ZAP70 hypomorphic mutations in mice and humans with a spectrum of hypoactive or hyperactive activities, we have gained insights into mechanisms of central and peripheral tolerance. Interestingly, both hypoactive and hyperactive ZAP70 can lead to the development of autoimmune diseases, albeit through distinct mechanisms. Immature thymocytes and mature T cells rely on normal ZAP70 function to complete their development in the thymus and to modulate T cell responses in the periphery. Hypoactive ZAP70 function compromises key developmental checkpoints required to establish central tolerance, allowing thymocytes with potentially self‐reactive TCRs a greater chance to escape negative selection. Such ‘forbidden clones’ may escape into the periphery and may pose a greater risk for autoimmune disease development since they may not engage negative regulatory mechanisms as effectively. Hyperactive ZAP70 enhances thymic negative selection but some thymocytes will, nonetheless, escape negative selection and have greater sensitivity to weak and self‐ligands. Such cells must be controlled by mechanisms involved in anergy, expansion of Tregs, and upregulation of inhibitory receptors or signaling molecules. However, such potentially autoreactive cells may still be able to escape control by peripheral negative regulatory constraints. Consistent with findings in Zap70 mutants, the signaling defects in at least one ZAP70 substrate, LAT, can also lead to autoimmune disease. By dissecting the similarities and differences among mouse models of patient disease or mutations in ZAP70 that affect TCR signaling strength, we have gained insights into how perturbed ZAP70 function can lead to autoimmunity. Because of our work and that of others on ZAP70, it is likely that perturbations in other molecules affecting TCR signaling strength will be identified that also overcome tolerance mechanisms and cause autoimmunity. Delineating these molecular pathways could lead to the development of much needed new therapeutic targets in these complex diseases.Establishing both central and peripheral tolerance requires the appropriate TCR signaling strength to discriminate self‐ from agonist‐peptide bound to self MHC molecules. ZAP70, a cytoplasmic tyrosine kinase, directly interacts with the TCR complex and plays a central and requisite role in TCR signaling in both thymocytes and peripheral T cells. By studying  This state of unresponsiveness to self generally defines a state of tolerance. Reactivity, of course, depends upon the recognition by the T cell antigen receptor (TCR) of pathogen‐ or oncogene‐derived peptides bound to class I or class II MHC molecules (agonist pMHC). Such recognition of agonist pMHC leads to generation of activation signals dependent upon well‐characterized intracellular biochemical events occurring at the TCR Figure . These eThe robust response to antigenic threats by the host does not imply that there is a complete lack of any recognition of self‐pMHC since naive T cells depend upon recognition of self‐pMHC for survival.Distinct tolerance mechanisms operate centrally or peripherally. Central T cell tolerance occurs during thymocyte development. Cells expressing clonally rearranged and displayed TCRs undergo a quality control assessment to select for a population of thymocytes expressing TCRs that interact appropriately (positive selection) but not too strongly with self‐pMHC . Here, we will focus on several systems in which inappropriate or insufficient signaling via the TCR alters the tolerance threshold centrally or peripherally. We will focus our discussion on recent work from our labs that have studied mutants of a single kinase, ZAP70, and its substrate, LAT. ZAP70 is a cytoplasmic tyrosine kinase critically important in proximal events involved in TCR signaling. The mutants we will discuss either decrease or increase TCR signaling function.1.1Together with LCK, ZAP70 plays a critical role in proximal events linked to initiating TCR signaling. Engagement of the TCR by pMHC or by anti‐receptor (anti‐TCRαβ or anti‐CD3) monoclonal antibodies (mAbs) initiates critical biochemical events involving LCK and ZAP70 that are summarized for simplicity in Figure LCK, like other SRC family kinases (SFKs), can autoactivate via trans‐autophosphorylation. Thus, in the resting T cell, a pool of active LCK exists.In the non‐ligand‐bound state, the TCR CD3‐ and ζ‐chains are not tyrosine phosphorylated  or severe CID (SCID) caused by recessive homozygous/compound heterozygous loss‐of‐function mutations in the 2.2Zap70 mutant SKG mouse model of arthritis (discussed below), making it one of the few mouse models to capture the contribution of an autoreactive TCR repertoire with impaired TCR signal transduction to the pathogenesis of arthritis.The link between immunodeficiency and autoimmunity has long been appreciated in humans. Perhaps it is most evident in patients with primary immunodeficiency where up to 20%‐25% may develop autoimmune cytopenias, rheumatoid arthritis (RA), or other autoimmune diseases.ZAP70 mutations, clinical manifestations, and frequent need for treatment with a hematopoietic stem cell transplant (HSCT), can make it difficult to achieve a comprehensive immunologic and molecular view of ZAP70 deficiency in humans. However, mouse models  can provide additional insight into the importance of ZAP70 function for immune cell development, T cell repertoire selection, and the propensity for autoimmunity in Zap70 murine mutants.Likewise, a subset of the ZAP70‐deficient patients described by Sharifinejad et al2.3That T cells with severely impaired signaling can effectively differentiate into pathologic effector cells that mediate an inflammatory, autoimmune syndrome seems counter‐intuitive. Yet, there are multiple reports linking immune deficiency with immune dysregulation and autoimmunity.2.4Zap70 mutants from an ENU mutagenesis screen. Studies from these Zap70 mutants demonstrated that impaired TCR signaling and thymic selection can produce a potentially autoreactive repertoire of TCRs, and revealed a signaling threshold below which autoimmunity develops.Impairments in T cell signaling are linked to the pathogenesis of certain T‐cell‐mediated autoimmune diseases in humans,Zap70 variant has a functionally impaired C‐SH2‐binding domain that prevents optimal interaction with the stimulated, phosphorylated TCR complex. This causes severely impaired downstream TCR signaling events resulting in altered positive and negative thymic selection. As a consequence, SKG T cells exhibiting the strongest affinity for self‐pMHC ligands are positively selected instead of undergoing deletion, giving rise to a more autoreactive TCR repertoire.The SKG genetic mouse model of arthritis susceptibility on the BALB/c background, is yet another example of autoimmunity in the setting of immune deficiency.The SKG mice not only exhibit a loss in central and likely peripheral tolerance that can be molecularly dissected but they also recapitulate the paradoxical ability of RA CD4 T cells to differentiate into pathogenic effector cells despite impaired TCR signaling.2.5Zap70 mutant mouse (YYAA) in which two tyrosines, Y315 and Y319  production in BALB/c mice challenged with zymosan but did not produce frank arthritis in response to identical environmental challenges that produced arthritis in the SKG line.Zap70 mutations in YYAA and SKG mice may differentially skew their TCR repertoires and have T cells with altered TCR signaling in ways that manifest as different autoimmune syndromes.Our lab previously generated another 2.6Nr4a1 (encoding the orphan nuclear hormone receptor Nur77), which is rapidly and selectively upregulated in response to antigen, but not inflammatory stimuli.hi relative to GFPlo fractions, see Figure hi) T cells marked their reactivity to self‐pMHC in an autologous mixed lymphocyte reaction (AMLR). We established that these SKG GFPhi naive CD4 T cells were more arthritogenic than the GFPlo subset using an established adoptive transfer model in which SKG CD4 T cells are sufficient and necessary to cause arthritis in a lymphopenic host.hi CD4 T cells from SKGNur mice were hyperresponsive to IL‐6 receptor signaling.One specific arthritogenic TCR directed against a ubiquitous self‐antigen was identified in the SKG model,SOCS3 expression was similarly downregulated in RA synovium and suggests a similar mechanism of IL‐6 hyper‐responsiveness in RA joints. Taken together, our findings suggest that despite impaired TCR signaling, autoreactive T cells exposed to chronic antigen stimulation exhibit heightened sensitivity to IL‐6 receptor (IL‐6R) signaling, which contributes to their arthritogenicity in SKG mice  were present in RA synovium compared to matched PBMC's from the same donor.Recently, we have characterized these arthritogenic SKG CD4 T cells in greater detail. We have performed single‐cell RNA and TCR sequencing analyses and have identified genes that are up‐ or downregulated and have also identified TCRs that are enriched in this subset of pathogenic T cells even prior to the development of arthritis. Our unpublished data suggest that impaired negative selection of of thymocytes with TCRs that recognize endogenous antigens in SKG mice creates a biased repertoire of autoreactive naive CD4 T cells that are poised to contribute to disease pathogenesis through their altered transcriptome as they encounter antigen in the periphery.3Recent studies on two hypermorphic ZAP70 mutations, R360P and W131A, illustrate how increased ZAP70 function associated with disrupting ZAP70 autoinhibtion impacts T cell function and immune tolerance  presented by H‐2Kb with varied agonist affinity, the R360P CD8 OTI T cells exhibited selectively enhanced CD69 upregulation and proliferation in response to weak peptide agonists.329‐336.Our recent work on ZAP70 R360P homozygote knock‐in mice provides further insights into the mechanism by which the R360P mutation contributes to the complex autoimmune syndrome in humans.Although ZAP70 is primarily expressed in T cells and NK cells, it is intriguing that these patients with familial autoimmune syndrome developed autoantibody‐mediated diseases including bullous pemphigoid and anti‐factor VIII antibody. Our study of the R360P mice showed that there was an increase in the differentiation of antigen‐specific follicular helper T (Tfh) cells in R360P mice following acute LCMV infection. There were also substantial increases in IgG and IgG1 amounts in 10‐month‐old R360P mice compared with those of control mice, which likely reflects a long‐term consequence of enhanced Tfh cell activity.Taken together, our work highlights how the R360P mutation contributed to human autoimmunity via impaired autoinhibition of ZAP70 regulation. However, in contrast to human patients, R360P mice do not spontaneously develop a detectable autoimmune phenotype on the C57BL/6 background. This could be multifactorial. It is likely that differences in genetic background, the presence of other genetic modifiers, or unique environmental factors contribute to this discrepancy. Additionally, aged R360P mice accumulate regulatory and anergic T cells,3.3Our recent studies on Zap70 W131A mutant miceW131A mutant mice with a polyclonal repertoire exhibited relatively normal T cell development and normal TCR‐induced activation suggesting that compensatory mechanisms, such as a TCR repertoire shift, might have masked the effect of the W131A mutation on TCR signaling.