www.nature.com/scientificreports

OPEN

Received: 23 March 2017
Accepted: 21 July 2017
Published: xx xx xxxx

CUBIC pathology: threedimensional imaging forpathological diagnosis
Satoshi Nojima1,2, Etsuo A. Susaki3,4,5, Kyotaro Yoshida6, Hiroyoshi Takemoto7, Naoto
Tsujimura7, Shohei Iijima8, Ko Takachi7, Yujiro Nakahara7, Shinichiro Tahara1, Kenji Ohshima1,
Masako Kurashige1, Yumiko Hori1, Naoki Wada1, Jun-ichiro Ikeda1, Atsushi Kumanogoh2,9,Eiichi Morii1 & Hiroki R. Ueda3,4
The examination of hematoxylin and eosin (H&E)-stained tissues on glass slides by conventional lightmicroscopy is the foundation for histopathological diagnosis. However, this conventional method hassome limitations in x-y axes due to its relatively narrow range of observation area and in z-axis due to
its two-dimensionality. In this study, we applied a CUBIC pipeline, which is the most powerful tissueclearing and three-dimensional (3D)-imaging technique, to clinical pathology. CUBIC was applicable
to 3D imaging of both normal and abnormal patient-derived, human lung and lymph node tissues.
Notably, the combination of deparaffinization and CUBIC enabled 3D imaging of specimens derived
from paraffin-embedded tissue blocks, allowing quantitative evaluation of nuclear and structural atypiaof an archival malignant lymphoma tissue. Furthermore, to examine whether CUBIC can be applied topractical use in pathological diagnosis, we performed a histopathological screening of a lymph nodemetastasis based on CUBIC, which successfully improved the sensitivity in detecting minor metastatic
carcinoma nodules in lymph nodes. Collectively, our results indicate that CUBIC significantly contributes
to retrospective and prospective clinicopathological diagnosis, which might lead to the establishmentof a novel field of medical science based on 3D histopathology.
Hematoxylin and eosin (H&E) staining, together with other assistive techniques such as immunohistochemistry
or in situ hybridization, is the foundation for histopathological diagnosis. Pathologists examine stained tissue
preparations with bright-field microscopy to estimate various types of histological and pathological findings suchas cell malignancy, degree of inflammation and fibrosis, depth of tumor invasion, presence of tumor components
in the cut margin, and lymph node metastasis status. Although these conventional methods provide plenty of
information about morphologic changes of cells and tissues, they also have fundamental limitations. For instance,
the conventional methods can provide only planar 2-dimentional (2D) images, limiting their ability to observe
3-dimentional (3D) structures consisting of a variety of cells in diverse anatomical structures. In addition, particularly in a histopathological diagnosis for large pathological specimens such as surgically resected whole organ
specimens, only representative lesions identified by a macroscopic observation are typically evaluated. Therefore,
a concern that an additional critical lesion may be present in the non-evaluated areas still remains to be addressed.

1

Department of Pathology, Graduate School of Medicine, Osaka University, 2-2 Yamadaoka, Suita, Osaka, 5650871, Japan. 2Department of Immunopathology, WPI Immunology Frontier Research Center, Osaka University, 3-1
Yamadaoka, Suita, Osaka, 565-0871, Japan. 3Department of Systems Pharmacology, Graduate School of Medicine,
The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan. 4Laboratory for Synthetic Biology,
RIKEN Quantitative Biology Center, 1-3 Yamadaoka, Suita, Osaka, 565-0871, Japan. 5PRESTO, Japan Science andTechnology Agency (JST), 4-1-8 Honcho, Kawaguchi, Saitama, 332-0012, Japan. 6Department of Pathology, Kinki
Central Hospital, 3-1 Kurumazuka, Itami, Hyogo, 664-8533, Japan. 7Department of Surgery, Kinki Central Hospital,
3-1 Kurumazuka, Itami, Hyogo, 664-8533, Japan. 8Department of Nutrition Oncology, Osaka International Cancer
Institute, 3-1-69, Otemae, Chuo-ku, Osaka-shi, Osaka, 541-8567, Japan. 9Department of Respiratory Medicine,
Allergy and Rheumatic Disease, Graduate School of Medicine, Osaka University, 2-2 Yamadaoka, Suita, Osaka, 5650871, Japan. Correspondence and requests for materials should be addressed to E.M. (email: morii@molpath.med.
osaka-u.ac.jp) or H.R.U. (email: uedah-tky@umin.ac.jp)
Scientific Reports | 7: 9269 | DOI:10.1038/s41598-017-09117-01

www.nature.com/scientificreports/
To enable more comprehensive and efficient pathological diagnosis, there have been efforts to serially section
and image relatively large samples, followed by the reconstruction of 3D images. Early cases of such efforts were
performed in the late 1960s and 1970s, in which gross images were matched with corresponding histologicalsections of 6–8 μm-thickness1–3. Today, it is possible to generate reconstructed 3D images by computer-processed
imaging of serially sectioned tissue, which enables 3D histopathological observation of lesions, such as breast
carcinoma, in biopsy specimens4–7. However, this section-based method does not enable perfectly continuous
observation of tissues structures due to its inevitable discontinuity caused by tissue sectioning, although it enables
the observation of the rough structure of lesions, such as tumor volume, branches of tumor nodule, and presenceor absence of lumina inside tumors7. Moreover, to obtain such reconstructed 3D images by this method, hundreds of glass slides from serially sectioned tissues are needed, which is a high cost and labor-intensive process.
On the other hand, remarkable advances have been recently made in tissue-clearing techniques8–24. Thesecan be classified by (1) hydrophobic reagents, (2) hydrophilic reagents, or (3) hydrogel-based methods, and havedifferent characteristics8, 25. These techniques make an organ transparent so that light can illuminate cells deep inthe tissues. Therefore, it enables the acquisition of volumetric images with various optical microscopies such asconfocal fluorescence microscopy, multiphoton fluorescence microscopy, and light-sheet fluorescence microscopy (LSFM).
The advantages of such tissue-clearing and 3D-imaging techniques have been probed in a several pathological studies. For example, the change of islets’ volume and number in a 3D image of a whole pancreas fromstreptozotocin-induced diabetic mouse has been quantitatively evaluated9. 3D imaging also enabled quantification of abnormal ladder-shaped structures formed by neurites in a human autism patient14. More recently,
quantitative analyses of β-amyloid plaque distribution, structure, heterogeneity, and spatial relationship with glial
cells and vessels were performed in the brains of a mouse model and human patients of Alzheimer’s disease11, 16.
Other groups also demonstrated the advantages of 3D observation with normal and patient-derived tissues16, 26–31.
For more practical use in clinical pathology, compatibility with paraffin-embedding or H&E staining were also
tested27, 32, 33. Despite these potential applications, the emerging tissue-clearing and 3D-imaging techniques havebeen applied to only a small number of pathological samples, and there are no reports demonstrating that thetechniques practically contribute to the improvement of sensitivity and/or specificity of clinicopathological examination, particularly in a comprehensive study using a large number of pathological samples.
To validate the applicability of these techniques to 3D clinical diagnostic pathology, we applied the Clear,
Unobstructed Brain/Body Imaging Cocktails and Computational analysis (CUBIC) pipeline to human organs
and evaluated its efficacy on pathological specimens. CUBIC is a hydrophilic tissue-clearing and 3D-imaging
technique, which offers rapid and high-performance whole-organ and whole-body 3D imaging9, 34. Its usefulness
in deep and comprehensive imaging of murine organs including brain, heart, and liver has been already evaluated by several groups35–37. In fact, we demonstrate, in this study, that the current version of CUBIC protocol
efficiently cleared human lung and lymph node tissues, whose detailed structures such as bronchi, vasculature,or lymphoid follicles were successfully visualized in 3D. CUBIC was also applicable to specimens derived fromparaffin-embedded tissue blocks. This method enabled the evaluation of nuclear and structural atypia of a malignant lymphoma tissue prepared from an archival paraffin-embedded tissue block. In addition, the CUBIC-based
screening of lymph node metastasis improved the sensitivity for detection of metastatic carcinoma nodules inlymph nodes. Thus, CUBIC significantly contributes to both retrospective and prospective clinicopathologicaldiagnosis. We also note that CUBIC did not impair a routine pathological examination because conventional
H&E evaluation was successfully performed even after tissue clearing by CUBIC. These results suggest thattissue-clearing and 3D-imaging techniques can expand the coverage of standard histopathological examinationfrom 2D to 3D as well as from a limited area to a wider region, and hence potentially contribute to more accurate
clinical diagnosis.

