Advanced Stage Non-Small Cell Lung Cancer Patients

BACKGROUND: Patients with non-small cell lung cancer (NSCLC) driven by activating epidermal growth factor receptor (EGFR) mutations are best treated with therapies targeting EGFR, i.e., tyrosine kinase inhibitors (TKI). Radiolabeled EGFR-TKI and PET have been investigated to study EGFR-TKI kinetics and its potential role as biomarker of response in NSCLC patients with EGFR mutations (EGFRm). In this study we aimed to compare the biodistribution and kinetics of three different EGFR-TKI, i.e., 11C-erlotinib, 18F-afatinib and 11C-osimertinib. METHODS: Data of three prospective studies and 1 ongoing study were re-analysed; data from thirteen patients (EGFRm) were included for 11C-erlotinib, seven patients for 18F-afatinib (EGFRm and EGFR wild type) and four patients for 11C-osimertinib (EGFRm). From dynamic and static scans, SUV and tumor-to-blood (TBR) values were derived for tumor, lung, spleen, liver, vertebra and, if possible, brain tissue. AUC values were calculated using dynamic time-activity-curves. Parent fraction, plasma-to-blood ratio and SUV values were derived from arterial blood data. Tumor-to-lung contrast was calculated, as well as (background) noise to assess image quality. RESULTS: 11C-osimertinib showed the highest SUV and TBR (AUC) values in nearly all tissues. Spleen uptake was notably high for 11C-osimertinib and to a lesser extent for 18F-afatinib. For EGFRm, 11C-erlotinib and 18F-afatinib demonstrated the highest tumor-to-lung contrast, compared to an inverse contrast observed for 11C-osimertinib. Tumor-to-lung contrast and spleen uptake of the three TKI ranked accordingly to the expected lysosomal sequestration. CONCLUSION: Comparison of biodistribution and tracer kinetics showed that 11C-erlotinib and 18F-afatinib demonstrated the highest tumor-to-background contrast in EGFRm positive tumors. Image quality, based on contrast and noise analysis, was superior for 11C-erlotinib and 18F-afatinib (EGFRm) scans compared to 11C-osimertinib and 18F-afatinib (EGFR wild type) scans

Identifying advanced stage NSCLC patients who benefit from afatinib therapy using 18F-afatinib PET/CT imaging

Objectives: Non-small cell lung cancer (NSCLC) tumors harboring common (exon19del, L858R) and uncommon (e.g. G719X, L861Q) activating epidermal growth factor receptor (EGFR) mutations are best treated with EGFR tyrosine kinase inhibitors (TKI) such as the first-generation EGFR TKI erlotinib, second-generation afatinib or third-generation osimertinib. However, identifying these patients through biopsy is not always possible. Therefore, our aim was to evaluate whether 18F-afatinib PET/CT could identify patients with common and uncommon EGFR mutations. Furthermore, we evaluated the relation between tumor 18F-afatinib uptake and response to afatinib therapy. Materials and methods: 18F-afatinib PET/CT was performed in 12 patients: 6 EGFR wild type (WT), 3 EGFR common and 3 EGFR uncommon mutations. Tumor uptake of 18F-afatinib was quantified using TBR_WB60−90 (tumor-to-whole blood activity ratio 60−90 min post-injection) for each tumor. Response was quantified per lesion using percentage of change (PC): [(response measurement (RM)–baseline measurement (BM))/BM]×100. Statistical analyses were performed using t-tests, correlation plots and sensitivity/specificity analysis. Results: Twenty-one tumors were identified. Injected dose was 348 ± 31 MBq. Group differences were significant between WT versus EGFR (common and uncommon) activating mutations (p = 0.03). There was no significant difference between EGFR common versus uncommon mutations (p = 0.94). A TBR_WB60−90 cut-off value of 6 showed the best relationship with response with a sensitivity of 70 %, a specificity of 100 % and a positive predictive value of 100 %. Conclusion: 18F-afatinib uptake was higher in tumors with EGFR mutations (common and uncommon) compared to WT. Furthermore, a TBR_WB60−90 cut-off of 6 was found to best predict response to therapy. 18F-afatinib PET/CT could provide a means to identify EGFR mutation positive patients who benefit from afatinib therapy