− (non‐Treg) CD73+FR4+ phenotype,Since not all self‐antigens are effectively presented in the thymus and negative selection mechanisms are likely to be incomplete,323‐339 peptide or TCR stimulation.Peripheral W131AOTII CD4 T cells displayed classical characteristics of T cell anergy, such as greatly impaired TCR‐induced signaling as well as reduced production of IL‐2, proliferation, and induction of activation markers, including CD25, CD69, and Nur77 in response to OVA323‐339 peptide and TCR stimulation despite evidence of the presence of a relevant self pMHC based on the increased negative selection in the thymus. Consistent with this notion, and in contrast to enriched tolerized gene signatures and impaired TCR signaling observed in peripheral CD4 T cells, CD4 single‐positive thymocytes exhibited biochemical TCR signaling and gene expression in W131AOTII mice that were comparable to those observed in control OTII mice. Therefore, since increased Tregs and anergic T cells were detected in the periphery, our results suggest that peripheral tolerance is not established in the thymus but, instead, is established in the periphery. This likely involves encounter of a self‐ pMHC in the periphery since we found the maintenance of CD4 T cell anergy and survival of anergic T cells in W131AOTII mice required antigen presentation via MHC‐II molecules.We utilized this genetically encoded mouse model of T cell anergy to answer a key question: Is T cell anergy induced and established in the thymus or in the periphery? Using the W131AOTII model, we found that T cell anergy is induced and established in the periphery.In mice, recent thymic emigrants take up to 3 weeks to differentiate into mature T cells.Multiple negative regulators that target TCR signaling pathways, including PD‐1 and E3 ubiquitin ligases, are highly expressed in anergic T cells and contribute to establishing the unresponsive state in anergic T cells.−/−W131AOTII T cells relied on NFAT‐dependent signaling pathways, based on sensitivity to cyclosporin A. Furthermore, loss of Cbl‐b in W131AOTII mice resulted in profound differences in the gene expression profiles associated with improved T cell responsiveness.We examined the relative contribution of these three negative regulators in the W131AOTII model using mice deficient in each of these negative regulators.−/− and PD‐1−/− T cells were reported to be resistant to other anergic models, including in vitro culture with ionomycin or TGF‐β or Treg, or in vivo oral tolerance or peptide‐induced anergy.Although germline PD‐1 deletion did not rescue functional anergy, we had previously found that PD‐1 blockade by anti‐PD‐1 treatment partially eliminated T cell unresponsiveness in young 4‐week‐old W131AOTII mice.Taken together, our studies with ZAP70 hypermorphic mutants suggest that both central and peripheral tolerance mechanisms may be engaged in systems for which heightened TCR signaling must be compensated. Our genetically encoded mouse model of T cell anergy reveals that T cell anergy is induced in the periphery. The maintenance of the anergized unresponsive state is dependent on Cbl‐b, but not PD1 or Grail. Understanding the mechanisms governing T cell unresponsiveness in anergic T cells may contribute to the development of new therapeutic strategies to induce tolerance in the setting of autoimmune diseases.3.4As discussed above, ZAP70 activation is a key step prior to the diversification of TCR signal transduction pathways that elicit T cell activation.Recently, we and others have discovered that this signaling step—ZAP70‐mediated LAT phosphorylation—plays a critical role in determining T cell sensitivity and ligand discrimination. The efficiency and kinetics of LAT phosphorylation not only allow TCR signals to propagate and LAT signalosomes to assemble but also through a specific spatial and temporal sequence to orchestrate the dynamics of signaling proteins.We recently found that phosphorylation of LAT is spatially regulated within the vicinity of the agonist pMHC‐engaged TCR complexes through the formation of LCK‐ZAP70‐LAT tri‐molecular complexes following TCR stimulation.Interestingly, the public database for human single‐nucleotide variations shows a naturally occurring missense SNP (dsSNP reference cluster id: rs41292396) localized within that specific PIPRSP motif in LAT that is required for the association of Lck‐ZAP70‐LAT multiple protein complexes. Ectopic expression of this SNP‐encoded LAT variant shows impaired TCR signaling (unpublished data), similar to signaling defects observed in T cells that express the mutant LAT that lacks the functional PIPRSP motif.LAT genetic mutations in humans.3 and 0‐30 cells/mm3, respectively), consistent with impaired T cell development observed in Lat‐deficient murine models,Two recent studies have offered clinical insights into LAT mutations presents a more complicated phenotype with some unexpected clinical and immunologic features.LAT genomic locus that also resulted in a C‐terminal partially truncated LAT protein. However, this mutant LAT has a short intracellular tail (the first 88 amino acids) which lacks all five key tyrosine residues (Figure LAT mutation resulted in immunodeficiency, while in others it led to autoimmune disease.Interestingly, similar to the hypomorphic ZAP70 mutations that can lead to immunodeficiency and/or autoimmunity in humans,s Figure . SimilarSeveral possible mechanisms may explain how impaired TCR signaling leads to such autoimmune‐like phenotypes were discussed earlier in this review. Here we will discuss how LAT's role in TCR signaling may further contribute to the various observed clinical phenotypes. First, a key difference between the two clinical cases is the remaining intracellular domain of LAT.LAT caused autoimmune phenotypes in patients,Additionally, considering the similarities between the Y136F murine4ZAP70 mutations in mouse and human, our laboratory has established a panel of ZAP70 variant alleles that exhibit a wide spectrum of hyporeactive or hyperreactive ZAP70 activities. Interestingly, both hypoactive and hyperactive ZAP70 may lead to the development of autoimmune diseases, albeit through distinct mechanisms. Immature thymocytes, and mature T cells rely on normal ZAP70 function to complete their developmental process in the thymus or to modulate T cell responses in the periphery. Hypoactive ZAP70 activity compromises the developmental checkpoints that are important to maintain central tolerance, allowing thymocytes with potentially self‐reactive TCRs to have a greater chance to escape negative selection. Such “forbidden clones” may escape into the periphery, and eventually pose a greater risk to cause autoimmune disease. In fact, the majority of mutations in ZAP70 that are associated with immunodeficiency or autoimmunity in human and mice are hypomorphic alleles that result in complete or partial loss of ZAP70 function.Zap70 mutants, the signaling defects in ZAP70 substrate, LAT, can also lead to autoimmune diseases. Taken together, our work and others reveal the essential role of ZAP70 in maintaining central tolerance and peripheral tolerance. Considering that each Zap70 mutant we have studied may abrogate a specific function or regulation of ZAP70, it is likely that other mutations that disturb TCR signaling thresholds may influence tolerance mechanisms and cause autoimmunity. Future work will aim to further dissect the similarities and differences among mouse models of patient disease or mutations in ZAP70 that affect TCR signaling. The resulting insights will help us delineate the role of each regulatory step of ZAP70 activity in determining T cell functions and responses.As one of the first kinases to be activated during TCR activation, ZAP70 plays a central role in orchestrating T cell functionality. Gained from the insights of studying All authors declare they have no conflicts of interest to disclose.


Wnt signaling plays crucial roles in development and tissue homeostasis, and its dysregulation leads to various diseases, notably cancer. Wnt/β-catenin signaling is initiated when the glycoprotein Wnt binds to and forms a ternary complex with the Frizzled and low-density lipoprotein receptor-related protein 5/6 (LRP5/6). Despite being identified as a Wnt co-receptor over 20 years ago, the molecular mechanisms governing how LRP6 senses Wnt and transduces downstream signaling cascades are still being deciphered. Due to its role as one of the main Wnt signaling components, the dysregulation or mutation of LRP6 is implicated in several diseases such as cancer, neurodegeneration, metabolic syndrome and skeletal disease. Herein, we will review how LRP6 is activated by Wnt stimulation and explore the various regulatory mechanisms involved. The participation of LRP6 in other signaling pathways will also be discussed. Finally, the relationship between LRP6 dysregulation and disease will be examined in detail. For exarylation . DVL is rylation . Interesrylation  and thusrylation .2-dependent manner, where it recruits Axin, CK1γ, and GSK3β to promote LRP6 phosphorylation (2 (PIP2) and subsequent LRP6 phosphorylation  translocates to the plasma membrane in a PtdInsPrylation . ADP-ribrylation . LY6/PLArylation . A lipidrylation . Thereforylation .Next, we review other proteins that influence LRP6 phosphorylation and negatively regulate Wnt/β-catenin signaling. In contrast to CK1γ, whose phosphorylation of LRP6 enhances Wnt/β-catenin signaling, CK1ε inhibits Wnt/β-catenin signaling by interacting with and phosphorylating LRP6 at the S1420 and S1430 residues that are not present in PPPS/TP motifs . MoreoveReceptor-mediated internalization plays a crucial role in signal transduction. LRP6 is internalized after binding to ligands, and internalized LRP6 can either positively or negatively regulate Wnt/β-catenin signaling. For instance, the secreted Wnt modulator Dkk1, by