Results

Tissue clearing of various human organs with CUBIC. We first tested the compatibility of the firstversion of the CUBIC protocol9, 34, 38 for various human organs. 2–5 mm-thick tissue blocks cut out from formaldehyde-fixed human brains, hearts, lungs, livers, kidneys, spleens, intestines, and lymph nodes were subjected
to tissue-clearing procedure according to the protocol described in the original paper (Fig. 1a)34. Among theseorgans, lung and lymph node tissues were significantly cleared with the efficiency comparable to that of mouseorgans (Fig. 1b). Furthermore, these cleared tissues can be subjected to paraffin-embedding, sectioning, andH&E staining without any problems after the release from CUBIC clearing by PBS wash. Images of the H&Estained sections indicated that the CUBIC clearing caused only negligible, if any, degeneration of the tissues(Fig. 1b and Supplementary Fig. 1), suggesting that application of CUBIC to the pathological specimens does notlead to any disadvantages for the subsequent H&E staining, which is required in routine pathological diagnosis
in hospitals. In addition, tissue clearing with CUBIC preserved the antigenicity of some of diagnostic markers
such as Cytokeratin, α-SMA, CD68, CD79a and CD3 in these tissues (Fig. 1c), suggesting that pathologists may
perform immunohistochemistry for accurate diagnosis even after tissue clearing with CUBIC. These results are
consistent with a previous study using CUBIC-cleared murine mammary gland tissues39. Taken together, the
CUBIC clearing protocol can be applied to some human tissues without any disadvantages for routine proceduresof histopathological examination. On the other hand, the first version of CUBIC reagents did not completely clear
a human brain, heart, liver, kidney, spleen, and intestine as efficiently as lungs and lymph nodes (Supplementary
Fig. 1). Although it was reported that CUBIC reagents enable efficient decolorization of endogenous chromophores (e.g., heme) inside murine tissues9, endogenous chromophores in human heart, liver, and spleen were notcompletely decolorized. The issue in tissue-clearing performance for these tissues will be addressed in future studies to update CUBIC reagents with more efficient clearing capability. In the following experiments of this study,
we primarily used lung and lymph node to test the further feasibility of 3D pathology with CUBIC.
Scientific Reports | 7: 9269 | DOI:10.1038/s41598-017-09117-02

www.nature.com/scientificreports/

Figure 1. Tissue clearing of various human organs with CUBIC. (a) Schematic diagram of clearing protocol
for human organs. IHC, immunohistochemistry. (b) Gross and microscopic images of human or mouse lungand lymph nodes. After gross image acquisition at the indicated time points, lung and lymph node tissues were
washed with PBS, followed by paraffin embedding, sectioning, and H&E staining. (c) Representative imagesof immunohistochemistry of human lung and lymph node tissues after clearing by CUBIC. Serial sections
prepared from lung or lymph node tissues which were histologically evaluated in (b) were immunostainedwith anti-cytokeratin (epithelial cell marker), anti-α-SMA (smooth muscle cell marker), or anti-CD68(monocyte/macrophage marker) antibodies (lungs), or immunostained with anti-CD79a (B-cell marker),
anti-CD3 (T-cell marker), or anti-CD68 (monocyte/macrophage marker) antibodies (lymph nodes). DAB,
3,3′-diaminobenzidine.

3D imaging of various human organs with CUBIC. Next, we tested whether the 3D imaging can be
performed on cleared normal human tissues. First, we cleared tissue blocks of human lung based on the CUBIC
clearing protocol (Fig. 2a). We then performed immunostaining with an anti-α-smooth muscle actin (α-SMA)
antibody and counterstaining of cell nuclei with a cell-permeable green-fluorescent nucleic acid stain SYTO 16(Fig. 2a). We imaged the cleared and stained lung samples by confocal microscopy and LSFM. As shown in Fig. 2b
and Supplementary Movie 1, reconstructed 3D images obtained by confocal microscopy successfully visualized
detailed 3D tissue structures including the network of bronchial branches, vasculature, and interstitial fibers in
the SYTO 16-stained human lung tissue. Immunohistochemistry with an anti-α-SMA antibody allowed selective
labeling of the network of blood vessels running through the interstitial spaces (Fig. 2b). We could observe lungtissue structures as deep as at least 400 μm when the tissue was cleared by CUBIC, whereas only scattered fluorescent signals were detected at maximum depth of 150 μm without tissue clearing (Fig. 2b,c). In addition, the tilescanning tool of the confocal microscopy allowed us to image a larger area of the tissue with the same resolution(Supplementary Fig. 2).
We also performed clearing, staining and imaging with LSFM for acquiring an entire 3D image of several
human tissues. Reconstructed 3D images of SYTO 16-stained human lung, lymph node and coronary artery of
the heart visualized the macroscopic anatomical features of each tissue; networks of alveolus, bronchi, and vasculature in the lung, lymphoid follicles in the lymph node, and peripheral branches of coronary artery (Fig. 2d,
Supplementary Movie 2, and Supplementary Movie 3). Furthermore, actin staining by phalloidin helped us to

Scientific Reports | 7: 9269 | DOI:10.1038/s41598-017-09117-03

www.nature.com/scientificreports/

Figure 2. 3D imaging of various human organs with CUBIC. (a) Schematic diagram of clearing andimmunostaining protocol for human lungs, lymph nodes, and peripheral arteries. IHC, immunohistochemistry.
(b,c) The reconstructed 3D images and orthogonal section images of human lung tissue blocks stainedwith Alexa Fluor 647-conjugated anti-α-SMA antibody and SYTO 16, with or without clearing by CUBIC.
Images were obtained by confocal microscopy (z-stack: 1 μm/slice). (d) The reconstructed 3D images of
SYTO 16-stained human lung tissue block, SYTO 16-stained half-cut human mesenteric lymph node, SYTO
16-stained peripheral branch of coronary artery which was dissected from a human heart, and SYTO 16- andAlexa Fluor 594-labeled phalloidin-stained peripheral arteries in the surface of human cerebral cortex block.
Images were obtained by light-sheet fluorescence microscopy (LSFM) (z-stack: 5 μm/slice).

selectively label small arteries in the surface of human brain cortex, which were also visualized in reconstructed
3D images (Fig. 2d). Taken together, CUBIC is applicable to 3D histology and anatomy of various human organs.

Tissue clearing and 3D imaging of pathological specimens with CUBIC.

We next explored theapplicability of CUBIC to pathological specimens derived from patients. Since lung and peripheral arteries were
efficiently cleared and visualized as shown above, we focused on lung amyloidosis. This disease is characterized
by the deposition of an abnormal protein called amyloid in the blood vessel walls and connective tissues, resulting
in systemic organ dysfunction. To visualize the amyloid deposits in blood vessel walls, blocks of the patient’s lungtissue remaining after usual pathological diagnosis were subjected to clearing and whole-mount Congo Red staining (Fig. 3a). Congo Red is commonly used for amyloid staining in the usual pathological diagnosis together with
H&E staining (Fig. 3b). Congo Red staining worked efficiently even after CUBIC clearing; the amyloid deposits
in the tissue block were macroscopically visible in the specimen (Fig. 3c). 3D imaging of the cleared and stained
samples using confocal microscopy or LSFM showed tubular amyloid deposition in the blood vessel walls of thelung (Fig. 3d and Supplementary Movie 4). A similar image was also acquired by using Thioflavin T staining,

Scientific Reports | 7: 9269 | DOI:10.1038/s41598-017-09117-0

4www.nature.com/scientificreports/

Figure 3. Tissue clearing and 3D imaging of pathological specimens with CUBIC. (a) Schematic diagram ofclearing and Congo Red staining protocol for human tissue blocks of lung amyloidosis. (b) Representative
histopathological images of this case of lung amyloidosis, which was obtained from glass slides generated forpost-mortem diagnosis. H&E staining (upper) and Congo Red staining (lower) show pink-colored amyloid
deposition in blood vessel walls in lung. (c) Gross images of amyloidosis patient-derived and normal lung tissue
blocks after Congo red staining or PBS soaking. An image of an amyloidosis patient-derived lung tissue block(upper, left) shows that arteries are macroscopically visible in red. (d) The reconstructed 3D images of humanlung tissue block stained with Congo Red, showing that amyloid deposition in artery wall in lung. The images
were obtained by LSFM (z-stack: 5 μm/slice) (upper panels) or confocal microscopy (z-stack: 1 μm/slice) (lower
panels).

another fluorescent dye used for amyloid staining (Supplementary Fig. 3). These results indicate that CUBIC
enabled 3D imaging of pathological specimens derived from patients.

Tissue clearing and 3D imaging of deparaffinized samples with CUBIC.

