Tissue clearing for whole lung cellular imaging

While computed tomography (CT) offers noninvasive detection of tumour nodules in the lung of live animals (Fig. 1a), resolution limitations typically prevent accurate analysis of total tumour burden in the mouse. Drawing insight from optical clearing methods currently being used in brain imaging, we extended their application to pulmonary imaging. To accomplish this, we derived a clearing method from the CUBIC protocol26, substituting whole-animal perfusion for a right-ventricular perfusion and use of a shorter post-perfusion fixation time (Table 1). We also identified that samples can be imaged in CUBIC 1 in the lung at similar fidelity as with the index-matched CUBIC-2 solution (Supplementary Fig. 7). Importantly, this modified protocol applies intravenous administration of imaging probes to stain cell and tissue compartments of interest with high fidelity. For example, pre-injection of fluorophore-tagged lectin and macrophage-targeting NPs enabled visualization of vasculature and TAM, respectively, throughout the organ. Labelling TAM by pre-injection was superior to post-clearing antibody labelling because it removed the time consuming blocking and staining steps of antibody labelling. Penetration of antibodies in cleared or permeabilized tissue can be slow, requiring more than 7 days in the brain and likely longer in dense tumour tissue (a tumour contains 5–10 × more cells per mm3 than healthy brain tissue27,28).

Figure 1: Clearing of lung tissue allows visualization of tumour burden and other biologically relevant features. (a) CT scan of KP-tumour-bearing mouse and identification of large lung tumour (big arrow). (b–d) Process of clearing and imaging lungs and identification of small tumours (small arrows). (e) Wide-field image of whole lung from KP tumour-bearing animal. (f) × 4 slice of a tumour from box in e. (g) × 20-magnification imaging slice of a single tumour from box in f. (h) Computational 3D-rendering of a whole-lung tumour nodule. Scale bars, 5 mm (b); 1,000 μm (e,f); 100 μm (g,h). Full size image

Table 1 Effect of clearing protocol on affinity ligands. Full size table

To image pulmonary carcinoma, we applied the clearing and imaging technique in a lung adenocarcinoma model, in which tumour cells from a KRAS and p53 mutant mouse (KP) were injected intravenously29,30,31. This model of metastatic disease differs from primary lung cancers which develop in aged KP mice29. The clearing method revealed many more and smaller KP lung tumour nodules than found by conventional micro-CT (μCT) (Fig. 1b–d). Tumour cells and nodules were easily identified by fluorescence imaging upon staining with nuclear markers, such as DAPI or SYTO dyes, as tumours exhibited higher cellular density relative to healthy lung tissue (Supplementary Fig. 1d). In a comparison between DAPI and GFP-expressing KP tumours, we observed a Spearman’s rank correlation value of 0.95, indicating that both labelling procedures can be interchangeably used for tumour identification and segmentation. Other endogenous features could be imaged in cleared lungs, such as the biotin-rich airways with fluorophore-conjugated streptavidin32 (Supplementary Fig. 1e and Supplementary Movie 2) and collagen fibres with two-photon second-harmonic generation (Supplementary Fig. 1f). It is advantageous to use fluorochromes that bleach minimally and retain brightness through fixation and clearing. Several BODIPY, Alexa Fluor and cyanine analogues achieve this. Fluorescent proteins are sensitive to over-fixation and are only compatible with aqueous clearing methods (for example, sca/e, CUBIC and CLARITY).