forming a ternary complex with the single transmembrane protein Kremen1/2 and LRP6, internalizes LRP6 and decreases its plasma membrane levels, leading to Wnt/β-catenin signaling inhibition . Interna2-dependent manner  interacts with Kremen1 and inhibits Kremen1-Dkk2-LRP6 complex formation and internalization, resulting in activation of Wnt/β-catenin signaling . In the Proper folding and maturation are essential for LRP6 to carry out its functions at the plasma membrane, and there are several components involved in these processes. Although mature LRP6 is known to be a stable protein , its staPost-translational modifications (PTMs) have also been found to be important for regulating LRP6 folding and maturation. By using an endogenous antibody against LRP6, it has been found that LRP6 is N-glycosylated, and that N-glycosylation is necessary for the membrane localization of LRP6 . On the The R-spondin family members are secreted proteins that influence LRP6 stability . R-spondO-GlcNAcylation, a PTM that induces the attachment of N-acetylglucosamine (GlcNAc) to Ser/Thr residues, also plays a crucial role in LRP6 stability. During serum starvation, O-GlcNAcylation of LRP6 is reduced, which is followed by lysosomal degradation of LRP6  signaling, G protein-coupled receptor (GPCR) and Hippo signaling.s . Previous reports have shown that PTH facilitates LRP6 phosphorylation and activation of Wnt/β-catenin signaling in osteoblasts . Originally, identified via kinome-wide RNAi screening in  of LRP6 . Cyclin  of LRP6 . Mechani of LRP6 . Suppres of LRP6 . Importa of LRP6 . Another of LRP6 . Moreove of LRP6 . These d of LRP6 .LRP6 is highly expressed in several cancer cell lines and overexpression of LRP6 promotes cancer cell proliferation   . In addia (OSCC) . LRP6 isn levels . Finallyn levels .Cognitive and behavioral disorders caused by functional neuron failure and neuronal death are referred to as neurodegeneration. Representative examples include Alzheimer’s, Parkinson’s, and Huntington’s diseases. The causes of neurodegeneration include genetic mutations, protein aggregation, mitochondrial dysfunction, etc. However, the molecular mechanisms underlying neurodegeneration still require further elucidation . The relLRP6 is specifically deleted in the forebrain, synapse formation is suppressed while amyloid-β accumulation and neuronal apoptosis are promoted, altogether resulting in aggravation of Alzheimer’s disease symptoms (DKK1 is highly expressed and causes suppression of LRP6-amyloid precursor protein (APP)-mediated Wnt/β-catenin signaling, which results in accumulation of amyloid-β and synapse loss  in the 1062 residue of LRP6, which converts isoleucine to valine , leads to reduced Wnt/β-catenin signaling and is implicated in Alzheimer’s disease . In addisymptoms . Consistpse loss . These dpse loss , and Wntpse loss . Moreovepse loss .PARK8 are implicated in Parkinson’s disease  in the body and is highly associated with cardiovascular disease and diabetes. Risk factors for metabolic syndrome are diet, low physical activity, aging, and genetics . The relIt is well known that dysregulation of LRP6 is highly associated with coronary artery disease (CAD) and atherosclerosis. Through genome-wide analysis of CAD patients, R473Q, R360H, N433S, and R611C residue mutations in LRP6 were found to be correlated with CAD pathogenesis, as determined by high glucose, lipid, and low-density lipoprotein (LDL) levels in blood vessels . In addiR611C/R611C mutants  via activation of PDGF signaling is a well-known cause of atherosclerosis . Wild-ty mutants . Moreove via SP1 . Consequ via SP1 . In summ via SP1 .TCF7L2-dependent transcription of the insulin receptor (IR) and reduces its protein levels. This results in low insulin sensitivity and high glucose level in blood vessels, both of which contribute to type II diabetes  in heart tissue and reduces carnitine palmitoyltransferase 1b (CPT1b) . Since COrgan homeostasis is maintained through the coordinated action of inflammatory cytokines with host defense function, and dysregulation of inflammatory cytokines is implicated in immune disease or cancer . MoreoveBone mass formation and maintenance is regulated by the activity of osteoblasts, which form bone, and osteoclasts, which degrade bone. Dysregulation of bone mass leads to osteoporosis or sclerosteosis, diseases that are heavily influenced by genetic factors . For insSOST gene) cause sclerosteosis (Several proteins that bind to LRP6 regulate bone formation via modulation of Wnt/β-catenin signaling. It is well-known that loss-of-functions mutation in sclerostin (expressed by the osteosis . Sclerososteosis . Biglycaosteosis .LRP6 reduces the expression of osteoblast differentiation-related genes and suppresses bone formation, even in the presence of PTH (Parathyroid hormone interacts with PTH1R to promote LRP6 phosphorylation and activate Wnt/β-catenin signaling in osteoblasts, leading to increased bone formation . Osteoble of PTH , 2016.Oxidized phospholipids bind to LRP6 and reduce LRP6 plasma membrane levels via clathrin-dependent endocytosis . As a reO-GlcNAcylation are also essential for regulating LRP6 activity. Moreover, LRP6 is involved in multiple signaling cascades apart from Wnt/β-catenin. These include, but are not limited to, non-canonical Wnt signaling, GPCR signaling, cell cycle-related signaling, and Hippo signaling (It has been more than 20 years since LRP6 was discovered as a co-receptor for Wnt/β-catenin signaling. Most studies focusing on the mechanisms underlying LRP6-mediated Wnt/β-catenin signaling have concentrated on phosphorylation events in the intracellular domain of LRP6. However, recent reports have determined that additional PTMs such as ubiquitination, acetylation, and ignaling . Until nWJ planned and wrote the manuscript. EJ directed, edited, and finalized the manuscript. Both authors read and approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Chronic inflammation and dysregulated epithelial differentiation, especially of hair follicle keratinocytes, have been suggested as the major pathogenetic pathways of hidradenitis suppurativa/acne inversa (HS). On the other hand, obesity and metabolic syndrome have additionally been considered as an important risk factor. With adalimumab, a drug has already been approved and numerous other compounds are in advanced-stage clinical studies. A systematic review was conducted to detect and corroborate HS pathogenetic mechanisms at the molecular level and identify HS molecular markers. The obtained data were used to confirm studied and off-label administered drugs and to identify additional compounds for drug repurposing. A robust, strongly associated group of HS biomarkers was detected. The triad of HS pathogenesis, namely upregulated inflammation, altered epithelial differentiation and dysregulated metabolism/hormone signaling was confirmed, the molecular association of HS with certain comorbid disorders, such as inflammatory bowel disease, arthritis, type I diabetes mellitus and lipids/atherosclerosis/adipogenesis was verified and common biomarkers were identified. The molecular suitability of compounds in clinical studies was confirmed and 31 potential HS repurposing drugs, among them 10 drugs already launched for other disorders, were detected. This systematic review provides evidence for the importance of molecular studies to advance the knowledge regarding pathogenesis, future treatment and biomarker-supported clinical course follow-up in HS. Hidradenitis suppurativa/acne inversa (HS) is a chronic, inflammatory, recurrent, debilitating skin disease of the hair follicle that usually presents after puberty with painful, deep-seated, inflamed lesions in the apocrine gland-bearing areas of the body, most commonly at the axillae, inguinal and anogenital regions . A consiCurrent own transcriptome and proteome studies highlighted a panel of immune-related drivers in HS, which induce an innate immunity response in epithelial skin cells in a targeted manner . An inflDespite the beneficial therapeutic effectiveness of several compounds ,6, treatNew technology, including inverse virtual screening  and compThis systematic review was conducted and narrated in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)  utilizinFirst the duplicates among bibliographic records were removed. Titles and abstracts were then scrutinized by two reviewers (V.A.Z. and K.C.Z.) working independently according to predefined inclusion and exclusion criteria. This was followed by scrutiny of full texts of eligible studies. Discrepancies were resolved by discussion with the senior investigator (C.C.Z.). After eligible studies were identified, their bibliographies were screened for studies judged suitable for inclusion. Original investigations of HS molecular signatures and protein studies followed by the identification of molecular mediators were selected for further analysis.Data pertaining to characteristics of publications under study and quantitative data were extracted by two of the reviewers (V.A.Z. and K.C.Z.) working independently using a predetermined customized extraction form. Characteristics of publications included publication year and affiliation of corresponding authors. Molecular characteristics included transcriptome and/or proteome of HS, and drug repurposing/repositioning/reprogramming.Qualitative gene/protein data from the studies were pooled to detect HS signature pathways. Gene nomenclature was verified through the HUGO Gene Nomenclature Committee, European Bioinformatics Institute  public domain . Gene taFor drug repurposing, the detected overall HS molecular signature was compared with the drugs’ molecular signatures of The Drug Repurposing Hub public domain, Eli and Edy L. Broad Institute, MIT and Harvard University   and the Statistics were automatically performed by the applied public domains used ,21,22,23A total of 123 bibliographic records were identified after electronic database searches, 36 through other sources and six through bibliographic record citation search. Among them, 61 records were removed as duplicates, leaving 104 titles and abstracts to be screened. After careful screening and manual search, six records were excluded based on title and abstract and 49 records due to inappropriate design and two records due to overlapping data sets with another record, resulting in 47 studies that were included in the quantitative synthesis ,67,68,69The comparison of lesional skin vs. non-lesional skin as well as of blood of patients vs. controls at the mRNA and protein levels (cumulatively reported as “targets”) without restrictions revealed 386 differentially expressed genes (DEGs) in HS .CXCL10, IL6, IL17A, IL36A, IL36G, S100A8, S100A9) and none in all four targets  have been described in 2/4 targets in two articles, seven in 3/4 targets , 51 in the JAK-STAT signaling pathway (2.6 × 10−34), 39 in the chemokine signaling pathway (2.7 × 10−18), 32 in the IL-17 signaling pathway (1.8 × 10−22), 31 in the Th17 cell differentiation pathway (2.6 × 10−18), 28 in the Toll-like receptor (TLR) pathway (2.2 × 10−16) and 26 in the inflammatory bowel disease pathway (3.6 × 10−26)  receptor interaction pathway (−log× 10−26) .