Compositions and methods for the treatment of systemic sclerosis and other fibrotic diseases and conditions

Abstract

Provided herein are compositions and methods for the treatment of systemic sclerosis and related diseases and conditions. In particular, provided herein are Hippo pathway effectors and their uses in the treatment of systemic sclerosis and related and other fibrotic diseases and conditions.

Description

[0001] COMPOSITIONS AND METHODS FOR THE TREATMENT OF SYSTEMIC SCLEROSIS AND OTHER FIBROTIC DISEASES AND CONDITIONS

[0002] The present application claims priority to United States Provisional Patent Application Serial Number 63 / 598,805, filed November 14, 2023, the disclosure of which is herein incorporated by reference in its entirety.

[0003] SEQUENCE LISTING

[0004] The text of the computer readable sequence listing filed herewith, titled “42597- 601 SEQUENCE LISTING”, created November 14, 2024, having a file size of 53,912 bytes, is hereby incorporated by reference in its entirety.

[0005] FIELD

[0006] Provided herein are compositions and methods for the treatment of systemic sclerosis and related diseases and conditions. In particular, provided herein are Hippo pathway effectors and their uses in the treatment of systemic sclerosis and related and other fibrotic diseases and conditions.

[0007] BACKGROUND

[0008] Systemic sclerosis (SSc) (also known as systemic scleroderma) is a devastating autoimmune disease characterized by excessive production and accumulation of extracellular matrix leading to fibrosis of skin and other internal organs. Systemic sclerosis is associated with mortality rates that in its most severe form are comparable to metastatic cancers (1,2). The etiology of SSc remains poorly understood but involves genetic predisposition (3), female sex (4), and environmental exposures (5,6), resulting in autoimmunity, fibrosis in the skin and internal organs, along with prominent microvasculopathy (7).

[0009] Skin thickening in SSc is due to increased deposition of extracellular matrix (ECM) components, most prominently type I collagen (9,10). With disease progression, there is increasing dermal fibrosis and loss of adnexa (11). The increased skin tightness correlates with accumulation of myofibroblasts in the skin (12,13). Myofibroblasts are mesenchymal cells of fibroblast lineage that are transiently activated during normal wound healing (14). In contrast to fibroblasts, myofibroblasts express the contractile protein alpha smooth muscle actin, and form characteristic stress fibers (15). Myofibroblasts are commonly first detected in the deep dermis (16), and their persistence in SSc (17,18) is thought to be responsible for the exaggerated and uncontrolled ECM production (15,18). The factors driving differentiation and accumulation of myofibroblasts in SSc have been extensively investigated. It is currently thought that TGF-P and mechanical forces are key factors in myofibroblast development (14,19). Notably, mechanical stiffness itself activated latent TGF-P (20-23), setting up a self- sustaining amplification circuit for tissue fibrosis in SSc skin (10).

[0010] Vascular dysfunction and structural abnormalities, particularly involving the arterioles, are among the earliest manifestations of SSc and precede development of fibrosis (24). This vascular dysfunction results in altered capillary architecture with reduced vessel density, a hallmark of SSc, causing decreased capillary blood flow and tissue hypoxia (25). Clinically, these microvascular changes underlie painful digital ulcerations, pulmonary arterial hypertension, gastric vascular ectasia, mucocutaneous telangiectasia and scleroderma renal crisis (26-28). Larger vessels, including arterioles in the lung and the kidney, may show intimal proliferation (onion skinning) and adventitial fibrosis, accompanied by loss of pericytes. Apoptosis of endothelial cells in SSc was first noted over 25 years ago (29), and there is accumulating evidence that this endothelial damage may be immune-mediated (30). Immune mechanisms underlying the endothelial damage in SSc include cytotoxic T cells (8) and anti-endothelial autoantibodies (31). Upon microvascular injury, endothelial cells can acquire a mesenchymal phenotype through a process termed endothelial-to-mesenchymal transition (EndoMT) (32). EndoMT is characterized by the loss of cell-cell junctions and endothelial markers, such as von Willebrand factor, CD31, and VE-cadherin, coupled with the acquisition of invasive properties and gain of mesenchymal markers such as alpha SMA and collagens (33). EndoMT has been implicated in driving the pathogenesis of fibrosis in multiple fibrotic conditions, including SSc (34).

[0011] The mechanisms and the main cellular participants in SSc skin fibrosis remain incompletely understood. Current treatment paradigms can slow, but not halt or reverse, fibrosis (8). There are no treatments that can cure or stop the fibrosis associated with SSc. Antifibrotic agents (D-penicillamine, interferon alfa and interferon gamma, and immunomodulatory agents (photopheresis, corticosteroids, methotrexate, chlorambucil, mycophenolate mofetil cyclosporine, FK506, thalidomide, cyclophosphamide, and statins)) have been investigated, although results have varied and none is clearly shown to be of consistent benefit. Treatments are primarily limited to attempts to help control symptoms and prevent complications. SUMMARY

[0012] Experiments conducted during the development of embodiments of the present technology demonstrated a dual source of extracellular matrix deposition in SSc skin from both myofibroblasts and endothelial to mesenchymal transitioning cells (EndoMTs), characterized their differentiation trajectories at a single cell level, and defined a central role of Hippo pathway effectors in promoting and maintaining myofibroblast differentiation and EndoMT. Further, ligand-receptor analysis revealed that myofibroblasts and EndoMTs act as central communication hubs that drive key pro-fibrotic signaling pathways in SSc. Together, these discoveries provide comprehensive and detailed characterization of myofibroblast differentiation and EndoMT in SSc skin and demonstrate that modulation of the Hippo pathway can reverse the pro-fibrotic phenotypes in myofibroblasts and EndoMTs. As such, Hippo pathway modulators find use in the treatment and / or prevention SSc.

[0013] The Hippo pathway is a highly conserved signaling pathway that regulates cell proliferation, apoptosis, and sternness in response to a wide range of extracellular and intracellular signals. Downstream effects of Hippo pathway signaling are mediated by the YAP and TAZ transcription co-activators through binding with members of the TEAD family of transcription factors (35). When the Hippo pathway is inactive, YAP / TAZ enters the nucleus, competes with VGLL family of transcription co-factors for binding to TEADs, and recruits other factors to induce gene transcription (35,36). When Hippo pathway is active, YAP / TAZ is phosphorylated by LATS1 / 2 on multiple sites and is retained in the cytoplasm due to interaction with 14-3-3 proteins and eventually removed through poly-ubiquitination and degradation (35). Hippo signaling has been shown to regulate the expression of ligands for WNT, TGF-P, JAK-STAT, EGFR, and Notch pathways (37), placing this pathway at the nexus of multiple biological processes, many of which have been implicated in SSc pathogenesis (38-42).

[0014] In some embodiments, provided herein are methods, and compositions for use in such methods, comprising: treating a subject having systemic sclerosis (SSc) with a Hippo pathway effector under conditions that reduce or prevent fibrosis. In some embodiments, the subject (e.g., a human patient) is previously diagnosed with SSc. In some embodiments, the subject is suspected of having SSc. In some embodiments, the Hippo pathway effector is a TEAD inhibitor (e.g., a protein-protein interaction disruptor of TEAD / YAP, a TEAD inhibitor that prevents YAP translocation to the nucleus to activate TEAD, etc.). In some embodiments, the TEAD inhibitor is one or more of Verteporfin (e.g., without light activation), (R)-PFI 2 hydrochloride, TAT-PDHPS1, TM2 TEAD inhibitor, K-975, IK-930, IAG933, GNE-7883, YTP-17, VT3989, BPI-460372, GH658, BGI-9004, SPR1-0117, VT- 107, VT103, TED-347, MYF-01-37, YAP-TEAD-IN-1 TFA, YAP-TEAD-IN-2, YAP- TEAD-IN-3, YAP / TAZ inhibitor- 1 (WO2017058716), VT104, YAP / TZ inhibitor-2, MSC- 4106, TT-10, Super-TDU, TEAD-IN-3, Super-TDU (1-31) (TFA), SWTX-143, MY- 1076, TEAD-IN-6, RNAi, siRNA, or shRNA modulation (e.g., YAP-depletion), CRISPR-mediated regulators (see e.g., Quinton and Ganem, Methods Mol. Biol., 1893:203-214 (2019), herein incorporated by reference in its entirety), or nanobody or other target-specific protein- or peptide-based inhibition. In some embodiments, the Hippo pathway effector is a VGLL3 regulator (e.g., an agent that blocks an interaction between VGLL3 and TEAD.

[0015] In some embodiments, the subject is evaluated, at one or more time intervals, prior to, during, or following administration of a Hippo pathway effector. In some embodiments, the evaluation comprises the step of assessing efficacy of the Hippo pathway effector in reducing or preventing fibrosis. In some embodiments, the assessing comprises evaluating a sign or symptom of SSc. In some embodiments, the assessing comprises evaluating a cellular or molecular biomarker (e.g., assessing a profibrotic phenotype or reversal of profibrotic phenotype of myofibroblasts and / or endothelial to mesenchymal transitioning cells (EndoMTs)).

[0016] In some embodiments, the treating comprises systemic delivery of the Hippo pathway effector (e.g., TEAD inhibitor) to the subject. In some embodiments, the systemic delivery comprises injection, oral, or transdermal delivery. In some embodiments, the injection comprises intravenous, subcutaneous, or intraperitoneal administration. Administration may comprise infusion.

[0017] In some embodiments, the treating further comprises co-administering an agent or conducting a procedure that controls symptoms and / or prevents complications of SSc. In some embodiments, the symptoms comprise one or more Raynaud syndrome (e.g., nerve surgery, botulinum toxin A, calcium channel blockers, vasodilators), polyarthralgia / arthritis (e.g., NSAIDs, COX-2 inhibitors, acetaminophen), dysphagia (e.g., dietary changes, tube feeding, learning exercises, surgery, corticosteroids), heartburn (e.g., antiacids, H2 blockers, proton pump inhibitor), gastroparesis (promotility agents), constipation (promotility agents, stool softeners), skin swelling (e.g., antihistamine, corticosteroid creams, immunomodulators), skin tightening (e.g., radiofrequency therapy, laser treatment, intense pulsed light), and contractures of fingers (e.g., needling, steroids, collagenase, surgery). In some embodiments, the complications comprise one or more of interstitial lung disease (e.g., corticosteroids, pirfenidone, nintedanib, H2 blockers, immunosuppressive and biologies therapy, proton pump inhibitors, oxygen therapy, surgery), pulmonary arterial hypertension (e.g., vasodilators, soluble guanylate cyclase stimulators, calcium channel blockers, digoxin, anticoagulants, diuretics, oxygen therapy), and scleroderma renal crisis (ACE-I therapy, endothelin receptor blockers, surgery).

