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The extracellular matrix (ECM) is a master regulator of cellular phenotype and behavior. It has a crucial role in both normal tissue homeostasis and disease pathology. Here we present a fast and efficient approach to enhance the study of ECM composition and structure. Termed in situ decellularization of tissues (ISDoT), it allows whole organs to be decellularized, leaving native ECM architecture intact. These three-dimensional decellularized tissues can be studied using high-resolution fluorescence and second harmonic imaging, and can be used for quantitative proteomic interrogation of the ECM. Our method is superior to other methods tested in its ability to preserve the structural integrity of the ECM, facilitate high-resolution imaging and quantitatively detect ECM proteins. In particular, we performed high-resolution sub-micron imaging of matrix topography in normal tissue and over the course of primary tumor development and progression to metastasis in mice, providing the first detailed imaging of the metastatic niche. These data show that cancer-driven ECM remodeling is organ specific, and that it is accompanied by comprehensive changes in ECM composition and topological structure. We also describe differing patterns of basement-membrane organization surrounding different types of blood vessels in healthy and diseased tissues. The ISDoT procedure allows for the study of native ECM structure under normal and pathological conditions in unprecedented detail.

The ECM spans the intercellular space in all solid tissues. It is com-posed of a highly complex and diverse collection of more than 300 proteins and sugars1. The ECM is considered to be one of the most important regulators of cellular and tissue function in the body, providing crucial topological, mechanical and biochemical cues to cells2. In solid tissues, ECM remodeling and homeostasis is essential for development, wound healing and normal organ function. Deregulation of ECM homeostasis, including degradation, overproduction or biochemical and biomechanical alterations, form the basis of many types of pathology and disease, including cancer3. Both ‘deregulated’ and ‘normal’ ECM provide strong signaling cues

to cells that confer selective advantages and disadvantages4. Thus, the extrinsic influence of the ECM is as important as intrinsic cellular drivers in tissue homeostasis and disease. As such, changes in the ECM mark significant transition events in disease progression5. With this in mind, a better characterization of native ECM composition and its biochemistry, spatial distribution and organization is needed to provide a more complete understanding of its role in normal and pathological settings.

Whereas early studies typically characterized single ECM compo-nents, recent advances in mass spectrometry have accelerated the pace of ECM cataloging in disease (reviewed in ref. 6). Although this information is invaluable in understanding how ECM composition changes in disease, we still lack tools to facilitate high-definition inter-rogation of global three-dimensional (3D) topology of the ECM, or to study cell interactions with native ECM. Current methodologies designed to enable deeper probing into native tissues have focused on tissue fixation and clearing approaches and on advances in micros-copy to increase optical access through large volumes of tissue. These approaches include PACT, CLARITY, Scale/ScaleA2, SeeDB, PARS, ClearT/ClearT2, 3DISCO, RIMS, FocusClear, CUBIC, LUMOS, DBE and BABB7–18. Some of these methodologies are tailored to specific organs, in particular, neuronal tissues such as the brain, whereas others, such as 3DISCO, can be applied more broadly. The key aim of these approaches is to increase imaging resolution while preserving cellular structure. These approaches are not, however, optimized for improv-ing the resolution at which the ECM architecture can be imaged. Moreover, many of these approaches involve tissue fixation, which could affect tissue integrity and biomolecular structures, introduce artifacts or irreversibly denature biomolecules.

To address these limitations, we have developed a novel method-ology termed ISDoT. Our approach is designed to achieve complete decellularization of any tissue or anatomical organ system in situ while preserving ECM architecture. The ISDoT methodology makes use of native tissue and organ vasculature to efficiently remove cells, prevent tissue collapse and leave the structural ECM of tissues unal-tered. Following ISDoT, we analyzed decellularized tissue by global

ISDoT: in situ decellularization of tissues for high-resolution imaging and proteomic analysis of native extracellular matrixAlejandro E Mayorca-Guiliani1,4, Chris D Madsen1,2,4, Thomas R Cox1,3,4, Edward R Horton1, Freja A Venning1 & Janine T Erler1

1Biotech Research and Innovation Centre (BRIC), University of Copenhagen (UCPH), Copenhagen, Denmark. 2Department of Laboratory Medicine, Division of Translational Cancer Research, Lund University, Lund, Sweden. 3The Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Cancer Division, St Vincent’s Clinical School, Faculty of Medicine, University of New South Wales Sydney (UNSW Sydney), Sydney, New South Wales, Australia. 4These authors contributed equally to this work. Correspondence should be addressed to J.T.E. (janine.erler@bric.ku.dk).

Received 4 August 2016; accepted 11 May 2017; published online 12 June 2017; doi:10.1038/nm.4352

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proteomic cataloging and spatially mapped ECM proteins in the tis-sue. Using ISDoT, we provide what is, to our knowledge, the first detailed high-resolution sub-micron imaging of matrix topography in in vivo models of ECM remodeling.

RESULTSDecellularization of target organsOptimal decellularization of tissue removes all cellular components while leaving the supporting acellular matrix intact and undamaged. To achieve this goal, we developed a new vascular-flow-directed decellularization approach, which efficiently delivers decellulariza-tion reagents through the cardiovascular system of the mouse to any organ or tissue of choice. As a first step, major vessels of the heart are liberated from their surrounding connective tissues. The vessels are then clamped to allow vascular flow to be directed to the tissue or organ of interest. Retrograde-shunted flow through the descend-ing aorta allows for the perfusion of target tissues or organs with specific reagents through a peristaltic pump for rapid and efficient decellularization (Supplementary Fig. 1a). A fully narrated operation can be seen in an accompanying video (Supplementary Video 1). Surgical direction of vascular flow through selected vessels allows for the targeted decellularization of any anatomical area and tissue of interest. The anatomical configurations for decellularization of the mammary fat pads (Fig. 1a), lungs (Fig. 1b), head and neck regions (Supplementary Fig. 1b) and liver (Supplementary Fig. 1c) are sum-marized in Supplementary Table 1. A representative timeline for decellularization of the lungs is shown in Figure 1c. By carrying out the decellularization process in situ under controlled flow rates19, we prevent collapse of the vascular system and, in turn, of the tissue, which greatly facilitates the preservation of the delicate structure and 3D distribution of native ECM.

Verification of decellularization efficacy and assessment of tissue integrityWe first verified that the ISDoT procedure led to the complete removal of resident cells by assessing the decellularized tissue for DNA content in healthy mammary fat pad, lymph node, lung and tongue of mice, following a perfusion schedule of deionized water, 0.5% sodium deoxycholate, Triton x-100, 0.01% peracetic acid and PBS (Supplementary Fig. 1d). In addition to this, we stained for filamentous actin in fresh and decellularized mammary fat pad using FITC-phalloidin (Supplementary Fig. 1e). No detectable cells and no substantial levels of cellular DNA remained present after the ISDoT procedure.

To determine whether basement membrane (BM) integrity sur-rounding blood vessels was maintained following the ISDoT proce-dure, we perfused ISDoT lungs through the pulmonary vein with a red poly-methyl-methacrylate to generate a vascular cast (Fig. 2a). The poly-methyl-methacrylate was contained within the BM of the venous pulmonary circulation (Fig. 2a, left and center). The removal of organic tissue from the cast using chemical maceration agents allowed for the determination of the integrity of vessels. In these casts, vessels with a luminal diameter of less than 20 µm remained intact (Fig. 2a, right). To determine the integrity of smaller vessels, we perfused lungs with 5 × 105 Da dextran-TRITC through the pulmonary veins immediately after decellularization was completed. 30 min after dextran-TRITC perfusion, imaging of the ISDoT lung tissue showed that the dextran was contained within blood vessels with lumen sizes as narrow as ~3 µm (Fig. 2b). These findings confirm

that the integrity of even the smallest blood vessels is maintained post decellularization when ISDoT is used.

To ensure that ISDoT does not distort the tissue morphology or spa-tial distribution of ECM components, we evaluated fibrillar collagen expression and distribution, given that this represents the bulk of many tissues and can be visualized natively without immunolabeling, using second harmonic generation (SHG) imaging. Comparison of fresh and matched ISDoT tissues showed no evidence of distortion of fibril-lar collagen in mammary fat pads, lymph nodes, liver or lungs (Fig. 2c, Supplementary Figs. 2,3 and 4a and Supplementary Videos 2–5). The distribution and orientation of collagen fibers were assessed as previously described20, and showed no significant differences between fresh and ISDoT decellularized tissue (Fig. 2c, bottom). Assessment of inter-fibril gaps21,22 showed no difference between fresh and ISDoT lung tissue (Fig. 2d), which, if present, would be indicative of an overinflated or collapsed tissue structure during decellularization. To verify fibril integrity, we measured fibril diameter in fresh and ISDoT mammary fat pads, lungs and 4T1 orthotopically implanted mammary tumors. We observed no notable variation in collagen fibril diameters between fresh and ISDoT tissue (Supplementary Fig. 3). Thus, we find that ISDoT preserves the overall integrity and structure of the native ECM in these tissues.

