Quantifying PD-L1 Expression to Monitor Immune Checkpoint Therapy: Opportunities and Challenges

Abstract

Therapeutics targeting programmed death ligand 1 (PD-L1) protein and its receptor PD-1 are now dominant players in restoring anti-tumor immune responses. PD-L1 detection by immunohistochemistry (IHC) is emerging as a reproducible biomarker for guiding patient stratification for those therapies in some cancers. However, PD-L1 expression in the tumor microenvironment is highly complex. It is upregulated by aberrant genetic alterations, and is highly regulated at the transcriptional, posttranscriptional, and protein levels. Thus, PD-L1 IHC is inadequate to fully understand the relevance of PD-L1 levels in the whole body and their dynamics to improve therapeutic outcomes. Imaging technologies could potentially assist in meeting that need. Early clinical investigations show promising results in quantifying PD-L1 expression in the whole body by positron emission tomography (PET). Within this context, this review summarizes advancements in regulation of PD-L1 expression and imaging agents, and in PD-L1 PET for drug development, and discusses opportunities and challenges presented by these innovations for guiding immune checkpoint therapy (ICT).

Keywords: PET imaging; immune checkpoints; immuno-Oncology; interferon-γ signaling; tumor microenvironment; tumor mutational burden.

Figure 1

WL12 binding interactions with PD-L1 overlap with those of PD-1. (A) Structural representation of WL12 and its analogs; (B) predicted binding mode of WL12 to PD-L1. WL12 forms a beta sheet-like structure in the groove of PD-L1. WL12 is shown in cyan. The surface representation of PD-L1 is shown in gray, with the ribbons and key side chains shown in magenta; WL12 mimics PD-1 binding to PD-L1. The structure of PD-1 is shown in teal. The two main interacting beta strands of PD-1 overlap well with the conformation adopted by WL12 bound to PD-L1. (C) NSG mice with hPD-L1 (red arrow) and CHO tumors (blue arrow) were administered intravenously with 150 μCi of [⁶⁴Cu]WL12 and images were acquired at 10, 60, and 120 min after the injection of the radiotracer. 3D volume rendered images show specific accumulation of [⁶⁴Cu]WL12 in hPD-L1 tumors. (D) PD-L1 IHC shows strong immunoreactivity (brown color) in hPD-L1 tumors (from [153]).

Figure 2

⁸⁹Zr-atezolizumab tumor uptake. (a) Examples of PET/CT images of four patients illustrating ⁸⁹Zr-atezolizumab tumor uptake in five different locations on day 7 post injection (white arrows indicate tumor lesions; PET scans were performed once per patient and time point). Images (i) and (ii) are from the same patient, whereas images (iii), (iv), and (v) are from a separate patients. (b) Overview of ⁸⁹Zr-atezolizumab uptake as SUVmax at day 7 post injection in 196 tumor lesions with a diameter >2 cm grouped per tumor type and ordered by increasing geometric mean SUVmax per patient, visualizing tumor size and site, and with blood pool background uptake as reference. Horizontal bar indicates geometric mean SUVmax per patient. (c) Violin plot of actual distribution of SUVmax in lesions per site of lesion with bottom and top 1% of SUVmax values truncated (first, fiftieth, and ninety-ninth SUVmax percentiles: 1.7, 7.9, 19.6 for lung; 3.9, 5.6, 16.4 for bone; 4.6, 9.7, 40.1 for lymph node; 16.1, 23.3, 34.1 for liver); black vertical lines are 95% CIs of geometric mean SUVmax; white dots within black lines and values below the violin plot are the actual geometric means, all based on a linear mixed regression model with two-sided Wald p values using Satterthwaite approximations to degrees of freedom under restricted maximum likelihood, shown above the graph; n_lung = 44 in ten patients, n_bone = 62 in nine patients, n_{lymph node} = 54 in 20 patients, n_liver = 19 in one patient. (d) Violin plot of SUVmax in lesions per tumor type with bottom and top 1% of SUVmax values truncated (first, fiftieth, and ninety-ninth SUVmax percentiles: 3.6, 10.9, 38.0 for bladder; 1.7, 9.7, 19.6 for NSCLC; 3.4, 5.6, 11.7 for TNBC); black vertical lines are 95% CIs of geometric mean SUVmax; white dots within black lines and values below the violin plot are the actual geometric means, all based on a linear mixed regression model with two-sided Wald p values using Satterthwaite approximations to degrees of freedom under restricted maximum likelihood, shown above the graph; n_bladder = 85 in nine patients, n_NSCLC = 43 in nine patients, n_TNBC = 68 in four patients from [155].

Figure 3

¹⁸F-BMS-986192 tumor uptake in patients. Patient 2 with tumor with PD-L1 expression > 95% (left panel). ¹⁸F-BMS-986192 PET (145.7 MBq, imaging time point 1 h post injection (p.i.)) demonstrates heterogeneous tracer uptake within and between tumors. Patient 3 with tumor PD-L1 expression < 1% (right panel). ¹⁸F-BMS-986192 PET (214.62 MBq, 1 h p.i.) demonstrates low tumor tracer uptake. Physiological expression=driven uptake in the spleen and non-specific uptake in the liver were observed with ¹⁸F-BMS-986192. Red and blue in the images represent maximum and minimum accumulated radioactivity, respectively, if a rainbow color scale is used(from [156]).

Figure 4

Tumor PD-L1 engagement by 3 distinct PD-L1 therapeutic antibodies quantified using [⁶⁴Cu] WL12. (A–E) [⁶⁴Cu]WL12 uptake in MDA-MB-231 xenografts is significantly reduced in mice receiving AtzMab (20 mg/kg), AveMab (10 mg/kg), or DurMab (10 mg/kg) 24 h prior to radiotracer injection. Whole-body volume-rendered [⁶⁴Cu]WL12 PET-CT images of saline- (A) AtzMab- (B) AveMab- (C) and DurMab-treated (D) mice, and ex vivo biodistribution (E) at 2 h after [⁶⁴Cu]WL12 injection (n = 6–9/group). (F) IHC staining for PD-L1 in the corresponding tumor. Scale bars: 100 μm. Box-and-whisker graphs showing minimum to maximum and all data points, with the horizontal line representing the median. **** p < 0.0001; NS, not significant, by 1-way ANOVA and Dunnett’s multiple comparisons test in E (From [173]).