[0018] Also provided herein are ex vivo systems and methods for determining an effect of a therapeutic agent, comprising one or more or all of the steps of: a) obtaining a tissue sample from a subject, b) contacting the tissue sample (e.g., cells in suspension) with an agent ex vivo to produce treated cells, c) isolating treating cells (e.g., using barcoded beads) to generated isolated cells, d) preparing a nucleic acid sequencing library from said isolated cells; e) sequencing the sequencing library to generate sequencing data, and f) analyzing the sequencing data to determine an effect of said agent on said tissue. In some embodiments, the analyzing comprises comparing sequencing data to data obtained from a control sample not contacted with the agent or to a different treatment condition (e.g., treatment with a different agent, with multiple agents, or with a different dose or formulation of the same agent). In some embodiments the analyzing comprises determining an effect of the agent on two or more (e.g., 3 or more, 5 or more, 10 or more, etc.) different cell types found in said tissue sample. In some embodiments, the analyzing comprises determining cell differentiation status of one or more cell types found in said tissue sample. In some embodiments, the analyzing comprises generating a report that identifies shifts in cell populations between treated cells and control cells. In some embodiments, the analyzing comprises identifying a change in pathogenic cell-cell interactions in response to treatment with said agent.

[0019] Definitions

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. However, in case of conflict, the present specification, including definitions, will control. Accordingly, in the context of the embodiments described herein, the following definitions apply. As used herein and in the appended claims, the singular forms “a”, “an” and “the” include plural reference unless the context clearly dictates otherwise.

[0021] As used herein, the term “comprise” and linguistic variations thereof denote the presence of recited feature(s), element(s), method step(s), etc. without the exclusion of the presence of additional feature(s), element(s), method step(s), etc. Conversely, the term “consisting of’ and linguistic variations thereof, denotes the presence of recited feature(s), element(s), method step(s), etc. and excludes any unrecited feature(s), element(s), method step(s), etc., except for ordinarily-associated impurities. The phrase “consisting essentially of’ denotes the recited feature(s), element(s), method step(s), etc. and any additional feature(s), element(s), method step(s), etc. that do not materially affect the basic nature of the composition, system, or method. Many embodiments herein are described using open “comprising” language. Such embodiments encompass multiple closed “consisting of’ and / or “consisting essentially of’ embodiments, which may alternatively be claimed or described using such language.

[0022] As used herein, the term “subject” broadly refers to any animal, including but not limited to, human and non-human animals (e.g., dogs, cats, cows, horses, sheep, poultry, fish, crustaceans, etc.). As used herein, the term “patient” typically refers to a human subject that is being treated for a disease or condition.

[0023] As used herein, the term “effective amount” refers to the amount sufficient to effect beneficial or desired results. An effective amount can be administered in one or more administrations, applications or dosages and is not intended to be limited to a particular formulation or administration route.

[0024] As used herein, the terms “administration” and “administering” refer to the act of giving a drug, prodrug, or other agent, or therapeutic treatment to a subject or in vivo, in vitro, or ex vivo cells, tissues, and organs. Exemplary routes of administration to the human body can be by injection (e.g., intravenously, subcutaneously, intraperitoneally, etc.), mouth (oral), skin (topical or transdermal), and the like.

[0025] As used herein, the terms “co-administration” and “co-administering” refer to the administration of at least two agent(s) or therapies to a subject. In some embodiments, the coadministration of two or more agents or therapies is concurrent. In other embodiments, a first agent / therapy is administered prior to a second agent / therapy. Those of skill in the art understand that the formulations and / or routes of administration of the various agents or therapies used may vary. The appropriate dosage for co-administration can be readily determined by one skilled in the art. In some embodiments, when agents or therapies are coadministered, the respective agents or therapies are administered at lower dosages than appropriate for their administration alone. Thus, co-administration is especially desirable in embodiments where the co-administration of the agents or therapies lowers the requisite dosage of a potentially harmful (e.g., toxic) agent(s), and / or when co-administration of two or more agents results in sensitization of a subject to beneficial effects of one of the agents via co-administration of the other agent.

[0026] As used herein, the term “treatment” means an approach to obtaining a beneficial or intended clinical result. The beneficial or intended clinical result may include alleviation of symptoms, a reduction in the severity of the disease, inhibiting an underlying cause of a disease or condition, steadying diseases in a non-advanced state, delaying the progress of a disease, and / or improvement or alleviation of disease conditions.

[0027] As used herein, the term “pharmaceutical composition” refers to the combination of an active agent with a carrier, inert or active, making the composition especially suitable for diagnostic or therapeutic use in vitro, in vivo or ex vivo.

[0028] The terms “pharmaceutically acceptable” or “pharmacologically acceptable,” as used herein, refer to compositions that do not substantially produce adverse reactions, e.g., toxic, allergic, or immunological reactions, when administered to a subject.

[0029] As used herein, the term “pharmaceutically acceptable carrier” refers to any of the standard pharmaceutical carriers including, but not limited to, phosphate buffered saline solution, water, emulsions (e.g., such as an oil / water or water / oil emulsions), and various types of wetting agents, any and all solvents, dispersion media, coatings, sodium lauryl sulfate, isotonic and absorption delaying agents, disintegrants (e.g., potato starch or sodium starch glycolate), and the like. The compositions also can include stabilizers and preservatives. For examples of carriers, stabilizers and adjuvants, see, e.g., Martin, Remington's Pharmaceutical Sciences, 15th Ed., Mack Publ. Co., Easton, Pa. (1975), incorporated herein by reference in its entirety.

[0030] As used herein, a “Hippo pathway effector” refers to an agent or agents (e.g., small molecule, RNAi molecule, peptide, protein, gene editing system, etc.) that activate or inhibit a component of the Hippo signal transduction pathway resulting in an “off’ mode of the Hippo pathway that promotes cell growth via activation of TEAD (transcriptional enhanced associated domain) protein(s) (e.g., TEAD1, TEAD2, TEAD3, and / or TEAD4) via YAP (yes-associated protein) translocation to the nucleus and YAP binding and activation of TEAD; or an “on” mode of the Hippo pathway that prevents YAP from translocating to the nucleus and / or binding to and / or activating TEAD resulting in a “stop growing” mode. Hippo pathway effectors include, for example, TEAD inhibitors. TEAD inhibitors include agents that function as protein-protein interaction disruptors (PPIDs) that disrupt the ability of YAP to functionally bind to TEAD, as well as agents that prevent YAP from translocating to the nucleus to activate TEAD. TEAD inhibitors may be pan-TEAD inhibitors or may have specificity for one or a sub-set of TEADs (e.g., TEAD 1 -specific, TEAD1- and TEAD4- specific, etc.). TEAD PPIDs may interact with TEAD in a central pocket and / or at one or more surface interfaces (Interface 1, Interface 2, Interface 3). TEAD inhibitors include, but are not limited to, Verteporfm (e.g., without light activation), (R)-PFI 2 hydrochloride, TAT- PDHPS1, TM2 TEAD inhibitor, K-975, IK-930, IAG933, GNE-7883, YTP-17, VT3989, BPI-460372, GH658, BGI-9004, SPR1-0117, VT-107, VT103, TED-347, MYF-01-37, YAP- TEAD-IN-1 TFA, YAP-TEAD-IN-2, YAP-TEAD-IN-3, YAP / TAZ inhibitor- 1 (WO2017058716), VT104, YAP / TZ inhibitor-2, MSC-4106, TT-10, Super-TDU, TEAD-IN- 3, Super-TDU (1-31) (TFA), SWTX-143, MY-1076, and TEAD-IN-6. In some embodiments, the Hippo pathway effector regulates MST1 / 2, LATS1 / 2, 14-3-3, SAV1, and / or M0B1. In some embodiments, the Hippo pathway effector regulates an association between VGLL3 and TEAD.

[0031] Description of Figures

[0032] FIG. 1 shows cell types observed in SSc skin and their spatial locations, a. UMAP plot showing 96,174 cells colored by cell types, b. UMAP plot showing the cells colored by disease conditions. SSc: systemic sclerosis; NS: normal skin. c. Bar plot showing the abundance composition across the disease conditions for each cell type in scRNA-seq. d. Dot plot showing representative marker genes for each cell type. The color scale represents the scaled expression of each gene. The size of the dot represents the percentage of cells expressing each gene of interest, e. Spatial plot showing the deconvolution score for each cell type. The coordinates of the spot correspond to the location in the tissue (spatial data representative of n=4).

[0033] FIG. 2 shows identification of fibroblast subtypes and their spatial locations, a. UMAP plot showing 25,182 fibroblasts colored by subtypes, b. UMAP plot showing the fibroblasts colored by disease conditions, c. Bar plot showing the abundance composition across the disease conditions for each fibroblast subtype, d. Violin plot showing the extracellular matrix module scores in the fibroblast subtypes, e. Dot plot showing the top marker genes for each fibroblast subtype. The color scale represents the scaled expression of each gene. The size of the dot represents the percentage of cells expressing the gene of interest, f. The left two panels show the COL1 Al expression and extracellular matrix module score across all the spots in four spatial-seq samples. The right two columns show the deconvolution score for the SFRP2+ FB and C0L8A1+ FB in the fibroblast-rich spots, g. Immunohistochemistry staining for SMA in SSc skin tissue. The size bar represents 100 um (staining is representative of n=3). h. Immunofluorescence showing the colocalization of Vimentin and SMA in the SSc and NS tissues (staining is representative of n=3). The size bar represents 100 um.

[0034] FIG. 3 shows Hippo pathway regulation of myofibroblast differentiation in SSc skin, a. UMAP plot showing the SFRP2+ FB and COL8A1+ FB colored by groups, b. UMAP plot showing the SFRP2+ FB and COL8A1+ FB colored by disease conditions, c. UMAP plots showing the expression level of ACTA2, TAGLN and COL8A1 in the three fibroblast groups, d. UMAP plot showing the CytoTRACE score in the three fibroblast groups. A higher CytoTRACE score suggests the cell being more differentiated, e. Violin plots showing the extracellular matrix, TGF-P and IL-4 module scores in the three fibroblast groups, f. Violin plots showing the expression level of CTGF and CYR61 in the three fibroblast groups, g. Pseudotime trajectory colored by the pseudotime of the three fibroblast groups, h. Pseudotime trajectory colored by the group identity of the three fibroblast groups, i. Scatter plots showing the correlation between the fibroblast pseudotime and the target score or the upstream regulators. The color represents the group identity of the cell. Correlation test was applied, j . Quantitative PCR results showing the effect of TRULI or verteporfm (both 10 pM) on ACTA2 and COL1 Al expression in dcSSc fibroblasts. Data normalized to NT. N=5-7. Data presented as mean + / - SD. Unpaired t-test was applied. P<0.05 was designated as statistically significant, k. Effect of TRULI or verteporfm (both 10 uM) on COL1 and SMA levels by Western blotting. Data normalized to NT. Unpaired t-test was applied. P<0.05 was designated as statistically significant. 1. Immunofluorescence showing TRULI enhanced while verteporfm Inhibited COL1 and SMA expression in dcSSc fibroblasts, m. TRULI enhanced while verteporfm blocked gel contraction in dcSSc fibroblasts. Data normalized to the corresponding NT group. N=3. n. TRULI increased cell proliferation while verteporfm dose-dependently blocked cell growth. Cell proliferation was monitored by analyzing the occupied area by cells over time, using the IncuCyte® S3 Analysis software. N=3. Two-way ANOVA test was applied. P<0.05 was designated as statistically significant, o. TRULI enhanced cell migration while verteporfin blocked migration in a dose-dependent manner. Two-way ANOVA test was applied. P<0.05 was designated as statistically significant, p. Extent of knockdown of genes relevant in the Hippo pathway in dcSSc fibroblasts. N=5. Paired t-test was applied. P<0.05 was designated as statistically significant, q. Knockdown of genes involved in the Hippo pathway resulted in downregulation of ACTA2 and COL1A1. N=4-6. Unpaired t-test was applied. P<0.05 was designated as statistically significant.