After clearing, lung tissue was mounted in 2-mm-thick chambers (Supplementary Fig. 1a) and imaged using confocal microscopy, thereby rendering lungs transparent (Supplementary Fig. 10) and enabling complete observation of lung tumour burden at cellular resolution throughout the whole-tumour mass (Fig. 1e–g). Surveying the whole lung for measurement of tumour volumes and immune infiltrate was possible after reconstruction of a grid of × 2 image stacks (Fig. 1e). Finer detail on TAM localization and its relation to the tumour mass could then be ascertained at × 4 magnification (Fig. 1f), and cellular resolution could be obtained at × 10–20 magnification (Fig. 1g, × 20). Computationally rendering image stacks allowed visualization of tumours in three dimensions (Fig. 1h and Supplementary Movie 1, 1.7 mm3 tumour, × 10) so as to contextualize tumour, TAM and vascular architecture. We found that 2–6-mm-thick sample chambers were advantageous for high-resolution spot imaging, since a thin chamber allows the lobes to spread apart such that and any tumour in the chamber can be imaged with minimal distortion, scattering or absorption penalties through thicker tissues. Direct comparison of unrestricted and 2 mm chambers yielded similar results (Supplementary Fig. 9). While advantageous for moldable organs such as lung, intestine and pancreas, it would be more suitable to image slices of organs with more defined structure (kidney, brain and liver). Table 2 summarizes the different experimental steps and acquisition times required for pulmonary imaging at different resolutions. Finally, while it was ideal to image lungs immediately after clearing, they were also stored at 4 °C for several weeks with little loss of fidelity in imaging. Collectively, these data show that entire lungs can be surveyed and tumours imaged at cellular resolution within reasonable amounts of time.

Table 2 Overview of times required for different experiments steps. Full size table

Quantitative analysis of immune infiltration

Analysis of TAM content in the tumour stroma can yield strong prognostic13,33 and possibly therapeutic9 information. With this in mind, we sought to use the clearing method to visualize and quantify TAM invasion in individual tumours in whole lung tissue. Using GFP-labelled KP lung tumours and dextran NPs with avidity towards macrophage34, we found TAM to be associated with all tumour nodules investigated, at multiple stages of tumour progression. Figure 2 shows representative images of lungs cleared at 29 and 40 days after IV administration of 2.5 × 106 KP tumour cells. Interestingly, TAM could be observed at even the earliest stage of tumour formation (day 12) when only a few cancer cells were present (Fig. 2a), and substantial heterogeneity was evident in tumour size, anatomical positioning and immune infiltration at later time-points (Fig. 2b).

Figure 2: Detection and analysis of whole lung tumour burden. (a) Identification of TAM presence surrounding early-stage tumours. TAM infiltration is observed in response to 16 individual tumour cells within a single nascent nodule. Scale bars, 1,000 μm (top); 100 μm (middle/bottom). (b) Analysis of tumours in mice at two stages of disease progression revealing facile detection of tumours and a heterogeneous distribution of TAM and tumour location. Dashed lines outline the lung. Scale bars, 1,000 μm. For all, days denote time post inoculation. Full size image

Building on previous reports of macrophage-selective uptake of dextran-coated iron oxide NPs35,36, we performed histology (Fig. 3a,b), flow cytometry (Fig. 3c) and imaging subcutaneously implanted HT1080 tumours in a NOD-SCID MERTKGFP/+ fluorescent reporter mouse (Supplementary Fig. 2) model to verify that the macrophage-avid NPs accurately identified TAM upon i.v. injection. Immunohistochemistry (IHC) showed that the majority of CD68+ TAM had internalized fluorescent NPs (at a level detectable by IHC), and about half were alternatively activated M2-like macrophages (Fig. 3a,b). Neutrophils are also phagocytic myeloid cells that can take up NP35. In the KP flank tumour model 72±3% (n=12) of the NP+ signal is due to CD11b+ CD11c+ F4/80+ TAM, and the remainder due to other phagocytes. Flow cytometry indicated that NP-positive cells were predominantly CD11b+ CD11c+ F4/80+ Ly6C− and thus resembled TAM phenotypically (Fig. 3b). In cleared tumours grown in MERTKGFP/+ reporter mice, good co-localization was observed between the NP and GFP at × 10 magnification (R=0.89, Supplementary Fig. 2a). Computational single-cell segmentation was use for co-localization analysis of higher magnification images, and showed that 79% of GFP+ cells contained NP and 95% of NP-positive cells expressed GFP (Supplementary Fig. 2b). Thus, NP injection provides a convenient method to accurately identify TAM, and may represent a method for therapeutic drug delivery. For high-throughput quantification of cellular TAM levels, wide-field integrated fluorescence density of a series of tumours was computationally mapped to high-resolution images of the same series of tumours for automated cell segmentation and counting (Supplementary Fig. 3). A conversion factor between wide-field images and cell segmentation results was generated with a correlation coefficient of 0.9, P<0.0001 (two-tailed Student’s t-test). Using this relationship, fluorescence density in other wide-field images was then used to infer cellular TAM density.