−43, −19, −14, −20), 18 in the rheumatoid arthritis pathway (1.2 × 10−17), 13 in the Th17 cell differentiation pathway (1.5 × 10−9), 13 in the lipid and atherosclerosis pathway (1.2 × 10−5), 10 in the TLR pathway (4.3 × 10−6), 9 in C-type leptin receptor signaling pathway (6.1 × 10−5), 8 in the tumor necrosis factor (TNF) signaling pathway (1.1 × 10−3) and 7 in the type I diabetes mellitus pathway (8.5 × 10−6)  .Concerning the individual cytokine signaling, IL-17, IL-4, IL-13, IL-10, IL-20 family, IL-1 family, IL-18, IL-36, IL-2 family, IL-21 and IL-12 family signaling included DEGs in HS .Epithelial differentiation signaling dysregulation in HS was represented by the epidermal growth factor receptor (EGFR), IL-1, IL-1 receptor, formation of the cornified envelope, TLRs and antimicrobial peptides .Metabolic/obesity-associated dysregulation in HS was detected through type I diabetes mellitus signaling, lipid and atherosclerosis, C-type leptin receptor signaling, estrogen-dependent nuclear events and extranuclear signaling, adipogenesis and resistin signaling .Interestingly, infection-indicating signaling pathways did not exhibit any major involvement in our study .IFNG signaling), signal transduction  and developmental biology (formation of the cornified envelope pathway) pathways as the mainly HS-associated ones , a result that indicates a robust strong protein–protein association in HS (p < 0.0001), indicating that the biomarker selection procedure increased the HS/protein association.The protein-based connectivity map occurring from an assumed gene biomarker translation (103 proteins our of 109 genes) resulted in 2465 interactions compared with the expected 531 interactions , 19 in the JAK-STAT signaling pathway (6.2 × 10−12), 17 in the Th17 cell differentiation pathway (5.2 × 10−13), 17 in the IL-17 signaling pathway (6.0 × 10−14), 16 in the inflammatory bowel disease pathway (1.5 × 10−16), 14 in the TLR signaling pathway (6.0 × 10−14), 14 in the C-type leptin receptor signaling pathway (2.4 × 10−9) and 13 in the TNF signaling pathway (8.4 × 10−8).The 116 druggable genes were enriched in relevant signaling pathways according to the KEGG GO  and the The majority of registered, studied or off-label administered drugs modify HS-associated DEGs. On the other hand, the evaluation of the detected 105 HS-associated druggable genes proposed 452 potentially therapeutic compounds, among them 120 launched drugs, 178 compounds in clinical studies and 154 in preclinical evaluation . Among tIL-1 and IL-17 signaling pathways are activated in HS lesions and circulating neutrophils [IL-1 signaling pathway is also prominent in HS with upregulation of molecules causing immune cell infiltration and extracellular matrix degradation and could be reversed by application of IL-1 receptor antagonist [IL1B signaling pathway-associated genes, such as IL1R1, IL1RN, IFNG, IL6, IL18, IL18R1, IL32, IL33, IL36A, IL36B, IL36G, IL36RN, IL37, TLR2, TLR3, TLR4, S100A7, S100A7A, S100A8, S100A9 and S100A12 were HS-associated DEGs, as detected in our systemic review. Inflammation doubtlessly plays a major role in the pathogenesis of HS ,7,8. Protrophils ,71,72,73trophils . Among otrophils  providedtrophils . IL-17 htrophils . Thus, Itagonist ,76. IL1BThe inflammatory process in HS seems to be coupled with impaired barrier function, altered epidermal cell differentiation, formation of the cornified envelope, TLRs and antimicrobial peptides , the latADIPOQ and PLIN1, shown in this systematic review, might be beneficial in HS treatment. Indeed, thiazolidine derivatives act as PPARγ agonists and effectively increase the adiponectin concentration and adipogenic gene expression [Although HS has well-documented associations with the metabolic syndrome, which is characterized by systemic inflammation identified at a molecular level , the rolpression ,78. Unsapression . FurtherIn conclusion, inflammatory signaling, mainly innate immunity signaling pathways, mostly that of IL-1 and IL-17, epithelial differentiation signaling pathways, primarily of follicular keratinocytes and skin gland duct cells and metabolic signaling pathways, especially that of obesity/adipogenesis, represent pathogenetic HS cascades, whose activity may be targeted by future therapeutic means.HS has been associated with a variety of comorbid disorders, such as inflammatory bowel diseases, especially Crohn’s disease, axial spondylarthritis without or with follicular occlusion, triad signs, genetic keratin disorders associated with follicular occlusion, such as pachyonychia congenita, steatocystoma multiplex, Dowling-Degos disease without and with arthritis, as well as other genetic disorders, such as keratitis–ichthyosis–deafness syndrome and Down syndrome . MoreoveIn addition to the only registered drug in HS, namely adalimumab ,82,83, tThe current review provides robust molecular evidence on the pathogenetic triads of HS, namely upregulated inflammation, dysregulated epithelial cell differentiation and obesity signaling/hormone involvement. In addition, evidence of the negligible role of infectious agents is included. Moreover, HS biomarkers with strong protein–protein connectivity in HS are presented. While adalimumab, the only currently registered drug in HS, and the majority of studied and off-label administered drugs regulate DEGs and their proteins in HS, numerous compounds are eligible for HS repurposing due to their molecular signaling. Among them, 31 compounds are designated probable, following our classification, with 10 of them already being launched for other indications.


Livestock production contributes to a significant part of the economy in developing countries. Although artificial insemination techniques brought substantial improvements in reproductive efficiency, male infertility remains a leading challenge in livestock. Current strategies for the diagnosis of male infertility largely depend on the evaluation of semen parameters and fail to diagnose idiopathic infertility in most cases. Recent evidences show that spermatozoa contains a suit of RNA population whose profile differs between fertile and infertile males. Studies have also demonstrated the crucial roles of spermatozoal RNA (spRNA) in spermatogenesis, fertilization, and early embryonic development. Thus, the spRNA profile may serve as unique molecular signatures of fertile sperm and may play pivotal roles in the diagnosis and treatment of male fertility. This manuscript provides an update on various spRNA populations, including protein-coding and non-coding RNAs, in livestock species and their potential role in semen quality, particularly sperm motility, freezability, and fertility. The contribution of seminal plasma to the spRNA population is also discussed. Furthermore, we discussed the significance of rare non-coding RNAs (ncRNAs) such as long ncRNAs (lncRNAs) and circular RNAs (circRNAs) in spermatogenic events. Numerous functional assays have also been developed to evaluate the competence of spermatozoa within the female genital tract and include assessment of on (IVF) . Assessmon (IVF) . Howeveron (IVF) . Thus, tde novo protein synthesis , intranuclearRNAs, small nucleolar RNAs (snRNAs), etc. The concentration of spermatozoal RNA (spRNA) may be as much as 0.015 pg per sperm (in humans), which is conspicuously high considering the high nuclear: cytoplasmic ratio and very low volume of cytoplasm in sperm . Microarynthesis .IGF2 are bound with histone protein in the sperm nucleus, it has been suggested that spRNAs may have a role in meditating imprinting mechanism or chromatin repackaging following fertilization , the stem cells at the basement of germinal epithelium, are responsible for the maintenance of spermatogenesis throughout the adulthood of males. They possess the ability to self-renew themselves and differentiate into haploid spermatozoa through the well-orchestrated spermatogenesis process. Upon molecular cues to differentiate, the SSCs initially divide mitotically to produce spermatogonia and subsequently undergo a meiotic process to produce spermatocytes, followed by the production of haploid spermatids . The spede novo translation or any possible alternative roles of spRNAs in spermatozoa beyond the delivery of a paternal genome. Thus, the presence of spRNA not only aroused controversies but is intriguing to date from the discovery of sperm-borne RNAs in zygotes  or microarray analysis of spermatozoal samples from epididymis and ejaculates. The spermatozoal samples have been compared between fertilie and infertile males for spRNA profiling  and repo zygotes . The pre zygotes . It was ogenesis . Conversogenesis .de novo under certain circumstances , mitochondrial RNAs, ribosomal RNAs (rRNAs), and some intronic retained elements , the accmstances .UBE2B  , embryonic morphogenesis, microtubule function , mitochondrial function , calcium signaling , and centrosome organization . Bovine cDNA microarray analysis of spermatozoa from different segments of epididymis further revealed segmental differences in the transcriptome. Among the differentially expressed genes (DEGs), the top 10 DEGs were related to reproductive function  and five DEGs  were related to the immune response and cellular defense  , oocyte  defense . Notablyogenesis . The speididymis .RPL23, RPL27A, and RPS18) and degraded rRNAs  have also been reported in bull spermatozoa  and DNA packaging (PRM2) (COX7C) was negatively correlates with male fertility  accounted for 97.4% of the variation of conception rate from frozen-thawed Holstein bulls, which was indicative of the sire fertility index  in low-fertile crossbred bulls annotated to biological functions like apoptosis, cellular differentiation, apoptosis of germ cells, spermatogenesis, fertilization, and early embryo development  were found to be modulating the cytoskeletal organization and acrosome formation , which are involved in sperm capacitation, fertilization, and cellular remodeling during trophoblast adhesion  . Differeg (PRM2) . Expressertility . In anotty index . The uprelopment  whereas ormation . The TSSlization . The upradhesion . These sFGF-14 and BAMBI), energy