Tamoxifen mechanically reprograms the tumor microenvironment via HIF ‐1A and reduces cancer cell survival
2018; Springer Nature; Volume: 20; Issue: 1 Linguagem: Inglês
10.15252/embr.201846557
ISSN1469-3178
AutoresErnesto Cortés, Dariusz Lachowski, Benjamin Robinson, Müge Sarper, Jaakko Teppo, Stephen D. Thorpe, Tyler J. Lieberthal, Kazunari Iwamoto, David A. Lee, Mariko Okada, Markku Varjosalo, Armando E. del Río Hernández,
Tópico(s)Cancer Research and Treatments
ResumoArticle12 December 2018Open Access Transparent process Tamoxifen mechanically reprograms the tumor microenvironment via HIF-1A and reduces cancer cell survival Ernesto Cortes Ernesto Cortes Cellular and Molecular Biomechanics Laboratory, Department of Bioengineering, Imperial College London, London, UK Search for more papers by this author Dariusz Lachowski Dariusz Lachowski orcid.org/0000-0003-1194-8019 Cellular and Molecular Biomechanics Laboratory, Department of Bioengineering, Imperial College London, London, UK Search for more papers by this author Benjamin Robinson Benjamin Robinson Cellular and Molecular Biomechanics Laboratory, Department of Bioengineering, Imperial College London, London, UK Search for more papers by this author Muge Sarper Muge Sarper Cellular and Molecular Biomechanics Laboratory, Department of Bioengineering, Imperial College London, London, UK Search for more papers by this author Jaakko S Teppo Jaakko S Teppo orcid.org/0000-0003-1022-5572 Institute of Biotechnology, University of Helsinki, Helsinki, Finland Search for more papers by this author Stephen D Thorpe Stephen D Thorpe Institute of Bioengineering, School of Engineering and Materials Science, Queen Mary University of London, London, UK Search for more papers by this author Tyler J Lieberthal Tyler J Lieberthal Cellular and Molecular Biomechanics Laboratory, Department of Bioengineering, Imperial College London, London, UK Search for more papers by this author Kazunari Iwamoto Kazunari Iwamoto Laboratory of Cell Systems, Institute for Protein Research, Osaka University, Suita, Osaka, Japan Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Kanagawa, Japan Search for more papers by this author David A Lee David A Lee orcid.org/0000-0001-7646-4643 Institute of Bioengineering, School of Engineering and Materials Science, Queen Mary University of London, London, UK Search for more papers by this author Mariko Okada-Hatakeyama Mariko Okada-Hatakeyama Laboratory of Cell Systems, Institute for Protein Research, Osaka University, Suita, Osaka, Japan Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Kanagawa, Japan Search for more papers by this author Markku T Varjosalo Markku T Varjosalo Institute of Biotechnology, University of Helsinki, Helsinki, Finland Search for more papers by this author Armando E del Río Hernández Corresponding Author Armando E del Río Hernández [email protected] orcid.org/0000-0001-5062-8910 Cellular and Molecular Biomechanics Laboratory, Department of Bioengineering, Imperial College London, London, UK Search for more papers by this author Ernesto Cortes Ernesto Cortes Cellular and Molecular Biomechanics Laboratory, Department of Bioengineering, Imperial College London, London, UK Search for more papers by this author Dariusz Lachowski Dariusz Lachowski orcid.org/0000-0003-1194-8019 Cellular and Molecular Biomechanics Laboratory, Department of Bioengineering, Imperial College London, London, UK Search for more papers by this author Benjamin Robinson Benjamin Robinson Cellular and Molecular Biomechanics Laboratory, Department of Bioengineering, Imperial College London, London, UK Search for more papers by this author Muge Sarper Muge Sarper Cellular and Molecular Biomechanics Laboratory, Department of Bioengineering, Imperial College London, London, UK Search for more papers by this author Jaakko S Teppo Jaakko S Teppo orcid.org/0000-0003-1022-5572 Institute of Biotechnology, University of Helsinki, Helsinki, Finland Search for more papers by this author Stephen D Thorpe Stephen D Thorpe Institute of Bioengineering, School of Engineering and Materials Science, Queen Mary University of London, London, UK Search for more papers by this author Tyler J Lieberthal Tyler J Lieberthal Cellular