[0035] FIG. 4 shows characterization of endothelial to mesenchymal transition in SSc skin. a. UMAP plot showing 5,070 endothelial cells colored by sub-clusters, b. UMAP plot showing the endothelial cells colored by disease conditions, c. Dot plot showing the top marker genes for each endothelial sub-cluster. The color scale represents the scaled expression of each gene. The size of the dot represents the percentage of cells expressing the gene of interest, d. Violin plots showing the expression level of representative genes in the endothelial subcluster 0, 1 and 2. e. Violin plots showing the extracellular matrix module score in the endothelial sub-clusters, f. UMAP plot showing the CytoTRACE score in the endothelial subclusters. A higher CytoTRACE score suggests the cell being more differentiated, g. Immunofluorescence showing the colocalization of SMA and CD31 in the NS and SSc skin tissues. Images shown are representative of n=3. The size bar represents 20 um. h. Pseudotime trajectory colored by the pseudotime (left) and sub-cluster identity (right) of three endothelial sub-clusters, i. Scatter plot showing the correlation coefficients between the target score of the upstream regulators and the fibroblast pseudotime (X axis) and endothelial pseudotime (Y axis), j. Immunofluorescence showing the colocalization of TEAD1 / CD31 (left) and TEAD3 / CD31 (right) in the NS and SSc skin tissues. Images shown are representative of n=3. The size bar represents 20 um. k. Bar plots showing the percentage of cells expressing the gene in the endothelial sub-cluster 0, 1 and 2. 1. Bar plot showing the top five Gene Ontology pathways enriched for the 240 common up-regulated genes in fibroblast group 3 compared to group 1, 2 and endothelial sub-cluster 2 compared to sub-cluster 0, 1.

[0036] FIG. 5 shows Hippo pathway regulation of endothelial to mesenchymal transition in SSc skin. a. The effect of TRULI (10 uM) and verteporfin (1 uM) on ACTA2, COL1A1, PECAM1, and CDH5 expression in dcSSc endothelial cells. Mann-Whitney test was applied. P<0.05 was designated as statistically significant, b. Western blotting showing the effect of TRULI or verteporfin on VWF, COL1, and SMA in dcSSc endothelial cells. The expression levels of each protein in healthy dermal ECs are shown for comparison. Student’s t-test was applied. P<0.05 was designated as statistically significant. NL: normal c.

[0037] Immunofluorescence showing TRULI enhanced the mesenchymal phenotype while verteporfin promoted the endothelial phenotype in dcSSc endothelial cells, while in healthy ECs, TRULI induced EndoMT to a lesser extent, while verteporfin had minimal effect. Images shown are representative of n=3. Scale bar = 50 um. d. The extent of knockdown of YAP1, VGLL3, or TEAD3 in dcSSc endothelial cells. N=3. Unpaired t-test was applied. P<0.05 was designated as statistically significant, e. Knockdown of genes involved in the Hippo pathway blocked the EndoMT phenotype in dcSSc endothelial cells. Unpaired t-test was applied. P<0.05 was designated as statistically significant. Data presented as mean + / - SD.

[0038] FIG. 6 shows that myofibroblasts and EndoMTs act as central hubs in cell-cell communications, a. Heatmap showing the number of ligand-receptor pairs with interaction scores higher in SSc compared to NS. Row, cell type expressing the ligand; column, cell type expressing the receptor. Color scale, number of ligand-receptor pairs. EC, endothelial cell; FB, fibroblast; ML, myeloid cell; BC, B cell. Mast, mast cell; SMC, smooth muscle cell; KC, keratinocyte; PRC, pericyte. TC, T cell; ECG, eccrine gland cell; MLNC, melanocyte, b. Connectome web analysis of interacting subtypes in the SSc samples. Vertex (colored cell node) size is proportional to the number of interactions to and from that cell type, whereas the thickness of the connecting lines is proportional to the number of interactions between two nodes, c. Dot plots showing expression of the ligands (left) and receptors (right) in endothelial and fibroblast subtypes in the SSc samples. Color scale indicates the level of expression in positive cells, whereas dot size reflects the percentage of cells expressing the gene.

[0039] FIG. 7 shows cell type deconvolution for four SSc spatial-seq samples, a-d. Each panel contains one SSc spatial-seq sample. The top plot shows the H & E staining of the skin biopsy. The bottom scatter pie plot shows the cell type composition for each spot in the spatial-seq sample. Each spot is represented as a pie chart showing the relative proportion of the cell types.

[0040] FIG. 8 shows cell type deconvolution for four SSc spatial-seq samples, a. UMAP plot showing 25,182 fibroblasts colored by sub-clusters, b. Dot plot showing the expression of all the collagen genes across the fibroblast subtypes. The color scale represents the scaled expression of each gene. The size of the dot represents the percentage of cells expressing the gene of interest, c. Spatial plots showing the deconvolution score for the other five fibroblast subtypes in the fibroblast-rich spots.

[0041] FIG. 9 shows that Hippo pathways regulates myofibroblast differentiation in SSc skin, a. Heatmap showing expression of significant marker genes corresponding to five expression patterns that span the fibroblast pseudotime trajectory. Color scale, scaled gene expression across pseudotime. b. Bar plots showing the percentage of cells expressing the gene in the three fibroblast groups, c. The basal levels of C0L1 and SMA in healthy dermal fibroblasts, d. Immunofluorescence showing TRULI enhanced while verteporfin Inhibited COL1 and SMA expression in dcSSc fibroblasts. Similar results were observed in normal dermal fibroblasts. However, TRULI appeared to have a smaller effect in these cells than dcSSc fibroblasts. Scale bar = 50 um. e. TRULI enhanced while verteporfin blocked proliferation in dcSSc fibroblasts. In contrast, in healthy fibroblasts, these drugs had minimal effects (Truli lOuM and Verteporfin 0.5 uM). A two-way ANOVA test was applied. P<0.05 was designated as statistically significant, f. TRULI enhanced cell migration while verteporfin blocked migration in dcSSc fibroblasts. In healthy fibroblasts, these drugs had minimal effects (Truli lOuM and Verteporfin 0.25 uM). A two-way ANOVA test was applied. P<0.05 was designated as statistically significant.

[0042] FIG. 10 shows characterization of endothelial to mesenchymal transition in SSc skin, a. UMAP plots showing the expression level of endothelial marker genes and mesenchymal marker genes in the endothelial sub-clusters, b. Dot plot showing the expression of all the collagen genes across the endothelial sub-clusters. The color scale represents the scaled expression of each gene. The size of the dot represents the percentage of cells expressing the gene of interest, c. Bar plot showing the abundance composition across the disease conditions for each endothelial sub-cluster, d. Heatmap showing expression of significant marker genes corresponding to five expression patterns that span the endothelial pseudotime trajectory. Color scale, scaled marker gene expression across pseudotime.

[0043] FIG. 11 shows identification of keratinocyte, pericyte, smooth muscle, myeloid and T cell subtypes, a. Identification of keratinocyte subtypes, b. Identification of T cell subtypes, c. Identification of myeloid subtypes, d. Identification of pericyte and smooth muscle subtypes. FIG. 12 shows identification of eccrine gland, melanocyte, nerve, mast cell and B cell subtypes, a. Identification of eccrine gland subtypes, b. Identification of melanocyte subtypes, c. Identification of nerve cell subtypes, d. Identification of mast cell subtypes, e. Identification of B cell subtypes.

[0044] FIG. 13 shows cell-cell communications in the NS samples, a. Bar plot showing the number of self-interactions that are higher in SSc compared to NS in each cell type. b. Heatmap showing the number of ligand-receptor pairs with interaction scores higher in NS compared to SSc. Row, cell type expressing the ligand; column, cell type expressing the receptor. Color scale, number of ligand-receptor pairs. EC, endothelial cell; FB, fibroblast; ML, myeloid cell; Mast, mast cell; KC, keratinocyte; PRC, pericyte. TC, T cell; ECG, eccrine gland cell; MLNC, melanocyte, c. Connectome web analysis of interacting subtypes in the NS samples. Vertex (colored cell node) size is proportional to the number of interactions to and from that cell type, whereas the thickness of the connecting lines is proportional to the number of interactions between two nodes. The Vertex size and the line thickness follow the same scales as in Fig. 6b.

[0045] FIG. 14 shows a schematic overview of the critical role of Hippo pathway in modulating myofibroblast differentiation and endothelial to mesenchymal transition in SSc skin.

[0046] FIG. 15 shows ex vivo data with processing steps (A), identified cell populations in both vehicle and treatment samples (B), shifts in cell populations (including disappearance of myofibroblasts with verteporfm treatment) (C and D), collapse in pathogenic cell-cell interactions in scleroderma with verteporfm treatment (E), and impact on myofibroblast differentiation without impacting cell death (F).

[0047] DETAILED DESCRIPTION

[0048] Fibroblast-myofibroblast transition and vascular dysfunction have long been recognized as key pathologic features in SSc (17,18,24). Vascular abnormalities involving the arterioles are among the earliest manifestations occurring in almost every SSc patient (25). This vascular dysfunction precedes development of fibrosis and manifests clinically as Raynaud’s phenomenon, digital ulcerations, and increased prominence of nailfold capillary loops (24,25). The subsequent fibrosis is thought to result from exaggerated and uncontrolled production of ECM components mainly by myofibroblasts in SSc skin (15,18). However, the relationship between the vascular dysfunction and triggering of fibrosis has remained unclear. Experiments conducted during the development of embodiments of the present invention demonstrated that, in the SSc environment, the SFRP2+ FB progressively acquires qualities of myofibroblasts as it transitions into fully developed myofibroblasts defined by ACTA2 and C0L8A1 expression. The SFRP2+ FB and myofibroblasts are the major source of COL1 Al expression by fibroblastic lineage cells in SSc skin. Strikingly, with spatial-seq and scRNA-seq integration, we observe prominent compartmentalization of the fibrotic process in SSc skin, with increased COL1 Al expression and ECM activity occurring in localized areas both superficially and deep in the dermis. Those areas correspond to the SFRP2+ FB and myofibroblast signatures, with the SFRP2+ FB being most prominent in the superficial dermis whereas myofibroblasts predominate in the deeper layers of the dermis. The experiments further demonstrate that EndoMT represents another source of ECM in SSc skin, which provides novel insight into the molecular mechanisms driving EndoMT at single cell resolution.