metabolism , protein phosphorylation , autophagy , inflammation, and apoptosis  have been reported to be significantly up-regulated in poor freezable ejaculates of boar semen  and upregulation of genes associated with the cellular component organization , endocytic receptor activity , membrane channels  and translation regulator activity . Transcripts regulating sperm motility during in vitro capacitation, such as CATSPERG (CatSper channel auxiliary subunit gamma) was upregulated, and CATSPERB (CatSper channel auxiliary subunit beta) was down-regulated in high-fertility pigs. The DEGs annotating to zinc finger nucleases (ZFNs) such as LOC100739821, ZNRF4, PLAGL2, ZFN25, and ZDHHC7 were primarily upregulated in high-fertility boars  were downregulated in high fertile groups and were involved with sonic hedgehog signaling pathway . These transcripts were also marked as potential regulators of spermiogenesis, oocyte fertilization, cellular growth, and cleavage (ODF2 and SPATA18), nuclear genome structure , mitochondrial function , and fertilization  were observed to be associated with compaction of sperm chromatin, energy metabolism, oxidative stress, apoptosis, and early embryo development (TSARG1 transcript in spermatozoa might be involved in inhibiting apoptosis (TSARG1 and testis-specific kinase 1 (TESK1), which are members of the DnaJ-like protein family and serine/threonine kinases, respectively, were significantly higher in the sperm pools collected in winter than in summer. The transcriptome analysis of pig testis and epididymis revealed several transcripts associated with different regions of the epididymis  were found to be positively correlated with fertility, while mRNA transcripts of CCT8 and PRM2 were found to be negatively correlated  were also observed that are known to promote the translation of mRNAs in germ cells. The latter may thus, suggest the importance of spRNAs in regulating protein translation during spermatogenesis , inhibits AKT signaling and activates RAF1/ERK signaling to initiate sperm maturation. Two miRNA poptosis .The spermatozoal miRNA have also been shown to differ in gonadotoxicity, heat stress, and impaired spermatogenesis. Differentially expressed miRNAs have been reported between normal and abnormal spermatozoa of bulls affected by Fescue toxicosis . An incrThe miRNAome of boar spermatozoa has been described in several studies  and may IL-23R) was down-regulated in high-fertility boars  signaling pathway  . Later oviz. ATP6V0A2, PPA2, PAIP2, and PAXIP1 have been directly implicated in spermatozoal function and male fertility. Among these, the PPA2 is a pyrophosphatase enzyme located at the mitochondrial membrane and is involved in ATP production during sperm capacitation and motility  have also been found to be influenced by circRNAs. Remarkably, four circRNAs host genes  showed a significant correlation with the motility of spermatozoa.Circular RNAs (circRNAs) are a class of ncRNAs having a closed-loop structure formed by alternative back splicing of pre-mRNA in which the 3′-end of an exon is spliced to the 5′-end of an upstream exon . Dependimotility . On the  in mice . The TES in mice . The SPA in mice . Genes rPOC1A gene) and germ cell development . Due to their stability and spatiotemporal specificity, circRNAs such as circRNA 10187, circRNA 6,682, circRNA 10979, and circRNA 18456 could be used as biomarkers of boar sexual maturity. The circRNA 1774 (derived from CDC42 gene) and circRNA 18184 (derived from PTEN gene) were significantly downregulated whereas circRNA 40370 (derived from the RICTOR gene) was significantly upregulated in the testis of the sexually mature boars. The circRNAs were involved in signaling pathways that regulate stem cell pluripotency , tight junction , and adhesion connections , hedgehog signaling pathways , cAMP signaling pathways , mTOR signaling pathways , and phosphatidylinositol signaling systems . The expression profile of circRNAs in neonatal and adult cattle testis revealed some of the potential target genes of circRNAs mainly involved in cell-to-cell junction, oocyte maturation, and TGFβ signaling pathway  and, therefore, are excluded from IVF and intracytoplasmic injection (ICSI) of ejaculated sperm. The ARTs have resulted in successful fertilization, pregnancy, and live birth of offspring in humans  and animPRM1 in seminal plasma was positively correlated with mitochondrial membrane potential, and lateral movement of sperm head was associated with expression of BMP2, UBE2D3, TRADD, and CASP3 , tsRNA , miRNA, and piRNA. There were 325 miRNAs, of which 37 novel miRNAs were identified in boar . The stund CASP3 . In thisThe terminal stages of spermatogenesis are accompanied by chromatin condensation and the replacement of histones by protamines. These changes are primarily driven by transition proteins and cleavage of rRNAs by nuclease activities and lead to the progressive shutdown of transcriptional and translational activities in mature spermatozoa . InteresSRPK1) and calcium/calmodulin-dependent protein kinase 4 (CAMK4), followed by rapid dephosphorylation to establish disulfide bonds between the unmasked cysteine residues of dephosphorylated protamines (H2B and TH2B) incorporate into spermatids with the help of transition proteins , which supersede with protamines   . Histone1, PRM2) . The sig1, PRM2) . The sta1, PRM2) .2+ oscillations that play a critical role during oocyte activation. Several studies also identified Calcium ion channels such as CatSper in the spRNA population, which is essential in regulating capacitation and sperm motility in livestock species as well as humans  of spRNA may find its application in semen evaluation for diagnosing idiopathic male infertility and devising newer methods for treatment.In conclusion, various types of protein-coding and non-coding spRNAs have been documented in the literature with their potential roles in regulating male reproduction and fertility. These spRNAs may be exploited


Skin color is determined by the processes of melanin synthesis and distribution. Problems in various molecules or signaling pathways involved in melanin synthesis contribute to skin pigmentation defects. Several trials have been conducted on the production of pigmentation-regulating agents, and drug repositioning has emerged as a modern technique to identify new uses for existing drugs. Our research team has researched substances or drugs associated with pigmentation control and, as a result, nilotinib, sorafenib, and ICG-001 have been found to promote pigmentation, while 5-iodotubercidin inhibits pigmentation. Therefore, these substances or medications were suggested as potential therapeutics for pigmentation disorders by drug repositioning. Melanocytes are cells that play an important role in expressing skin color, with a particular function in the synthesis and distribution of melanin. Melanin synthesis occurs in melanosomes, specialized membrane-bound organelles inside melanocytes. Each melanocyte is linked to several keratinocytes, and melanin pigments are continuously distributed to the surroundings . SeveralDrug development by drug repositioning has been in progress in various fields in recent years but has not been adequately implemented in fields related to pigmentation-regulating agents. For several years, our research team has been undertaking experiments to identify substances or drugs involved in the pigmentation process. We investigated 800 drugs approved by the United States (US) Food and Drug Administration (FDA), and in vitro or in vivo experiments were conducted. In the in vitro experiments, pigmented cell lines, promoter assays, and normal human melanocytes were used, and in the in vivo experiments, zebrafish were used. It is thought that the probability of identifying compounds for therapeutic use, which is proved from studies of novel mechanisms involved in the regulation of pigmentation in addition to the already known effects of drugs, is strong. This review briefly identifies the mechanisms of melanin synthesis and development to explain the etiology of associated pigmentation disorders, and discusses the use of drug repositioning as a potential development strategy for pigmentation-regulating agents. Specifically, it presents a review of the findings and interpretations of several studies on pigmentation-regulating substances and drugs undertaken by our research team.For this review, we used the adapted preferred reporting items for systematic reviews and meta-analyses (PRISMA) model. For the literature search, we used an electronic database search in PubMed and Scopus . We searched these databases using the following search terms: “pigmentation”, “melanogenesis” OR “drug repositioning”.We scanned all articles included in the research field. We included English articles referring to drug repositioning in melanogenesis. Due to the small number of search results, we did not apply filters regarding the year of publication or type of study. Articles that analyzed the general mechanisms of regulating melanogenesis, the concept of drug repositioning and examples of applications in dermatology were included. We included our previous research on the development of pigmentation-regulating agents by drug repositioning. We excluded articles in which the mechanisms were not related to melanogenesis or in which there was no mention of drug repositioning.Of a total of 258 articles, 35 were duplicates and were removed. The title and abstract of 223 articles were screened, and 82 articles were reviewed in full text. Subsequently, full-text assessment resulted in the exclusion of 42 studies in total, including 26 studies that were not associated with clinical outcomes and 16 studies that did not have the full text available. In the end, 40 studies were included in this review. A flowchart for study selection is depicted in Melanogenesis is a complicated process mediated by multiple signaling pathways, and microphthalmia-associated transcription factor (MITF), which exists downstream of these pathways, is emphasized as a major regulator of melanocyte production. Transcription of the MITF gene is regulated by major signaling pathways including α-melanocyte-stimulating hormone (α-MSH)/melanocortin 1 receptor (MC1R), wingless-related integration site (Wnt)/β-catenin, and stem cell factor (SCF)/tyrosine kinase receptor (KIT) pathways. Problems in these signaling pathways can lead to defects in skin pigmentation such as hypopigmentation and hyperpigmentation. We discuss the regulation of melanogenesis by several signaling pathways  Figure .The melanogenic inducer α-MSH combines with the MC1R on melanocytes to activate intracellular