We subsequently compared ISDoT to previously published tissue decellularization approaches that utilize ex vivo agitation and ex vivo perfusion, using sodium dodecyl sulfate (SDS)23–26. The ISDoT method, by using low (0.5% to 1%) sodium deoxycholate (DOC) in an environment where perfusion and decellularization occur in situ at a flow rate lower than the physiological flow rate (Supplementary Table 1), when directed by surgical vascular shunt-ing, produced decellularized tissues with a collagen structure identi-cal to that of fresh tissue in the fat pad, lung, lymph node, and liver tissue (Fig. 2 and Supplementary Figs. 2–4). By contrast, the previ-ously published methods that we tested—1% SDS-based agitation23 and ex vivo perfusion with 1% SDS24–26—led to alterations in col-lagen structure and organization (Supplementary Figs. 2 and 4), as well as marked differences in BM surrounding vessels of the lung (Supplementary Fig. 4b). More specifically, we observed that the agi-tation approach has the tendency to physically and chemically disrupt the tissue, as exemplified by loss of the SHG signal (Supplementary Figs. 2a and 4a) and an apparent loss of ECM from the entire cortical surface of the lungs (Supplementary Fig. 2b, bottom). The ex vivo perfusion approach24–26, on the other hand, led to artificial linearization of normally curly collagen fibrils in the mammary fat pad (Supplementary Fig. 2a, center two images). The optimal com-position of detergents for the ISDoT procedure, as well as the optimal flow rate for decellularization of each individual organ, are shown in Supplementary Table 1. For instance, the lymph nodes and tongue were not affected by the choice of detergent, whereas the structure of the mammary fat pad and liver collagen was preserved only when sodium deoxycholate was used as the detergent (Supplementary Fig. 2a). Thus, our data highlight the advantage of ISDoT tissue-specific protocols over previously published approaches.

ECM remodeling of the mammary gland during lactationFirst, we applied ISDoT to study remodeling of the mammary gland during lactation, a normal developmental program that leads to sub-stantial ECM and vascular remodelling27,28. We visualized the glan-dular and ductal structures of a mammary gland from a lactating mouse in ISDoT tissues by both SHG imaging and by staining for

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collagen type IV. A tiled image of a 5 × 5–mm region of a whole-mount mammary gland confirmed the presence of enlarged and dilated lactating ducts and alveoli27, which were accompanied by de novo angiogenesis around the gland lobules (Supplementary Fig. 5a,b). Structural characterization of collagen fibers revealed prominent

remodeling, resulting in the linearization of fibers (Supplementary Fig. 5a,c). In line with these findings, ductal outgrowth of ‘terminal end buds’ during puberty and lactation have previously been shown to run parallel to clusters of collagen fibers29.

Basal lamina of peripheral nervesPeripheral nerves are protected by three layers of connective tissue (the epineurium, perineurium and endoneurium) that surround the nerve (Supplementary Fig. 5d)30,31. These layers comprise both fibrillar collagen and BM containing collagen type IV31–33. In view of their delicate and complex structure, they provided a challenging test case for the ISDoT approach. Because ISDoT clears all cellular content, we were able to stain the entire organ or tissue to visual-ize the organization of structures such as peripheral nerves in 3D. Collagen-type-IV staining of ISDoT mammary fat pads clearly showed the structure of peripheral nerve bundles in the mammary fat pad (Supplementary Fig. 5d,e and Supplementary Video 6). Collagen type IV was found in both the perineurium and endoneurium of the nerves (Supplementary Fig. 5e,f). The staining also revealed vessels running along the outside of the peripheral nerves (Supplementary Fig. 5e, arrowheads), as well as intraneural vessels running inside the perineurium (Supplementary Fig. 5f, center and right, arrow-heads). The staining also highlighted the presence of nodes of Ranvier (asterisk, Supplementary Fig. 5f, right), which are points of discon-tinuity between adjacent myelin sheaths in which the axon is not covered by myelin34,35. Finally, our imaging clearly showed the pres-ence of terminal nerve endings, similar to the ones observed in the skin36, within the mammary fat pad (Supplementary Fig. 5f). To our knowledge, these are the first 3D reconstructions of the BM organiza-tion of peripheral nerves and their terminal endings.

The 3D structure of the primary breast cancer nicheNext, we used ISDoT to investigate the ECM during the progression of primary breast cancer. ISDoT was performed on 4T1 mouse mam-mary tumors grown orthotopically in the mammary fat pad. In line with previous research37, we found that tumor growth was associated with the linearization of collagen fibers around and within the developing tumor (Fig. 3a). We also stained ISDoT primary tumors for nidogen-1 to visualize tumor-associated angiogenesis. Nidogen-1 deposition was associated with abnormal vessel structures (asterisk, Fig. 3b), as well as with filamentous structures disconnected from the vasculature (arrowheads, Fig. 3b and Supplementary Video 7). Although nidogen-1 has previously been observed at the invasive front of human endometrial tumors and has been shown to enhance endometrial tumor growth and metastatic dissemination38, these thin nidogen-1 fibers (~500 nm in diameter) have not, to our knowledge, previously been observed. Their presence suggests that nidogen-1 might have functions independent of its role in the vascular BM in breast cancer.

We also observed disrupted BM architecture adjacent to the primary tumor. Nidogen-1 staining revealed mammary-gland-like structures in the perilesional region that exhibited discontinuous nidogen-1 coverage (asterisk, Fig. 3c), and holes with a diameter of between 7 and 17 µm (arrowheads, Fig. 3c). Such BM perforations have been observed during branching morphogenesis of the mouse salivary, lung and kidney glands39, and these perforations are thought to promote branch outgrowth39. These observations suggest that remodeling of blood vessels accompanies tumor growth at the invasive edge, and they indicate the presence of a ‘field effect,’ which has been shown to be important in tumor progression and metastasis40,41.

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Figure 1 Surgical modification of vascular flow for decellularization. (a) Left, operation for decellularization of the left mammary fat pad, the upper extremity and the base of the neck. Clamp 1, aortic arch before the emergence of the left subclavian artery; clamp 2, left brachiocephalic vein; clamp 3, descending cava vein. Black arrowhead, left mammary artery; green arrow, retrograde catheterization of the thoracic aorta; red arrow, flow evacuation through the left mammary artery. Middle, dark-field microscopy images of the axillary lymph node (top; scale bar, 300 µm) and the mammary fat pad (bottom; scale bar, 2 mm) using the ISDoT procedure, according to the operation shown at left. Right, operation for decellularization of the right mammary fat pad, the upper extremity and the base of the neck. Clamp 1, left brachiocephalic vein; clamp 2, left subclavian artery; clamp 3, left common carotid artery; clamp 4, aortic arch before the emergence of the brachiocephalic artery; clamp 5, right common carotid artery; clamp 6, descending cava vein. Black arrowhead, right mammary artery; green arrow, retrograde catheterization of the thoracic aorta; red arrow, flow evacuation through the right mammary artery. (b) Left, operation for decellularization of the cardiopulmonary complex. Clamp 1, left brachiocephalic vein; clamp 2, left subclavian artery; clamp 3, left common carotid artery; clamp 4, brachiocephalic artery; clamp 5, right brachiocephalic vein before the entrance of the parasternal vein; clamp 6, descending cava vein. Black arrowhead, aorta; green arrow, retrograde catheterization of the thoracic aorta; red arrow, flow evacuation through the right parasternal vein. Right, dark-field microscopy images of a left lung (left image) and a right lung lobe (right image) using the ISDoT procedure, according to the operation shown at left (scale bars, 2 mm). (c) Photographic images of a lung at the indicated time points after commencing perfusion for decellularization (scale bars, 4 mm).

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Cataloging the ECM at the cancer nicheBy efficiently removing cellular components from tissues, ISDoT enriches tissue samples for ECM components. To demonstrate the potential of this approach for biochemical analysis of the enriched tissue ECM using global quantitative approaches such as mass spec-trometry (MS), we carried out rapid, single-shot, unfractionated, label-free, quantitative proteomics on normal and tumor-remodeled ECM isolated using ISDoT (Supplementary Fig. 6a). We took advan-tage of the orthotopic 4T1 breast cancer model that develops spon-taneous metastases to multiple organs, including lymph nodes and lungs (Fig. 4a)42–44. Proteomic analysis of 4T1 primary tumors, meta-static lymph nodes and metastatic lungs, along with their matching healthy tissue, was cross-referenced to the matrisome database (http://matrisomeproject.mit.edu; June 2016 version)1. The matri-some database compiles in silico and experimental data on matrisome genes and proteins.