[0049] Notably, most of the cellular interactions activated in SSc skin involved only two major cell types, endothelial cells, and fibroblasts. Of those, the most pronounced cell-cell interactions were seen between the EndoMTs (EC2) and myofibroblasts (C0L8A1+ FB). These interactions involve different chemokines (CCL2, CCL8, CCL11, CXCL1), cytokines (IL6, IL11, TGFB1, TFGB3, TNFSF4, TNFSF9, TNFSF12), growth factors (FGF2, FGF7, FGF18, VEGFA, VEGFB), and WNT ligands (WNT2, WNT4). Many of these mediators have been implicated in SSc pathogenesis including CCL2 and CCL8 in promoting dendritic cell differentiation (66), IL6 and IL11 in promoting fibrosis (39,59,67), TNFSF4 as genetic predisposition in SSc (68), FGF7 in fibroblast activation (69), VEGF in vascular dysfunction (70), and WNT2 in dermal fibrillin deposition (40).

[0050] The data presented here also implicate non-stromal cell populations in SSc pathogenesis, particularly immune cells including B cells and T cells. B cells were highly enriched in SSc skin and may provide a link between pathological processes in the skin and development of autoantibodies, found in most patients with SSc (88). CD8 T cells have been postulated to serve as key drivers in the prominent endothelial dysfunction in SSc (8), with some of the earliest features SSc being perivascular edema along with perivascular mononuclear infiltrate particularly in the upper and mid-dermis (11). These early changes coincide with the same dermal locations where EndoMTs, characterized by SMA+CD31+, are prominent. Besides immune cells, other stromal cells, such as the smooth muscle cells, which were primarily derived from the SSc biopsies, may also play a role in pathogenesis. It is demonstrated herein that the profibrotic phenotypes of myofibroblasts and EndoMTs in SSc are reversed by inhibiting TEAD transcriptional activity.

[0051] Thus, in some embodiments, provided herein are compositions and methods for the treatment of SSc and related and other fibrotic diseases and conditions (e.g., diseases and conditions showing a similar profibrotic phenotype of myofibroblasts and EndoMTs), as well as inflammatory diseases and conditions (e.g., inflammatory diseases and conditions that include scarring, such as cutaneous lupus), by the administration of a Hippo pathway effector (e.g., TEAD inhibitor) to a subject having, or suspected of having, the disease or condition. In some embodiments, the related and / or other fibrotic diseases and conditions are idiopathic pulmonary fibrosis (IPF), cardiac fibrosis, kidney fibrosis, and liver fibrosis. In some embodiments, the related and / or other fibrotic and / or inflammatory disease and condition is Hidradenitis Suppurativa. Systemic sclerosis is classified into two subsets based on the extent of skin involvement - limited systemic sclerosis (IcSSc) and diffuse systemic sclerosis (dsSSc). Patients with fibrosis of the skin affecting acral parts of the body - face and limbs (distal to the knees and elbows) - are classified as having IcSSc, whereas those with fibrosis of the trunk and proximal parts of the limbs are classified as having dsSSc. Although IcSSc has slow progression of skin fibrosis and Raynaud’s phenomenon starts long before the skin symptoms, it is not limited to skin involvement and is also associated with the involvement of the esophagus and lungs. However, late and slow organ involvement in IcSSc is associated with relatively good prognosis with 10-year survival over 90%. Patients with dsSSc have poorer prognosis because of fast progression of skin and organ involvement including cardiovascular system, lungs, kidneys, gastrointestinal tract and even central and peripheral nervous system. In dsSSc there is typically a shorter time period between the onset of Raynaud’s phenomenon and skin symptoms. The overall 10-year survival rate in dsSSc ranges from 65 to 82%, which is a result of the wide range of systemic complications. The most life-threatening of them affect the heart, lungs and kidneys.

[0052] Gastrointestinal tract (GIT) involvement is common (90%) in patients with SSc, affecting all parts of the GIT. Within the oral cavity the most frequent complications of SSc are microstomia and xerostomia. The latter can be an effect of a concomitant Sjogren’s syndrome. The esophagus is the most frequently involved organ of GIT in SSc - almost 67% of patients complaint of one or more symptoms: dysphagia, odynophagia, regurgitation, pyrosis, chronic cough or hoarseness. They are a result of structural and functional alterations of the esophagus, such as amyotonia contributing to dilation of the lumen, dysfunction of the lower esophageal sphincter (LES) and hiatal hernia - which lead to the increased incidence of gastroesophageal reflux disease (GERD) in SSc. Additionally, reduced LES pressure may lead to chronic reflux changes such as strictures and Barrett’s esophagus. The predominant alteration of the stomach in SSc is gastric antral vascular ectasia (GAVE).

[0053] In some embodiments, one or more tests are conducted prior to, during, or after treatment to assess the status and / or progression of disease or related signs, symptoms, and / or complications. In some embodiments, the test involves detection of one or more disease biomarkers. Biomarkers include, but are not limited to, cells (e.g., myofibroblasts and EndoMTs and their fibrotic status), proteins (e.g., autoantibodies (e.g., anti-topoisomerase I, anti-RNA polymerase III, anti-U3RNP, anti-Th / To, anti-Ul-RNP, anti-centromere, antiOhUBF)), peptides, and nucleic acid molecules (e.g., expressed RNA molecules). Testing finds use for research (drug screening), identifying therapeutic agents, selecting therapeutic agents, monitoring efficacy of therapeutic approaches, and modifying therapeutic approaches (e.g., changing drugs, changing doses, stopping therapy, adding additional drugs or other interventions, etc.). In some embodiments, a patient is tested, treated, and then tested again to monitor the response to therapy. In some embodiments, cycles of testing and treatment may occur without limitation to the pattern of testing and treating (e.g., test / treat, test / treat / test, test / treat / test / treat, test / treat / test / treat / test, test / treat / treat / test / treat / treat, etc.), the periodicity, or the duration of the interval between each testing and treatment phase.

[0054] In some embodiments, provided herein pharmaceutical compositions including a Hippo pathway effector (e.g., TEAD inhibitor) alone or in combination with one or more additional therapeutic agents in admixture with a pharmaceutically acceptable excipient. One of skill in the art will recognize that the pharmaceutical compositions may include a pharmaceutically acceptable salts of the compounds described herein.

[0055] In some embodiments, the Hippo pathway effector is a nucleic acid molecule that reduces or prevents the expression of a Hippo pathway protein or a Hippo pathway protein effector. In some embodiments, nucleic acids are RNAi nucleic acids. “RNA interference (RNAi)” is the process of sequence-specific, post-transcriptional gene silencing initiated by a small interfering RNA (siRNA), shRNA, or microRNA (miRNA). During RNAi, the RNA induces degradation of target mRNA with consequent sequence-specific inhibition of gene expression. In “RNA interference,” or “RNAi,” a “small interfering RNA” or “short interfering RNA” or “siRNA” or “short hairpin RNA” or “shRNA” molecule, or “miRNA” an RNAi (e.g., single strand, duplex, or hairpin) of nucleotides is targeted to a nucleic acid sequence of interest, for example, TEAD (e.g., TEAD1 or TEAD3) and / or VGLL3. An “RNA duplex” refers to the structure formed by the complementary pairing between two regions of a RNA molecule. The RNA using in RNAi is “targeted” to a gene in that the nucleotide sequence of the duplex portion of the RNAi is complementary to a nucleotide sequence of the targeted gene. In certain embodiments, the RNAi is are targeted to the sequence encoding TEAD and / or VGLL3. In some embodiments, the length of the RNAi is less than 30 base pairs. In some embodiments, the RNA can be 32, 31, 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11 or 10 base pairs in length. In some embodiments, the length of the RNAi is 19 to 32 base pairs in length. In certain embodiment, the length of the RNAi is 19 or 21 base pairs in length. In some embodiments, RNAi comprises a hairpin structure (e.g., shRNA). In addition to the duplex portion, the hairpin structure may contain a loop portion positioned between the two sequences that form the duplex. The loop can vary in length. In some embodiments the loop is 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26 or 27 nucleotides in length. In certain embodiments, the loop is 18 nucleotides in length. The hairpin structure can also contain 3' and / or 5' overhang portions. In some embodiments, the overhang is a 3' and / or a 5' overhang 0, 1, 2, 3, 4 or 5 nucleotides in length. "miRNA" or "miR" means a non-coding RNA between 18 and 25 nucleobases in length which hybridizes to and regulates the expression of a coding RNA. In certain embodiments, a miRNA is the product of cleavage of a pre-miRNA by the enzyme Dicer. Examples of miRNAs are found in the miRNA database known as miRBase. As used herein, Dicer- substrate RNAs (DsiRNAs) are chemically synthesized asymmetric 25-mer / 27-mer duplex RNAs that have increased potency in RNA interference compared to traditional RNAi. Traditional 21-mer RNAi molecules are designed to mimic Dicer products and therefore bypass interaction with the enzyme Dicer. Dicer has been recently shown to be a component of RISC and involved with entry of the RNAi into RISC. Dicer-substrate RNAi molecules are designed to be optimally processed by Dicer and show increased potency by engaging this natural processing pathway. Using this approach, sustained knockdown has been regularly achieved using sub-nanomolar concentrations. (U.S. Pat. No. 8,084,599; Kim et al., Nature Biotechnology 23:222 2005; Rose et al., Nucleic Acids Res., 33:4140 2005). The transcriptional unit of a “shRNA” is comprised of sense and antisense sequences connected by a loop of unpaired nucleotides. shRNAs are exported from the nucleus by Exportin-5, and once in the cytoplasm, are processed by Dicer to generate functional RNAi molecules. “miRNAs” stem-loops are comprised of sense and antisense sequences connected by a loop of unpaired nucleotides typically expressed as part of larger primary transcripts (pri-miRNAs), which are excised by the Drosha-DGCR8 complex generating intermediates known as pre-miRNAs, which are subsequently exported from the nucleus by Exportin-5, and once in the cytoplasm, are processed by Dicer to generate functional miRNAs or siRNAs. “Artificial miRNA” or an “artificial miRNA shuttle vector”, as used herein interchangeably, refers to a primary miRNA transcript that has had a region of the duplex stem loop (at least about 9-20 nucleotides) which is excised via Drosha and Dicer processing replaced with the siRNA sequences for the target gene while retaining the structural elements within the stem loop necessary for effective Drosha processing. The term “artificial” arises from the fact the flanking sequences (e.g., about 35 nucleotides upstream and about 40 nucleotides downstream) arise from restriction enzyme sites within the multiple cloning site of the RNAi. As used herein the term “miRNA” encompasses both the naturally occurring miRNA sequences as well as artificially generated miRNA shuttle vectors. The RNAi can be encoded by a nucleic acid sequence, and the nucleic acid sequence can also include a promoter. The nucleic acid sequence can also include a polyadenylation signal. In some embodiments, the polyadenylation signal is a synthetic minimal polyadenylation signal or a sequence of six Ts.