and Molecular Biomechanics Laboratory, Department of Bioengineering, Imperial College London, London, UK Search for more papers by this author Kazunari Iwamoto Kazunari Iwamoto Laboratory of Cell Systems, Institute for Protein Research, Osaka University, Suita, Osaka, Japan Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Kanagawa, Japan Search for more papers by this author David A Lee David A Lee orcid.org/0000-0001-7646-4643 Institute of Bioengineering, School of Engineering and Materials Science, Queen Mary University of London, London, UK Search for more papers by this author Mariko Okada-Hatakeyama Mariko Okada-Hatakeyama Laboratory of Cell Systems, Institute for Protein Research, Osaka University, Suita, Osaka, Japan Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Kanagawa, Japan Search for more papers by this author Markku T Varjosalo Markku T Varjosalo Institute of Biotechnology, University of Helsinki, Helsinki, Finland Search for more papers by this author Armando E del Río Hernández Corresponding Author Armando E del Río Hernández [email protected] orcid.org/0000-0001-5062-8910 Cellular and Molecular Biomechanics Laboratory, Department of Bioengineering, Imperial College London, London, UK Search for more papers by this author Author Information Ernesto Cortes1, Dariusz Lachowski1, Benjamin Robinson1, Muge Sarper1, Jaakko S Teppo2, Stephen D Thorpe3, Tyler J Lieberthal1, Kazunari Iwamoto4,5, David A Lee3, Mariko Okada-Hatakeyama4,5, Markku T Varjosalo2 and Armando E Río Hernández *,1 1Cellular and Molecular Biomechanics Laboratory, Department of Bioengineering, Imperial College London, London, UK 2Institute of Biotechnology, University of Helsinki, Helsinki, Finland 3Institute of Bioengineering, School of Engineering and Materials Science, Queen Mary University of London, London, UK 4Laboratory of Cell Systems, Institute for Protein Research, Osaka University, Suita, Osaka, Japan 5Laboratory for Integrated Cellular Systems, RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Kanagawa, Japan *Corresponding author. Tel: +44(0)2075948157; E-mail: [email protected] EMBO Reports (2019)20:e46557https://doi.org/10.15252/embr.201846557 See also: E Cortes et al (January 2019) and M Pein & T Oskarsson (January 2019) PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract The tumor microenvironment is fundamental to cancer progression, and the influence of its mechanical properties is increasingly being appreciated. Tamoxifen has been used for many years to treat estrogen-positive breast cancer. Here we report that tamoxifen regulates the level and activity of collagen cross-linking and degradative enzymes, and hence the organization of the extracellular matrix, via a mechanism involving both the G protein-coupled estrogen receptor (GPER) and hypoxia-inducible factor-1 alpha (HIF-1A). We show that tamoxifen reduces HIF-1A levels by suppressing myosin-dependent contractility and matrix stiffness mechanosensing. Tamoxifen also downregulates hypoxia-regulated genes and increases vascularization in PDAC tissues. Our findings implicate the GPER/HIF-1A axis as a master regulator of peri-tumoral stromal remodeling and the fibrovascular tumor microenvironment and offer a paradigm shift for tamoxifen from a well-established drug in breast cancer hormonal therapy to an alternative candidate for stromal targeting strategies in PDAC and possibly other cancers. Synopsis Tamoxifen biomechanically remodels the tumor microenvironment in pancreatic cancer independent of the nuclear estrogen receptors, but involving the GPER/HIF-1A axis. Tamoxifen also reduces the ability of pancreatic cancer cells to survive under hypoxic conditions. Tamoxifen inhibits HIF-1A through a hypoxia independent mechanism. Tamoxifen regulates the composition and organization of the ECM in pancreatic cancer. Tamoxifen suppresses the adaptive response of PDAC to hypoxia and increases vascular density. Introduction Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer and one of the leading causes of cancer-related death despite substantial efforts in recent years aimed at optimizing therapies. PDAC is distinguished by a strong desmoplasia in the tumor microenvironment or stroma that has