We identified 3,522 proteins in all the samples analyzed, includ-ing 226 ECM proteins that are annotated in the matrisome database (Fig. 4b, Supplementary Fig. 6b–d and Supplementary Table 2). These results demonstrate that the ISDoT procedure can be used to analyze all subclasses of ECM components (collagens, proteoglycans, glycoproteins, ECM-affiliated proteins, ECM regulators and secreted factors) (Fig. 4b and Supplementary Table 2). In particular, ISDoT allowed for the proteomic detection of secreted proteins (including MMP9, nine members of the S100 family (a1, a4, a6, a8, a9, a10, a11, a13 and a14), epidermal growth factor–like protein 7, angiopoietin 2, host cell factor C2, CCL6/MRP1 and interleukin 1 receptor antagonist), as well as proteoglycans (including HSPG2, biglycan, decorin, lumican and versican) (Fig. 4c and Supplementary Table 2). All subclasses of ECM components could be detected in all organs studied (Supplementary Fig. 6b–d and Supplementary Table 2), which suggests that ISDoT can be applied to a variety of tissues and organs without the loss of ECM components.

Differential analysis between matched normal and diseased tissue highlighted tumor- and metastasis-specific changes in ECM com-position (Fig. 4c). Interestingly, different ECM proteins showed alternate changes in abundance at the two metastatic sites (lymph node and lungs), as compared to the corresponding normal tissue. Unsupervised clustering demonstrated that changes in the ECM com-position in metastatic lung are more similar to changes in ECM com-position at the primary tumor, when compared to changes in ECM composition in metastatic lymph nodes (Supplementary Fig. 6e). This concept is further illustrated by a functional-enrichment analysis in which changes in protein abundance are hierarchically clustered according to cellular components (Fig. 4d) and biological processes (Supplementary Fig. 6f). This clustering shows that there are oppos-ing effects on the abundance of subclasses of ECM components at the two metastatic sites. For example, the majority of extracellular matrix, basal lamina and BM proteins, including collagen type IV, laminins and nidogen, are downregulated in metastatic lung, when compared to normal lung, whereas they are highly upregulated in metastatic lymph node relative to in normal lymph node (Fig. 4d).

ISDoT enhances the depth and clarity of imagingTo demonstrate that ISDoT enhances the depth and clarity of imaging, we performed a side-by-side comparison of the maximum achievable imaging depth in freshly excised lymph node, PFA-fixed lymph node and ISDoT-decellularized lymph node. Using identical configurations and laser settings, we were able to detect the SHG signal at a depth of 100 µm in freshly excised lymph nodes, whereas we could reach a

depth of more than 200 µm in ISDoT lymph nodes (Supplementary Fig. 7a). We then turned our attention to immunostained tissue. PFA-fixed and ISDoT lymph nodes were simultaneously stained and imaged for collagen type IV. The detection limit was approxi-mately 20 µm in PFA-fixed lymph nodes, but reached over 150 µm in ISDoT lymph nodes using the exact same staining and image-acqui-sition protocol (Supplementary Fig. 7b,c and Supplementary Video 8). Increasing the laser power further improved the penetra-tion depths (Supplementary Fig. 7d). These results show that the

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Figure 2 Integrity validation and analysis of the structure of ISDoT tissues. (a) Polymer cast of ISDoT lungs. Left, image of ISDoT lung lobes after intra-aortic injection of casting polymer (scale bar, 1 mm). Middle, image of polymer casting in the vascular compartment of pulmonary ECM (scale bar, 1 mm). Right, image of plastic casting polymer in the terminal vessels of a lung after removal of the ECM; the lumen diameter of two terminal vessels is indicated (scale bar, 40 µm). (b) SHG and fluorescence imaging of ISDoT lungs perfused with dextran-TRITC (MW: 5 × 105 Da). Dextran is still retained within the vessels 30 min after perfusion. Vessel diameter as indicated (scale bars, 100 µm, and 25 µm in the inset). (c) Fibril-orientation analysis of mammary fat pad, lymph node and lung ISDoT organs. Top row, fibril-orientation analysis overlay of SHG imaging of fresh mammary fat pad, lymph node and lung. Middle row, fibril-orientation analysis overlay of SHG imaging of ISDoT fat pad, lymph node and lung (scale bars, 40 µm). Bottom row, fibril-alignment analysis of fresh to matched ISDoT fat pad (n = 13 per group), lymph node (n = 6 per group) and lung (n = 8 per group). Color scale bar indicates the color overlay assigned to a specific angle of the fibrils. Scale bars, 40 µm. (d) Inter-fiber gap analysis of SHG imaging of fresh lung (top) and ISDoT lung (middle). Bottom right, quantification of inter-fiber gaps (n = 8 per group). (Scale bars, 40 µm). Statistics performed using Mann–Whitney U test.

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ISDoT platform improves imaging depth and clarity for both SHG imaging and immunostained samples. It also underlines its supe-rior application for 3D reconstruction of immunostained tissue (Supplementary Video 8).

Visualization of metastatic-lymph-node remodelingThe spread of cancer cells to the lymph nodes is accompanied by changes in the density and structure of the vascular network within the lymph node. These findings are supported by our proteomics data showing altered levels of many BM proteins, including collagen type IV, laminins and nidogen (Fig. 4 and Supplementary Fig. 6). To image vascular changes in the metastatic lymph node, we performed ISDoT on metastatic lymph nodes in two metastasis models, the 4T1 orthotopic breast cancer model44 and the B16 oral cancer model45. Consistent with the proteomic data, staining of whole-mount ISDoT lymph nodes obtained from both cancer models showed altered deposition of various BM components in metastatic lymph nodes as compared to matched healthy lymph nodes (Fig. 5a, Supplementary Fig. 8a–c and Supplementary Videos 9 and 10). In some instances, we observed laminin rings around vessels that followed a periodic pattern and were themselves surrounded by a sheath of fibrillar collagen (Fig. 5b, Supplementary Fig. 8d and Supplementary Video 11). This regular pattern is comparable to that of mural cells covering arterioles46,47. In other cases, we noted an irregular and disorganized BM around the vessels in metastatic lymph nodes (Fig. 5c,d and Supplementary Fig. 8c); in these situations, the BM appeared to be undergoing ‘sprouting outgrowth’ directed by a reticular network of collagen type IV fibers (Fig. 5c)48. BM sprouting similar to this has previously been described in MCa-IV mammary mouse carcinomas49, but not in lymph nodes.

We observed other alterations in the BM of the metastatic niche that, to our knowledge, have not been previously described. In metastatic lymph nodes, bleb-like protrusions were present along the subcortical vascular network (Fig. 5e). These bleb-like structures are indicative of a different type of vascular remodeling than the sprouting protrusions described above. We speculate that these bleb-like structures could be similar to the unusual bleb-like protrusions observed in melanoma-associated endothelial cells50.

Visualization of metastatic lung remodelingMetastasis has been linked to changes in the ECM at secondary sites. In spontaneous lung macro-metastases, we observed fibrillar colla-gen remodeling, as assessed by fiber-alignment analysis, in ISDoT tissue similar to that seen in fresh metastatic tissue, reconfirming that the ISDoT procedure does not distort the integrity of the ECM in the metastatic niche (Fig. 6a, right top). However, healthy and metastatic ISDoT lungs showed a significant difference in fiber align-ment, indicating linearization and realignment of collagen within metastatic lung tissue (Fig. 6a). We also observed clear evidence of tissue remodeling at the site of early lung metastases (Fig. 6b,c). These data suggest that ECM remodeling during lung colonization goes through phases; with an initial remodeling phase in micro-metastases in which small holes in the lung are generated, followed by a late phase in which the rapidly growing tumor (macro-metastases) expands and pushes the native collagen fibers outwards, generat-ing linearized fibers that surround the tumor. Moreover, imaging of the BM surrounding lung macro-metastases revealed deposition and remodeling of collagen type IV both in the metastasis paren-chyma and at its invasive front; along with deposition of linear-ized collagen type I in the invasive front of the metastasis (Fig. 6d),

illustrating the transition from normal to cancer-associated ECM at the tumor margin. Collagen-type-IV staining also demonstrated alterations in the vasculature within metastases as compared to the surrounding network in the normal alveoli (Fig. 6d). To our knowledge, these are the first high-resolution images showing ECM and BM remodeling in breast cancer lung metastases.