cyclic adenosine monophosphate (cAMP). The effect of increased cAMP is regulated by cAMP-dependent protein kinase A (PKA). This protein triggers the phosphorylation of the cAMP response element-binding protein (CREB), which promotes the gathering of the CREB-binding protein (CBP). Pigmentation-related gene expression, including MITF, tyrosinase, and tyrosinase-related proteins (TRPs), is subsequently increased ,7.Another regulatory process for melanocyte development is the Wnt/β-catenin signaling pathway. As Wnt binds to the receptors, the stability of cytoplasmic β-catenin increases and activates MITF transcription in the nucleus . The amoIn melanogenesis, the SCF/KIT signaling pathway is also important. When SCF interacts with c-KIT, its receptor, tyrosine kinase activity is stimulated, triggering receptor phosphorylation. The phosphorylation of c-KIT involves the stimulation of mitogen-activated protein kinase (MAPK) and CREB phosphorylation occurs, activating MITF. Thus, inhibiting the SCF/KIT signaling pathway can decrease melanin pigmentation .In the process of ultraviolet B (UVB)-induced pigmentation, endothelin (ET), which is formed in keratinocytes, is a mediator for melanocytes. Exposure to ultraviolet B (UVB) rays induces the connection of ET between melanocytes and keratinocytes. ET increases tyrosinase activity and enhances gene expression, including tyrosinase and tyrosinase-related protein-1 (TRP-1) expression ,11.The cholinergic system may be a negative regulator of skin pigmentation. The release of acetylcholine (ACh) from keratinocytes is activated by solar light. ACh binds to the acetylcholine receptor (AChR) and acetylcholinesterase (AChE) of melanocytes, resulting in the inhibition of the cAMP-dependent signaling pathway. Melanogenesis caused by solar light in melanocytes is suppressed by ACh and AChE inhibitors, indicating that the cholinergic mechanism plays a part in inhibiting melanogenesis ,13.Phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling, which prevents the process of pigmentation, is another mechanism. The activation of AKT signaling suppresses GSK3β and blocks pigmentation, resulting in a decrease in the melanin content. On the other hand, the inhibition of PI3K and downstream AKT signaling promotes GSK3β activation, facilitating the process of MITF attaching to the promoter of tyrosinase. Consequently, the expression of pigmentation-associated genes is enhanced .The extracellular signal-regulated protein kinase (ERK) signaling pathway is activated by c-KIT, and also promotes the phosphorylation of CREB. Activated ERK signaling also stimulates phosphorylation and causes the degradation of MITF, which prevents the synthesis of melanin ,15.The production of a new drug involves complicated stages, including discovery and preclinical stages, safety review, clinical research, FDA review, and FDA post-market safety monitoring . SeveralMany instances of drug repositioning have been used to treat dermatological disorders . InitialFinasteride is a medication that was initially formulated to treat benign prostatic hyperplasia. Finasteride inhibits 5α-reductase, inhibiting testosterone conversion to dihydrotestosterone (DHT). Low doses of finasteride have been used to treat hair loss in men as this process is often associated with androgenic alopecia .Minoxidil was originally developed for the treatment of hypertension as a potent peripheral vasodilator but was found to have hair growth as one of the clinical side effects. Minoxidil has also been developed for the treatment of androgenic alopecia .A representative example of drug repositioning in pigmentation disorders is tranexamic acid. Tranexamic acid, a plasmin inhibitor, has been used as an anticoagulant in the past but is now used as a melasma-whitening agent . ChemicaMany research groups have looked into the mechanism of drug repositioning related to the inhibition of tyrosinase activity. Ethionamide, a secondary anti-tuberculosis agent used to treat multidrug-resistant tuberculosis, shares a chemical similarity with tyrosinase inhibitors, and reduces melanin content .Thiopurine drugs offer other examples of drug repositioning as tyrosinase inhibitors. Thioguanine, a drug used to treat acute leukemia, has been shown to decrease melanin content by inhibiting tyrosinase activity .BRAF and NRAS mutant melanomas to MAPK pathway inhibitors [Nelfinavir, an HIV1-protease inhibitor, was identified as a potent suppressor of MITF expression in a drug repositioning study relevant to the MAPK pathway. Nelfinavir improves the approach of targeted melanoma therapy by sensitizing hibitors .We present an overview of several studies on the regulation of melanogenesis through drug repositioning in BCR-ABL tyrosine kinase is a particular inhibitor developed to resolve the issue of intolerance of and resistance to imatinib [p38 MAPK [Nilotinib is a drug approved by the FDA to treat chronic myeloid leukemia (CML). imatinib ,31. Origp38 MAPK . Furtherp38 MAPK . Such daIn our research on the effect of nilotinib on pigmentation, we found that in melanoma cells, nilotinib induced pigmentation . When niIn our study, we observed that nilotinib had the effect of controlling signaling pathways involved in pigmentation processes such as AKT and cAMP/PKA to enhance pigmentation in melanoma cells . Our resRaf1, there is some evidence that sorafenib has several other target proteins. For example, by targeting vascular endothelial growth factor (VEGF) receptors and platelet-derived growth factor (PDGF) receptors, sorafenib prevents angiogenesis [Sorafenib is a therapeutic agent approved by the FDA that can be used to treat a number of cancers, including unresectable hepatocellular carcinoma (HCC) and advanced renal cell carcinoma (RCC) . Althougogenesis .Reinforcing the concept of several target proteins, our study found that by controlling many signal pathways, sorafenib may promote pigmentation in melanoma cells . The pigIn our research, we found that sorafenib induced pigmentation in melanoma cells by inhibiting the AKT and ERK signaling pathways and regulating the β-catenin signaling pathway . FurtherICG-001, which targets Wnt/β-catenin signaling, was initially designed to treat colorectal cancer by binding to CBP and preventing the connection between β-catenin and CBP . As descSeveral Wnt/β-catenin signaling inhibitors including tankyrase, porcupine, and CBP have been tested in our research . ContrarIn our research, we observed that many inhibitors of Wnt/β-catenin signaling did not alter pigmentation in melanoma cells, whereas ICG-001, an effective inhibitor of Wnt/-β-catenin signaling, induced pigmentation in melanoma cells by triggering the PKA signaling pathway. Our results suggest that PKA signaling beyond Wnt/β-catenin signaling is essential in the pigmentation mechanism itself. Furthermore, ICG-001 may be an alternative substance for the treatment of hypopigmentation disorders.5-Iodotubercidin is an adenosine kinase inhibitor that has been identified as an activator of tumor suppressor p53 and has demonstrated anti-tumor efficacy by decreasing the size of tumors. 5-Iodotubercidin has been investigated as a possible genotoxic drug in chemotherapy since tumor suppressor p53 has been identified as an important target in the production of anti-cancer drugs .We showed an inhibitory effect of 5-iodotubercidin on the pigmentation process in melanoma cells . When weOur research demonstrated that 5-iodotubercidin had an inhibitory effect on melanogenesis by regulating many signaling pathways related to pigmentation . 5-IodotDrug repositioning is an effective method to identify new drug uses by leveraging the effects of medications that have already been approved. Not only does this minimize the time and expense needed for new drug production, but since their efficacy has already been demonstrated, it also has a high likelihood of showing effectiveness in drug development. Our research team has researched the pathways involved in pigmentation modulation by treating melanocytes with particular substances or medications . Based oBy influencing the pathways linked to pigmentation, all four forms, nilotinib, sorafenib, ICG-001, and 5-iodotubercidin, can be used to regulate pigmentation. In particular, the first three compounds or medications have been found to play a role in encouraging pigmentation, with the fourth compound serving to suppress pigmentation. It is also proposed that, for pigmentation disorders, these compounds or medications may be used as therapeutic or cosmetic agents.


Drosophila macrophages, also known as plasmatocytes or hemocytes, utilizes enhanced cortical F-actin levels stimulated by the Drosophila member of the fos proto oncogene transcription factor family . RNA sequencing analysis and live imaging show that Dfos enhances F-actin levels around the entire macrophage surface by increasing mRNA levels of the membrane spanning molecular scaffold tetraspanin TM4SF, and the actin cross-linking filamin Cheerio, which are themselves required for invasion. Both the filamin and the tetraspanin enhance the cortical activity of Rho1 and the formin Diaphanous and thus the assembly of cortical actin, which is a critical function since expressing a dominant active form of Diaphanous can rescue the Dfos macrophage invasion defect. In vivo imaging shows that Dfos enhances the efficiency of the initial phases of macrophage tissue entry. Genetic evidence argues that this Dfos-induced program in macrophages counteracts the constraint produced by the tension of surrounding tissues and buffers the properties of the macrophage nucleus from affecting tissue entry. We thus identify strengthening the cortical actin cytoskeleton through Dfos as a key process allowing efficient forward movement of an immune cell into surrounding tissues.The infiltration of immune cells into tissues underlies the establishment of tissue-resident macrophages and responses to infections and tumors. Yet the mechanisms immune cells utilize to negotiate tissue barriers in living organisms are not well understood, and a role for cortical actin has not been examined. Here, we find that the tissue invasion of  The infiltration of immune cells into tissue underlies the establishment of tissue-resident macrophages, and responses to infections and tumors, but how do they overcome tissue barriers? This study shows that macrophages upregulate the proto-oncogene Fos, increasing the density and crosslinking of cortical actin, thereby counteracting the tension of surrounding tissues and protecting the macrophage nucleus. The classical model of cell migration on a surface postulated in the 1980s by Abercrombie has been extended . Much ofMigration in 2D and 3D environments requires actin polymerization to power forward progress. The assembly of actin at the leading edge, when coupled to Integrin adhesion to anchor points in the surrounding extracellular matrix (ECM), can allow the front of the cell to progress . This anDrosophila macrophage migration into the embryonic germband (gb) to investigate mechanisms of immune cell tissue invasion. Macrophages, also called plasmatocytes or hemocytes, are the primary phagocytic cell in Drosophila and share striking similarities with vertebrate macrophages  (control), UAS-cher RNAi KK107451, UAS-TM4SF RNAi KK102206, UAS-Lam RNAi1 GD45636, UAS-Lam RNAi2 KK107419 lines were obtained from the Vienna Drosophila Resource Center (Austria).SF, USA) . Oregon Here, we list the lines used in each figure; we state first the name from FlyBase; in parentheses, the name used in the figure panels is provided.Oregon R. srpHemo-GAL4, UAS-GFP (control). srpHemo-Gal4, srpHemo-H2A::3xmCherry/P{CaryP}attP2 (control). srpHemo-GAL4, UAS-GFP; kay1(Dfos1). srpHemo-GAL4, UAS-GFP::nls/+ (control 1). srpHemo-GAL4, UAS-GFP/+; kay1(Dfos1). srpHemo-GAL4, UAS-GFP::nls/+; kay2(Dfos2). srpHemo-GAL4, UAS-GFP::nls/(UAS-Fra)2; kay2. 