been associated with aggressiveness of the disease 1, but has also been reported to restrain tumor growth 23, suggesting that stromal contribution varies depending on the context. Therefore, there is an urgent need for studies that characterize the structure of this desmoplastic stroma in order to decipher its complex and dynamic interaction with the tumor. PDAC is one of the stiffest solid carcinomas, which intuitively leads to the idea of disrupted mechanical communication between cancer and stromal cells and unbalanced tissue tension within the extracellular matrix (ECM). Thus, PDAC can be viewed as a complex multifaceted disease of altered mechanobiology. Indeed, a recent study has shown that enhanced mechanosignaling in the tumor epithelia can promote PDAC progression in mouse models, overriding the need for p53 mutation 4, while another study showed that targeting focal adhesion kinase in vivo could reduce fibrosis and therefore sensitize pancreatic cancer cells to immunotherapy 5. The strong desmoplasia severely impacts vascular function in PDAC, which hosts a remarkably hypovascularized tumor microenvironment. This dysfunctional vasculature has represented a major hurdle for chemotherapy delivery and has been used as a diagnostic tool in PDAC imaging for many years 1. PDAC, like other hypovascularized tumors, has substantial hypoxic areas 67. The ability of cancer and stromal cells to thrive under these hostile conditions of subpar oxygen supply depends on their capacity to trigger pathways necessary for development under hypoxic conditions. The hypoxia-inducible factor (HIF) pathway is the main mechanism activated in cells to adapt to hypoxia. Under these conditions, hypoxia-inducible factor-1 alpha (HIF-1A) translocates to the nucleus and binds to the hypoxia-response elements, thereby activating the expression of genes that control multiple functions in cells such as metabolism, survival, proliferation and apoptosis, migration, energetic balance, and pH 8. Notably, PDAC seems to progress without the need of excessive angiogenesis and a recent study suggests a lack of correlation between the hypovascular nature of PDAC and hypoxia 910. Pancreatic stellate cells (PSCs) are the main group of resident cells in the stroma and the key drivers of the desmoplastic reaction 11. In PDAC, like other cancer-associated fibroblasts (CAFs), PSCs are activated and adopt a myofibroblastic phenotype with high contractile activity, leading to stiffening of the ECM and extensive deposition of ECM proteins such as collagen and fibronectin 121314. PSCs orchestrate ECM organization, not only via force-mediated matrix remodeling or through the synthesis and deposition of ECM proteins, but also by regulated secretion of elevated levels of matrix cross-linking enzymes such as lysyl oxidase (LOX) and degradative proteases such as metalloproteinases (MMPs) and their inhibitors (tissue inhibitor of metalloproteinases, TIMPs) 111516. The controlled balance between these cross-linking and degradative enzymes regulates ECM architecture in normal pancreas, but loss of this balance in PDAC triggers and sustains the desmoplastic reaction 12. Interestingly, the LOX/hypoxia axis correlates with poor prognosis in PDAC patients and targeting this axis in PDAC mice has been shown to decrease tumorigenesis, augment chemotherapy efficacy, and decrease metastasis 17. Moreover, treating PDAC mouse models with ATRA (all trans-retinoic acid), which abrogates force-mediated ECM remodeling by PSCs 16, increased vascular density and decreased hypoxia 18. Tamoxifen has been used for many years to treat breast cancers based on its genomic effect on the nuclear estrogen receptors. Here we report a previously unidentified mechanism that is independent of the nuclear estrogen receptors and involves the G protein-coupled estrogen receptor (GPER) and hypoxia-inducible factor-1 alpha (HIF-1A). We show that tamoxifen reduces the adaptive response of PDAC to hypoxia via a mechanical downregulation of HIF-1Α, and increases vascularization in PDAC mouse models. Tamoxifen tunes the balance between cross-linking (LOX) and degrading enzymes (MMPs) secreted by PSCs to modulate collagen and fibronectin fiber