[0056] Exemplary siRNA molecule are provided in Table 1 (VGLL3), Table 2 (TEAD1), and Table 3 (TEAD3), below.

[0057] Table 1 (VGLL3 siRNA sequences) Table 2 (TEAD1 siRNA sequences)

[0058] Table 3 (TEAD3 siRNA sequences) Nucleic acid molecules may be modified to provide enhanced in vivo stability. Such modifications include any chemical modifications to the nucleotides that provide stability without significantly interfering with the targeting effector abilities of the nucleic acid molecule. Such modifications include but are not limited to, phosphorothioate, O-methyl, and 2-fluoro modifications. The present disclosure contemplates the use of any genetic manipulation for use in modulating the expression of TEAD and / or VGLL3. Examples of genetic manipulation include, but are not limited to, gene knockout (e.g., removing the TEAD, VGLL3, or another Hippo pathway gene from the chromosome using, for example, recombination), expression of antisense constructs with or without inducible promoters, and the like. Delivery of nucleic acid construct to cells in vitro or in vivo may be conducted using any suitable method. A suitable method is one that introduces the nucleic acid construct into the cell such that the desired event occurs (e.g., expression of an antisense construct).

[0059] Depending on the specific conditions being treated, such agents may be formulated into liquid or solid dosage forms and administered systemically or locally. The agents may be delivered, for example, in a timed- or sustained-slow release form as is known to those skilled in the art. Techniques for formulation and administration may be found in Remington: The Science and Practice of Pharmacy (20th ed.) Lippincott, Williams & Wilkins (2000). Suitable routes may include oral, buccal, by inhalation spray, sublingual, rectal, transdermal, vaginal, transmucosal, nasal or intestinal administration; parenteral delivery, including intramuscular, subcutaneous, intramedullary injections, as well as intrathecal, direct intraventricular, intravenous, intra-articullar, intra-sternal, intra-synovial, intra-hepatic, intralesional, intracranial, intraperitoneal, intranasal, or intraocular injections or other modes of delivery.

[0060] Pharmaceutical compositions suitable for use in the present disclosure include compositions wherein the active ingredients are contained in an effective amount to achieve their intended purpose. Determination of the effective amounts is well within the capability of those skilled in the art, especially in light of the detailed disclosure provided herein. Generally, the compounds according to the disclosure are effective over a wide dosage range. For example, in the treatment of adult humans, dosages from 0.01 to 1000 mg, from 0.5 to 100 mg, from 1 to 50 mg per day, and from 5 to 40 mg per day are examples of dosages that may be used. A non-limiting dosage is 10 to 30 mg per day. The exact dosage will depend upon the route of administration, the form in which the compound is administered, the subject to be treated, the body weight of the subject to be treated, the bioavailability of the compound(s), the adsorption, distribution, metabolism, and excretion (ADME) toxicity of the compound(s), and the preference and experience of the attending physician.

[0061] In addition to the active ingredients, these pharmaceutical compositions may contain suitable pharmaceutically acceptable carriers comprising excipients and auxiliaries which facilitate processing of the active compounds into preparations which can be used pharmaceutically.

[0062] EXAMPLES

[0063] Methods

[0064] Human sample acquisition

[0065] 22 systemic sclerosis patients and 18 healthy donors were recruited for single cell RNA sequencing, and additional 4 systemic sclerosis patients were recruited for spatial sequencing. Skin biopsies were taken from the affected forearm of patients. The study was approved by the University of Michigan Institutional Review Board (IRB), and all patients gave written consent. The study was conducted according to the Declaration of Helsinki Principles.

[0066] Single-cell RNA-seq library preparation, sequencing, and alignment

[0067] Generation of single-cell suspensions for scRNA-seq was performed as follows: Skin biopsies were incubated overnight in 0.4% dispase (Life Technologies) in Hank’s Balanced Saline Solution (Gibco) at 4°C. Epidermis and dermis were separated. Epidermis was digested in 0.25% Trypsin-EDTA (Gibco) with lOU / mL DNase I (Thermo Scientific) for 1 hour at 37°C, quenched with FBS (Atlanta Biologicals), and strained through a 70pM mesh. Dermis was minced, digested in 0.2% Collagenase II (Life Technologies) and 0.2% Collagenase V (Sigma) in plain medium for 1.5 hours at 37°C and strained through a 70pM mesh. For the samples collected from the University of Pittsburgh, epidermal and dermal cells were combined in 1 : 1 ratio. For three of the samples collected from the University of Michigan, the epidermal and dermal cells were prepared in different libraries that were constructed by the University of Michigan Advanced Genomics Core on the 10X Chromium system with chemistry v3. For the remaining samples the epidermis and dermis were combined in 1 : 1 ratio. Libraries were then sequenced on the Illumina NovaSeq 6000 sequencer to generate 150 bp paired-end reads. Data processing including quality control, read alignment (hg38), and gene quantification was conducted using the 10X Cell Ranger software. The samples were then merged into a single expression matrix using the cellranger aggr pipeline. Cell clustering and cell type annotation

[0068] The R package Seurat (v3.1.2) was used to cluster the cells in the merged matrix. Cells with less than 500 transcripts or 100 genes or more than le5 transcripts or 15% of mitochondrial expression were first filtered out as low-quality cells. The NormalizeData function was used to normalize the expression level for each cell with default parameters. The FindVariableFeatures function was used to select variable genes with default parameters. The ScaleData function was used to scale and center the counts in the dataset. Principal component analysis (PCA) was performed on the variable genes. The RunHarmony function from the Harmony package was applied to remove potential batch effect among samples processed in different batches. Uniform Manifold Approximation and Projection (UMAP) dimensional reduction was performed using the RunUMAP function. The clusters were obtained using the FindNeighbors and FindClusters functions with the resolution set to 0.6. The cluster marker genes were found using the Find AllMarkers function. The cell types were annotated by overlapping the cluster markers with the canonical cell type signature genes. To calculate the disease composition based on cell type, the number of cells for each cell type from each disease condition were counted. The counts were then divided by the total number of cells for each disease condition and scaled to 100 percent for each cell type. Differential expression analysis between any two groups of cells were carried out using the FindMarkers function.

[0069] Cell type sub-clustering

[0070] Sub-clustering was performed on the abundant cell types. The same functions described above were used to obtain the sub-clusters. Sub-clusters that were defined exclusively by mitochondrial gene expression, indicating low quality, were removed from further analysis. The subtypes were annotated by overlapping the marker genes for the subclusters with the canonical subtype signature genes. The module scores were calculated using the AddModule Score function on the intended gene lists. The ECM score was calculated on the genes from the extracellular matrix pathway from the Gene Ontology database. The TGF- P and IL-4 score for fibroblast subtypes were calculated on induced genes in fibroblasts after stimulation with TGF-P or IL-4 (89). The module scores for the upstream regulators were calculated on the target gene lists from the Ingenuity Pathway Analysis software.

[0071] Ligand receptor interaction analysis CellphoneDB (v2.0.0) was applied for ligand-receptor analysis. Each subtype was separated by their disease classifications (SSc or NS), and a separate run was performed for each disease classification. If a subtype contains fewer than 10 cells for a disease classification, it was not considered in the ligand-receptor analysis for this disease classification. Pairs with p value > 0.05 were filtered out from further analysis. To compare between the two disease conditions, each pair was assigned to the condition in which it showed the higher interaction score. The number of interactions between each subtype pair was then calculated. The connectome web was plotted using the R package igraph.

[0072] Pseudotime trajectory construction

[0073] Pseudotime trajectories for the fibroblast and endothelial transitions were constructed using the R package Monocle (v2.22.0). The raw counts for cells were extracted from the Seurat analysis and normalized by the estimateSizeFactors and estimateDispersions functions with the default parameters. Genes detected in >10 cells were retained for further analysis. Variable genes were determined by the differentialGeneTest function with a model against the group identities for the fibroblast transition and the Seurat sub-cluster identities for the endothelial transition. The orders of the cells were determined by the orderCells function, and the trajectory was constructed by the reduceDimension function with default parameters. Differential expression analysis was carried out using the differentialGeneTest function with a model against the pseudotime, and genes with an adjusted p value smaller than 0.05 were clustered into five patterns and plotted in the heatmap. Ingenuity Pathway Analysis was used to determine the upstream regulators for the genes in each expression pattern. A module score was calculated for each upstream regulator on the target genes from all five patterns. The module scores were calculated using the Seurat function AddModule Score with default parameters. Pearson correlation was then performed between the upstream regulator module scores and the pseudotime.

[0074] Spatial sequencing library preparation

[0075] Skin samples were frozen in OCT medium and stored at -80°C until sectioning. Optimization of tissue permeabilization was performed on 20 pm sections using Visium Spatial Tissue Optimization Reagents Kit (10X Genomics, Pleasanton, CA, USA), which established an optimal permeabilization time to be 9 minutes. Samples were mounted onto a Gene Expression slide (10X Genomics), fixed in ice-cold methanol, stained with hematoxylin and eosin, and scanned under a microscope (Keyence, Itasca, IL, USA). Tissue permeabilization was performed to release the poly-A mRNA for capture by the poly(dT) primers that are precoated on the slide and include an Illumina TruSeq Read, spatial barcode, and unique molecular identifier (UMI). Visium Spatial Gene Expression Reagent Kit (10X Genomics) was used for reverse transcription to produce spatially barcoded full-length cDNA and for second strand synthesis followed by denaturation to allow a transfer of the cDNA from the slide into a tube for amplification and library construction. Visium Spatial Single Cell 3' Gene Expression libraries consisting of Illumina paired-end sequences flanked with P5 / P7 were constructed after enzymatic fragmentation, size selection, end repair, A-tailing, adaptor ligation, and PCR. Dual Index Kit TT Set A (10X Genomics) was used to add unique i7 and i5 sample indexes and generate TruSeq Read 1 for sequencing the spatial barcode and UMI and TruSeq Read 2 for sequencing the cDNA insert, respectively. Libraries were then sequenced on the Illumina NovaSeq 6000 sequencer to generate 150 bp paired end reads.

