1.

Introduction

The incidence of malignant melanoma has been increasing rapidly worldwide in the last few decades.¹ Despite significant improvements in diagnosis, surgical techniques, general patient care, and local and systemic adjuvant therapies, the most fearsome aspect of cancer is that most deaths are due to metastasis.^2,3 Currently, the model of pulmonary melanoma metastasis in C57BL/6 mice has been used more and more to study the process of metastasis and to screen novel anti-metastatic drugs as this cancer can be examined over a relatively short period.^4–7 However, the biological heterogeneity of cancer cells in the primary neoplasm and metastases and the modification response of a metastatic tumor cell to systemic therapy in the specific organ microenvironment are the main barriers to the treatment of metastases. This reveals that understanding the process of metastasis on the systemic, cellular and molecular levels are the pressing goals of cancer research.^2,8–10

Many methods, such as biochemical,^11,12 cell biology^13,14 and statistical macroscopy,^7,15 are classified according to different monitored objectives and have been employed to inspect the physiological changes of pulmonary melanoma metastasis for studying the process of metastasis and evaluating the drug effects. However, these methods can’t provide high spatial resolution of the pulmonary tissue. Histological examination is the gold standard for cancer diagnosis as it can reveal tissue and cellular morphologic features with submicron spatial resolution to identify the pathologic stages of the cancer tissue. Nonetheless, the procedure of histological biopsy is both invasive and time-consuming as it requires hematoxylin and eosin (HE) stain and physical sectioning. Therefore, new techniques that not only provide high spatial resolution but also monitor the physiological changes of pulmonary melanoma metastasis without complicated sample processing are urgently needed.

Nonlinear optical microscopy (NOM) based on multiphoton absorption and second harmonic generation (SHG) has been widely employed to study the structure and function of cells and tissues due to its unique features of submicron resolution, greater penetration depth, low photo-damage and inherent optical sectioning ability.¹⁶ In particular, NOM can provide the visualization of cellular and subcellular structures using plentiful intrinsic chromophores without any pretreatment for the tissue.¹⁷ Intracellular nicotinamide adenine dinucleotide (NADH), triphosphopyridine nucleotide (NADPH) and flavin adenine dinucleotide (FAD) can take part in cellular energy metabolism and induce multiphoton autofluorescence (MAF), shedding light on associated carcinogenesis.^18,19 In addition, SHG signals arising from collagen fibers can reveal the remodeling of the extracellular matrix (ECM) in the tissue.^20,21 SHG imaging can evaluate strategies for altering the aging, atherosclerosis and tumor effectively.^22–24 In a recent study, it has been demonstrated that the diagnosis based on the morphologic features obtained by NOM agreed with histological examination for 88.6% of the specimens.²⁵

Unfortunately, to the best of our knowledge, NOM has not been employed in the research of pulmonary melanoma metastasis to monitor the physiological changes of pulmonary tissue during the whole process of colonization, which is the one of two important steps of metastasis.⁸ In addition, although qualitative differences in morphologic features and quantitative measurement of the MAF and SHG tissue images are feasible enough to evaluate the pathologic stages of the cancer tissue,^26–28 special challenges remain for NOM to study the process of pulmonary melanoma metastasis. First, the diameter of intact pulmonary metastasis melanoma nodules in C57BL/6 mice is usually several millimeters in size in the middle and late stages. Conventional NOM cannot provide morphologic features of such a large region with high resolution due to the limited field of view of hundreds of square microns. Second, accuracy of the quantitative analysis of the tissue is important to evaluate the pathological states. However, it requires large area imaging rather than imaging of a small portion of the tumor tissue.

We report here on monitoring the process of pulmonary melanoma metastasis ex vivo using a home-built large area nonlinear optical microscope (LA-NOM) and intrinsic fluorophores in C57BL/6 mice. Lung tissue at different time points after a tail vein injection of cancer cells are characterized by MAF and SHG imaging in a volume of $\sim 2.2\mathrm{mm}\times 2.2\mathrm{mm}\times 30\mathrm{\mu m}$. Combined with the morphological analysis of MAF and SHG images, quantitative analysis by the MAF and SHG intensity ratio (MAFIR and SHGIR) between pathological tissue and normal tissue, and the MAF to SHG index (MAFSI) are employed to evaluate physiological changes of pulmonary melanoma metastasis. Our results demonstrate that LA-NOM succeeds in evaluating the pathological changes of pulmonary melanoma metastasis in C57BL/6 mice.

2.

Materials and Methods

2.2.