Figure 3: Identification and quantification of TAM infiltration. (a) IHC on formalin-fixed KP tumour sections, staining for CD68 and CD206 macrophage markers. Scale bar, 10 μm. (b) Analysis of NP+ cells by IHC for CD68 and CD206 (n=3 images). (c) NP was found in TAM (CD11b+ CD11c+ F4/80+ Ly6C−), whereas the NP did not accumulate in tumour cells (RFP). (d) Average TAM density in KP, KP-GFP and LLC tumour models as calculated from imaging (KP, n=158; KP-GFP, n=38; LLC, n=6; ***P=0.0003; ****P<.0001; one-way ANOVA). (e) Tumours plotted by size and TAM infiltrate for one mouse (top) and in relation to 20 other mice (bottom) to show range of tumour size and TAM infiltration. Scale bars, 10 μm. ANOVA, analysis of variance. Full size image

With a method to visually identify and measure tumour cells and TAM, we next sought to apply the analysis over many tumours and animals to obtain a more complete understanding of TAM heterogeneity in lung adenocarcinoma. The number and volume of pulmonary tumours in a given mouse largely depended on the time elapsed since tumour inoculation. Four weeks post inoculation (day 29), the average number of pulmonary metastases was 44 and ranged from 29 to 57. To expand the analyses, we investigated several hundred tumour nodules in 21 different mice (Fig. 3e). For example, in a given KP mouse, the average TAM density was 17,000 TAM mm−3 within a tumour, but this varied sevenfold among tumours of a similar size. In other words, across 1 mm3 tumours, TAM density varied from 8,000 to 60,000 in other similarly sized nodules. No discernible pattern was found in anatomic location or vascular features that predicted TAM density. We extended this analysis to a Lewis lung carcinoma model37 and GFP-expressing KP model. In both of these models, the TAM density in tumours was slightly higher (Lewis lung cell carcinoma (LLC): 43,000 TAM mm−3 tumour P<0.0001; KP-GFP: 21,000 TAM mm−3 tumour P=0.0001; one-way analysis of variance) than in the non-GFP KP model (Fig. 3d). In sum, these data show the variability of host-cell infiltration across pulmonary tumours within the same animal and across animals. Notably, no single lesion was devoid of innate immune cells.

PLX3397 reduces tumour burden but not TAM density

The innate immune composition of the tumour microenvironment has emerged as an attractive therapeutic target and efforts are underway to modulate TAM numbers or molecular phenotypes to control cancer progression9. The presence of TAM can be essential for the efficacy of nanotherapeutics31,35 and the heterogeneity of TAM infiltrates among tumours may play a key role in varying response to therapy38. With respect to the latter, colony-stimulating factor receptor (CSF-1R) inhibitors have emerged as an attractive modulation method. Experimental CSF-1R blockade has been shown to result in altered TAM recruitment or M1/M2 polarization and lower tumour burden1,39. Some CSF-1R inhibitors are now progressing in clinical trials, which led us to investigate the effect of the CSF-1R and cKit inhibitor PLX3397 (refs 10, 40, 41) in the KP model. KP1.9 cells lack CSF-1R (Supplementary Fig. 8). Furthermore, PLX3397 was not toxic to KP1.9 cells nor RAW 264.7 cells at concentrations tested. To assess PLX3397 effects on TAM in vivo, tumours were grown for 21 days and mice were then treated with 30 mg kg−1 PLX3397 i.p. for 7 days. Lungs were then prepared for imaging.