10XUAS-IVS-myr::GFP/+; srpHemo-Gal4, srpHemo-H2A::3xmCherry/+ (control 2 and control). UAS-DfosDN/+; srpHemo-Gal4, srpHemo-H2A::3xmCherry/+ (mac>DfosDN). srpHemo-Gal4, srpHemo-H2A::3xmCherry/ UAS GFP::nls (ctrl). srpHemo-Gal4, srpHemo-H2A::3xmCherry/UAS-fbz (mac>DfosDN). srpHemo-Gal4, srpHemo-H2A::3xmCherry /+ (ctrl). srpHemo-Gal4, srpHemo-H2A::3xmCherry/UAS-DfosDN (mac>DfosDN). UAS-GFP; srpHemo-Gal4, srpHemo-H2A::3xmCherry (ctrl). UAS-Dfos RNAi HMS00254/srpHemo-Gal4, srpHemo-H2A::3xmCherry (mac>DfosRNAi1). UAS-Dfos RNAi JF02804/srpHemo-Gal4, srpHemo-H2A::3xmCherry (mac>DfosRNAi2). srpHemo-GAL4, UAS-GFP::nls/+ or /(UAS-Fra)2 (mac>Dfos). UAS-GFP; UAS-Dfos RNAi HMS00254/ srpHemo-Gal4, srpHemo-H2A::3xmCherry (mac>DfosRNAi1+ GFP). UAS-GFP; UAS-Dfos RNAi JF02804/srpHemo-Gal4, srpHemo-H2A::3xmCherry (mac>DfosRNAi2+ GFP).srpHemo-H2A::3xmCherry/+ (control). srpHemo-Gal4, srpHemo-H2A::3xmCherry/+ (3 movies) and Resille::GFP/+; srpHemo-Gal4, srpHemo-H2A::3xmCherry/+  and Resille::GFP/+; srpHemo-Gal4, srpHemo-H2A::3xmCherry/+ (3 movies) and Resille::GFP/+; srpHemo-Gal4, srpHemo-H2A::3xmCherry/UAS-DfosDN . srpHemo-Gal4, srpHemo-H2A::3xmCherry/UAS-fbz (mac>DfosDN). srpHemo-GAL4, UAS-GFP.nls/+ (control). srpHemo-GAL4, UAS-GFP.nls/+; kay2(Dfos2).UAS-Dicer2;; srpHemo-Gal4, srpHemo-H2A::3xmCherry/w1118 (control). UAS-Dicer2; UAS-TM4SF RNAi KK10220/+; srpHemo-Gal4, srpHemo-H2A::3xmCherry/+ (mac>TM4SF RNAi). UAS-Dicer2; UAS-cher RNAi KK107451/+; srpHemo-Gal4, srpHemo-H2A::3xmCherry/+ (mac>cher RNAi). UAS-Dicer2; UAS-cher RNAi KK107451/UAS-TM4SF RNAi KK102206; srpHemo-Gal4, srpHemo-H2A::3xmCherry/+ . srpHemo-GAL4, UAS-mCherry::nls/UAS-mCD8::GFP (control). srpHemo-GAL4, UAS-mCherry::nls/UAS-mCD8::GFP; UAS-fbz/+ (mac>DfosDN). srpHemo-GAL4,UAS-mCherry::nls/UAS-cheerio::FLAG; UAS-fbz/+ . srpHemo-GAL4,UAS-mCherry.nls/UAS-TM4SF; UAS-fbz/+ . srpHemo-GAL4, UAS-mCherry::nls/ UAS-TM4SF (mac>TM4SF). srpHemo-GAL4, UAS-mCherry::nls/UAS-cher (mac>cher). srpHemo-Gal4, srpHemo-3xmCherry/+ (control). srpHemo-Gal4, srpHemo-3xmCherry/UAS-fbz (mac>DfosDN).srpHemo-3xmCherry; kay1 (Dfos1) and srpHemo-3xmCherry; +. srpHemo-Gal4, srpHemo-moe::3xmCherry/+;UAS-mCD8::GFP/+(Control). srpHemo-Gal4, srpHemo-moe::3xmCherry/UAS-fbz (mac>DfosDN). w118. srpHemo-Gal4, srpHemo-moe::3xmCherry/w118 (Control). srpHemo-Gal4, srpHemo-moe::3xmCherry/UAS-cher RNAi KK107451 (mac>cher RNAi). srpHemo-Gal4, srpHemo-moe::3xmCherry/UAS-TM4SF RNAi KK102206 (mac>TM4SF RNAi). srpHemo-GAL4, UAS-mCherry.nls/UAS-mCD8::GFP (control). srpHemo-GAL4, UAS-mCherry.nls/UAS-DiaΔDad::EGFP; UAS-fbz/+ . srpHemo-GAL4, UAS-mCherry.nls/UAS-mCD8::GFP; UAS-fbz/+ (mac>DfosDN). srpHemo-GAL4, UAS-mCherry.nls/ UAS-DiaΔDad::EGFP (mac>diaCA). UAS-GFPnls; srpHemo-Gal4, srpHemo-H2A::3xmCherry. #2: UAS-GFPnls/srpHemo-Gal4, srpHemo-H2A::3xmCherry; Dfos1. #3: UAS-GFPnls/ srpHemo-Gal4, srpHemo-H2A::3xmCherry; Dfos2. #4: UAS-DiaΔDad::EGFP/srpHemo-Gal4, srpHemo-H2A::3xmCherry; Dfos1. #5: UAS-DiaΔDad::EGFP/srpHemo-Gal4, srpHemo-H2A::3xmCherry; Dfos2. UAS-Dicer2;; srpHemo-Gal4, srpHemo-H2A::3xmCherry/P{CaryP}attP40 (control). UAS-Dicer2;+; srpHemo-Gal4, srpHemo-H2A::3xmCherry/ UAS-dia RNAi HM05027 (mac>dia RNAi1). UAS-Dicer2;+; srpHemo-Gal4, srpHemo-H2A::3xmCherry/UAS-dia RNAi HMS00308 (mac>dia RNAi2). UAS-dia::EGFP/+; UAS-nlacz/ srpHemo-Gal4, 10XUAS-IVS-myr::tdTomato. UAS-dia::EGFP/+; UAS-Rho1N.19)/srpHemo-Gal4, 10XUAS-IVS-myr::tdTomato (mac>Rho1DN). UAS-dia::EGFP/+; UAS-fbz/srpHemo-Gal4, 10XUAS-IVS-myr::tdTomato (mac>DfosDN). UAS-dia::EGFP/+; UAS-cher RNAi KK107451/srpHemo-Gal4, 10XUAS-IVS-myr::tdTomato (mac>cher RNAi). UAS-dia::EGFP/+; UAS-TM4SF RNAi KK102206/srpHemo-Gal4, 10XUAS-IVS-myr::tdTomato (mac>TM4SF RNAi). UAS-diaRBD::GFP/+; srpHemo-Gal4, 10XUAS-IVS-myr::tdTomato/UAS-nlacZ (control). UAS-diaRBD::GFP/+; srpHemo-Gal4, 10XUAS-IVS-myr::tdTomato/UAS-Rho1N.19 (mac>Rho1DN). UAS-diaRBD::GFP/UAS-fbz; srpHemo-Gal4, 10XUAS-IVS-myr::tdTomato/+ (mac>DfosDN). UAS-diaRBD::GFP/UAS-cher RNAi KK107451; srpHemo-Gal4, 10XUAS-IVS-myr::tdTomato/+ (mac>cher RNAi). UAS-diaRBD::GFP/UAS-TM4SF RNAi KK102206; srpHemo-Gal4, 10XUAS-IVS-myr::tdTomato/+ (mac>TM4SF RNAi).srpHemo-Gal4 UAS-LifeActGFP UAS-RedStinger (control); srpHemo-Gal4 UAS-LifeActGFP UAS-RedStinger; UAS-DfosDN (mac>DfosDN). srpHemo-Gal4, UAS-CLIP::GFP, UAS-RedStinger (control). srpHemo-Gal4, UAS-CLIP::GFP, UAS-RedStinger; UAS-fbz (mac>DfosDN). srpHemo-GAL4, UAS-mCherry.nls/UAS-mCD8::GFP (control). srpHemo-GAL4, UAS-mCherry.nls/UAS-Lamin RNAi GD45636, KK107419 . srpHemo-GAL4, UAS-mCherry.nls/UAS-LaminC RNAi TRIP JF01406 (mac>LamC RNAi). srpHemo-GAL4, UAS-mCherry.nls/UAS-mCD8::GFP; UAS-fbz/+ (mac>DfosDN). srpHemo-GAL4, UAS-mCherry.nls/UAS-Lam RNAi ; UAS-fbz/+ . srpHemo-GAL4, UAS-mCherry.nls/UAS-LaminC RNAi TRIP JF01406; UAS-fbz/+ . e22c-Gal4,srpHemo-H2A::3xmCherry/+ (control). srpHemo-QF/ srpHemo-H2A::3xmCherry; QUAS-fbz/UAS-Rho1.N12 (mac<>DfosDN). e22c-Gal4, srpHemo-H2A::3xmCherry/srpHemo-QF; +/ UAS-Rho1.N12 (ecto>Rho1DN). srpHemo-QF/ e22c-Gal4, srpHemo-H2A::3xmCherry; UAS-Rho1.N12/QUAS-fbz . +;UAS-GFP::nls, srpHemo-GAL4 (control). +;UAS-GFP::Lamin, srpHemo-GAL4 (mac>Lam).UAS-fbz (UAS-Dfos DN) line [The fragment was amplified from genomic DNA of the published DN) line  using pry1M{vas-int.Dm}ZH-2A w*; M{3xP3-RFP.attP}ZH-51D, BL 24483), to produce second chromosome inserts. All male survivors were crossed to w; Sp/CyO; PrDr/TM3Ser virgins. Transformants were recognized by eye color and crossed again to w; Sp/CyO; PrDr/TM3Ser virgins to get rid of the X chromosomal integrase.The TM4SF open reading frame was amplified from the DGRC GH07902 cDNA clone , using primers acagcgGAATTCATGGCATTGCCGAAGAAAAT and acagcgTCTAGATTAAAAGCTAATCGTCTGTCATT. The PCR product and the pUASt-aTTB vector (DGRC plasmid #1419) were digested with EcoRI and XbaI, and ligated. After sequencing, the construct was injected into the landing site line,  against the C-terminal end of g. Then 10 μg of the cleared lysate were separated by SDS-PAGE using 4% to 15% Mini-PROTEAN TGX Precast Protein gels  and blotted onto a Amersham Protran Premium western blotting nitrocellulose membrane . The nitrocellulose membrane was blocked with Pierce Clear Milk blocking buffer  and incubated in blocking buffer with anti-mCherry  at 1:1,000, and anti-Profilin  [Cages were prefed on fresh yeast plates for 2 days. Late stage 11/early stage 12 embryos were handpicked using a Leica M205 fluorescent microscope on ice-cold apple juice plates. They were transferred to RIPA buffer  with a Halt Protease/Phosphatase inhibitor cocktail  and lysed. After a 30-minute incubation on ice, they were centrifuged 15 minutes at 4°C at 15,000#chi 1J)  at 1:50 Dfos2 for which the setting was 25°C.Embryos were dechorionated in 50% bleach for 5 minutes, washed with water, and mounted in halocarbon oil 27 (Sigma) on a 24 × 50 mm high precision coverslip  between 2 bridges (approximately 0.5 cm high) of coverslips glued on top of each other or mounted in halocarbon oil 27 (Sigma) between an 18 × 18 mm coverslip  and an oxygen permeable membrane (YSI). The embryo was imaged on an upright multiphoton microscope  equipped with a W Plan-Apochromat 40X/1.4 oil immersion objective (Olympus). GFP and mCherry were imaged at 860 nm and 1,100 nm excitation wavelengths, respectively, using a Ti-Sapphire femtosecond laser system (Coherent Chameleon Ultra) combined with optical parametric oscillator technology (Coherent Chameleon Compact OPO). Excitation intensity profiles were adjusted to tissue penetration depth and Z-sectioning for imaging was set at 1 μm for tracking. For long-term imaging, movies were acquired for 60 to 150 minutes with a frame rate of 25 to 45 seconds. A temperature control unit set to 29°C was utilized for all genotypes except Dfos RNAi, embryos with 70% gb retraction (Stage 13) were used for vnc counts. The pre-gb zone was defined based on embryo and yolk autofluorescence as an area on the yolk sac underneath the amnioserosa with borders defined posteriorly by the gb ectoderm and anteriorly by the head. Macrophages were visualized using confocal microscopy with a Z-stack step size of 2 μm, and macrophage numbers within the gb or the segments of the vnc were calculated in individual slices (and then aggregated) using the Cell Counter plugin in FIJI. Total macrophage numbers were obtained using Imaris (Bitplane) by detecting all the macrophage nuclei as spots.Autofluorescence of the embryo revealed the position of the gb for staging of fixed samples. Embryos with 40% (±5%) gb retraction (Stage 12) were analyzed for macrophage numbers in the pre-gb, within the gb, along the vnc, and in the whole embryo. For the srpHemo-H2A::3xmCherry and the surrounding tissues with Resille::GFP, or with only macrophages labeled by srpHemo-H2A::3xmCherry, or srpHemo>GFP::nls were imaged, and 250 × 250 × 40 μm3 3D stacks were typically acquired with approximately 0.2 × 0.2 × 1 μm3 voxel size every 39 to 41 seconds for approximately 2 hours. For imaging macrophages on vnc, frames were acquired at every 40 to 43 seconds for 30 minutes after macrophages started spreading into abdominal segment 2  are its instantaneous velocities. Only trajectories with a minimal duration of 15 time frames were used. Calculated persistence values were averaged over all trajectories to obtain a persistence index (I) for the duration of measurement (with −1 being the lowest and 1 the maximum). From 3 to 6 embryos were recorded and analyzed for each genotype; numbers of control and perturbed