ECM remodeling in oral cancerTo further illustrate the versatility of ISDoT in organ decellulariza-tion and imaging, we studied a second cancer model. In this model, the implantation of B16-F10 cells into the tongue resulted in loss of the normal ECM structure of the tongue, illustrating how oral cancer remodels the native ECM (Supplementary Fig. 9a). It is possible to use residual melanin autofluorescence as a surrogate marker for tumor cell presence after decellularization (Supplementary Fig. 9a). In a sagittal view of the tip of the tongue, processed using ISDoT and immunostained for collagen type IV, we observe collagen

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Figure 3 The 3D structure of the primary breast cancer niche. (a) Fibril-orientation analysis from SHG imaging of mammary fat pads. The micrographs show SHG imaging of normal, fresh fat pad, (left); normal ISDoT fat pad (middle); 4T1 breast tumor ISDoT tissue (right). Scale bars, 40 µm. The graph shows quantitative data comparing fiber orientation in ISDoT normal fat pad and 4T1 breast tumors. Color codes refer to fiber-orientation angle. (b) Left, whole-mount staining of nidogen 1 (Alexa-Fluor 488) in ISDoT 4T1 mammary carcinoma. The image shown is a maximum projection of a z-stack. White arrowheads, intratumoral nidogen-1 fibers. Right, the same image, including SHG imaging, merged with nidogen-1 staining. Scale bars, 50 µm. (c) Left, whole-mount staining of nidogen 1 (green) in ISDoT mammary ducts adjacent to a 4T1 tumor. The image shown is a maximum projection of a z-stack. Right, higher-magnification views of z-stacks at of the boxed area in the left micrograph. “Z” values indicate the depth of the stack in the z-plane. White arrowheads, perforations in duct structures; asterisks, discontinuous ducts. Scale bars, 100 µm. Statistics performed using Mann–Whitney U test.

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–1.2

–1.5

–1.7

–0.9

–0.3

–1.8

2.0

0.9

–1.5

2.6

1.7

3.4

1.4

0.8

4.2

–1.5

–0.6

0.4

2.4

1.9

1.5

3.1

1.4

6.0

–2.8

–1.3

3.0

0.3

–3.7

met

LN/L

N

3.2

0.7

–0.6

2.1

11.5

3.5

3.4

4.1

1.8

1.8

0.2

–1.1

1.1

1.7

2.7

1.4

0.3

0.4

2.0

1.0

–0.2

1.6

2.1

3.7

2.1

0.8

1.4

2.4

0.9

–0.4

2.7

0.5

–0.7

0.9

0.1

0.7

2.4

–0.1

–0.2

4.6

0.3

6.7

met

Lung

/lung

0.6

–4.0

–4.7

–3.3

–3.2

–1.9

–3.4

–3.1

–2.6

–3.7

4.3

1.9

0.2

–2.6

–1.5

–0.7

–0.6

–1.5

–1.7

–1.1

4.3

–1.5

2.4

–1.1

–3.0

–2.9

–3.3

–3.4

–0.9

0.7

–2.5

–2.2

3.2

–1.8

0.0

7.5

–1.8

0.2

2.2

5.6

–3.9

–1.6

–0.4

–1.2

0.5

–0.1

–1.4

–4.6

–0.9

8.6

–3.7

–1.5

–3.3

–0.2

–2.9

–3.7

Itih2

Itih3

Itih5

Lama1

Lama2

Lama3

Lama4

Lama5

Lamb1

Lamb2

Lamb3

Lamc1

Lamc2

Lgals1

Lgals3

Lgals9

Lman1

Loxl1

Ltbp1

Ltbp4

Lum

Mbl2

Megf6

Mfap2

Mfap4

Mfap5

Mfge8

Mmp9

Mmrn1

Mmrn2

Nid1

Nid2

Npnt

Ogn

Plg

Postn

Prelp

Prg2

Pxdn

S100a10

S100a13

S100a6

S100a8

S100a9

Serpina1b

Serpina3k

Serpinb1a

Serpine2

Serpinh1

Sftpa1

Sftpb

Sftpd

Spon1

Tgfbi

Tgm2

Thbs1

Tinag

Tinagl1

Tnc

Tnxb

Vcan

Vtn

Vwa1

Vwf

Wisp2

Tum

/FP

–1.3

1.6

3.2

2.9

1.6

1.8

2.2

0.4

0.4

1.4

–0.7

0.9

4.9

7.9

0.0

–1.9

1.5

–0.1

–0.2

0.7

–0.3

0.1

0.6

1.0

0.5

0.4

7.4

2.5

1.0

0.7

0.8

–1.4

–0.6

1.3

–0.1

–0.3

0.2

0.3

2.6

4.2

5.0

–0.1

0.8

0.7

1.1

0.7

2.7

–0.3

met

LN/L

N

1.7

6.2

–0.3

–1.0

–1.1

1.8

–1.5

–2.1

–2.2

–3.0

1.0

2.7

1.5

0.3

–1.6

2.2

0.1

–0.6

–1.1

0.9

1.3

0.3

0.4

–0.4

0.6

0.8

0.0

6.0

–1.0

4.4

–0.1

0.3

–2.1

1.6

1.4

3.7

0.4

–0.2

1.1

2.2

3.5

2.7

0.9

0.0

0.2

1.4

0.7

1.0

–0.8

1.4

0.5

met

Lung

/lung

–0.7

–2.5

–2.1

3.9

1.3

1.3

3.6

1.0

3.1

1.3

3.1

–4.7

–0.4

–2.2

1.1

–0.1

–0.7

–0.4

0.5

–0.3

0.9

–0.1

–1.9

–4.7

–3.5

–1.8

–0.1

–1.1

–1.4

–1.6

3.5

–0.6

5.6

–1.0

5.5

4.3

–1.7

–1.0

–1.3

–3.2

–0.4

–1.6

3.2

–0.5

0.5

–2.1

2.5

0.7

3.3

–3.4

–0.9

0.5

0.5

–0.7

–0.3

0.1

2.0

–2.6

–2.0

–1.6

2.1

A2m

Agrn

Ambp

Anxa1

Anxa11

Anxa2

Anxa3

Anxa4

Anxa5

Anxa6

Anxa7

Aspn

Bgn

Bmper

C1qa

C1qb

Col12a1

Col14a1

Col15a1

Col18a1

Col1a1

Col1a2

Col3a1

Col4a1

Col4a2

Col4a3

Col4a4

Col4a5

Col5a2

Col6a1

Col6a2

Col6a3

Col6a5

Col6a6

Col7a1

Colec12

Ctsb

Ctsd

Ctsg

Ctsz

Dcn

Dpt

Ecm1

Efemp1

Efemp2

Egfl7

Elane

Eln

Emid1

Emilin1

Emilin2

F13a1

Fbln2

Fbln5

Fbn1

Fbn2

Fga

Fgb

Fgg

Fn1

Hcfc1

Hmcn1

Hspg2

Htra1

Igfbp7

ca

b

dFat pad

Lymph node

Collagens

ECM glycoproteins

Proteoglycans

ECM affiliated

ECM regulators

Core matrisome

Secreted factors

Matrisome associated

6(21%)

13(11%)

30(15%)

104(58%)

43(27%)

Full matrisome

17(21%)

34(42%)

30(37%)

79(69%)

23(22%)

Matrisome(24)

Matrisome(60)

Matrisome(92)

Matrisome(8)

Matrisome(51)

Matrisome(143)

Matrisome(5)

Matrisome(18)

Matrisome(28)

ISDoT-MS(23)

ISDoT-MS(68)

ISDoT-MS(102)

ISDoT-MS(11)

ISDoT-MS(64)

ISDoT-MS(166)

ISDoT-MS(11)

Healthyfatpadenriched

HealthyLNenriched

Basal lamina

Extracellular matrix

Basement membraneExtracellular matrix partFibrillar collagen

Collagen IV Sarcolemma

Fibrillar collagenBasal lamina

Extracellular matrix

Extracellular matrix part

Extracellular spaceSarcolemma

Collagen IV

Basement membrane

MetastaticLN

enriched

Healthylungenriched

Metastaticlung

enriched

Primarytumor

enriched

Fibrillar collagen

Basal lamina

Extracellular matrix

Extracellular spaceSarcolemmaExtrinsic to membrane

Collagen lV

Basement membrane

ISDoT-MS(24)

ISDoT-MS(29)

18(62%)

5(17%)

7(9%)

0(0%)

6(20%)

1(8%)

4(33%)

7(58%)

10(26%)

18(46%)

11(28%)

12(40%)

12(40%)

8(73%)

3(27%)

53(71%)

15(20%)