architecture in the tumor microenvironment. Tamoxifen treatment also decreases the fitness of pancreatic cancer cells to cope with hypoxic conditions via mechanical downregulation of HIF-1A. Results Tamoxifen treatment induces changes in protein content of PDAC tissues and gene expression profiles in PSCs We treated KPC mice (Pdx-1 Cre, KRasG12D/+, p53R172H/+), which are known to recapitulate the clinical and histological features of human PDAC 2, with 2 mg of tamoxifen, and used quantitative shotgun proteomic analysis to investigate whether tamoxifen treatment induced changes in the protein content of PDAC tissues. This dose in mice (100 mg/kg) produces a tamoxifen serum concentration around 0.5 μM, which corresponds to the serum concentration found in humans after administration of clinical doses of 20 mg/day 19. In total, 110 proteins showed statistically significant changes (Fig EV1 and Dataset EV1, EV2 and EV3). From this group, more than half of the downregulated proteins are involved in ECM organization, cell adhesion, and wound healing. These data have been deposited in the PeptideAtlas under the reference PASS01070. Click here to expand this figure. Figure EV1. Tissue proteomics—the tumors in KPC mice treated with 2 mg tamoxifen show changes in their protein content A. In total, 110 proteins show statistically significant (P < 0.05) changes, of which 45 are upregulated (by 50%; red) and 30 downregulated (by 50%; blue). B, C. Enriched (P < 0.05) Gene Ontology Biological Processes (GO-BP) for proteins upregulated (B) and downregulated (C) by the tamoxifen treatment. Download figure Download PowerPoint To study the effect of tamoxifen on the main resident cells in the tumor microenvironment, PSCs were treated with 5 μM of tamoxifen as higher doses showed toxicity (Fig EV2). RNA sequencing and gene profile analysis of control and treated PSCs showed that from the nearly 20,000 expressed genes, 649 were upregulated and 688 downregulated (Fig EV3, Dataset EV4, EV5, and EV6). The larger group of upregulated genes is associated with blood vessel morphogenesis, and the downregulated genes are involved in ECM organization, cell migration, cell–ECM adhesion, and the response to hypoxia. These data have been deposited in the European Nucleotide Archive, accession number ERP023834. Click here to expand this figure. Figure EV2. Toxicity curve and proliferation of PSCs under tamoxifen treatment Killing curve for tamoxifen doses. Quantification of cell counting percent relative to time 0—PSCs proliferation. Data information: Error bars are SEM. **P < 0.01, ***P < 0.0001, n.s. is not significant, t-test. N = 3 experimental replicates and more than 15 fields of view analyzed per condition. Download figure Download PowerPoint Click here to expand this figure. Figure EV3. RNA Sequencing of PSCs—Gene ontology analysis of differentially expressed genes—DEG (upregulated and downregulated)13 downregulated and 15 upregulated GO terms selected based on the number of DEGs included in each GO term are shown. Color and circle size represent false discovery rate (FDR) and fraction of DEGs assigned to each GO term to total number of DEGs, respectively. Download figure Download PowerPoint Tamoxifen reduces hypoxia and increases vascularization in PDAC tissues In order to investigate the effect of tamoxifen treatment on hypoxia and vascularization levels in PDAC tissues, we used GLUT1 and CD31 immunofluorescence staining of pancreatic tissues from KPC mice treated with 2 and 5 mg of tamoxifen (Fig 1A). The level of the hypoxia marker GLUT1 was significantly reduced from control mice to mice treated with 5 mg (fourfold reduction) in a dose-dependent fashion (Fig 1B). We also observed a pronounced reduction in Glut1 content in PDAC tissues from treated mice relative to control using quantitative proteomics analysis (Fig 1C). A twofold increase in vascularization was observed in mice treated with the highest doses compared to untreated mice (Fig 1D). Figure 1. Tamoxifen decreases hypoxia and increases vascularization A. Immunofluorescence images of PDAC tissues from KPC mice treated with vehicle control of tamoxifen, scale bar 100 μm. B–D. (B, D) Quantification of GLUT1 (hypoxia marker) and