Imaging Instrumentation and Protocol

Combined MAF and SHG imaging was performed on the home-built LA-NOM in this study, as shown in Fig. 1. Ti:Sapphire laser (Maitai BB, Spectra-Physics) was used as the excitation source ($\text{pulse duration}:\sim 100\mathrm{fs}$, repetition rate: 80 MHz and tunable range: 710 to 980 nm). The excitation beam was scanned by two perpendicular galvanometer mirrors (Model 6215, Cambridge Technology). Serial images were obtained by translating the specimen using a sample translation stage (ES111, Prior Scientific) after each optical scanning imaging and combined into a large area imaging section. Axial scanning was achieved by a piezoelectric stage (P-563.3CD, Physik Instrumente). After splitting from the excitation laser by a long wave pass dichroic mirror (FF665, Semrock) and through a short wave pass emission filter (FF680/SP, Semrock), the autofluorescence and SHG signals were separated into two simultaneous detection channels by a dichroic mirror (FF409, Semrock). Two filters ($380/14\mathrm{nm}$ and $485/70\mathrm{nm}$, Semrock) and PMTs (H7422-40 and H7421-40, Hamamastu) were used to detect SHG and autofluorescence, respectively.

Fig. 1

Setup of large area nonlinear optical microscopy. ND: neutral density filter; D: diaphragm; DCM: dichroic mirror; SP: short-pass filter; F: band-pass filter; O: objective lens; PZT stage: piezoelectric stage; PMT: photomultiplier tube.

The specimens were placed into a home-built chamber, which was specially tailored for LA-NOM to image the fresh tissue. A two-photon excitation laser light (wavelength of 760 nm) was used for LA-NOM imaging of the lung specimens. The excitation beam was focused and the emitted signals were collected through a low magnification apochromat objective (UPLSAPO $20\times /0.75\mathrm{NA}$, Olympus) to achieve a large field of view and high spatial resolution. The lateral and axial resolution was 0.9 μm and 2.1 μm, respectively. The imaging area of each section was $\sim 2.2\mathrm{mm}\times 2\mathrm{mm}$ composed of $13\times 13$ small area optical scanning images with $200\mathrm{\mu m}\times 200\mathrm{\mu m}$ ($256\times 256\text{pixels}$). The dwell time per pixel was 24 μs and the time per small optical scanning image was 1.6 s. The axial image stacks were generated using a 2 μm step size. For each specimen, three image stacks were acquired at different regions. Six image stacks were obtained at each time point and a total of 60 image stacks were achieved in this study. To perform the quantitative comparison, all of the specimens were imaged with the same average power of 7.8 mW. All imaging was completed within four hours after the animal sacrifice.

3.

Results

3.1.

Morphological Analysis

Large-area and high-resolution MAF, SHG and merged MAF and SHG images of normal C57BL/6 mice pulmonary tissue are shown in the first row of Fig. 2(a)–2(c). The imaging depth is 2 μm below the lung tissue surface. The magnified views of marked areas in Fig. 2(a)–2(c) are shown in Fig. 2(d)–2(f), respectively. Morphologically, observation from MAF images in the first row of Fig. 2(a) and 2(d) shows that alveoluses have uniform structure and are evenly distributed in the normal tissue. As illustrated in the first row of Fig. 2(b) and 2(c), collagen fibers are continuously distributed with high density in the normal tissue. In addition, image-merged MAF and SHG in the first row of Fig. 2(f) shows that the collagen fibers are round in the vicinity of the alveoli regularly in the normal tissue.

Fig. 2

MAF and SHG imaging for normal pulmonary tissue and pathological pulmonary tissue of C57BL6 mice on the time of days 3, 10, 15, 25 after tail vein injection. (a)–(c) are MAF, SHG and merged MAF and SHG large area images ($2.2\mathrm{mm}\times 2.2\mathrm{mm}$). The arrows indicate the intact nodules. Scale bar is 400 μm. (d)–(f) are magnified views of marked areas in (a)–(c), respectively. The magnified MAF images reveal that the uniform structure of alveolus has been destroyed gradually and cancer cells appeared after day 15, while the continuous collagen have been ruptured into point-point distribution in the pulmonary metastasis nodules. The arrowheads show cancer cells. Scale bar is 40 μm. (g) HE images of pulmonary tissue at different time points. Scale bar is 40 μm.

Unlike in the normal tissue, the morphologic features of pathological tissue become disorderly with the time-lapse after tail vein injection. The representative results of day 3, day 10, day 15, and day 25 are also shown in Fig. 2. As illustrated in Fig. 2, the feature of lung tissue at day 3 is similar with the normal tissue, except the low intensity of the MAF and SHG. After day 10, the small nodules appear in the lung tissue, while the profile of alveolus becomes blurry and the collagen fibers become discontinuous. Particularly after day 15, the cancer cells are clearly observed in the MAF image, as indicated by the arrowheads in Fig. 2. MAF and SHG images of intact nodules are shown by the arrows, especially at day 25, which reveals that the structures of alveolus are disappeared and the collagen fibers ruptured into point-point distribution in the pulmonary metastasis nodules.

