18F-FDG PET/CT to predict tumor PD-L1 expression and response to PD-(L)1 blockade in patients with non-small-cell lung cancer
Editorial Commentary

18F-FDG PET/CT to predict tumor PD-L1 expression and response to PD-(L)1 blockade in patients with non-small-cell lung cancer

Frank Johannes Borm, Adrianus Johannes De Langen

Department of Thoracic Oncology, Netherlands Cancer Institute Antoni van Leeuwenhoek, Amsterdam, The Netherlands

Correspondence to: Adrianus Johannes De Langen, MD, MSc, PhD. Department of Thoracic Oncology, Netherlands Cancer Institute Antoni van Leeuwenhoek, Postbus 90203, 1006 BE, Amsterdam, The Netherlands. Email: j.d.langen@NKI.nl.

Provenance and Peer Review: This article was commissioned and reviewed by the Section Editor Jun Zhou (Department of Nuclear Medicine, Zhongshan Hospital, Fudan University, Shanghai, China).

Comment on: Jreige M, Letovanec I, Chaba K, et al. 18F-FDG PET metabolic-to-morphological volume ratio predicts PD-L1 tumour expression and response to PD-1 blockade in non-small-cell lung cancer. Eur J Nucl Med Mol Imaging 2019;46:1859-68.

Submitted Feb 04, 2020. Accepted for publication Feb 26, 2020.

doi: 10.21037/jtd.2020.03.12

Since the introduction of PD-(L)1 checkpoint inhibitor therapy for the treatment of non-small-cell lung cancer (NSCLC) there is a search for a biomarker that distinguishes responders from non-responders. A reliable biomarker has not been found yet. Tumor PD-L1 expression, assessed by immunohistochemistry (IHC) on a histological tumor sample, is at this point the most widely used and best validated biomarker. Absence of tumor PD-L1 expression predicts for a low overall response rate (ORR) of ~10%, while a tumor PD-L1 expression of ≥50% predicts for an ORR of 30% to 45% (1-3). To acquire enough tumor material in NSCLC for IHC testing and molecular analysis can be challenging. Frailty and comorbidities of patients and limited accessibility of lesions for biopsy on one hand and the increasing number of IHC and genetic tests being requested on the other hand are a constant challenge. Non-invasive techniques for tumor profiling are therefore attractive alternatives.

Multiple studies evaluated pretreatment Fluor-18-deoxyglucose positron emission tomography (18FDG-PET) as predictive imaging biomarker for response to immune checkpoint inhibitor therapy in NSCLC. In general, these studies show that a higher total lesion glycolysis (TLG) correlates with a poor response to PD-(L)1 inhibitors (4-6). Takada et al. studied the correlation of PD-L1 IHC (cut-off ≥5%) with the standardized uptake value (SUV) assessed by 18FDG-PET (7). The study was conducted in an early stage NSCLC cohort and PD-L1 IHC assessment was done on resection specimens. They found that SUVmax was significantly higher in NSCLC patients with PD-L1 IHC ≥5%.

Jreige et al. recently published their paper in the European Journal of Nuclear Medicine and Molecular Imaging (8). This group evaluated the predictive value of metabolic to morphological volume ratio (MMVR) for tumor PD-L1 expression. MMVR was measured by dividing the metabolic tumor volume (delineated on the 18FDG-PET/CT) by the total tumor volume as delineated on the CT scan. MMVR showed an inverse correlation with tumor PD-L1 expression. This difference with the study by Takada et al. might be due to a substantial number of patients with necrotic tumors in the study by Jreige et al.; Necrotic tumors can have a high SUVmax, but a low MMVR.

Tumor necrosis is associated with higher PD-L1/PD-1 expression in NSCLC (9). Therefore, low MMVR seems to correlate with necrosis and a higher PD-L1 expression.

Interestingly Jreige et al. found a significant correlation between disease control and MMVR in 17 patients treated with PD-(L)1 blockade, while TLG was not predictive for response. Patients with disease control also showed higher PD-L1 tumor expression. Jreige et al. pointed out in the discussion that tumor necrosis upregulates PD-L1 expression on tumor cells. Tumor necrosis factor α (TNFα), which is an inflammatory cytokine that arises in a necrotic environment, might be responsible for this PD-L1 induction. A recent study (10) showed that not TNFα is responsible for PD-L1 expression and response to PD-(L)1 inhibitors, but IL-6 is. IL-6 is also known to be excreted in a hypoxic pulmonary environment (11). These mechanisms might partly explain the association between response to anti PD-(L)1 therapy and tumor necrosis.

Next to using 18FDG uptake to predict PD-L1 expression and response to PD-(L)1 blockade, it is possible to use more specific tracers. A PET imaging study with 89Zirconium labeled atezolizumab in patients with NSCLC, bladder cancer or triple negative breast cancer showed remarkable results (12). Radiotracer uptake correlated with response to atezolizumab treatment, while in this study PD-L1 IHC did not. There was no correlation found between atezolizumab uptake and PD-L1 IHC. Since checkpoint inhibitors are large proteins, biodistribution from the intravascular space to their PD-L1 target takes several days. This makes these kind of PET-scans less feasible for routine care. In the study by Niemeijer et al. (13) a small molecule PD-L1 adnectin bound to 18Fluor correlated with PD-L1 IHC as well as tumor response in patients with NSCLC that were treated with nivolumab. The latter was not significant, possibly due to the small number of patients. Interestingly, both studies showed substantial PD-L1 tracer uptake heterogeneity between patients and also within patients between different tumor lesions. These results demonstrate the power of whole-body imaging; although at a lower spatial resolution than microscopy, it allows to image and quantify target expression for all tumor sites at the same time.

The study of Jreige et al. is promising in the sense that it is pushing clinicians into a new direction. 18FDG-PET derived MMVR shows a remarkable correlation with response to PD-(L)1 blockade. As most patients receive a 18FDG-PET scan before treatment initiation, it will be simple to use this biomarker in the clinic and to generate more data for research purposes. Ideally, this biomarker information should be combined with other patient statistics (pathology, performance, etc.) and possibly novel techniques like immune PET-imaging to study more complex and hopefully more reliable predictive biomarkers. In radiomics for example, hundreds of imaged features are collected from routinely performed scans. Bioinformatics and artificial intelligence are then used on these data sets. It has been shown that the predictive and prognostic value can be improved (14,15). At this moment, more research on MMVR and other 18FDG-PET derived features must be generated in larger patient groups in order to use this biomarker for clinical decision making (i.e., to direct patient treatment). Hopefully, one day, these imaging biomarkers lead to less biopsies and more individualized and effective treatment.


Funding: None.


Conflicts of Interest: Both authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/jtd.2020.03.12). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.


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Cite this article as: Borm FJ, De Langen AJ. 18F-FDG PET/CT to predict tumor PD-L1 expression and response to PD-(L)1 blockade in patients with non-small-cell lung cancer. J Thorac Dis 2020;12(7):3883-3885. doi: 10.21037/jtd.2020.03.12

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