Another attractive challenge in pathological examination is to expand the application of the tissue-clearing and 3D-imaging techniques
to pathological specimens from paraffin-embedded tissue blocks. As routine pathological procedure in hospitals,
tissues or organs removed from patients are fixed with formaldehyde, and subjected to macroscopic observationin order to select and trim the representative pathological regions. The selected area of tissues is then subjectedto paraffin-embedding, sectioning, and H&E staining. These paraffin-embedded tissue blocks of various diseases
are thus archived in the department of pathology in hospitals all over the world. Therefore, we next tested whether
CUBIC was applicable to these paraffin-embedded archives toward retrospective and collective examination of
3D histopathology.
We first prepared tissue blocks from formaldehyde-fixed normal human lung and lymph node. These blocks
were then cut in half. One half was kept in PBS whereas another half was first embedded into a paraffin block, wasrecovered by deparaffinization, and then was subjected to tissue clearing by CUBIC (Fig. 4a,b). The gross appearance of the resulting samples was not distinguishable and had an equivalent transparency (Fig. 4c). Note that aparaffin-embedded and deparaffinised specimen but without CUBIC-1 step was not efficiently cleared, suggesting
the necessity of further delipidation by CUBIC-1 despite an expectation that a certain amount of lipids would be
removed through paraffin-embedding process (Supplementary Fig. 4). Next, we performed LSFM imaging toobtain 3D images of cleared lung and lymph node stained by SYTO 16, which demonstrated similar image quality(Fig. 4d). We also confirmed that the degree of tissue degeneration in the H&E section after the CUBIC procedure was basically equivalent between the tissues with or without paraffin-embedding and deparaffinization steps(Fig. 4e, Supplementary Fig. 5). These results indicated that paraffin-embedded tissues in pathology archives canbe used for CUBIC procedures after a suitable deparaffinization and recovery procedures.

Quantitative analysis of cellular atypia in an archival paraffin-embedded malignant lymphoma tissue. The successful tissue clearing and 3D imaging of pathological specimens derived fromparaffin-embedded tissues led us to test the retrospective histopathological examination of patient-derived
tissues recovered from paraffin-embedded tissues stored in the pathological archives of hospitals. We used aparaffin-embedded tissue block of malignant lymphoma stocked for years, together with a newly-prepared

Scientific Reports | 7: 9269 | DOI:10.1038/s41598-017-09117-0

5www.nature.com/scientificreports/

Figure 4. Tissue clearing and 3D imaging of deparaffinized samples with CUBIC. (a) Schematic diagram of
deparaffinization and subsequent tissue clearing of specimens derived from paraffin-embedded tissue blocks.
(b) Tissues were cut out from paraffin-embedded tissue blocks with a blade, followed by heating at 65 °C on aheat block until paraffin was macroscopically removed from tissues. (c) Gross images of human lung and lymph
node tissue blocks after deparaffinization and tissue clearing procedures. Formaldehyde-fixed human lung or
lymph node tissues were cut in half. One was embedded into paraffin block, followed by deparaffinization andtissue clearing according to the protocol shown in (a). The other was kept in PBS instead of paraffin-embedding,followed by the tissue clearing. (d) The reconstructed 3D images of SYTO 16-stained lung tissue blocks withor without paraffin embedding and deparaffinization steps. Formaldehyde-fixed human lung or lymph node
tissues were cut in half. One half was subjected to paraffin-embedding and deparaffinization before clearing.
Then, the samples were cleared, stained with SYTO 16 and imaged with LSFM (z-stack: 5 μm/slice) according
to the protocol shown in (a). x-y plane optical slices (Lung, Paraffin-embedded, slice #375, z = 1.875 mm; Lung,
Not embedded, slice #275, z = 1.375 mm; Lymph node, Paraffin-embedded, slice #425, z = 2.125 mm; Lymphnode, Not embedded, slice #315, z = 1.575 mm) are also presented. (e) Representative images of H&E stainingof the human lung and lymph node tissues after clearing and imaging in (d).
normal lymph node block as a control. Malignant lymphoma is a lymph tissue-origin neoplasm and histopathologically characterized by abnormal morphology such as the disordered histological structure (structural atypia),
the morphological changes of nucleus (nuclear atypia), and the variability in the size and shape of the malignant
cells (pleomorphism). Since lymphoma cells have scant cytoplasm, the degree of nuclear atypia and pleomorphism is particularly important in the diagnosis of malignant lymphoma. To test whether these hallmarks could
be observed and quantified by 3D imaging, we recovered, cleared and imaged the paraffin-embedded lymph
nodes with CUBIC (Fig. 5a). The tissues were punched out from paraffin-embedded tissue blocks using a biopsy
punch with 4 mm diameter in order to minimize the loss of tissues (Supplementary Fig. 6). We obtained reconstructed 3D images and representative 2D optical slice images by LSFM and found that malignant lymphoma
cells demonstrated diffusely infiltrating pattern, which reflects their structural atypia, while lymphocytes in the
Scientific Reports | 7: 9269 | DOI:10.1038/s41598-017-09117-0

6

www.nature.com/scientificreports/

Figure 5. Tissue clearing and 3D imaging of paraffin-embedded tissues in pathology archives with CUBIC.
(a) Schematic diagram of deparaffinization and subsequent tissue clearing and staining of specimens derived
from paraffin-embedded tissue blocks. (b) The reconstructed 3D images and representative optically sliced
images of malignant lymphoma or control normal lymph node tissues derived from paraffin-embedded tissue
blocks, obtained by LSFM imaging (z-stack: 5 μm/slice). The tissues were subjected to deparaffinization,clearing, and staining according to the protocol shown in (a). x-y plane optical slices (Malignant lymphoma,
slice #250, z = 1.25 mm; Normal lymph node, slice #250, z = 1.25 mm) are also presented. After the imaging,
the tissue was washed with PBS and used for the subsequent H&E staining. (c) The reconstructed 3D images
and orthogonal section images of malignant lymphoma and control normal lymph node tissues derived fromparaffin-embedded tissue blocks. Images were obtained by confocal microscopy (z-stack: 1 μm/slice). After theimaging, the tissue was washed with PBS and used for the subsequent H&E staining. (d) Quantitative analysis

Scientific Reports | 7: 9269 | DOI:10.1038/s41598-017-09117-0

7

www.nature.com/scientificreports/of the area and circularity of malignant lymphoma cells and normal lymphocytes. 10 independent optical slices
were selected from the z-stacked image shown in (b). 10 cells per respective slices were randomly selected
and the areas and circularity of these cells were measured using Image J software. Circularity is defined as theformula: circularity = 4π(area/perimeter2), which gives the value = 1 when the object is a precise circle. Meansof two sets of data were statistically evaluated with Welch’s t-test, because Kolmogorov-Smirnov test and F-test
demonstrated that the two groups are normal distributions without equal variance. ***P < 0.01 (Welch’s t-test).

normal lymph node formed lymphoid follicles (Fig. 5b). In addition, phalloidin-stained actin fibers of infiltrating
fibroblast cells were regionally visible in a lymphoma specimen, which helped us to evaluate the degree of fibrosis
induced by invasion of lymphoma cells (Fig. 5b). Section images of conventional H&E staining after CUBIC gave
consistent results with these histopathological features (Fig. 5b). Furthermore, images with higher resolution
by confocal microscopy showed more precise nucleic morphology of the cells; lymphoma cells showed nuclear
atypia and pleomorphism, as compared with normal lymphocytes with more uniform nucleic shape and size
(Fig. 5c). Statistical analysis from the stacked images confirmed the abnormality in the nuclear shapes of lymphoma cells, such as increased nuclear size and decreased nuclear circularity (nuclear atypia), and larger varianceof these parameters (nuclear pleomorphism) (Fig. 5d). These findings indicated that 3D pathological examinationof clinical specimens stored in the paraffin-embedded archives could be performed with the CUBIC pipeline.