CD31 (endothelial cell marker). Control (n = 5), 2 mg (n = 5), and 5 mg (n = 4). In all cases, bars represent mean ± SEM. (C) Relative values of protein levels for Glut1 in PDAC tumors assessed by proteomic analysis (6 mice for control and 2 mg and 3 mice for 5 mg, and samples were analyzed in duplicates). E, F. Expression levels of DEGs relevant to response to hypoxia (left) and blood vessel morphogenesis (right). The values were normalized by tubulin family genes. G. Immunofluorescence images of PDAC tissues from KPC mice treated with vehicle control and 5 mg of tamoxifen, scale bar 100 μm. H. Quantification of HIF-1A in PDAC tissues. Control (n = 5) and 5 mg (n = 4). In the box-and-whisker plot, the central box represents values from the lower to upper quartile. The middle line represents the mean. The vertical line extends from the minimum to the maximum value. I. qPCR levels of HIF-1A in PSCs, normalized to RPLP0 and relative to control. J. Western blot bands for protein expression in PSCs (p-Tmod is post-translational modification). The plot shows the quantification of the sum of band intensities corresponding to isoform 1, isoform 2, isoform 3, and post-transcriptionally modified HIF-1A (n = 8 control and n = 8 tam). Data information: All histogram bars represent mean ± SEM; *P < 0.05, **P < 0.01, ***P < 0.001 (t-test for H and J; ANOVA and Tukey's post hoc test for B, D, I). For (A and G), n ≥ 5 sections per animal. Results collected during 3 or more separate experiments. Download figure Download PowerPoint RNA sequencing of PSCs revealed more than 25 hypoxia-related genes downregulated and more than 30 blood vessel morphogenesis genes upregulated after tamoxifen treatment (Figs 1E and F, and EV3). We then focused on the hypoxia-inducible factor (HIF) and vascular endothelial growth factor (VEGF) families as key players associated with hypoxia and blood vessels respectively (Appendix Fig S1). For the HIF family, we found that while HIF-3A did not change, HIF-1A was significantly reduced and HIF-2A (also known as EPAS1) was significantly upregulated. We observed an increase in the expression levels of VEGFB and a downregulation of VEGFC. qPCR was used to validate RNA sequencing data that showed a clear trend but did not display significant differences. The analysis of the downregulated hypoxia-related genes revealed a map of interactions centered in HIF-1A (Appendix Fig S2). We observed a nearly 70% reduction in HIF-1A levels in PDAC tissues from KPC mice treated with 5 mg of tamoxifen relative to control KPC mice treated with vehicle (Fig 1G and H). We also confirmed that the effect of tamoxifen on the HIF-1A levels of PSCs is mediated by GPER, as the use of GPER antagonist (but not ER antagonist) returned the HIF-1A values to the levels found in control PSCs (Fig 1I). We used immunoblotting to investigate the effect of tamoxifen on the levels of HIF-1A in PSCs and observed an overall 25% reduction in the 3 main HIF-1A isoforms (1–3) and also in the posttranslationally modified HIF-1A (Fig 1J and Appendix Fig S3). Taken together, these data show that tamoxifen induces the expression of genes that promote blood vessels formation and downregulates hypoxia-related genes, with many of them converging in HIF-1A. Tamoxifen decreases LOX-L2 levels in PSCs and PDAC tissues The lysyl oxidase (LOX) gene encodes the lysyl oxidase family of extracellular copper-dependent enzymes that catalyses the cross-linking of collagen fibers. Within this family, LOX is the most characterized member and LOX-L2 (lysyl oxidase homolog-2) has been comprehensively documented to participate in ECM remodeling of the tumor and fibrotic microenvironments. All LOX members contain a highly conserved copper binding and catalytic C-terminal domain, responsible for the cross-linking function of these enzymes 20. The LOX family has been known to promote fibrosis and tumorigenesis, and accumulated evidence supports the use of β-aminopropionitrile (βAPN) and simtuzumab to inhibit LOX and LOX-L2 activities in fibrosis and cancer 13. These inhibitors have reverberated across the fields of inflammation and cancer as potential agents to restore normal collagen architecture and mechanical