Figure 4 summarizes the results of CSF-1R treatment. The lungs of mice treated with PLX3397 had a much lower tumour burden than lungs in the control group (Fig. 4d): the pulmonary tumour volume in the treatment group was ∼6 mm3, whereas it was ∼93 mm3 in the control group (Fig. 4a, n=3 per group, P=0.015; unpaired t-test). Correlating tumour volume with TAM density for all tumour nodules (Fig. 4b) revealed that PLX3397 treatment significantly reduced individual tumour size (n=423, P<0.0001; unpaired t-test); however the average TAM density among tumours remained unchanged from the 16,500 TAM mm−3 observed in the untreated cohort (Fig. 4b,c, Supplementary Fig. 2b). Nonetheless, further spatial analyses by imaging individual tumour cross-sections (Fig. 4e) revealed that TAM in PLX3397-treated animals showed a distinct spatial distribution. In untreated mice, TAM density was highest in the tumour periphery as shown in cross-sectional TAM density profiles (Fig. 4f) averaged from of images through the centre of the tumour. In treated animals, TAM were instead more abundant at the centre of the tumour nodules (Fig. 4g, n=28, P=0.025; unpaired t-test), likely reflecting a response to tumour cell death and repair. These data indicate that CSF-1R inhibitors can effectively control lung cancer progression without affecting TAM density in whole tumours, but can profoundly alter TAM spatial distribution within lesions and/or their polar phenotype41,42,43,44.

Figure 4: PLX3397 monotherapy decreases tumour burden and alters TAM density and infiltration. (a) Reduced tumour burden in PLX3397 (PLX) treated mice relative to untreated (NT) (n=6, P=.015; unpaired t-test). Bars represent total tumour volume with number of identified tumours indicated above each bar. (b) Plot of TAM density against tumour volume, showing PLX3397-treatment resulted in significantly smaller tumour nodules (n=423, P<.0001; unpaired t-test) (c) Data from b arranged to compare TAM densities in tumours from untreated and PLX3397-treated mice. (d) Representative images of lungs from untreated and PLX3397-treated lungs before tissue clearing (compare to a and b). Scale bar, 5 mm. (e) Representative images of treated and untreated tumours illustrate differences in TAM invasion. Scale bar, 1,000 μm. (f) NP fluorescence intensity corresponding to linear regions of interest placed across treated and untreated tumours, generating TAM intensity profiles. Tumours were normalized by size and plotted as a function of NP signal. (g) TAM localization was significantly altered within individual nodules. PLX3397-treated tumours have a greater ratio of NP signal in the tumour core relative to the rim (n=14 for each group, P=.025, 40–60% across tumour/0–10%+90–100%; unpaired t-test). Full size image

Nanoparticle based drug delivery to tumours

Prior research has shown that nanoencapsulated chemotherapeutics accumulate in cancers via the enhanced permeability and retention effect and can thus potentiate efficacy, while minimizing systemic toxicities31,35,45. Less clear, however, is how heterogeneous drug delivery manifests in metastatic contexts, and what governs such heterogeneity. To demonstrate the feasibility of imaging drug delivery with the clearing method, we administered dually labelled taxane-encapsulated polymeric nanoparticles to KP-bearing animals. Using a polymeric nano-formulation scheme previously optimized for intravital imaging31, near-infrared labelled docetaxel46 was encapsulated into a red-fluorescent polymeric micelle comprising the block co-polymer poly(lactic-co-glycolic acid)-b-polyethyleneglycol (PLGA-b-PEG) and the co-encapsulated fluorescent PLGA-BODIPY-TMR. Drug-loaded NPs were intravenously injected 18 h before killing. Figure 5 summarizes some of the results showing that taxane was present in each of the pulmonary metastases. Quite remarkably, certain metastases showed much higher accumulation, correlating well with TAM density (Fig. 5b,c). Furthermore, our data show that there was a tight correlation between PLGA-PEG and taxane delivery (R2= 0.94; Supplementary Fig. 6c). Previous efforts have demonstrated that TAM depletion decreases the efficacy of nanoparticle-based therapy, emphasizing the potential for TAM to serve as drug depots31.