3D clinicopathological screening of metastatic carcinoma nodules in lymph nodes with
CUBIC. Finally, we tested the practical effectiveness of 3D pathology on prospective clinicopathological exam-

ination. For this purpose, we performed a CUBIC-based screening to detect metastatic colorectal adenocarcinoma nodules in lymph nodes (Fig. 6a). In this screening, we used half-cut lymph nodes accompanying surgical
specimens of colorectal cancer (see also the Methods section). One half of each cut lymph node was subjectedto paraffin-embedding, sectioning, and H&E staining, followed by histological evaluation at the maximum cut
surface, which was based on a routine pathological diagnostic method in the pathology department in hospitals.
While in principle this routine method has sensitivity of practical significance, it is unable to detect minor tumor
nodules which are macroscopically unrecognizable and away from the cut surface. Therefore, we hypothesisedthat 3D imaging after whole-mount immunostaining with a tumor-specific marker might further improve thesensitivity for the detection of metastatic carcinoma. To verify this hypothesis, the other half of the cut lymph
node was cleared, and immunostained with anti-cytokeratin antibody conjugated with Alexa Fluor 647 (Figs 2a
and 6a). The cleared and stained specimen was then imaged with LSFM, followed by section-based histologicalevaluation for a final diagnosis (Fig. 6a).
In this CUBIC-based screening, we tested surgical lymph nodes samples [total 74 lymph nodes out of 7
patients who had been diagnosed as having metastasis at least in a single lymph node (>pT1) by routine diagnosis
in the hospital. The stained specimens were subjected to 3D imaging followed by 2D sectioning and H&E stainingof suspicious signals (3D → Section). This two-step evaluation enabled us to (1) definitively confirm the tumor
cells from our standard section-based criteria, and (2) exclude artefactual signals from autofluorescence of red
blood cells or blood vessels, dust, bubbles, or antibody aggregates. Therefore, the results were classified as (1) positive in both a routine diagnosis method and a CUBIC-based screening ([Routine]+/[3D → Section]+), 2) negativein both a routine diagnosis method and a CUBIC-based screening ([Routine]−/[3D → Section]−), (3) negativein a routine diagnosis method but positive in a CUBIC-based screening ([Routine]−/[3D → Section]+), and (4)positive in a routine diagnosis method but negative in a CUBIC-based screening ([Routine]+/[3D → Section]−)(Fig. 6b–d).
In the [Routine]+/[3D → Section]+ case, the 3D imaging and the following section-based evaluation at the
maximum surface clearly depicted the carcinoma nodules inside the specimen (Fig. 6b). In addition, H&E
and cytokeratin immunostaining after the CUBIC procedure gave comparable results, suggesting that the
CUBIC-based screening can be added on to the routine histopathological procedure. Note that such large tumor
nodules remained opaque and were macroscopically visible even after CUBIC clearing (Supplementary Fig. 7),
suggesting the usefulness of CUBIC for gross pathology as well.
On the other hand, some of the specimens did not include any significant signal for possible tumor nodules both by routine diagnosis or CUBIC-based screening (Fig. 6c). Therefore, these cases were classified as[Routine]−/[3D → Section]−. After 3D imaging, these negative samples were deeply sectioned for denying false
negative. In the case that a potent tumor nodule was detected for the first time in 3D image, the section plane
including the nodule position was then prepared and histologically evaluated (Fig. 6a). Some of the cases, inwhich the 3D image contained the artefactual signals as above but no tumor cell was detected in the following
section-based evaluation (Supplementary Fig. 8), were reclassified as [Routine]−/[3D → Section]−. However,
the remaining cases indeed contained a small tumor cell nodule inside, which was further confirmed by thesection-based evaluation at the position and thus classified as [Routine]−/[3D → Section]+ (Fig. 6d). Importantly,
for diagnosis of [3D → Section]+/−, the suspected nodular signal in the 3D image was subsequently examined bysectioning and H&E staining in all of the cases. Because of the experimental design, [3D → Section]− data did notinclude false positive. In addition, since all tumor nodules identified in routine examination were again detectedin CUBIC-based screening, there was no case of [Routine]+/[3D → Section]−.
The results are summarized in Table 1. Four lymph nodes out of 74 were newly diagnosed as positive metastasis only by the CUBIC-based screening. Because [3D → Section]− samples were subjected to a deep-cut sectioning for excluding false negative, the numbers in the CUBIC-based screening can be considered as true positive
values. Therefore, these results yielded the sensitivity of a routine diagnosis method as 85.2% (23/27) with four
false negative. This means that CUBIC-based screening provided 14.8% (4/27) improved sensitivity over the

Scientific Reports | 7: 9269 | DOI:10.1038/s41598-017-09117-08www.nature.com/scientificreports/

Figure 6. 3D clinical pathology of metastatic carcinoma nodules in lymph nodes with CUBIC. (a) Schematic
diagram of the metastasis screening protocol. Formaldehyde-fixed lymph nodes accompanying surgical
specimens of colorectal cancer were cut in half. One half was subjected to the histological evaluation according
to routine pathological diagnostic method in hospitals (Counterpart for routine diagnosis). The other half was
subjected to CUBIC screening, which was cleared and immunostained with an Alexa Fluor 647-conjugatedanti-cytokeratin antibody for LSFM imaging (z-stack: 5 μm/slice). If a suspicious tumor nodule was detected inthe 3D image, the x-y plane including this nodule was sectioned for the subsequent evaluation with H&E andimmunohistochemical staining. Otherwise the sample was deeply sectioned to disprove the false negative. IHC,
immunohistochemistry. (b–d) The reconstructed 3D images for screening and H&E or immunohistochemical
staining for final histological evaluation after the CUBIC screening. The 3D images were obtained with LSFM
(z-stack: 5 μm/slice). (b) [Routine]+/[3D → Section]+ lymph node contained obvious metastatic carcinoma
nodules which was positive in both routine diagnosis method and CUBIC screening. (c) [Routine]−/[3D → Section]− lymph node did not contain any metastasis, confirmed both routine diagnosis and CUBIC
screening. (d) [Routine]−/[3D → Section]+ lymph node contained small carcinoma nodules which were only
identified by CUBIC screening but were not detected by routine diagnosis method.

Scientific Reports | 7: 9269 | DOI:10.1038/s41598-017-09117-0

9www.nature.com/scientificreports/
3D → sectioning

Routine method

Positive (n = 27)

Negative (n = 47)

Positive (n = 23)

23

0

Negative (n = 51)

447

Table 1. Performance of CUBIC-based lymph nodes metastasis screening. 74 lymph nodes were selectedfrom the cases in which at least one lymph node, among all regional lymph nodes for each case, was diagnosed
as positive for metastasis (>pT1) by the routine diagnosis method. Four lymph nodes out of 74 were
newly diagnosed as positive for metastasis only by the CUBIC-based screening (3D → sectioning), making
the sensitivity of the routine diagnosis method 85.2% (23/27) with four false negative, i.e. 14.8% (4/27)
improvement in sensitivity with CUBIC.

routine method. Taken together, the 3D pathological screening thus can increase the sensitivity of this definitive
diagnosis in the clinical evaluation of cancer metastasis.