Anx

a1A

nxa1

Anx

a2A

nxa2

Col

1a2

Col

1a2

Col

18a1

Col

3a1

Col

7a1

Fn1 Tnc

Tnc

Tnx

b

Col

15a1

Col

6a2

Fbn

2M

fap5

Em

id1

Em

id1

Lgal

s3

Prg

2T

gfbi

Col

4a1

Col

4a1

Col

4a2

Col

4a2

Col

5a2

Col

5a2

Col

1a1

Col

1a1

S10

0a13

S10

0a13

Col

4a3

Col

4a4

Col

4a5

Agr

n

Agr

n

Hsp

g2

Hsp

g2

Lam

a4

Lam

a4

Lam

a3La

ma3

Lam

a5

Lam

a2

Lam

a5La

mb1

Lam

b1La

mc1

Fbn

1

Fn1

Nid

2

Nid

1M

mrn

2La

mb2

Vw

a1E

gfl7

Mfg

e8B

gn

Col

7a1

Fbn

2M

fap5

Col

18a1

Lam

b3La

mc1

Lam

c2La

ma2

Fbn

1C

ol15

a1H

mcn

1

Nid

2N

pnt

Lam

b2M

mrn

2N

id1

Vw

a1B

mpe

rS

erpi

na1b

Bgn

Col

6a1

Col

6a2

Col

6a1

Col

6a3

Col

6a3

Fbl

n5F

bln5

Loxl

1Lo

xl1

Prg

2Lg

als3

Em

ilin1

Asp

nP

ostn

Ltbp

1T

gm2

Tgf

biLt

bp4

Lum

Vtn

Asp

nE

fem

p2E

mili

n1Lu

mLt

bp4

Tgm

2V

tnV

can

Ltbp

1P

ostn

Tnx

b

Ecm

lT

hbs1

Mfg

e8

Anx

a1C

ol3a

1C

ol5a

2C

ol4a

2A

grn

Lam

a5La

mb1

Lam

c2La

mb3

Fbn

2F

n1C

ol7a

1C

ol18

a1 Tnc

Vw

a1B

gnC

ol6a

1C

ol6a

2C

ol6a

3P

rg2

Em

ilin1

Ltbp

4Lg

als3 Vtn

Ltbp

1P

ostn

Tgm

2

Col

1a1

Col

1a2

Col

4a1

Lam

a2H

spg2

Lam

a4La

ma1

Lam

a3La

mc1

Fbn

1M

fap5

Col

15a1

Nid

1La

mb2

Nid

2Lo

xl1

Asp

nV

can

Lum

Tnx

bM

bl2

Mfg

e8S

erpi

na1b

Egf

l7

Lung

Protein

Protein

Protein

Cel

lula

r co

mpo

nent

Cel

lula

r co

mpo

nent

Cel

lula

r co

mpo

nent

Tgf

biE

cm1

Lgal

s1S

100a

13T

hbs1

Anx

a2 Plg

S10

0a10

–

Decellularization

0+

Figure 4 Mass spectrometry analysis of ISDoT ECM-enriched tissues. (a) ISDoT removes cellular material and enriches for ECM components. (b) Overlap between identified matrisomal proteins from ISDoT-MS samples (pink) and the Matrisome Project (blue) in lung tissue. Numbers within circles indicate the total number of identified proteins (the percentage of the total number of proteins is shown in parentheses). Numbers below indicate the total number of proteins detected in sample. n = 3 independent tissues processed for mass spectrometry per condition. (c) Heat map showing expression ratios for the indicated proteins in the indicated diseased relative to healthy tissues. FP, fat pad; LN, lymph node; metLung, lung metastasis; tum, tumor. (d) The over-represented cellular-component terms from proteins identified in ISDoT fat pad, lung and lymph node tissues were hierarchically clustered according to fold change in normal tissue relative to disease tissue (primary tumor or sites of metastases). Pink and blue boxes indicate proteins with increased and decreased abundance in diseased tissues, respectively. Clusters of proteins associated with a similar set of functional terms are grouped, as indicated by black bars (right-hand side).

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lamina of muscle cells and the BM of blood and lymph vessels51. The preservation of fibrillar collagen and collagen type IV in both the BM of the papillae and dorsum of the tongue (Supplementary Fig. 9b,c) show that ISDoT efficiently decellularizes and preserves specialized ECM structures in dense tissues such as muscle.

fibers arranged in a parallel pattern (Supplementary Fig. 9b). Moreover, collagen-type-IV immunostaining revealed vascular structures surrounded by collagen fibers (Supplementary Fig. 9b), which confirms previous reports that collagen type IV forms the basal

SHG Collagen type IV SHG collagen type IV Collagen type IV

SHG Collagen type IV SHG collagen type IV Collagen type IV

Collagen type IVCollagen type IV

SHG collagen type IV SHG collagen type IV Laminin SHG lamininHealthy Metastatica b

c

d

e

Figure 5 Visualization of metastatic lymph node remodeling. (a) Single-plane image of whole-mount staining for collagen type IV (green) and fibrillar collagen (SHG, white) in healthy C57BL/6 mouse (left) and B16-F10 melanoma metastatic (right) ISDoT lymph nodes (scale bars, 100 µm). (b) Maximum projection of z-stack taken from whole-mount staining of an ISDoT B16-F10 metastatic lymph node. Left, laminin staining (green) shows an arteriole with periodic deposition of laminin. Right, the same image merged with SHG imaging shows the arteriole surrounded by a sheath of fibrillar collagen (white) (scale bars, 20 µm). (c) Whole-mount staining for collagen type IV (green) in ISDoT 4T1 metastatic lymph nodes, revealing vascular basement-membrane structures. The images shown are the maximum projection of a z-stack. Boxed areas are enlarged in the insets. Left, note the irregular deposition of collagen type IV (scale bars, 25 µm); right, basement-membrane sprouts are clearly visible, including filopodia-like fibers (inset) (scale bars, 25 µm). (d,e) Whole-mount staining for collagen type IV (green) and fibrillar collagen (SHG, white) in ISDoT 4T1 metastatic lymph nodes showing vessel structures. The boxed areas in the second micrograph from the left are shown at higher magnification in the right-most micrograph. The images shown are the maximum projection of a z-stack. Note the presence of perforations in the basement membrane (d, white arrowheads) (scale bars, 25 µm; inset, 10 microns) and bleb-like protrusions emerging from vascular structure (e, white arrowheads) (scale bars, 50 µm; inset, 10 µm).

SHG SHG SHG SHG

Fresh

SHG

Decellularized

SHG

Met

Alveoli

SHG collagen type IV SHG collagen type IV

–90–60–30 0 30 60 900.0

0.5

1.0

1.5

2.0

2.5

3.0

–90–60–30 0 30 60 900.0

0.5

1.0

1.5

2.0

2.5

3.0

Fib

er-a

lignm

ent f

requ

ency

Alveoli

Met

SHG elastin SHG elastin SHG elastin SHG elastin

b

c

a

dMetastasis Alveoli

Metastasis Alveoli

ISDoT lung met (3)P = 0.7950

Fresh lung met (3)

Alveoli Met

Fiber-orientation analysis

Orientation angle (°)

Fiber-orientation analysis

Fib

er-a

lignm

ent f

requ

ency

Orientation angle (°)

ISDoT lung (8)ISDoT metastatic lung (24)P = 0.0004***

+90°

0°

–90°

Figure 6 Visualization of metastatic lung remodeling. (a) Top, SHG imaging of lung macro-metastases 35 d after cancer cell implantation in fresh (left) and ISDoT (center) tissue (met = metastasis) (scale bar (left), 100 µm; center, 200 µm) with accompanying fibril-orientation analysis of fresh and ISDoT tissues (right) (n = 3 per group, P = 0.7950). Bottom, higher-magnification views of the ISDoT metastatic lung shown above (boxed areas), showing alveolar tissue adjacent to a metastasis (Alveoli) and metastatic tissue (met), with accompanying fiber-orientation analysis (right) (n = 24 (metastatic lung) and n = 8 (healthy lung), P = 0.0004) (scale bars, 40 µm). (b) Decomposed z-stack of SHG imaging of an ISDoT 4T1 lung metastatic lesion, showing altered fibrillar collagen structure within the metastatic lesion (scale bars, 50 µm). (c) Elastin (autofluorescence, green) and fibrillar collagen (SHG, white) in a lung metastasis (scale bars, 50 µm). Z values indicate the depth of the stack in the z-plane. (d) Left, whole-mount staining for collagen type IV (green) and fibrillar collagen (SHG, white) in ISDoT metastatic lung tissue, showing the transition from tumor ECM (metastasis) to alveolar parenchyma (alveoli). Scale bar, 100 µm. Right, higher-magnification view of the transition in basement-membrane structure from the metastasis to normal alveoli. Scale bar, 25 µm. Statistics performed using Mann–Whitney U test.

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Long-term stability of ISDoT tissueTo test the feasibility of long-term storage of ISDoT tissues under aseptic conditions, we examined ISDoT ECM from tissues that were either freshly prepared or had been stored for 6 months at 4 °C. We demonstrate that the second harmonic signal—indicative of fibrillar collagen structure—and collagen type IV immunostaining of ISDoT tissues after 6 months of storage was similar to freshly excised tissues (Supplementary Fig. 10).