[0076] Spatial sequencing data analysis

[0077] After sequencing, the reads were aligned to the human genome (hg38), and the expression matrix was extracted using the spaceranger pipeline. Seurat was then used to analyze the expression matrix. Specifically, the SCTransform function was used to scale the data and find variable genes with default parameters. PCA and UMAP were applied for dimensional reduction. The FindTransferAnchors function was used to find a set of anchors between the spatial-seq data and scRNA-seq data, which were then transferred from the scRNA-seq to the spatial-seq data using the TransferData function. These two functions construct a weight matrix that defines the association between each query cell and each anchor. These weights sum to 1 for each spot and were used as the percentage of the cell type in the spot.

[0078] Immunofluorescence and Immunohistochemistry staining

[0079] Formalin-fixed embedded human tissues were sectioned and heated at 65 °C for 30 minutes, deparaffinized, and rehydrated. Slides were placed in pH 6 or pH 9 antigen retrieval buffer according to manufacture structure and heated at 125 °C for 30 seconds in a pressure cooker water bath. After cooling, slides were blocked and incubated with primary rabbit and mouse anti-human antibodies. Primary rabbit antibodies were used: anti-alpha smooth muscle actin (aSMA), anti-CollAl, anti-Vgll3, anti- Vimentin, anti-YAP anti-TEADl, anti-CD31 antibodies from (Abeam, cat # ab5694, LSB, cat # LS-C343921, Abeam, cat # ab254938, Abeam, cat # ab 92542, Cell Signaling, cat # 12292 and Abeam, cat # ab 32457, respectively). Along with rabbit primary antibodies, appropriate mouse-antihuman antibodies were also used: anti-aSMA (cat # ab 254938), anti- Vimentin (cat # ab 8978), anti-CD31(cat # ab 9498), all from Abeam and TEAD3 antibody from (Abnova, cat # H00007005). All primary rabbit antibodies mentioned above were diluted 1 : 100, except CD31 1 :250 dilution in blocking solution and coincubated with appropriate primary mouse antibodies (a-SMA, Vimentin and TEAD3 1 :50 dilutions and CD31 1 :100 overnight at 4°C. Appropriate negative (no primary or secondary antibodies or isotype control antibodies: rabbit IgG (abl72730), mouse IgGl (ab 280974) both from Abeam, IgG2ak (14-4724-82) from Invitrogen, antibodies were stained in parallel with each set of the slides mentioned above. Slides were then washed three times for 5 min each with phosphate-buffered saline / Tween 20 (PBST). All slides were then incubated with secondary antibodies fluorochrome-conjugated Alexa Fluor 594 conjugated anti-rabbit IgG (711-585-152) and Alexa Fluor 488 conjugated antimouse IgG (715-545-151) from Jackson Immuno Research. After 30 minutes coincubation, slides were washed three times for 5 min each with PBST. Mounted in an Prolong Dimond antifade with DAPI (Invitrogen). Photomicrographs were taken on Zeiss fluorescence microscope. All IMF exposures were compared against isotype control. The selected frames used in the figures were representative of the whole biopsy.

[0080] Paraffin embedded tissue sections (SSc and control skin) were heated at 60°C for 30 minutes, de-paraffinized, and rehydrated. Slides were placed in PH9 antigen retrieval buffer and heated at 125°C for 30 seconds in a pressure cooker water bath. After cooling, slides were treated with 3% H2O2 (5 minutes) and blocked using 10% goat serum (30 minutes). Overnight incubation (4°C) was then performed using anti-human primary antibody. Antibodies used were YAP1 (LifeSpan Biosciences Inc, LS-C331201, pH9, 2ug / ml), WWTR1 (LifeSpan Biosciences Inc, LS-C173295-100, pH9, 1 : 150), TEAD1, (LifeSpan Biosciences Inc, LS-B3534-100, pH9, 1 : 100), TEAD3 (LifeSpan Biosciences Inc, LS- C668058, pH9, 1 :300), VGLL3 (St. Johns Laboratories, STJ115228-100, pH9, 1 : 100). Slides were then washed, treated with secondary antibody, peroxidase (30 minutes) and diaminobenzidine substrate. Counterstain with Hematoxylin and dehydration was done and slides were mounted and viewed under the microscope.

[0081] Isolation and culture of fibroblasts and endothelial cells from SSc skin

[0082] Study participants were recruited from the University of Michigan Scleroderma Program. Dermal fibroblasts were isolated from punch biopsies from the distal forearm of healthy volunteers and diffuse cutaneous (dc)SSc patients. All patients met the ACR / EULAR criteria for the classification of SSc (90). All patients are diagnosed with dcSSc (2 males and 8 females; age 57.5 ± 13.0 years, mean ± SD), and the disease duration was 1.9 ± 0.9 years (mean ± SD). Their skin scores ranged from 0 to 40 with a mean of 19.1 ± 14.2 (mean ± SD). Negatively selected fibroblasts were cultured in RPMI 1640 with 10% FBS and antibiotics. This study was approved by the institutional review board and all participants signed an informed consent prior to enrollment. For endothelial cells, punch biopsies obtained from SSc patients were digested as previously described (91). After digestion, endothelial cells were magnetically labeled with anti-CD31 antibodies (CD31 MicroBead Kit 130-091-935, Miltenyi Biotech) and purified. These CD31+ endothelial cells were maintained in EBM-2 media with growth factors (Lonza CC-3202). Cells between passage 3 and 6 were used in all experiments.

[0083] Cell treatment and transfection

[0084] Dermal fibroblasts or endothelial cells from dcSSc patients were treated with 10 pM of LATS kinase inhibitor TRULI / Lats-IN-1 (MedChenExpress HY-138489) or YAP / TEAD inhibitor verteporfin (Cayman Chemical 17334) 0.1- 10 pM for 48 to 72 hours. Gene knockdown was done using Accell siRNAs (Dharmacon) in dermal fibroblasts and OnTarget siRNAs (Dharmacon) in dermal ECs, following protocols recommended by the manufacturer.

[0085] Functional endpoint experiments

[0086] Gene expression changes in cells were performed by qPCR after total RNA was extracted using Direct-zol™ RNA MiniPrep Kit (Zymo Research R2052). Quantitative PCR was performed in a ViiA™ 7 Real-Time PCR System. Protein expression changes were monitored using Western blotting. After blocking, the blots were probed with antibodies against collagen I (COL1, Abeam ab6308), VWF (Novus NBP2-33003) or aSMA (Abeam ab5694). For loading control, the blots were immunoblotted with antibodies against GAPDH (Cell Signaling #2118). Band quantification was performed using ImageJ. The IncuCyte® Live-Cell Imaging System was used to monitor cell proliferation or migration. After adding different treatments cells were monitored by IncuCyte®. Cell counts were analyzed by the IncuCyte® S3 Analysis software. Gel contraction assays were performed using the cell contraction kit from Cell Biolabs (CBA-201). Immunofluorescence on cells was performed using anti-SMA antibodies (Abeam ab5694) or anti-VWF antibodies (Novus NBP2-33003) followed by Alexa Fluor secondary antibodies (Thermo Fisher). Statistical analysis for in vitro experiments

[0087] For the in vitro experiments, normality test was first conducted to determine whether the data is normally distributed or skewed. To determine the differences between groups, unpaired t test, Mann-Whitney U test, one-way ANOVA with Sidak test, Kruskal-Wallis test with Dunn’s test, or two-way ANOVA with Dunnett’s test were performed using GraphPad Prism version 8 (GraphPad Software, Inc). P values of less than 0.05 were considered statistically significant. Results were expressed as mean ± SD unless specified.

[0088] Results scRNA-seq and spatial-seq reveal diverse cell types and their spatial locations in SSc skin

[0089] To understand the unbiased cellular composition and cell states of healthy normal skin (NS) and systemic sclerosis (SSc) skin, we generated single cell suspensions of skin biopsies from 18 NS donors and 22 SSc patients and performed scRNA-seq. The resulting quality- controlled SSc plus NS single cell atlas contained a total of 96,174 cells, with an average of 2,258 genes and 9,263 transcripts detected per cell. The cells were clustered based on differential expression of marker genes and visualized on a uniform manifold approximation and projection (UMAP) plot. Cluster annotation was corroborated by overlapping the cluster markers with the canonical lineage-specific genes reported in previous skin disease scRNA- seq studies (10,30,43-45). We recovered 12 major cell types across all the samples (FIG. la- d), including keratinocytes, melanocytes, eccrine gland cells, endothelial cells, fibroblasts, pericytes, smooth muscle cells, nerve cells, T cells, myeloid cells, mast cells, and B cells. Most of these cell types contained cells from both NS and SSc samples (FIG. lb, c). Notably, two small populations, smooth muscle cells, and B cells, were primarily derived from the SSc samples (FIG. 1c). Interestingly, clear separations were observed in keratinocytes, fibroblasts, pericytes, and endothelial cells between the NS and SSc cells, suggesting fundamental transcriptional differences between them (FIG. lb). By contrast, the other cell types displayed overlapping patterns for the NS and SSc cells.

[0090] To localize the major cell types detected by scRNA-seq in SSc skin, we performed spatial sequencing (spatial-seq) on four independent SSc skin samples using the 10X Visium platform. After the quality control steps, we detected 951 spatially defined spots with an 1 average of 805 genes and 1,647 transcripts per spot (FIG. 7a). We deconvoluted the spatial spots by the major cell types detected in scRNA-seq using the Seurat anchor-based label transfer method (Methods). The deconvolution scores for each cell type were displayed on the tissue (FIG. le) and combined into a scatter-pie plot representing the relative cell type composition for each spot (FIG. 7a). As expected, keratinocytes localized to the epidermis and the hair follicle. Melanocytes were enriched along the basal epidermis. Myeloid cells and T cells were primarily located in the superficial dermis in proximity to the epidermis and the hair follicle. B cells were aggregated adjacent to the hair follicle. Strikingly, fibroblasts, pericytes, and endothelial cells were distributed throughout a large proportion of the spots in the dermis, covering the regions of fibrosis. The other cell types represent small populations and were lowly detected in the spatial-seq sample. Spatial-seq of three additional SSc skin biopsy specimens analyzed in parallel revealed similar results (FIG. 7b-d).