Discussion

Tissue-clearing and 3D-imaging techniques enable comprehensive analysis of cells throughout whole organs
and organisms8, 25. These techniques have been further applied to optical clearing, histological labelling and
3D imaging of human samples11, 13–16, 40, 41. In this study, we investigated the applicability of tissue-clearing and
3D-imaging techniques to histopathological diagnosis of clinical specimens. We used CUBIC for this purpose
because CUBIC fulfills the criteria required for the pathological examination of clinical specimens such as clearing efficiency, ease of use, safety of the protocol, and proven performance in 3D imaging with LSFM and confocal
microscopy9, 34, 38. We tested the current version of CUBIC clearing protocol with various human organs andfound that the lung and the lymph node were efficiently cleared and could be used for the following feasibility
study (Fig. 1). We further found that CUBIC could be used for clearing, staining and 3D imaging of not only
newly fixed samples but also paraffin-embedded tissues stored in the pathological archives of hospitals (Figs 2–5
and Supplementary Figs 2–3). This point is practically important for the usage of other pathological archives inmany hospitals. Furthermore, the human samples after CUBIC could be evaluated by a conventional pathologicalexamination with H&E staining. These results highlighted that the tissue-clearing and 3D-imaging techniques
based on CUBIC could be applied to clinicopathological examination of human samples without losing its compatibility with the conventional pathology methods.
Tissue-clearing and 3D-imaging techniques have great advantages in objective and quantitative analysis. In
this study, we demonstrated these advantages in the pathological examination of clinical specimens by using
CUBIC. Tissue clearing and 3D imaging of lymph nodes of malignant lymphoma identified nuclear and structural atypia, suggesting the objectivity and quantitativeness of 3D pathological examination (Fig. 5). Furthermore,
3D pathological examination could increase the sensitivity of diagnostic testing by detecting small metastatic
colorectal adenocarcinoma nodules in the associated lymph nodes (Fig. 6 and Table 1). In this screening, we
adopted a two-step evaluation (CUBIC-based 3D imaging and subsequent 2D histopathological evaluation
using H&E-stained sections of the suspicious signals). The two-step evaluation successfully helped us to findminor metastatic lesions which could not be detected by conventional pathological examination. Although the
CUBIC-based 3D evaluation in this study could not completely distinguish artefactual signals from true metastatic lesion-derived signals without the subsequent H&E staining, further technical advancements in clearing,
staining and 3D imaging should realize a complete 3D imaging-based metastasis screening system. Collectively,
these results support the idea that the retrospective and prospective 3D clinical pathology can improve the diagnostic capability of routine pathological examinations by increasing its objectivity, quantitativeness and sensitivity. This 3D clinical pathology would also facilitate the accumulation of histopathological knowledge based on the
3D structure of diseased organs.
Concerning the compatibility of CUBIC with immunohistochemistry, we and other researchers have tested
dozens of antibodies and stains which work with the CUBIC-treated specimens9, 12, 34, 39, 42–45, suggesting theusefulness of CUBIC in a wide range of immunohistochemistry applications in histopathological studies anddiagnosis. This point is also important because fluorescent labelling by genetic tools cannot be utilized for humanspecimens8. However, while most of the clearing methods have been shown as to be compatible with histologicalstaining, including human tissue samples9, 11–15, 17, 34, 43 or more complicated multiplex staining or in situ hybridization for RNA detection41, 46, only few critical parameters for efficient penetration of stains, antibodies or probes
into the 3D tissue have been identified so far. Although electrophoresis or pressure-driven 3D staining have beentested12, 47, 48, establishment of a simple but robust staining method based only on diffusion penetration will beneeded to accelerate further applications of tissue-clearing and 3D-imaging techniques for 3D clinical pathology.
Ideally, further identification of staining reagents based on small molecules such as short peptides49 and nucleic
acids (e.g. aptamers)50 will also facilitate 3D clinical pathology. Antigenicity is also a general issue in immunohistochemistry. Since antigenicity is dependent on not only tissue clearing but also other histological preparation
conditions (e.g. fixation), the detailed histological preparation conditions should be described for each working
antibody.
The other remaining concern is the tissue clearing efficiency. In this study, we demonstrated the applicabilityof the first-generation CUBIC reagents to lymph nodes and lung. For other human organs, however, these CUBIC
reagents need to be updated so as to improve clearing efficiency. The efficiency of tissue clearing for human tissues
seemed generally worse than that for mouse tissues in our study, probably due to some significant difference ofindividual cell size, tightness between cells, and/or rigidity of stroma components. In particular, the difficulty on
Scientific Reports | 7: 9269 | DOI:10.1038/s41598-017-09117-010www.nature.com/scientificreports/
complete decolorization of endogenous chromophores inside colored human tissues is an issue to be addressed(Supplementary Fig. 1). Furthermore, melanin, a pigment derived from tyrosine via a multistep reaction, often
becomes an obstacle for tissue decolorization and no efficient protocol has been reported for removal of this typeof pigment8. Since the previous studies18, 34, 51 only screened a relatively small number of chemicals, more potent
tissue-clearing and decolorizing chemicals should be identified by a large-scale chemical screening in the future.
In conclusion, the CUBIC-based 3D clinical pathology (CUBIC pathology) demonstrated here provides anopportunity to increase the capability of diagnostic pathology. Further development and optimization of the
protocol would facilitate the future of routine pathology with 3D examination, and will allow pathologists toefficiently accumulate 3D pathological findings, leading to the establishment of a novel field of medical science.

Methods

The CUBIC clearing.

Two CUBIC reagents were prepared as previously reported34, 38. For preparationof CUBIC-treated samples, the formaldehyde-fixed organs were resected into tissue blocks (2–5 mm × 2–5
mm × 0.5–3 mm), followed by wash with PBS. These tissue blocks were immersed into 8–10 ml of 50% (v/v)
ScaleCUBIC-1 (designated as CUBIC-1) reagent (1: 1 mixture of water: CUBIC-1) for 1 day and further
immersed in 8–10 ml of CUBIC-1 reagent for 3 days (Figs 1–6) or 7 days (Supplementary Fig. 1). If counterstain was required, 1 μM SYTO 16 (Life Technologies Inc., Rockville, MD, S7578) was added into CUBIC-1 reagent on the second day. Subsequently, these samples were washed with PBS and immersed into 8–10 ml of 50%(v/v) ScaleCUBIC-2 (designated as CUBIC-2) reagent (1: 1 mixture of water: CUBIC-2) for 1 day and further
immersed in 8–10 ml of CUBIC-2 reagent for 2 days (Fig. 1), 1 day (Figs 2–6), or 7 days (Supplementary Fig. 1).

Pathology specimens. Tissue specimens used in Figs 1–5 were derived from the patients who underwent
pathological dissection at Osaka University Hospital from 2013 to 2015. Lymph node specimens used in Fig. 6
were derived from the patients who underwent surgery for colorectal carcinoma in Kinki Central Hospital in2015 to 2016. In this study, we used half-cut lymph nodes from the cases in which at least one lymph node, among
all regional lymph nodes belonging to each case, was diagnosed as positive for metastasis (>pT1) by the routine
diagnosis method. In diagnostic practice, formaldehyde-fixed lymph nodes accompanying surgical specimensof colorectal cancer were evaluated by sectioning to check subgrossly for metastatic nodules. If a massive metastatic nodule exists in a lymph node, it is sectioned at the maximum cut surface crossing the tumor nodule. If alymph node is small and with no macroscopically recognizable metastatic nodule, it is often sectioned at an arbitrary maximum cut surface. Such macroscopic diagnosis is carefully performed by pathologists according to theguideline52. Thus, we used such half-cut lymph node specimens in the screening shown in Fig. 6. The study wasapproved by the Ethical Review Board of the Graduate School of Medicine, Osaka University (No. 14470), Kinki
Central Hospital (No. 263), and the Graduate School of Medicine, The University of Tokyo (No. 10917), and was
performed in accordance with the committee guidelines and regulations. Informed consent was obtained fromall patients.
Mouse organs.

Mouse organs used as control in Fig. 1 and Supplementary Fig. 1 were prepared from
12-week-old female C57BL/6 J mice. Popliteal lymph nodes were prepared from 7-week-old female C57BL/6 J
mice immunized with Keyhole limpet hemocyanin (KLH) in complete Freund’s adjuvant (CFA) in the footpad.
Mice were bred at the Animal Resource Center for Infectious Diseases, Research Institute for Microbial Diseases
and Immunology Frontier Research Center, Osaka University. All animal procedures were approved by licensing
committees of Infectious Diseases, Research Institute for Microbial Diseases and Immunology Frontier ResearchCenter, Osaka University, and were conducted according to the institutional guidelines.

Microscopy and Image analysis.

3D images were acquired with confocal microscopy (Zeiss LSM710
Confocal/Multiphoton, Carl-Zeiss, Jena, Germany). All raw image data were exported as czi files, followed byanalysis with Imaris software (version 7.7.2, Bitplane, Zurich, Switzerland). All images were obtained with constant laser power. 3D images were also acquired with light-sheet fluorescence microscopy (Ultramicroscope,
LaVision BioTec, Germany) as reported previously10, 34. All raw image data were collected in a lossless 16-bit TIFF
format. 3D-rendered images were visualized, captured and analyzed with Imaris software (version 7.7.2, Bitplane,
Zurich, Switzerland).
Quantification of nuclear atypia and pleomorphism of lymphoma cells and lymphocytes was performed byusing ImageJ software (Fig. 5d)53. 10 independent optical slices were selected from the z-stacked images of malignant lymphoma and normal lymph node shown in Fig. 5c. 10 lymphoma cells or lymphocytes per respective
slices were randomly selected and contours of these cells were tracked by “Freehand selections” tool of ImageJsoftware, which were analyzed to evaluate their nuclear area and circularity. Lymphoma cells and lymphocytes
were morphologically distinguished from other kinds of cells, especially from antigen presenting cells (APCs),
because lymphoma cells and lymphocytes have scant cytoplasm whereas APCs have abundant and clear cytoplasm. For calculating nuclear area of lymphoid cells, the “Measure” function of ImageJ software was used. For
calculating nuclear circularity, the “Circularity” plugin was used (https://imagej.nih.gov/ij/plugins/circularity.
html). Circularity is defined as the formula: circularity = 4π(area/perimeter2), which gives the value = 1 when theobject is a precise circle.