DISCUSSIONHere we have developed a new method, ISDoT, that efficiently decel-lularizes tissues and organs in situ and preserves the delicate struc-ture of the ECM. This approach opens up the possibility of studying the composition and distribution of native ECM components, and for mapping the 3D spatial architecture of both healthy and diseased organs. Advantages of our methodology over previously existing methodologies are that (i) ISDoT permits the decellularization of single or multiple organs without leading to vascular or tissue collapse; (ii) organs obtained after the ISDoT procedure are highly suited to ‘omics’ interrogation and imaging of the native ECM, owing to their high level of enrichment for ECM components; and (iii) surgi-cal focusing of the vascular flow permits the decellularization of poorly vascularized tissue, such as tumors.

Detailed knowledge of ECM composition and structure in both healthy and diseased tissue is needed to understand disease pathogen-esis and progression and to develop therapies. Furthermore, a deeper understanding of ECM composition, architecture and dynamics is ultimately required for the construction of synthetic tissues and organs. Our data demonstrate that ISDoT is capable of producing native ECM scaffolds that can be used in multiple downstream studies, including proteomics and high-resolution 3D imaging.

Proteomics alone provides lists of proteins for subsequent analysis, but gives no information on the patterns of protein distribution throughout the tissue. At present, such information is only possible using imaging approaches, to which the highly optically translucent nature of tissues isolated using ISDoT is well suited. Thus, ISDoT scaffolds allow initial ‘omics’ interrogation to dovetail with high- resolution spatial imaging.

We have successfully mapped the spatial distribution of several ECM components across different organs in developmental and cancer models, and we have characterized remodeling of the ECM during both primary tumor progression and secondary metastatic site colonization. Although we have applied ISDoT to mouse models, the surgical approach is scalable, and in principle, could be applied to larger organisms or tissues, including resected human tissue, which could potentially be used for regenerative-medicine and tissue- engineering research24,52. In view of our data, the ISDoT methodology generates decellularized ECM scaffolds that recapitulate the compo-sition, microstructure and spatial organization of native tissues and organs. As such, this methodology has great potential for structural studies of the ECM remodeling that occurs during tissue development and homeostasis, as well as in disease progression.

METHODSMethods, including statements of data availability and any associated accession codes and references, are available in the online version of the paper.

Note: Any Supplementary Information and Source Data files are available in the online version of the paper.

ACknowlEDGMEnTsWe thank I. Novak and N. Meyn Christensen (Centre for Advanced Bioimaging (CAB), University of Copenhagen) for imaging assistance. We thank J.R. Brewer (University of Southern Denmark) for providing access to his custom-built two-photon microscope. We thank J. Koch for help with decellularization procedures. We thank E. Sahai (Francis Crick Institute) for providing the MATLAB code. We thank J. Couchman, K.B. Jensen (both from Biotech Research & Innovation Centre, University of Copenhagen) and E. Sahai for their critical reading of the manuscript. We thank R. Linding (BRIC, University of Copenhagen) for providing access to mass spectrometry facilities. This work was supported by the Danish Cancer Society (R56-A3342, R124-A7862) (A.E.M.-G. and E.R.H.); the Novo Nordisk Foundation (Hallas Møller Stipend; to C.D.M. and J.T.E.); the European Research Council (ERC-2015-CoG-682881-MATRICAN; to A.E.M.-G. and E.R.H.); the Ragnar Söderberg Foundation Sweden (N19/15; C.D.M.); Cancerfonden Sweden (CAN 2016/283); the Innovation Foundation Denmark (1311-00010B; to T.R.C.); the National Health and Medical Research Council (NHMRC) Australia (APP1129766; T.R.C.); and the Danish Council for Independent Research YDUN grant (1084181001; F.V.A.).

AuTHoR ConTRibuTionsA.E.M.-G. conceived the project, and the project was developed together with C.D.M., T.R.C. and J.T.E. Together, A.E.M.-G., C.D.M., T.R.C. and J.T.E. designed all experiments. A.E.M.-G. designed the surgical decellularization experiments. C.D.M. performed all imaging, assisted by A.E.M.-G., and T.R.C. performed and analyzed all mass spectrometry data. E.R.H. performed the clustering analysis. T.R.C. performed fiber orientation, diameter, gap and periodicity analyses, and was assisted by C.D.M. E.R.H., F.A.V. and A.E.M.-G. performed ECM staining. A.E.M.-G., C.D.M., T.R.C. and J.T.E. wrote and edited the manuscript.

COMPETING FINANCIAL INTERESTSThe authors declare no competing financial interests.

Reprints and permissions information is available online at http://www.nature.com/reprints/index.html. Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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ONLINE METHODSCell culture conditions. Mouse B16-F10 melanoma and mouse 4T1 breast cancer cells were cultured in DMEM with 100 µg/ml penicillin/streptomycin and 10% FBS. The 4T1 and B16-F10 cell lines were obtained from the American Type Culture Collection (ATCC, USA), where cell lines are authenticated regularly. All cell lines were routinely tested for mycoplasma and tested negative for murine pathogens by IMPACT testing (IDEXX Laboratories, USA).

Animals and ethics statement. 8-week-old female BALB/c and C57BL/6 mice were purchased from Taconic, USA. All experiments were carried out under authorization and guidance from the Danish Inspectorate for Animal Experimentation.

Primary and secondary tumor models. To generate primary and secondary decellularized tumors, we used two syngeneic cancer models: (i) an oral melanoma model in which B16-F10 cells are implanted in the tongue of 8-week-old female C57BL/6 mice (Taconic, USA); and (ii) a breast cancer model in which 4T1 cells are orthotopically implanted in the third thoracic mammary fat pad of 8-week-old female BALB/c mice (Taconic, USA).

The time course for the melanoma model begins on day 0 with the implanta-tion of 3 × 105 B16-F10 cells in the anterior third of the tongue of the mice by intramuscular injection, using a 27-gauge needle under general anesthesia by isoflurane. Melanoma in the tongue develops with 100% frequency (data not shown). The tumor is allowed to grow until day 6 after injection. At this point, the primary tumor reaches a diameter of approximately 3 mm, and metastases in lymphatics of the neck are present in 100% of the animals (data not shown). The mice are then prepared for the ISDoT procedure. We observed that tumors larger than 3.5 mm in diameter impair oral intake of food and block blood vessel flow in the lingual arteries, resulting in incomplete decellularization distal to the tumor (data not shown).

The time course for the breast cancer model begins on day 0 with the implan-tation of 5 × 105 4T1/H2B-GFP+ cells in the third thoracic left mammary fat pad under general anesthesia with isoflurane5. The primary tumors were allowed to grow for 21 d until they reached a maximum diameter of 10 mm. At this stage, lymphatic metastases in the axillary and brachial lymph nodes are found with 100% frequency (data not shown). The mice are then prepared for the ISDoT procedure.

For decellularization of secondary metastases, 5 × 105 4T1/H2B-GFP+ cells were implanted into the inguinal fat pad under anesthesia with isoflurane. When the tumors reached a diameter of 10 mm, the mice were placed under general anesthesia using an intraperitoneal injection of a mixture of xilazine hydrochloride, butorphanol tartrate, tiletamine hydrochloride and zolazepam hydrochloride. The skin over the tumors was shaved and disinfected with 70% ethanol and tincture of iodine. A skin incision was made with standard surgical straight scissors and dissected to reveal the primary tumor, which was then excised. The skin was then sutured with inverted stitches using 4-0 Vicryl (Johnson and Johnsons. USA). The body weight of the mice was then monitored daily; loss of 7–10% body weight was indicative of the presence of pulmonary metastases (usually between 21 and 35 d after cancer cell implanta-tion). The mice were then prepared for the ISDoT procedure.

Surgical preparation and procedure. A fully narrated video detailing the surgical procedure is available as Supplementary Video 1. A list of the surgical instruments necessary is in Supplementary Table 3. Mice were placed under general anesthesia with an intraperitoneal injection of a mixture of xilazine hydrochloride, butorphanol tartrate, tiletamine hydrochloride and zolazepam hydrochloride. Anesthetized mice were heparinized with a tail-vein injection of 20 U (600 U/kg) heparinic acid (Sigma-Aldrich, USA) diluted in 100 µl of distilled water. Mice were euthanized with an overdose of sodium thiopental delivered by intrahepatic injection. The animals were shaved, and the skin was disinfected with 70% ethanol and tincture of iodine. All procedures were carried out under sterile conditions using a surgical microscope (S6D micro-scope, Leica, Germany).