In order to validate the MAF and SHG imaging, HE images at different time points are also shown in the Fig. 2. Compared with normal tissue, the alveolar units disrupt in early stage and disappear in the late stage. At day 10, the cancer cells can be easily distinguished from normal cells for their large and anomalous nuclei. With the time elapsed, the volume of cancer cell nuclei increase rapidly, especially in the late stage. At day 25, the cancer cell nuclei are much larger than the normal cell nuclei and take up the major space of tissue. In addition, the normal lung tissue is abundant in collagen fiber, while the metastasis tissues are rich in vessels and cancer cell nuclei.

3.2.

Quantitative Analysis

The process of the pulmonary melanoma metastasis reflected by morphologic feature can also be quantified. The MAFIR and SHGIR of pathological tissue and normal tissue are shown in the Fig. 3. Combined with Fig. 2, three stages are divided by the time points of nodules appearing in microscope and being macroscopical. As illustrated in Fig. 3, both of the MAF and SHG intensity decrease at early stage from day 0 to day 7. The MAF intensity increases in the middle stage from day 10 to day 15 and decreases again in late stage after day 15, while the SHG intensity reduces to and maintains in a certain level after day 10. The two-tailed student’s $t$-test is performed on the MAFIR and SHGIR matrixs ($n=6$) at different stages, as shown in Fig. 3. The MAFIRs have significant difference, while the SHGIRs cannot be distinguished between each other in each stage. Nevertheless, the results demonstrate that MAFIR provided by LA-NOM can succeed in monitoring the process of the metastasis.

Fig. 3

MAFIR and SHGIR of pathological pulmonary tissue at different time points. All the MAF and SHG intensity in imaging volume of $2.2\mathrm{mm}\times 2.2\mathrm{mm}\times 30\mathrm{\mu m}$ at different time points were normalized according to the intensity of normal pulmonary tissue. $n=6$; error bars indicate standard deviation; asterisk, $P<0.05$ double asterisk, $P<0.01$ calculated using a two-tailed student’s $t$-test for the MAFIR and SHGIR in early (days 3, 5, and 7), middle (days 10, 12, and 15, marked by shadow rectangle) and late (days 18, 20, and 25) stages, respectively.

Layer-resolved MAFSI as a function of depth for the specimens excised at different time points are shown in Fig. 4. The markers represent mean of MAFSI data and the curves are the fitting results. The results reveal that both the surface of normal tissue and pathological tissue are rich in collagen fibers and the density of the collagen fiber decreases with the depth in the tissue. The results of $t$-test shown in Fig. 4(a) reveal that MAFSI can be effectively employed to monitor the pathologic stages of lung tissue in early stage without nodules. However, in the middle stage (from day 10 to 15), the MAFSIs have no significant difference at any depth. After day 15, MAFSIs decrease in the tissue surface, but maintain a certain value at depth below 20 μm. The MAFSIs have significant difference at depth of $0\sim 8\mathrm{\mu m}$, which can be used to monitor the physiological changes of pulmonary melanoma metastasis in late stage.

Fig. 4

Layer-resolved MAFSI as a function of depth in normal pulmonary tissue and pathological pulmonary tissue. A two-tailed student’s $t$-test is performed on the MAFSI matrix ($n=6$) at each depth point between different time points. (a)–(c) The MAFSI versus depth in early stage (days 0, 3, 5, and 7), middle stage (days 10, 12, and 15) and late stage (days 18, 20, and 25). The shadow rectangles in (a) and (c) indicate that the curves can be significantly distinguished by the $P$ value of $t$-test at special depth in the tissue. Error bars indicate standard error of mean; asterisk, $P<0.05$ double asterisk, $P<0.01$ triple asterisk, $P<0.001$.

4.