Whole-mount 3D immunohistochemistry. Whole-mount immunohistochemistry protocol for CUBIC
samples was done according to the previous paper34. Tissue samples were treated with CUBIC-1 reagent for
3 days, washed with PBS, immersed in 30% (w/v) sucrose in PBS, and frozen in O.C.T. compound at −80 °C
overnight. The frozen samples were then thawed, washed with PBS, and subjected to immunostaining with the
1:50 diluted fluorescent-labeled antibodies in 0.1% (v/v) Triton X-100 in PBS for 3 days at room temperature.
The stained samples were then washed with PBS several times at room temperature, followed by cross-linking in
Scientific Reports | 7: 9269 | DOI:10.1038/s41598-017-09117-0

11www.nature.com/scientificreports/
1% PFA in PBS for 3-4 hours at room temperature. The stained samples were then immersed into 50% CUBIC-2
reagent for 1 day and CUBIC-2 reagent for 1 day. The following antibodies were used for the staining: Alexa
Fluor 647-conjugated anti-α-smooth muscle actin (α-SMA) antibody (abcam, Cambridge, UK, ab196919) for
human lung (Fig. 2b and Supplementary Fig. 2), and Alexa Fluor 647-conjugated anti-Pan cytokeratin antibody(C-11) (Cell signaling, Danvers, MA, #4528) for human lymph nodes (Fig. 6b–d). For actin staining, Alexa Fluor
594-labeled phalloidin (ThermoFisher Scientific, Waltham, MA, A12381) was used with the 1:25 dilution in PBS(Figs 2d and 5b).

Whole-mount 3D staining with Congo Red and Thioflavin T.

Whole-mount Congo Red andThioflavin T staining were performed for amyloid staining according the standard protocol. For Congo Red
staining, tissue samples were treated with CUBIC-1 reagent for 3 days, washed with PBS, immersed in 30% (w/v)
sucrose in PBS, and frozen in O.C.T. compound at −80 °C overnight. The frozen samples were then thawed,
washed with PBS, and immersed into alcoholic salt solution (saturated NaCl in 80% alcohol) at 37 °C for 2 days.
These samples were then immersed into working Congo Red solution (Saturated Congo Red in 80% alcohol
saturated with NaCl, in which 1/100 (v/v) of 1% NaOH solution was added just before use) at 37 °C for 2 days.
The stained samples were washed consecutively with 100%, 90%, 80%, 70% ethanol diluted with water. Eachwashing time was within the range of 1–5 minutes, according to the degree of decolorization. Further, the samples
were washed with PBS for 30 minutes, and immersed into 50% CUBIC-2 reagent for 1 day and CUBIC-2 reagent
for 1 day. Fluorescence signal of Congo Red was measured by excitation at both 561 nm and 594 nm (confocal
microscopy) or at 594 nm (LSFM). For Thioflavin T staining, tissue samples were treated with CUBIC-1 reagent
for 3 days, washed with PBS, immersed in 30% (w/v) sucrose in PBS, and frozen in O.C.T. compound at −80 °C
overnight. The frozen samples were then thawed, washed with PBS, and immersed into working Thioflavin T
solution (50 mM Thioflavin T in PBS) at room temperature for 3 days. The samples were washed with PBS for
6 hours, and immersed into 50% CUBIC-2 reagent for 1 day and CUBIC-2 reagent for 1 day. Fluorescence signalof Thioflavin T was measured by excitation at 405 nm.

Deparaffinization of tissue from paraffin-embedded tissue blocks.

Deparaffinization of tissues
from paraffin-embedded tissue blocks was performed according to the protocols shown in Figs 4a and 5a. Tissues
were cut out with a blade (Fig. 4) or punched out by a ϕ 4-mm biopsy punch (Fig. 5 and Supplementary Fig. 6)
from paraffin-embedded tissue blocks, followed by heating at 65 °C on heatblock until paraffin was macroscopically removed from tissues. These samples were washed with Hemo-De (FALMA, CS-1001) overnight at room
temperature, followed by further wash with Hemo-De for 3 hours. The samples were washed with 100%, 90%,80%, 70% ethanol diluted with water for 3 hours respectively, which was further washed with PBS for 6 hours,
before being subjected to CUBIC tissue-clearing protocol.

Statistical analyses. Statistical analyses were performed using Microsoft Excel or EZR version 3.3.1(2016–06–21)54. The normality of the two sets of data was evaluated by Kolmogorov-Smirnov test at the significance levelof 0.05. When the normality was confirmed in the groups, the homogeneity of variance was tested by F-test at thesignificance level of 0.05. When two groups were normally distributed with or without equal variance, Student’s
t-test or Welch’s t-test were applied, respectively. In this study, Welch’s t-test was used in Fig. 5d.

References

1. Marcum, R. G. & Wellings, S. R. Subgross pathology of the human breast: method and initial observations. J. Natl. Cancer Inst. 42,
115–121 (1969).
2. Wellings, S. R. & Jensen, H. M. On the origin and progression of ductal carcinoma in the human breast. J. Natl. Cancer Inst. 50,
1111–1118 (1973).
3. Wellings, S. R., Jensen, H. M. & Marcum, R. G. An atlas of subgross pathology of the human breast with special reference to possible
precancerous lesions. J. Natl. Cancer Inst. 55, 231–273 (1975).
4. Marchio, C., Sapino, A., Arisio, R. & Bussolati, G. A new vision of tubular and tubulo-lobular carcinomas of the breast, as revealedby 3-D modelling. Histopathology 48, 556–562 (2006).
5. Sun, L., Wang, D., Zubovits, J. T., Yaffe, M. J. & Clarke, G. M. An improved processing method for breast whole-mount serial sections
for three-dimensional histopathology imaging. Am. J. Clin. Pathol. 131, 383–392 (2009).
6. Norton, K. A. et al. Automated reconstruction algorithm for identification of 3D architectures of cribriform ductal carcinoma in situ.
PLoS One 7, e44011 (2012).
7. Booth, M. E. et al. Three-dimensional reconstruction of ductal carcinoma in situ with virtual slides. Histopathology 66, 966–973(2015).
8. Susaki, E. A. & Ueda, H. R. Whole-body and Whole-Organ Clearing and Imaging Techniques with Single-Cell Resolution: Toward
Organism-Level Systems Biology in Mammals. Cell Chem. Biol. 23, 137–157 (2016).
9. Tainaka, K. et al. Whole-body imaging with single-cell resolution by tissue decolorization. Cell 159, 911–924 (2014).
10. Dodt, H. U. et al. Ultramicroscopy: Three-dimensional visualization of neuronal networks in the whole mouse brain. Nat. Methods
4, 331–336 (2007).
11. Hama, H. et al. ScaleS: an optical clearing palette for biological imaging. Nat. Neurosci. 18, 1518–1529 (2015).
12. Lee, E. et al. ACT-PRESTO: Rapid and consistent tissue clearing and labeling method for 3-dimensional (3D) imaging. Sci. Rep. 6,
18631 (2016).
13. Pan, C. et al. Shrinkage-mediated imaging of entire organs and organisms using uDISCO. Nat. Methods 13, 859–867 (2016).
14. Chung, K. et al. Structural and molecular interrogation of intact biological systems. Nature 497, 332–337 (2013).
15. Yang, B. et al. Single-cell phenotyping within transparent intact tissue through whole-body clearing. Cell 158, 945–958 (2014).
16. Liebmann, T. et al. Three-Dimensional Study of Alzheimer’s Disease Hallmarks Using the iDISCO Clearing Method. Cell Rep. 16,
1138–1152 (2016).
17. Renier, N. et al. iDISCO: a simple, rapid method to immunolabel large tissue samples for volume imaging. Cell 159, 896–910 (2014).
18. Becker, K., Jährling, N., Saghafi, S., Weiler, R. & Dodt, H. U. Chemical clearing and dehydration of GFP expressing mouse brains.
PLoS One 7, e33916 (2012).
19. Ertürk, A. et al. Three-dimensional imaging of solvent-cleared organs using 3DISCO. Nat. Protoc. 7, 1983–1995 (2012).