For all surgical procedures, the operation begins with a skin incision that goes from the lower abdomen to the submandibular region. The inci-sion is dissected with blunt scissors to expose the thorax and the peritoneal

wall. Sectioning of the pectoralis and intercostal muscles provides access to the thoracic cavity through the sixth intercostal space. This access is com-pleted by perpendicularly sectioning the sternum above the xyphoid proc-ess, followed by a sternotomy. Elevating and securing the thoracic walls exposes the heart, lungs and thymus. It is necessary to dissect and excise the thymus and pericardial fat to approach the major vessels. Because the thymus is held in place by loose connective tissue, it is not necessary to section it; gently pulling on the tissue is enough to break its attachment from the under-lying tissue. However, care must be taken not to disrupt the left brachiocephalic vein when starting to detach the thymus. Major vessels are then dissected free of surrounding connective tissue sequentially, as specified below.

Surgical procedure for mammary-fat-pad decellularization. This operation shunts vascular flow to the left mammary fat pad (Fig. 1a) by clamping the aortic arch (1) before the emergence of the left subclavian artery (arrowhead) and the left brachiocephalic vein (2). Flow is drained through vessels distal to the tumor. This approach leads to decellularization of the limb, manus, skeletal muscles, peripheral nerves, lymph nodes, thoracic mammary fat pads and mammary glands. A second operation shunts vascular flow to the right mammary thoracic fat pad (Fig. 1a) by clamping the left brachiocephalic vein (1), the left subclavian artery (2), the left common carotid artery (3), the aortic arch (4), the right common carotid artery (5) and the caudal cava vein (6). Flow is drained by the vessels distal to the mammary tumor (arrow). At the conclusion of both operations, the animal is sectioned at the height of the intervertebral disc between lumbar 1 and lumbar 2 to allow for the retrograde catheterization of the descending aorta (green arrow). A 27G catheter is secured along the tract of the thoracic aorta with two stitches that surround the catheterized aorta with 9-0 microsuture (B. Braun, Spain) made after the emergence of the left subclavian artery and 1 cm below. A third stitch that binds the catheterized aorta to the thoracic spine with 4-0 suture (Johnsons and Johnsons, USA) is made to avoid loss of pressure and unwanted movement of the catheter.

Surgical procedure for head and neck decellularization. This operation directs vascular flow through the carotid arteries to decellularize the head and neck region (Supplementary Fig. 1b). Clamping begins with the left brachiocephalic vein (1), followed by the left subclavian artery (2) and the aortic arch (3), before the emergence of the brachiocephalic artery, the right subclavian artery (4), the internal jugular vein (5) and the caudal cava vein (6). This approach leaves both of the common carotids (black arrowheads) open to ensure that the flow of decellularizing reagents is directed exclusively to the head and neck. The right parasternal vein is left open (red arrow) to provide an exit for the flow. At this point, the animal is catheterized, as described above. To finalize the operation, the head, neck and thoracic spine containing the catheterized aorta are excised from the mouse for decellularization.

Surgical procedure for lung decellularization. This operation directs flow toward the left side of the heart to decellularize the cardiopulmonary complex: clamping is performed on the left brachiocephalic vein (1), left subclavian artery (2), the left common carotid artery (3), the brachiocephalic artery (4), the right internal jugular vein above the entrance of the parasternal vein (5) and the caudal cava vein (6), while leaving the aorta open. This procedure provides access of reagents to the left ventricle, from where the reagents flow up to the atrium, into the pulmonary veins and to the lungs (Fig. 1b). Drainage flows through the right parasternal vein (red arrow).

Surgical procedure for liver decellularization. The surgical procedure (Supplementary Fig. 1c) is performed in two stages. First, the peritoneum is cut to reveal its contents; then the peritoneal content is elevated to reveal the abdominal aorta and its branches. Clamps are placed in the splenic artery (2) and the gastroduodenal artery (3), leaving the proper hepatic artery open. Second, the peritoneal contents are replaced to expose the anterior face of the liver, and the portal vein is identified and catheterized (4), allowing the flow to drain through the caudal cava vein (red arrow).

Decellularization procedure. Catheterized organs are connected to a system in which a peristaltic pump (Ole Dich, Denmark) connects a reagent reservoir

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to the catheter connector with sterile silicone tubes (Ole Dich, Denmark) (Supplementary Fig. 1a). The tubing has a lumen diameter of 2 mm and an external diameter of 4 mm. The waste-collection tubing has a lumen of 2.5 mm and an external diameter of 4.5 mm. The peristaltic pump is set to a flow output of 0.06 ml/min (90 ml/24 h).

Perfusion begins with 15 min of deionized water supplemented with 1% Pen-Strep, 0.25% Amphotericin B and 0.25% Plasmocin. This is followed by a detergent regimen, as detailed in Supplementary Table 1. The first deter-gent perfusion is followed by perfusion with de-ionized water for 30 min, 1% Triton X-100 in de-ionized water for 30 min, 0.1% peracetic acid for 30 min and de-ionized water for 2 h. ISDoT tissues can be stored in de-ionized water at 4 °C for more than six months (Supplementary Fig. 10).

Verification of decellularization efficacy. 8-week-old female BALB/c mice were euthanized by neck dislocation and the tongue, neck lymph node, lungs and mammary fat pad were surgically excised and processed to extract genomic DNA (DNA extraction kit, Qiagen, USA). DNA yields from each tissue were measured using a spectrometer (Nanodrop, USA). The tongue, lymph nodes, lungs and mammary fat pads from age- and sex-matched organs were collected according to the ISDoT procedure described above and processed using the same DNA extraction and measurement methods.

For F-actin staining, fresh mammary fat pads were excised and fixed in 4% paraformaldehyde for 12 h, washed in PBS for 6 h, permeabilized in 0.2% Triton and blocked in 6% goat serum (Thermo Fisher Scientific, Cat. #10000C) in PBS for 6 h, and immersed in a 1:1,000 solution of FITC-phalloidin (Sigma-Aldrich, USA) for 12 h. ISDoT tissues were treated by following the same protocol, and both fixed and ISDoT tissues were imaged with a confocal micro-scope (SPX5, Leica, Germany) to assess F-actin staining.

Verification of basement-membrane integrity. Lungs decellularized using the ISDoT procedure were injected through aortic catheterization with autopo-lymerizable red poly-methyl-methacrylate (Polysciences, USA). The lung tissue was removed using Batson’s Maceration solution (Polysciences Inc, USA), according to the manufacturer’s instructions, to remove tissue and leave a plastic cast of the pulmonary venous vascular tree.

To ascertain basement-membrane conservation after decellularization, we perfused ISDoT lungs with a solution of 5 × 105 Da (Sigma-Aldrich, USA) molecular weight Dextran labeled with tetramethylrhodamine (TRITC). Dextran-TRITC was imaged using the microscope described below.

Fibril-orientation analysis. The distribution of local orientation of collagen fibrils within fresh and ISDoT healthy and diseased tissues was assessed as previously described20. Briefly, the local orientation and isotropic properties of pixels making up collagen fibrils were derived from structure tensors. Tensors were evaluated for each pixel of an input image by computing the continuous spatial derivatives in the x and y dimensions using a cubic B-spline interpola-tion, and the local predominant orientation was obtained. Orientation distri-bution peaks were then aligned and normalized before unpaired two-tailed nonparametric testing (Mann–Whitney U) was used for determining statistical significance across distributions.

Gap analysis. The gap size distribution between SHG-imaged fibers in fresh and ISDoT normal and diseased tissues was assessed using MATLAB, as previously described21,22. The MATLAB code was a kind gift from E. Sahai at The Francis Crick Institute, London, UK. SHG images were preprocessed by thresholding and background subtraction to produce a binary image using ImageJ software, and the binary images were then imported into MATLAB. In brief, a circle-fitting algorithm was deployed to identify the largest circle that could fill gaps between fibers and that did not overlap with other fitted circles. The distribution of gap radii was then transformed from discrete pixels to micrometers and distributions were plotted as a proportion of gap area. The distributions of gap radii were tested for significance using unpaired two-tailed nonparametric testing (Mann Whitney U).

Fibril-diameter analysis. Fibril diameter in fresh and ISDoT mammary fat pads, lungs and 4T1 breast tumors was assessed using the diameter

characterization plugin (DiameterJ, National Institute of Standards and Technology, USA)53 integrated into ImageJ imaging software (NIH, USA). SHG images (300 × 300 µm) with matched acquisition parameters were seg-mented and binarized. The mean diameter of all fibrils in a single image was calculated. Data shown are mean ± s.d. for each image. Images from fresh and ISDoT tissues were compared using a parametric, two-tailed t-test (Supplementary Fig. 3).