[0091] Hippo pathway effectors promote and maintain myofibroblast differentiation in SSc skin

[0092] Due to their capacity to produce large amounts of pro-fibrotic extracellular matrix (ECM) components, myofibroblasts have long been regarded as central to the fibrotic response in SSc. A recent scRNA-seq study proposed SFRP2hi fibroblasts as the potential progenitors of myofibroblasts in SSc skin (10). To understand the heterogeneity of the fibroblasts and the myofibroblast differentiation process in SSc skin, we selected all the fibroblasts from our scRNA-seq dataset and performed sub-clustering (FIG. 8a). Based on previously published marker genes (10,47-49), we annotated the fibroblast sub-clusters into seven subtypes including SFRP2+ fibroblasts (FB), COL8A1+ FB, CCL19+ FB, FM01+ FB, FM02+ FB, TNN+ FB, and CLDN1+ FB (FIG. 2a, e). The COL8A1+ FB expressed high levels of ACTA2, SFRP4, POSTN, and PRSS23, representing myofibroblasts in our dataset (10). Strikingly, the COL8A1+ FBs, which were derived exclusively from the SSc samples, were contiguous with the SFRP2+ FB on the UMAP (FIG. 2b, c). Notably, the NS and SSc SFRP2+ FB were largely distinct on the UMAP, suggesting fundamental transcriptional differences between these two cell populations. Furthermore, only the SSc SFRP2+ FB, not the NS ones, connected to the COL8A1+ FB (FIG. 2a, b), suggesting that only in SSc did SFRP2+ FB have the potential of directly differentiate into myofibroblasts. To illustrate the capacity for ECM production by the different fibroblast subtypes, we calculated an ECM module score using the gene list from the extracellular matrix pathway from Gene Ontology (FIG. 2d) and plotted all the collagen genes across the subtypes (FIG. 8b). The COL8A1+ FB had the highest ECM score and highest expression pattern of the collagen genes, including C0L1A1, C0L1A2, C0L3A1, C0L5A1, COL5A2, COL6A3, C0L8A1, COL8A2, COL10A1, and COL12A1. The SFRP2+ FB ranked the second highest for the ECM score and collagen gene expression. To corroborate the spatial locations of the fibroblasts, we next plotted the expression of COL1 Al and the ECM score across the four spatial-seq samples and found them highly correlated with the fibroblast deconvolution scores (FIG. le, 2f, 7a-d). We then deconvoluted the fibroblast-rich spots (with fibroblast deconvolution score > 0.25) using the fibroblast subtypes (FIG. 2f, 8c). The SFRP2+ FB were primarily located in the superficial dermis, while the COL8A1+ FB were localized to the deeper dermis. We did not detect COL8A1+ FB in the third and fourth spatial-seq samples, likely due to sample heterogeneity and that we did not cut deep enough in these two tissue sections.

[0093] Immunohistochemistry and immunofluorescence of SMA (encoded by ACTA2) validated the location of myofibroblasts in the deeper dermis of SSc skin (FIG. 2g, h), overlapping with areas of intense fibrosis. Interestingly, SMA from the upper dermis of the SSc skin tissue was observed mainly in and around the blood vessels (FIG. 2g, h), suggesting endothelial to mesenchymal transition (EndoMT) in SSc skin.

[0094] To better characterize the differentiation process from SFRP2+ FB to COL8A1+ FB, we focused on these two subtypes and split them into three groups based on the fibroblast sub-clusters (FIG. 3a, 8a). Group 1 and 2 were mainly composed of NS SFRP2+ FB and SSc SFRP2+ FB, respectively, and group 3 was composed of COL8A1+ FB (FIG. 3b). The expression of myofibroblast marker genes ACTA2, TAGLN, and COL8A1 and the ECM score increased from group 1 to 2 to 3 (FIG. 3c, e). We calculated module scores using genes induced in cultured fibroblasts stimulated by two pro-fibrotic cytokines, TGF-P or IL-4, and found that these two module scores escalated from group 1 to 2 to 3 (FIG. 3e, Methods). Interestingly, the expression of two Hippo pathway target genes, CTGF and CYR61, displayed increasing trends from group 1 to 2 to 3 (FIG. 3f), suggesting involvement of the Hippo pathway in myofibroblast differentiation in SSc skin. Furthermore, CytoTRACE analysis (50) suggested that group 1 represented less differentiated cells and group 3 represented the most differentiated cells (FIG. 3d). Based on these observations, we performed pseudotime analysis on the three groups using Monocle and arranged the cells into a linear trajectory from group 1 to 2 to 3 (FIG. 3g, h). To identify the potential cytokines and transcription factors that drive the myofibroblast differentiation, we split the variable genes along the pseudotime into five expression patterns (FIG. 9a). We then inferred the upstream regulators for genes in each pattern using Ingenuity Pathway Analysis. For each upstream regulator, we calculated a module score using all target genes gathered from the five expression patterns (Methods). Consistent with the cytokine stimulation experiment, both TGF-pi and IL-4 target scores were highly correlated with the pseudotime (FIG. 3i). Previously reported transcription factors, STAT1, IRF7, RUNX1 and SMAD3, that promote the differentiation from SFRP2hi fibroblast to myofibroblasts (10), displayed a module score positively correlated with the pseudotime (FIG. 3i). The module scores for WWTR1 (TAZ) and TEAD1 were also highly correlated with the pseudotime, suggesting a contribution of the Hippo pathway in the differentiation from the SFRP2+ FB to the COL8A1+ FB. Indeed, multiple key molecules involved in Hippo pathway, including WWTR1, CTGF, CYR61, TEAD1, TEAD2, TEAD3, TEAD4, and VGLL3, were highly expressed in group 3 compared to groups 1 and 2 (FIG. 9b).

[0095] To determine the functional relevance of the Hippo pathway in SSc fibroblasts, we used primary dermal fibroblasts isolated from patients with early diffuse cutaneous (dc)SSc. Two inhibitors relevant to the Hippo pathway were used; TRULI, a LATS1 / 2 (large tumor suppressor kinase 1 and 2) inhibitor that decreases phosphorylation of YAP to promote its entry into the nucleus (51), and verteporfin, an inhibitor of YAP-TEAD interaction (52). In all assays, the two inhibitors showed opposite effects. TRULI treatment led to a significant increase in pro-fibrotic markers in dcSSc fibroblasts including ACTA2 and COL1A1 (FIG. 3j), and we validated this for SMA with western blotting, but the increase in COL1 Al did not reach significance (FIG. 3k). Further, these findings were validated by immunofluorescent staining with increased expression of SMA but only slight to moderate increase in COL1 Al expression (FIG. 31). Specifically for verteporfin, we found that its treatment in dcSSc fibroblasts downregulated both SMA and COL1 to levels comparable to what was observed in healthy fibroblasts at baseline (FIG. 9c, d). Since myofibroblasts exhibit higher contractility, increased proliferation, and migration capacities, we also measured these as functional endpoints. We found that TRULI enhanced gel contraction, proliferation, and migration in dcSSc fibroblasts (FIG. 3m-o), suggesting that TRULI promotes a pro-fibrotic phenotype in these cells. In contrast, verteporfin downregulated SMA and COL1 in dcSSc fibroblasts at both mRNA levels and protein levels (FIG. 3j -1). Verteporfin also inhibited gel contraction, proliferation, and migration in a dose-dependent manner (FIG. 3m-o). We also determined the impact of these inhibitors in healthy dermal fibroblasts. Verteporfin did not appear to have any effect on fibrotic gene expressions, proliferation, and migration in healthy fibroblasts, while TRULI upregulated SMA, though to a lesser extent compared to dcSSc fibroblasts, it did not affect proliferation or migration in healthy fibroblasts (FIG. 9e, f). To further delineate the roles of key mediators in the Hippo pathway in SSc fibroblasts, we knocked down YAP1, TEAD1, TEAD3, VGLL3, or TEAD1 / TEAD3 simultaneously in these cells (FIG. 3p) and measured ACTA2 and COL1 Al levels. Similar to what was observed with verteporfm treatment, knockdown of these key mediators resulted in downregulation of ACTA2 and COL1 Al (FIG. 3q). Altogether, these results point to a role for Hippo pathway effectors in promoting and maintaining the pro-fibrotic signal in dcSSc fibroblasts.

[0096] Hippo pathway effectors promote and maintain endothelial to mesenchymal transition in SSc skin

[0097] To characterize the heterogeneity of endothelial cells, we sub-clustered all the endothelial cells from the scRNA-seq dataset and obtained seven sub-clusters (FIG. 4a-c). Sub-cluster 6 represented the lymphatic endothelial cells with high expression of LYVE1 and MMRN1 (FIG. 4c). Sub-clusters 3, 4, and 5 represented the activated endothelial cells with high expression of SELP and SELE (FIG. 10a). Interestingly, sub-clusters 0, 1, and 2, expressed GJA4, a marker of arteriolar endothelial cells 53, and were aligned contiguously on the UMAP, suggesting a potential transition among these sub-clusters. Close examination of lineage marker genes in the three sub-clusters reinforced this transition hypothesis: expression of endothelial cell markers PECAM1 and CDH5, as well as Notch signaling genes NOTCH1, JAG2, and DLL4, decreased, while mesenchymal cell markers COL1A1, ACTA2, and TAGLN increased from sub-cluster 0 to 1 to 2 (FIG. 4d). Immunofluorescence confirmed co-expression of SMA and CD31 (encoded by PECAM1) in SSc but not NS skin (FIG. 4g). Sub-cluster 2 also had the highest ECM score (FIG. 4e) and expressed the highest level of collagen genes among all the endothelial sub-clusters (FIG. 10b). The disease composition revealed increasing proportions of SSc endothelial cells from sub-cluster 0 to 1 to 2 (FIG. 10c). Furthermore, the CytoTRACE score indicated that the cells in sub-cluster 2 were more differentiated compared to the cells in subcluster 0 and 1 (FIG. 4f). Taken together, the above evidence suggests EndoMT occurs during progression from sub-cluster 0 to 1 to 2.

[0098] To better characterize the EndoMT progression at the single cell level, we performed pseudotime analysis on these three sub-clusters using Monocle and aligned them into a linear trajectory (FIG. 4h). The pseudotime was assigned from early to late from sub-cluster 0 to 1 to 2. In parallel to the fibroblast trajectory analysis, we calculated the correlation coefficient between the target score for different upstream regulators and the pseudotime in the endothelial trajectory analysis (FIG. lOd). We focused on the key upstream regulators that promote the SFRP2+ FB to the C0L8A1+ FB transition and plotted the correlation coefficients in both fibroblast and endothelial trajectory analyses (FIG. 4i). TGF-P transcription factors displayed positive correlation in both the fibroblast and the endothelial transitions. Intriguingly, TEAD transcription factors were also highly correlated with both transitions, suggesting that Hippo pathway effectors promote both myofibroblast transition and EndoMT. Accordingly, key molecules involved in Hippo pathway, including YAP1, WWTR1, CTGF, CYR61, TEAD1, TEAD2, TEAD3, TEAD4, and VGLL3, were all expressed in higher percentage of cells in sub-cluster 2 compared to sub-clusters 0 and 1 (FIG. 4k). By contrast, the target scores of HIF1A, STAT1, IRF7, and RUNX1 were only positively correlated with the fibroblast pseudotime but not the endothelial pseudotime (FIG. 4i). We validated the expression of TEAD1 and TEAD3 by immunofluorescence and demonstrated their colocalization with CD31 in SSc but not NS samples (FIG. 4j). Given the similarity between fibroblast transition and endothelial transition, we sought to determine the common programs that were upregulated in both processes. To do so, we overlapped the up- regulated genes in group 3 compared to group 1 and 2 in the fibroblast transition and those in sub-cluster 2 compared to sub-cluster 0 and 1 in the endothelial transition. Enrichment analysis on the 240 common up-regulated genes implicated the extracellular matrix organization as the most prominent program commonly induced in both transitions (FIG. 41).