Scientific Reports | 7: 9269 | DOI:10.1038/s41598-017-09117-0

12www.nature.com/scientificreports/
20. Hama, H. et al. Scale: a chemical approach for fluorescence imaging and reconstruction of transparent mouse brain. Nat. Neurosci.
14, 1481–1488 (2011).
21. Ke, M. T., Fujimoto, S. & Imai, T. SeeDB: a simple and morphology-preserving optical clearing agent for neuronal circuitreconstruction. Nat. Neurosci. 16, 1154–1161 (2013).
22. Kuwajima, T. et al. ClearT: a detergent- and solvent-free clearing method for neuronal and non-neuronal tissue. Development 140,
1364–1368 (2013).
23. Aoyagi, Y., Kawakami, R., Osanai, H., Hibi, T. & Nemoto, T. A rapid optical clearing protocol using 2,2′-thiodiethanol for
microscopic observation of fixed mouse brain. PLoS One 10, e0116280 (2015).
24. Costantini, I. et al. A versatile clearing agent for multi-modal brain imaging. Sci. Rep. 5, 9808 (2015).
25. Tainaka, K., Kuno, A., Kubota, S. I., Murakami, T. & Ueda, H. R. Chemical Principles in Tissue Clearing and Staining Protocols for
Whole-Body Cell Profiling. Annu. Rev. Cell Dev. Biol. 32, 713–741 (2016).
26. Olson, E., Levene, M. J. & Torres, R. Multiphoton microscopy with clearing for three dimensional histology of kidney biopsies.
Biomed. Opt. Express 7, 3089–3096 (2016).
27. Torres, R. V. S. & Levene, M. J. High-resolution, 2- and 3-dimensional imaging of uncut, unembedded tissue biopsy samples. Arch.
Pathol. Lab. Med. 138, 395–402 (2014).
28. Sommer, G. et al. Biomechanical properties and microstructure of human ventricular myocardium. Acta. Biomater. 24, 172–192(2015).
29. Lai, H. M. et al. Rationalisation and Validation of an Acrylamide-Free Procedure in Three-Dimensional Histological Imaging. PLoS
One 11, e0158628 (2016).
30. Liu, A. K. et al. Bringing CLARITY to the human brain: visualization of Lewy pathology in three dimensions. Neuropathol. Appl.
Neurobiol. 42, 573–587 (2016).
31. Murata, T. et al. Three-dimensional evaluation of subclinical extension of extramammary Paget’s disease: Visualization ofhistological border and its comparison to clinical border. Br. J. Dermatol. (2016).
32. Neckel, P. H., Mattheus, U., Hirt, B., Just, L. & Mack, A. F. Large-scale tissue clearing (PACT): Technical evaluation and new
perspectives in immunofluorescence, histology, and ultrastructure. Sci. Rep. 6, 34331 (2016).
33. van Royen, M. E. et al. Three-dimensional microscopic analysis of clinical prostate specimens. Histopathology 69, 985–992 (2016).
34. Susaki, E. A. et al. Whole-brain imaging with single-cell resolution using chemical cocktails and computational analysis. Cell 157,
726–739 (2014).
35. Fumoto, S., Nishimura, K., Nishida, K. & Kawakami, S. Three-Dimensional Imaging of the Intracellular Fate of Plasmid DNA andTransgene Expression: ZsGreen1 and Tissue Clearing Method CUBIC Are an Optimal Combination for Multicolor Deep Imaging
in Murine Tissues. PLoS One 11, e0148233 (2016).
36. Nehrhoff, I. et al. 3D imaging in CUBIC-cleared mouse heart tissue: going deeper. Biomed. Opt. Express 7, 3716–3720 (2016).
37. Stefaniuk, M. et al. Light-sheet microscopy imaging of a whole cleared rat brain with Thy1-GFP transgene. Sci. Rep. 6, 28209 (2016).
38. Susaki, E. A. et al. Advanced CUBIC protocols for whole-brain and whole-body clearing and imaging. Nat. Protoc. 10, 1709–1727(2015).
39. Lloyd-Lewis, B. et al. Imaging the mammary gland and mammary tumours in 3D: optical tissue clearing and immunofluorescencemethods. Breast Cancer Res. 18, 127 (2016).
40. Casoni, F. et al. Development of the neurons controlling fertility in humans: new insights from 3D imaging and transparent fetal
brains. Development 143, 3969–3981 (2016).
41. Murray, E. et al. Simple, Scalable Proteomic Imaging for High-Dimensional Profiling of Intact Systems. Cell 163, 1500–1514 (2015).
42. Davis, F. M. et al. Single-cell lineage tracing in the mammary gland reveals stochastic clonal dispersion of stem/progenitor cellprogeny. Nat. Commun. 7, 13053 (2016).
43. Hirashima, T. & Adachi, T. Procedures for the quantification of whole-tissue immunofluorescence images obtained at single-cellresolution during murine tubular organ development. PLoS One 10, e0135343 (2015).
44. Ieyasu, A. et al. An All-Recombinant Protein-Based Culture System Specifically Identifies Hematopoietic Stem Cell MaintenanceFactors. Stem Cell Reports 8, 500–508 (2017).
45. Romanov, R. A. et al. Molecular interrogation of hypothalamic organization reveals distinct dopamine neuronal subtypes. Nat.
Neurosci. 20, 176–188 (2017).
46. Sylwestrak, E. L., Rajasethupathy, P., Wright, M. A., Jaffe, A. & Deisseroth, K. Multiplexed Intact-Tissue Transcriptional Analysis at
Cellular Resolution. Cell 164, 792–804 (2016).
47. Li, J., Czajkowsky, D. M., Li, X. & Shao, Z. Fast immuno-labeling by electrophoretically driven infiltration for intact tissue imaging.
Sci. Rep. 5, 10640 (2015).
48. Kim, S. Y. et al. Stochastic electrotransport selectively enhances the transport of highly electromobile molecules. Proc. Natl. Acad.
Sci. U. S. A. 112, E6274–6283 (2015).
49. Lee, S., Xie, J. & Chen, X. Peptide-based probes for targeted molecular imaging. Biochemistry 49, 1364–1376 (2010).
50. Juskowiak, B. Nucleic acid-based fluorescent probes and their analytical potential. Anal. Bioanal. Chem. 399, 3157–3176 (2011).
51. Kurihara, D., Mizuta, Y., Sato, Y. & Higashiyama, T. ClearSee: a rapid optical clearing reagent for whole-plant fluorescence imaging.
Development 142, 4168–4179 (2015).
52. Lanza, G., Messerini, L., Gafà, R. & Risio, M. Colorectal tumors: The histology report. Digestive and Liver Disease 43, S344–S355(2011).
53. Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675 (2012).
54. Kanda, Y. Investigation of the freely available easy-to-use software ‘EZR’ for medical statistics. Bone Marrow Transplant. 48, 452–458(2013).

Acknowledgements

We thank all the lab members at Department of Pathology, Osaka University Graduate School of Medicine, inparticular, Dr. Katsuyuki Aozasa for his advice on expert histopathological knowledge, Ms. Mayumi Kawashima,
Mr. Akira Naitoh, Mr. Masaharu Kohara, Mr. Tadasuke Nagatomo, Ms. Takako Sawamura, Ms. Megumi Nihei,
and Ms. Etsuko Maeno for their kind technical assistance. We also thank all the lab members at the Universityof Tokyo, in particular, Dr. Kazuki Tainaka for his technical advices on the project. We are grateful to Dr. Kylius
Wilkins (RIKEN QBiC) for proofreading. We also thank the medical staff at Department of Pathology, Kinki
Central Hospital of Mutual Aid Association of Public Teachers, Mr. Michihiro Kawamura, Mr. Hiroki Uchida,
Ms. Atsuko Fukuhara, and Mr. Kojiro Takagahara for their kind technical assistance. This study was supported
by Mr. Eiji Oiki, Center for Medical Research and Education, Graduate School of Medicine, Osaka University.
This work was supported by research grants from MEXT/JSPS KAKENHI (Scientific Research S, 25221004,
H.R.U.; Scientific Research C, T264604700, E.M.; Scientific Research C, 15K08423, S.N.; Young Scientists A,
15H05650, E.A.S.); AMED-CREST (H.R.U.), CREST (H.R.U.), Brain/MINDS (H.R.U.), Basic Science andPlatform Technology Program for Innovative Biological Medicine (H.R.U.); the strategic programs for R&D
Scientific Reports | 7: 9269 | DOI:10.1038/s41598-017-09117-0

13

www.nature.com/scientificreports/
of RIKEN (H.R.U.), an intramural Grant-in-Aid from the RIKEN QBiC (H.R.U.); Takeda Science Foundation(H.R.U. and E.A.S.); the Astellas Foundation for Research on Metabolic Disorders (S.N.); the Kanae Foundation
for the Promotion of Medical Science (S.N.); Senri Life Science Foundation (S.N.); the Nakajima Foundation(S.N.); PRESTO from JST (JPMJPR15F4, E.A.S.); the Japan Foundation for Applied Enzymology (E.A.S.); theBrain Sciences Project of the Center for Novel Science Initiatives of the National Institutes of Natural Sciences(BS281004 and BS291001, E.A.S.).

Author Contributions

H.R.U., E.M., S.N. and E.A.S. designed the study. S.N. performed most of the experiments with technicalassistance by E.A.S., K.Y., T.H., T.N., I.S., T.K. and Y.N. contributed to the preparation of pathological specimens.
S.T., K.O., M.K., N.W. and J.I. contributed to preparation of experimental materials. K.Y. and Y.H. managed theclinical information. A.K. provided advices on project planning and data interpretation. All authors discussed theresults and commented on the manuscript text.