Immunostaining. Whole ISDoT organs were washed with sterile, de-ionized water twice for 30 min; blocked at room temperature with 6% goat serum in PBS for 1 h; washed with 0.05% Tween 20 twice for 1h; and then incubated with primary antibodies 2 h in PBS, 3% goat serum and 0.05% Tween 20. Tissues were then washed three times in 0.02% Tween20 in de-ionized water for 30 min, incubated with Alexa-Fluor 488-conjugated secondary antibodies for 2 h, and finally, washed with 0.02% Tween in de-ionized water. All incubation and washing steps were performed on a rocking table at 10 r.p.m. Immunostaining of organs larger than a lung lobe may need longer incubation times. The following primary antibodies were used: anti-collagen type IV (1:100; M0785, Dako, Denmark), anti-pan-laminin (1:50; AB2034, Milipore), and anti-nidogen 1 (1:50; AP02274SU-N, Acris). Secondary Alexa-Fluor 488 conjugated antibody was used at 1:500 (A11008, Thermo Fisher Scientific).

Two-photon microscopy. Immunostained tissues were placed in water in a glass-bottom Mattek dish. All organs were imaged using an inverted Leica SP5-X MP multiphoton Leica microscope connected to a Ti-Sapphire laser (Spectra Physics MaiTai HP DeepSee Laser, Spectral Physics (Tunable wave-length: 690 nm to 1040 nm). Second harmonic generation (SHG) was imaged using two-photon excitation at 892 nm and emission between 426-446 nm was detected using a hybrid detector (HyD SP, Leica). The objective: HCX PL APO lambda blue 20×, 0.70NA IMM UV. Secondary antibodies conjugated with Alexa-Fluor 488 were also excited using two-photon excitation at 892 nm, and emission between 505 and 550 nm was detected. To detect elastin, samples were excited using a low-power Argon laser (Argon Ion Laser, Leica (65-mW multi-line (458, 476, 488, 496 and 514 nm)) at 488 nm, and emission between 505 and 550 nm was detected. Unless otherwise stated, all images are from back-scattered light and captured with a resolution of at least 1,024 × 1,024 pixels, at 100–200 Hz.

Assessment of maximum imaging depth. 4T1 tumor-draining lymph nodes were prepared in three different ways as follows: decellularized using ISDoT; excised and fixed with 1% PFA for 12 h; and resected immediately before imaging without fixation. ISDoT and PFA-fixed lymph nodes were immunos-tained to detect collagen type IV, as described above. All lymph nodes were imaged as described above using two-photon excitation at 10% laser power to produce z-stacks of 300 µm in depth, beginning at the cortex of the lymph node (slices were 10 µm in thickness) (Supplementary Fig. 7). Subsequently, a single image at a depth of 200 µm in the tissue was taken using 30% laser power (Supplementary Fig. 7d).

Mass spectrometry preparation, acquisition and analysis. Following ISDoT decellularization, organs were thoroughly washed and dissected free of extra-neous tissue before being ground in liquid nitrogen to a fine powder, using a chilled mortar and pestle. Tissues were then fully solubilized in in 6-M urea, 2-M thiourea, 10-mM HEPES, pH 8. Protein yields were assessed using the Bradford assay and were ready for submission for mass spectrometry analysis, as previously described54,55. Solubilized proteins were reduced in 5-mM DTT (Sigma-Aldrich) and alkylated with 10-mM chloroacetamide (Sigma-Aldrich) before deglycolsylation with PNGase F overnight at 37 °C with shaking (100 U per 10 mg tissue). Deglycosylated samples were then sequentially digested with 2.5 µg LysC (Wako Chemicals) per 100 mg starting tissue and MS-grade trypsin (7.5 µg per 100 mg starting tissue) overnight at 37 °C. Peptides were acidified with trifluoroacetic acid at a final concentration of 2%, after which they were desalted on an in-house packed C18 StageTips, as previ-ously described56. Briefly, two discs of C18 material (3M Empore) were packed into a 200-µl pipette tip and activated with 20 µl of methanol (HPLC grade) and 20 µl of 80% acetonitrile, 0.1% formic acid (FA). The C18 material was

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equilibrated twice with 20 µl of 1% trifluoroacetic acid (TFA), 3% acetonitrile. 5 µg of each sample was then loaded onto individual StageTips. After washing with twice with 20 µl 0.1% FA, peptides were eluted with twice with 40 µl 80% acetonitrile, 0.1% FA and concentrated to 5 µl in an Eppendorf Speedvac. This final concentrate was acidified with 4 µl 1% TFA, 2% acetonitrile for mass spectrometry analysis.

Each sample was run unfractionated as a single-shot fraction on a Thermo Fisher Q-Exactive Mass Spectrometer. For each run, 5 µg of peptide was loaded onto a 50-cm C18 reverse-phase analytical column (Thermo EasySpray ES803) using 100% Buffer A (0.1% formic acid in water) at a pressure of 720 bar using the Thermo EasyLC 1000 uHPLC system in a single-column setup, and the column oven operating at 45 °C. Peptides were eluted over a 4-h gradient ranging from 6% to 60% of a solution containing 80% acetonitrile, 0.1% formic acid. The Q-Exactive (Thermo Fisher Scientific) was run using the DD-MS2 top10 method. Full MS spectra were collected at a resolution of 70,000, with an Automatic Gain Control (AGC) target of 3 × 106 or a maximum injection time of 20 ms and a scan range of 300–1750 m/z. The MS2 spectra were obtained at a resolution of 17,500, with an AGC target value of 1 × 106 or a maximum injection time of 60 ms, a normalized collision energy of 25% and an underfill ratio of 0.1%. Dynamic exclusion was set to 45 s, and ions with a charge state of <2 or unknown were excluded. MS performance was verified for consistency by running complex cell lysate quality-control standards, and chromatography was monitored to check for reproducibility.

Raw MS/MS spectra were processed using MaxQuant version 1.5.1.2 soft-ware and searched against the mouse protein database UP000000589_10090 (released 25/02/16). Peptides identified with a false-discovery rate of <1.0% were assembled into identified proteins. MS/MS spectra searches allowed for carbamidomethylation of cysteines and possible acetylation of N-termini as fixed/mix modifications. Allowed variable modifications were oxi-dized methionine, deamidation of asparagine and pyroglutamic acid modification at N-terminal glutamine and hydroxyproline. To ensure high-confidence identifications and quantification, a MaxQuant score of >50 and a minimum of two unique peptides per protein detected by MS were required.

Functional-enrichment analysis was performed using High-Throughput GoMiner software57. 1,000 randomizations were performed, and the data were

thresholded for a 5% false-discovery rate. Over-represented biological-process and cellular-component terms with ≥5 and ≤500 assigned proteins were reported. The fold-change in diseased relative to healthy tissue was mapped onto proteins assigned to each over-represented term. The data matrix was subjected to hierarchical clustering analysis using Cluster 3.0 (version 1.52)58 on the basis of uncentered Pearson correlation analysis, and distances between hits were computed using a complete-linkage matrix. Clustered data were visualized using Java TreeView software (version 1.1.6r4)59.

Statistical analysis. Unless otherwise indicated, data are expressed as means ± s.d. Where data sets passed normality tests, differences between values were examined using the parametric two-tailed unpaired Student’s t-test or two-way analysis of variance (ANOVA), as indicated; other data sets were examined using the nonparametric Mann–Whitney U test, and differences were considered to be significant when P < 0.05.

Data availability. Raw mass spectrometry data are available online at ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) with the data set identifier PXD006579.

53. Hotaling, N.A., Bharti, K., Kriel, H., Simon, C.G. Jr. & Diameter, J. DiameterJ: A validated open source nanofiber diameter measurement tool. Biomaterials 61, 327–338 (2015).

54. Cox, T.R. et al. The hypoxic cancer secretome induces pre-metastatic bone lesions through lysyl oxidase. Nature 522, 106–110 (2015).

55. Cox, T.R., Schoof, E.M., Gartland, A., Erler, J.T. & Linding, R. Dataset for the proteomic inventory and quantitative analysis of the breast cancer hypoxic secretome associated with osteotropism. Data Brief 5, 621–625 (2015).

56. Rappsilber, J., Mann, M. & Ishihama, Y. Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips. Nat. Protoc. 2, 1896–1906 (2007).

57. Zeeberg, B.R. et al. High-Throughput GoMiner, an ‘industrial-strength’ integrative gene ontology tool for interpretation of multiple-microarray experiments, with application to studies of Common Variable Immune Deficiency (CVID). BMC Bioinformatics 6, 168 (2005).

58. de Hoon, M.J., Imoto, S., Nolan, J. & Miyano, S. Open source clustering software. Bioinformatics 20, 1453–1454 (2004).

59. Saldanha, A.J. Java Treeview—extensible visualization of microarray data. Bioinformatics 20, 3246–3248 (2004).