Discussion

The process of cancer metastasis consists of a long series of sequential and interrelated steps: tumor cells detach from the primary tumor, intravasate into the blood vessels or lymphatics, circulate in the body, adhere to vessel wall of distant organs, extravasate vessels, establish a new microenvironment and proliferate at the new site.² It has been demonstrated that degradation of collagen in ECM can promote invasion and metastasis of cancer cells.²⁹ With the malignant melanoma cells metastasizing into lung tissue, the ECM will be remodeled resulting in the transformation of density and distribution of collagen fibers,^18,23,30 which leads to the SHGIR decrease as shown in Fig. 3. The reduction of MAFIR from day 3 to day 7 in Fig. 3 may be induced by the decrease of the normal cells in the tissue, which is also revealed by the HE images from day 3 to day 7. At the middle stage, the proliferation of cancer cells and imposing metabolic stress of the tissue—which are enhanced by the remodeled tissue structure, growth factors released by tissue stroma and no pressure from the surrounding microenvironment—lead to the MAFRI rising from day 10 to day 15.^9,31 Eventually, unconstrained proliferation of cancer cell without migration results in large nodules within a “capsule” of ECM, which can induce the cell apoptosis due to the limited availability of nutrients and oxygen.^9,32 It has been demonstrated that excessive proliferative signaling can also trigger cell senescence and/or apoptosis.^33–35 In addition, the large nucleus of the cancer cell colonizing in the lung tissue cannot provide MAF, which is another reason of MAFRI reduction in later staged after day 18. According to the definition of MAFSI, the inflection point of each curve in Fig. 4 reveals that the density of collagen fibers at the depth of $\sim 2\mathrm{\mu m}$ is much higher than that at any other depth. In Fig. 4(a)–4(c), the changes of MAFSIs versus time, especially in the tissue surface, are primarily induced by the cooperation of MAF and SHG intensity discussed above.

In order to achieve large area images, the specimens were pressed lightly by a cover slip in the chamber. Our results reveal that this treatment has little influence on the morphologic features of lung tissue. Furthermore, quantitative parameters mentioned above can effectively eliminate this influence, mostly because MAFIR (SHGIR) is calculated using the MAF (SHG) intensity of the whole images stack and MAFSI represents the relative density of cellular chromophores and collagen fibers in each imaging section.

The imaging depth of NOM depends on the tissue properties of absorption and scattering, the excitation wavelength, the excitation laser power on the tissue, and the MAF and SHG signals-detection efficiency.³⁶ Generally, the imaging depth of NOM can be up to 100 micrometers in the fresh lung tissue.^21,37 In our study, we used the excitation wavelength of 760 nm, which is the optimal excitation wavelength for NAD(P)H and FAD.³⁸ Non-descanned detection, the most efficient fluorescence collection scheme,³⁹ and GaAsP photocathode PMT with high quantum efficiency ($\sim 42\%$ QE at peaking wavelength) used in the home-built system can provide high MAF and SHG signals-detection efficiency. Although, the detailed tissue structural information degrade with the increasing imaging depth, our home-built LA-NOM can allow for imaging depth of $\sim 120\mathrm{\mu m}$ in the lung tissue. However, the density of collagen fibers decreases with the depth and maintains a low level in deep lung tissue below 20 μm. Therefore, the MAF and SHG images were only obtained up to 30 μm below the tissue surface in this study.

In the middle and late stage of cancer, the macroscopic nodules can be easily discriminated from the lung tissue and its number and volume also can reflect the process of cancer. However, there is no nodule in the early stage of cancer. The physiological changes of the tissue should be evaluated during the whole process of pulmonary melanoma metastasis, especially during the early stage of cancer.^2,8,10 In addition, metastasis is a cell- and tissue-driven process, for which cancer cells and ECM interact and react throughout the progression of the disease.⁹ Therefore, monitoring the progress of pulmonary melanoma metastasis by label-free imaging with submicron spatial resolution is of significance.

For monitoring the process of metastasis, in vivo imaging that can eliminate the individual differences between the mice induced by the intrinsic properties of the tumor cells and responses of the host² can show more natural information than ex vivo imaging. Two techniques can achieve in vivo imaging with subcellular resolution; video-rate microscopy combined with a special window chamber and endoscopy.^37,40–42 Nevertheless, to apply these new methods to diagnosis and therapy, understanding the process of metastasis at the cellular level by using conventional full-format microscope is absolutely a prerequisite. The pilot study is helpful for the future in vivo applications of those new methods, such as endoscopy.

5.

Conclusion

In summary, we achieved label-free monitoring the progress of pulmonary melanoma metastasis of C57BL/6 mice ex vivo by LA-NOM. Microscopic morphologic changes during the process of pulmonary melanoma metastasis were depicted by MAF and SHG images at different time points. In addition, quantitative parameters, such as MAFRI, SHGRI, and MAFSI were used to quantify the pathological changes of pulmonary melanoma metastasis based on MAF and SHG intensity, especially in early and late stage after tail vein injection. Combining morphological analysis and quantitative analysis of the tissue, our results demonstrate that LA-NOM can be used to monitor the process of pulmonary melanoma metastasis, which indicates that LA-NOM can provide a powerful tool for the research in tumor pathophysiology and therapy evaluation.