Additional Information

Supplementary information accompanies this paper at doi:10.1038/s41598-017-09117-0
Competing Interests: The authors declare that they have no competing interests.
Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps andinstitutional affiliations.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International
License, which permits use, sharing, adaptation, distribution and reproduction in any medium or
format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in thisarticle are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to thematerial. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the
copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
© The Author(s) 2017

Scientific Reports | 7: 9269 | DOI:10.1038/s41598-017-09117-0

14

Supplementary Information
CUBIC pathology: three-dimensional
pathological diagnosis.

imagingforSatoshi Nojima, Etsuo A. Susaki, Kyotaro Yoshida, Hiroyoshi Takemoto, Naoto
Tsujimura, Shohei Iijima, Ko Takachi, Yujiro Nakahara, Shinichiro Tahara, Kenji
Ohshima, Masako Kurashige, Yumiko Hori, Naoki Wada, Jun-ichiro Ikeda,
Atsushi Kumanogoh, Eiichi Morii, Hiroki R. Ueda

(a) Organ clearing protocol
Day 0

1

2

50%
PBS CUBIC-1

5

4

3

6

CUBIC-1 (reflesh/day)

(b)

7

PBS

50%
CUBIC-2

12

Day 8

Human

Microscopic
(H&E)

Mouse

200 μm

Day 2

Day 3

Day 2

Day 3

Day 16Gross

Day 16200 μm

Day 3

Day 5

5 mm

200 μmGross
Microscopic
(H&E)

Mouse

Day 2

Gross

Day 0

Human

Day 8

Microscopic
(H&E)

Gross

Human

Microscopic
(H&E)
Gross

200 μm

Day 8

5 mm

Intestine

200 μm15
cmmm

Microscopic
(H&E)

Mouse

5 mm

Day 16200 μmSpleen

1 cm

Day 5

Gross

Microscopic
(H&E)

Human
Mouse

Gross
200 μm

Day 5

Day 8

200 μm5 mm

Microscopic
(H&E)

Gross
Microscopic
(H&E)

Mouse

5 mm

Day 3

Day 16200 μmDay 0

Day 16200 μm

Day 2

Day 8

KidneyDay 8

5 mm

Microscopic
(H&E)

Human

Day 5

Day 5

5 mm

Liver

Day 0

H&E
after CUBIC

5 mm
1 cm

Microscopic(H&E)

Microscopic
(H&E)

Day 0

Day 16

5 mm

Day 3

16
Macroscopy

CUBIC-2 (reflesh/day)

200 μm

Day 2

15

Gross

Day 5

5 mm

Day 0

14

Gross

Day 3

Gross

Day 2

13

Heart

Gross

Microscopic
(H&E)

Human

11

Brain
Day 0

Mouse

10

9

8

5 mm

200 μmFigure S1 | Tissue clearing of various human organs with CUBIC. (a) Schematic diagram ofclearing protocol for human organs. (b) Gross and microscopic images of human or mouse organs.
After gross image acquisition at the indicated time points, tissues were washed with PBS, followed byparaffin embedding, sectioning, and H&E staining.

Confocal microscopy

3D-reconstructed

500 μmyz

x
500 µmSYTO 16

α-SMA

Merge

Figure S2 | 3D observation of a larger area of human lung with CUBIC. (Upper panel) 3 × 3 tilingscan and Z-stack imaging by the confocal microscopy allows the acquisition of a larger area ofcleared and stained human lung. The reconstructed 3D images of the human lung tissue block
stained with SYTO 16 and Alexa Fluor 647-conjugated anti-α-SMA antibody. Images were obtainedby 3 × 3 tiling scan function of the confocal microscopy (z-stack: 1 μm/slice). (Lower panel) a detailed
view from the 3 × 3 tile scan images, detecting sinusoidal vascular structures inside the organ.

Confocal microscopy

3D-reconstructedyzx
200 µmSYTO 16

Thioflavin T

Merge

Figure S3 | Thioflavin T staining and 3D imaging of human amyloidosis lung with CUBIC.
The reconstructed 3D images of the human patient’s lung tissue block stained with STYO 16 andThioflavin T, also showing that the amyloid is deposited in artery wall in the lung. The images wereobtained by confocal microscopy.

Protocol without
CUBIC-1 step

Lung

Complete protocol

Lymph node

5 mm

3 mm

Figure S4 | The protocol without CUBIC-1 step cannot sufficiently clear deparaffinized tissue
specimens. Formaldehyde-fixed human lung and lymph node tissues were embedded into paraffinembedded tissue blocks, and then the tissues were recovered according to the protocol shown in
Figure 4. The recovered tissues were then subjected to tissue-clearing procedure according to thecomplete protocol (with both CUBIC-1 and CUBIC-2 clearing steps) or the protocol without CUBIC-1
step (with only CUBIC-2 clearing step). Tissues processed by the protocol without the CUBIC-1 step
were soaked into PBS, instead.

Post-deparaffinization &tissue clearing

Lung

Pre-deparaffinization &tissue clearing

Lymph node

100 µm

100 µmFigure S5 | The deparaffinization and tissue-clearing steps do not cause significant tissue
degeneration. Formaldehyde-fixed human lung and lymph node tissues were embedded into paraffin blocks. H&E sections were made from these blocks prior to the recovery step(“Pre-deparaffinization & tissue clearing”), which were subjected to deparaffinization and tissueclearing procedures according to a protocol similar to that in Figure 4. These specimens werere-embedded into paraffin blocks and H&E sections were generated from them(“Post-deparaffinization & tissue clearing”).

Punching a tissue from a paraffin-embedded tissue block

Figure S6 | A punching method for tissue clearing and 3D imaging of paraffin-embedded
tissues in pathology archives with CUBIC. For preparing samples in Figure 5, the tissues were
punched out from the paraffin-embedded tissue blocks by φ4 mm biopsy punch and then used for
deparaffinization and tissue clearing according to the protocol shown in Figure 5a.

Negative

Gross

Macroscopically
positive

H&E

2 mm

IHC
Cytokeratin

2 mm

2 mm

DAB Hematoxylin

Figure S7 | Macroscopically visualized metastatic carcinoma nodules in the lymph node with
CUBIC. (Upper panels) Gross images of the lymph nodes which were macroscopically positive or
negative for metastatic carcinoma, related to Figures 6b and 6c. As shown in the positive case, thenodules of metastatic carcinoma showed resistance to clearing and thus they were macroscopicallyobservable as yellowish-white masses which was distinguishable from transparent normal lymph
node areas. (Middle and lower panels) Post-CUBIC evaluation by H&E and immunohistochemical
staining of the samples above. After the gross image acquisition, the lymph nodes were washed with
PBS, and then subsequent paraffin embedding, sectioning, H&E staining and immunohistochemistrywith anti-cytokeratin antibody were performed.

H&E

Case #1

3D-reconstructed

1 mm

1 mm

1 mm

Case #2

1 mm

SYTO 16 Cytokeratin

Figure S8 | 3D models of lymph nodes with artefactual signals. The reconstructed 3D images oflymph nodes in which suspicious signals were observed in 3D evaluation but these were proven to
be artefact in subsequent 2D evaluation using H&E-stained sections at the suspicious signals. In thecases shown here, these signals (white arrowhead) seem to be derived from autofluorescence ofsmall vessels with congestion and/or hemorrhage around them (black arrowhead).

1

SUPPLEMENTARY MOVIE LEGENDS

2

4

Supplementary Movie 1. The human lung tissue stained with an anti-α-SMA
antibody and SYTO 16, related to Figure 2b.

5

The reconstructed 3D image of CUBIC-cleared human lung tissue stained with Alexa

6

Fluor 647-conjugated anti-α-SMA antibody and SYTO 16, which was obtained by

7

confocal microscopy.

389Supplementary Movie 2. The SYTO 16-stained human lung tissue, related to10

Figure 2d.

11

The reconstructed 3D image of CUBIC-cleared human lung tissue stained with SYTO

12

16, which was obtained by LSFM.

13
14

Supplementary Movie 3. The SYTO 16-stained human lymph node tissue,

15

related to Figure 2d.

16

The reconstructed 3D image of CUBIC-cleared human lymph node tissue stained

17with SYTO 16, which was obtained by LSFM.

1820

Supplementary Movie 4. The Congo Red-stained human lung tissue, related to
Figure 3d.

21

The reconstructed 3D image of CUBIC-cleared human lung tissue after Congo Red

22

staining, which was obtained by confocal microscopy.

19