[0099] We next determined whether the Hippo pathway is functionally involved in EndoMT in endothelial cells isolated from dcSSc skin. TRULI increased ACTA2 and COL1 Al expression in dcSSc endothelial cells while verteporfm downregulated these genes (FIG. 5a). Interestingly, TRULI had inconsistent effects on endothelial markers PEC AMI and CDH5, while verteporfm blocked the expression of both at the mRNA levels. The effect of these inhibitors on dcSSc endothelial cells were further validated using Western blotting (FIG. 5b). The expression levels in SSc ECs treated with verteporfm appeared to be comparable to the expression levels in ECs isolated from healthy controls. Of note, we were unable to detect COL1 expression in healthy ECs. By immunofluorescent staining we showed that TRULI enhanced EndoMT as shown by cell morphology and loss of endothelial marker VWF. In contrast, verteporfm reversed EndoMT by downregulating SMA expression in dcSSc endothelial cells (FIG. 5c). We also determined the effects of these inhibitors on ECs isolated from healthy subjects. It appears that TRULI induced EndoMT by downregulating VWF, upregulating SMA, and also induced morphological changes, while verteporfin appeared to increase VWF (FIG. 5c). The discrepancy of the effect of the inhibitors on EC markers in FIG. 5a-c could be due to posttranscriptional or translational modifications, or differences in protein and RNA degradation rates. To further dissect the roles of YAP1, TEAD3, or VGLL3 in mediating EndoMT in dcSSc endothelial cells, we knocked these genes down individually (FIG. 5d) and measured EndoMT markers. Knockdown of YAP1, TEAD3, or VGLL3, resulted in lower ACTA2 and COL1 Al levels, similar to what was observed with verteporfin treatment (FIG. 5e). TEAD3 and VGLL3 knock-down appeared to promote endothelial markers PECAM1 and CDH5, while YAP1 knock-down had minimal effect.

[0100] Myofibroblasts and EndoMTs act as central hubs in cell-cell communications

[0101] To comprehensively study the cell type composition and cell-cell communications in SSc skin, we sub-clustered the other cell types in the scRNA-seq dataset. We identified four subtypes of keratinocytes: basal, spinous, supraspinous, and inflammatory keratinocyte (FIG. I la). The T cells were sub-clustered and annotated into five subtypes: CD4 T cell (CD4T), regulatory T cell (Treg), CD8 T cell (CD8T), nature killer cell (NK cell), and innate lymphoid cell (ILC) (FIG. 1 lb). For myeloid cells, we annotated six subtypes, including Langerhans cell (LC), conventional type 1 DC-like cell (cDCl), conventional type 2A DC- like cell (cDC2A), conventional type 2B DC-like cell (cDC2B), monocyte (Mono), and macrophage (Mac) (FIG. 11c). We sub-clustered the pericytes and smooth muscle cells together due to their transcriptional similarities. We obtained four pericyte sub-clusters and two smooth muscle cell sub-clusters (FIG. l id). For the other cell types, we obtained five eccrine gland cell sub-clusters, six melanocyte sub-clusters, four nerve cell sub-clusters, five mast cell sub-clusters, and three B cell sub-clusters (FIG. 12a-e).

[0102] We then performed separate ligand-receptor analyses on the SSc and NS cellular subtypes using CellPhoneDB (Methods). To assess the changes that occur in SSc, we analyzed ligand-receptor pairs from the subtypes that had higher interaction scores in SSc compared to NS. By aggregating the total number of interactions for each cell type, we observed the largest ligand-receptor pair number changes in endothelial cells and fibroblasts (FIG. 6a). Connectome web analysis revealed endothelial sub-cluster 2 (EC2, EndoMTs) and the C0L8A1+ FB (myofibroblasts) as the central communication hubs. Of note, EC2 and C0L8A1+ FBs had the greatest number of self-interactions (FIG. 13a), many of which overlapped between EC2 and C0L8A1+ FB cells as these two subtypes share fibrotic features. Thus, these overlapping self-interactions account for some of the interactions highlighted between the two groups. Taken together, these data suggest dynamic interaction between these two key subtypes and other skin cell subtypes during the EndoMT and fibroblast to myofibroblast transition (FIG. 6c). Of note, several other endothelial and fibroblast subtypes were also relatively more active, including ECO, ECI, EC3, EC4, SFRP2+ FB, FM01+ FB, and CCL19+ FB, which mainly interacted with the two hubs. By contrast, fewer ligand-receptor interactions were higher in NS compared to SSc, with the majority of these representing keratinocyte-keratinocyte crosstalk (FIG. 13b, c). To this end, we focused on the interactions within the SSc endothelial cells and fibroblasts. To emphasize the roles of the two hubs, we selected the pairs from which the ligands were subtype-specific marker genes for either EC2 or C0L8A1+ FB, which uncovered various validated and uncharacterized signaling pathways implicated in fibrosis (FIG. 6c). Fibroblast growth factors (FGF2, FGF7, and FGF18) (54), platelet-derived growth factor (PDGFA and PDGFC) (55,56), transforming growth factor beta (TGFB1 and TGFB3), and vascular endothelial growth factor (VEGFA and VEGFB) (57) were known to be involved in fibrosis. WNT2 and WNT4 were specifically expressed by the C0L8A1+ FB and have been reported to promote cardiac fibrosis by activating NF-KB signaling 58. IL6 and IL11 served as pro-fibrotic cytokines; both have been reported to be elevated in SSc and proposed as therapeutic targets for SSc (59,60). Notably, our analysis revealed several other pro-inflammatory mediators, including CCL2, CCL8, CCL11, TNFSF4, TNFSF9, and TNFSF12, that were highly expressed by EC2 or the COL8A1+ FB. Together, these data illustrate pro-fibrotic shifts within the interactome in SSc and reinforce the essential roles of EC2 and the COL8A1+ FB in SSc skin fibrosis.

[0103] Ex Vivo Testing

[0104] Ex vivo testing was conducted with results shown in FIG. 15. Distinct steps of the Hippo pathway were tested using Verteporfin that was applied to SSc skin biopsies ex vivo (n=3 patients per treatment group). TRULI and MGH-CP1 were also tested. Biopsies from the same patients were treated in parallel with DMSO to be used as a patient-specific vehicle control. Molecular changes in affected cell populations were assessed by extensive scRNA- Seq analyses.

[0105] It was found that Verteporfin selectively depleted myofibroblasts and endothelial- mesenchymal transition cells (EndoMTs) - the stromal cells pathologically activated in SSc. It also reduced expression of inflammatory, pro-fibrotic, and endothelial activation markers. Moreover, cell-cell interactions that sustain disease signaling were markedly hindered by Verteporfin. There was a striking overlap between the genes downregulated by Verteporfin and those upregulated in SSc versus healthy patients across cell populations. Thus, targeting Hippo pathway by Verteporfin effectively reversed molecular hallmarks of SSc. The data further demonstrate the utility of this approach for modeling drug targeting ex vivo.

[0106] FIG. 15A shows the processing steps. Cells were obtained from a scleroderma skin sample and placed in suspension ex vivo. Cells were treated with Verteporfin or a control (DMSO). Cells were captured and barcoded and a sequencing library was prepared and sequenced. FIG. 15B shows identified cell populations in both vehicle and treatment samples. FIG. 15C and D shows shifts in cell populations, including disappearance of myofibroblasts with verteporfin treatment (C and D). FIG. 15E shows collapse in pathogenic cell-cell interactions in scleroderma with verteporfin treatment. FIG. 15F shows that Verteporfin selectively targeted myofibroblast differentiation with no effect on cell death.

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Claims

CLAIMSWe claim:

1. A method comprising: treating a subject having systemic sclerosis (SSc) or a fibrotic disease or condition with a Hippo pathway effector under conditions that reduce or prevent fibrosis.

2. The method of claim 1, wherein the Hippo pathway effector is a TEAD inhibitor.

3. The method of claim 2, wherein the TEAD inhibitor is a protein-protein interaction disruptor of TEAD / YAP.

4. The method of claim 2, wherein the TEAD inhibitor prevents YAP translocation to the nucleus to activate TEAD.

5. The method of claim 2, wherein the TEAD inhibitor is Verteporfin.

6. The method of claim 1, wherein Hippo pathway effector regulates an association between VGLL3 and TEAD.

7. The method of claim 1, further comprising the step of assessing efficacy of the Hippo pathway effector in reducing or preventing fibrosis.

8. The method of claim 6, wherein said assessing comprises evaluating a sign or symptom of SSc.

9. The method of claim 6, wherein said assessing comprises evaluating a cellular or molecular biomarker.

10. The method of claim 9, wherein said biomarker comprises profibrotic phenotype or reversal of profibrotic phenotype of myofibroblasts.

11. The method of claim 9, wherein said biomarker comprises profibrotic phenotype or reversal of profibrotic phenotype of endothelial to mesenchymal transitioning cells (EndoMTs).

12. The method of claim 1, wherein said treating comprises systemic delivery of the Hippo pathway effector to the subject.

13. The method of claim 12, wherein said systemic delivery comprises injection, oral, or transdermal delivery.

14. The method of claim 13, wherein said injection comprises intravenous, subcutaneous, or intraperitoneal administration.

15. The method of claim 1, wherein said treating further comprises coadministering an agent or conducting a procedure that controls symptoms and / or prevents one or more complications of SSc.

16. The method of claim 15, wherein the symptoms comprise one or more Raynaud syndrome, polyarthralgia, dysphagia, heartbum, skin swelling, skin tightening, and contractures of fingers.

17. The method of claim 15, wherein said complications comprise one or more of interstitial lung disease, pulmonary arterial hypertension, and scleroderma renal crisis.

18. An ex vivo method of determining effect of a therapeutic agent, comprising: a) obtaining a tissue sample from a subject, b) contacting said tissue sample with an agent ex vivo to produce treated cells, c) isolating treating cells to generated isolated cells, d) preparing a nucleic acid sequencing library from said isolated cells; e) sequencing the sequencing library to generate sequencing data, and f) analyzing the sequencing data to determine an effect of said agent on said tissue.

19. The method of claim 18, wherein said analyzing comprises comparing sequencing data to data obtained from a control sample not contacted with the agent.

20. The method of claim 18, wherein the analyzing comprises determining an effect of said agent on two or more different cell types found in said tissue sample.

21. The method of claim 18, wherein said analyzing comprises determining cell differentiation status of one or more cell types found in said tissue sample.

22. The method of claim 19, wherein said analyzing comprises generating a report that identifies shifts in cell populations between treated cells and control cells.

23. The method of claim 18, wherein said analyzing comprises identifying a change in pathogenic cell-cell interactions in response to treatment with said agent.

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