tissue homeostasis 21. Increased expression of LOX-L2 has been reported in human PDAC tissues with respect to normal stroma, and elevated LOX/hypoxia is associated with the shortest patient survival 1722. Given that we observed a significant downregulation of LOX-L2 after tamoxifen treatment in the analysis of the gene profile of PSCs, and LOX-L2 is elevated in PDAC and regulated by HIF-1A 2324, we focused first on this member of the LOX family and tested the LOX-L2 levels in PSCs following tamoxifen treatment. We observed a threefold decrease of LOX-L2 at the gene and protein levels compared to untreated control (Fig 2A and B). This effect was maintained when we used an estrogen receptor (ER) antagonist but not a GPER antagonist, which supports the notion that tamoxifen reduces LOX-L2 expression via GPER. Figure 2. Tamoxifen reduces LOX-L2 levels in PSCs and PDAC tissues qPCR levels of LOX-L2 in PSCs, normalized to RPLP0 and relative to control. Western blot levels of LOX-L2 in PSCs (n = 3 experimental replicates). Expression of LOX family genes obtained from RNA-seq data in control and tamoxifen-treated PSCs (n = 3 experimental replicates). Expression value was normalized by tubulin family genes. Asterisk means significant differences (P < 0.05). Mann-Whitney U-test. qPCR levels of LOX family in PSCs, normalized to RPLP0 and relative to control. Relative values of protein levels for LOX members in PDAC tumors assessed by proteomic analysis (6 mice for control and 2 mg and 3 mice for 5 mg, and samples were analyzed in duplicates). Immunofluorescence images of PDAC tissues from KPC mice treated with vehicle (control), and 2 mg and 5 mg of tamoxifen, scale bar 50 μm. Quantification of LOX-L2 for images in (F). n = 5 (control), 4 (2 mg), and 3 (5 mg), and n > 10 sections per animal. qPCR levels of LOX-L2 and HIF-1A in PSCs, normalized to RPLP0 and relative to 1 kPa. qPCR levels of LOX-L2 and HIF-1A in PSCs, normalized to RPLP0 and relative to control. Quantification of average forces applied by PSCs on pillars. BBI = blebbistatin. In the box-and-whisker plot, the central box represents values from the lower and upper quartile. The middle line represents the mean. The vertical line extends from the minimum to the maximum. Three experimental repeats. qPCR levels of LOX-L2 in PSCs, normalized to RPLP0 (60S acidic ribosomal protein P0) and relative to control. Data information: In all cases, histogram bars represent mean ± SEM. *P < 0.05, **P < 0.01, ***P < 0.001 (t-test for B, D, I; ANOVA and Tukey's post hoc test for A, G, H, J, K). For (A, D, H, I, J, and K) three replicates collected in at least three different experiments. Download figure Download PowerPoint Next, we examined the effect of tamoxifen treatment on the expression levels of all LOX family members in PSCs and PDAC tissues from KPC mice using RNA sequencing, qPCR, and quantitative proteomics analysis. Except for LOX-L1, we observed a marked decrease in the mRNA levels of all members expressed by PSCs, and there was a significant downregulation in the protein content of LOX-L2 and LOX-L3 in tissues coming from KPC mice treated with 5 mg tamoxifen (Fig 2C–E). This dose-dependent significant decrease of LOX-L2 in tissues was also validated by dual staining of LOX-L2 and αSMA (marker of PSCs) immunofluorescence analysis (Fig 2F and G). In order to gain insights in the mechanism by which tamoxifen decreases LOX-L2 levels in PSCs, we cultured these cells in polyacrylamide (PAA) matrices of varying rigidities: 1 kPa (soft matrix) or 25 kPa (stiff matrix) as previously reported 2526. LOX-L2 and HIF-1A levels were significantly upregulated in PSCs cultured on stiff compared to the soft matrices, and tamoxifen-treated PSCs cultured on stiff substrates expressed LOX-L2 and HIF-1A levels comparable to the ones shown on the soft matrices (Fig 2H). These results led us to investigate whether increased contractility in PSCs could per se increase the levels of expression of LOX-L2 and HIF-1A. We transfected PSCs with a myosin isoform that was constitutively active and monitored the levels of LOX-L2 and HIF-1A from PSCs cultured on glass. Both LOX-L2 and HIF-1A were significantly upregulated in PSCs transfected with active myosin compared to the values from control PSCs (Fig 2I). We used micropillars sensors as described previously 16 to observe that tamoxifen decreased myosin-dependent contractility in PSCs, with the endogenous forces applied to the matrix by tamoxifen-treated PSCs comparable to the forces observed with the use of blebbistatin (BBI), a strong inhibitor of myosin activation and cell contractility (Fig 2J). This decrease in traction forces was maintained with tamoxifen treatment in the presence of the ER antagonist but suppressed when the GPER antagonist was used. We also used siRNA against HIF-1A to knockdown HIF-1A expression in PSCs (Appendix Fig S4) and found that under these conditions, tamoxifen treatment did not reduce LOX-L2 levels beyond the values observed for PSCs transfected with siRNA against HIF-1A (Fig 2K). Collectively, these data show that tamoxifen decreases LOX-L2 in PSCs and PDAC tissues via GPER signaling and through a mechanism that involves mechanical downregulation of HIF-1A via myosin-dependent PSC contractility and matrix stiffness mechanosensing. Tamoxifen modulates collagen synthesis and matrix collagen remodeling by PSCs In order to study the effect of tamoxifen on the ability of PSCs to remodel the matrix, we used 3D organotypic assays in which PSCs were embedded within matrigel collagen gels and allowed to remodel the matrix for 72 h. Then, second harmonic generation (SHG) imaging was used to visualize type I fibrillar collagen (referred to as collagen hereafter) (Fig 3A). Untreated control PSCs modified the topology of fibrillar collagen in the ECM substantially differently than their tamoxifen-treated counterparts. We used the BoneJ plugin for ImageJ to quantify the thickness of fibrillar collagen fibers (Fig 3B), and a custom-made algorithm based on fast Fourier transforms (FFT) 15 to quantify the elliptical distribution of the fibrillar collagen network that indicates fiber alignment (Fig 3C). In this analysis, highly aligned collagen fibers exhibit values closer to 0 (elliptical distribution in Fig 3C inset), while randomly aligned fibers values close to 1 (circular distribution in Fig 3C inset). Overall, ECM remodeled by tamoxifen-treated PSCs showed a significant decrease in fibrillar collagen fiber diameter, length, and alignment compared to control PSCs (Fig 3D–F). Figure 3. Tamoxifen decreases collagen fiber thickness, length, and alignment A. Images of Matrigel collagen gels previously remodeled by PSCs, second harmonic generation signal for fibrillar collagen (green) and F-actin (red), scale bar 100 μm. B. Fiber thickness color-code map in a represented through the BoneJ plugin where larger spheres fit along fibers represent greater thickness, scale bar 100 μm. C. SHG fibrillar collagen images used for calculation of alignment through the FFT algorithm. Insets show FFTs of fibrillar collagen-I images, representing alignment with respect to the elliptical distribution of the FFT central maxima. Circular behavior (values approaching 1) represents no aligned orientation and lower values represent fiber orientation as alignment is displayed as a power distribution orthogonal to the orientation direction. Scale bar 20 μm. D–F. Quantification of fiber thickness, length, and alignment for images in (A–C). G. Quantification of collagen fiber thickness using the BoneJ algorithm for images in (B and H). H. Representative images of Matrigel collagen gels previously remodeled by PSCs, second harmonic generation signal for fibrillar collagen (green) and F-actin (red), scale bar 100 μm. Data information: n ≥ 6 matrices per condition. In the scatter plot in (E), each point represents a section. In the box-and-whisker plot in (D), the central box represents values from the lower to upper quartile. The middle line represents the mean. The vertical line extends from the minimum to the maximum value. Histogram bars (F and G) represent mean ± SEM. ***P < 0.001 (t-test for D, E, F; ANOVA and Tukey's post hoc test for G). Three experimental replicates for all panels. Download figure Download PowerPoint LOX-L2 catalyses the first step in the cross-linking of collagen bundles. In order
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