embryos are equal in each pairwise comparison.Cell speed and persistence were calculated from nuclei positions using custom Python scripts as described elsewhere . Briefly2 in each embryo. Analyses were carried out using standard Fiji software. From 4 to 5 embryos were analyzed per genotype. Macrophages in the pre-gb or gb entry zones were analyzed.The junctional intensity of F-actin  was calculated using linescan analysis as previously described  with thesrpHemo-moe::3xmCherry reporter line [DfosDN, cher RNAi, or TM4SF RNAi. Embryos were collected for 5 hours 30 minutes at 29°C, dechorionated in 50% bleach for 5 minutes, rinsed thoroughly with water, and aligned laterally side by side under a stereomicroscope using a fluorescence lamp to check for the presence of mCherry. Aligned embryos were then mounted as described in the live imaging section above. To image Moe::3xmCherry, a Zeiss LSM800 inverted microscope was used with the following settings: Plan-APOCHROMAT 40x/1.4 Oil, DIC, WD = 0.13 objective, 1.5× zoom, 1,025 × 1,025 pixel, speed 8, heating chamber set to 29°C, z-interval 1 μm. Laser settings were kept constant in all experiments. Images were acquired during macrophage invasion into the gb (St 12). Pseudo-coloring was conducted for the mCherry red channel. Each pixel in the image has a color ascribed to it via the fire “Look Up Table” translating the level of intensity of the mCherry channel into a defined amount of each color. The highest intensity of the image is represented as very bright yellow, and all other gray values are depicted as colors on the scale accordingly.To quantify cortical F-actin intensity in living embryos, a ter line  was crost test with Welch’s correction for DfosDN and one way-ANOVA for cher RNAi and TM4SF RNAi.For quantification of Moe::3xmCherry intensity, an ROI was drawn in Fiji software around macrophages at the gb entry site in 20 z-stacks for each embryo. The area mean intensity was measured in all ROIs, and the average/embryo was calculated. To normalize fluorescence intensities per batch, the average intensity/embryo of all ROIs in each sample was divided by the arithmetic mean of the average intensity/embryo of all ROIs in the control per batch. The normalized average intensities/embryo were then compared to each other using a https://github.com/Axmasha/Image_analysis_scripts.Methanol-fixed St 11 embryos were mounted either after staining with GFP antibody (Dia::GFP) or without staining (DiaRBD::GFP) and imaged with a Zeiss Inverted LSM800, Plain-Apochromat 63X/1.4 Oil Objective at an XY-resolution of 0.1 μm and a Z-resolution of 1 μm . All macrophages within 40 μm of the gb were analyzed. For the quantification of the levels of DiaRBD or the complete Dia protein at the plasma membrane versus the cytoplasm, confocal images were processed using Fiji and MATLAB-R2017b (MathWorks). Individual focal planes were used to segment a profile corresponding to an 8-pixel wide line drawn across the single outer membrane of individual macrophages chosen such that the extracellular portion of the line extended into surrounding tissue or space and not another macrophage. The corresponding intensity profiles of the Myr::Tomato and Dia::GFP or DiaRBD::GFP channels were extracted in Fiji using a custom macro and analyzed further using a custom MATLAB script. The membrane region was defined by finding the maximal value in the Tomato intensity profile and centering a 0.8-μm interval around it. The background was calculated for each GFP profile as the mean intensity in the 2 μm outside the cell, flanking the membrane region, and substracted from the entire profile. The integrated Dia::GFP or DiaRBD::GFP intensity at the membrane was calculated within the 0.8-μm interval defined above. The integrated cytoplasmic Dia::GFP or DiaRBD::GFP level was calculated as the mean intensity of 2 μm of the GFP profile inside the cell flanking the membrane region. Image analysis scripts are publicly available at UAS-CLIP::GFP under the control of srpHemo-Gal4. Briefly, 3D-stacks with 1 μm Z resolution were acquired every 35 to 45 seconds for approximately 1 hour. As the strength of the GAL4 expression increased over time, laser power was adjusted during acquisition to reach the best possible quality of visualization. Images acquired from mutiphoton microscopy were initially processed with ImSpector software (LaVision Bio Tec) to compile channels from the imaging data.Laterally oriented embryos were used to measure the maximal length and width of macrophages expressing We started measuring from the time the cell body of the first macrophage fully appeared at the interface between the ectoderm and mesoderm and yolk sac until it had moved 30 μm along the ectoderm mesoderm interface. At each time frame, a line was drawn in Fiji along the longest dimension of the macrophage in the direction of its front-rear polarization axis, denoted the maximal cell length, and along the orthologonal longest dimension, which was considered maximal cell width. We did not observe long CLIP::GFP protrusions, but when a small protrusion was present, it was not included in the length measurement; within this gb region, the front of the first macrophage was clearly outlined with CLIP::GFP. The border between the first and second entering macrophages was drawn based on the uninterrupted intense line of CLIP::GFP at the base of the first macrophage; only cells with a clearly visible border were measured. The length-to-width ratio was quantified for each time frame, and a probability density function was plotted: 5 embryos were recorded for each genotype.srpHemo-Gal4 UAS-LifeAct::GFP were used to image macrophage actin live with a 3D-stack resolution of 1 μm. See above description of CLIP::GFP labeled macrophage imaging for laser power and image compilation. Laser power was also increased further in the DfosDN samples to enhance actin visualization. We measured the length of the filopodia-like protrusion of the first entering macrophage with Imaris software (Bitplane) from the time when the protrusion was inserted into the ectoderm, mesoderm, and yolk sac interface until the macrophage started to translocate its cell body into that location.Laterally oriented embryos expressing w; +; srpHemo-Gal4, srpHemo-3xmCherry/+ or w; +; srpHemo-Gal4, srpHemo-3xmCherry/ UAS-DfosDN genotypes were placed into plastic cages closed with apple juice plates with applied yeast to enhance egg laying. Collections were performed at 29°C for 1 hour, then kept at 29°C for additional 5 hours 15 minutes to reach stage 11 to early stage 12. Embryos were harvested for 2 days with 6 to 7 collections per day and stored meanwhile at +4°C to slow down development. Collected embryos were dissociated and the macrophages sorted as previously described [5 macrophages were sorted within 30 minutes.Adult flies of either escribed . About 15 macrophages. RNA sequencing was performed by the CSF facility of Vienna Biocenter according to standard procedures (https://www.vbcf.ac.at/facilities/next-generation-sequencing/) on 3 replicates. Briefly, the cDNA library was synthesized using QuantSeq 3′ mRNA-seq Library Prep kit and sequenced on the Illumina HiSeq 2500 platform. The reads were mapped to the Drosophila melanogaster Ensembl BDGP6 reference genome with STAR (version 2.5.1b). The read counts for each gene were detected using HTSeq (version 0.5.4p3). Flybase annotation (r6.19) was used in both mapping and read counting. Counts were normalized to arbitrary units using the TMM normalization from edgeR package in R. Prior to statistical testing, the data were voom transformed, and then the differential expression between the sample groups was calculated with limma package in R. The functional analyses were done using the topGO and gage packages in R [Total RNA was isolated from FACS-sorted macrophages using Qiagen RNeasy Mini kit (Cat No. 74104). The quality and concentration of RNA was determined using Agilent 6000 Pico kit (Cat No. 5067–1513) on an Agilent 2100 Bioanalyzer: on average about 100 ng of total RNA was extracted from 1.5 × 10ges in R ,109. RNARNA isolation and qPCR was performed from bones of wild-type C57BL/6 mice and from bones and OS of H2-c-fosLTR as previously described with the primers in p-value <0.05 was considered statistically significant .Mouse experiments: Data are shown as mean ± SEM. One-way ANOVA followed by Tukey multiple comparisons posttest was applied to compare experimental groups. Statistical analysis was performed using GraphPad Prism 6.0 software. A Drosophila experiments: Statistical tests as well as the number of embryos, cells, tracks, or contacts assessed are listed in the figure legends. All statistical analyses were performed using GraphPad PRISM or R Studio, and significance was determined using a 95% confidence interval. No statistical method was used to predetermine sample size.Dfos mutant analyses in Representative images of Dfos antibody staining were analyzed per replicate per genotype and in situ hybridization are from experiments that were repeated 2 times with many embryos with reproducible results. S1 TableComparison of TF mRNA expression in macrophages at stages 11–12 and 13–16, based on data in . TFs exp(TIF)Click here for additional data file.S2 TableGenes are ordered according to the adjusted p-value from the RNA sequencing. Function is based on Flybase assignments . The mur(TIF)Click here for additional data file.S1 Raw imagessrpHemo-moe::3xmCherry expressing either CD8::GFP (ctrl) or DfosDN in macrophages. Rightmost western blot also contains a w- lane. Top row shows blots probed with an mCherry antibody, bottom row the same blots probed with a profilin antibody as a loading control. Cropped versions of the blots are shown in Three original uncropped western blots of St 11 embryo extracts from (PDF)Click here for additional data file.S1 DataThis Excel file contains the raw data of the quantification of embryo macrophage counts and linescan analyses along with movie outputs. Each tab in the file names the figure panel whose graph is based on the data shown in that chart.(XLSX)Click here for additional data file.S2 DatasrpHemo-3xmCherry control embryos and those expressing DfosDN in macrophages. The mean from 3 samples is shown for each genotype, organized by Flybase IDs (Fbgn), along with statistical analyses.Compendium of the RNA sequencing data obtained from FACSed macrophages from Stages 11–12 (XLSB)Click here for additional data file.S1 Fig2Dfos mutant embryos compared to the control (p = 0.37) SD: 6, 7. (C) The total number of macrophages (see schematic at left) was not altered from that in the control embryos expressing DfosDN in macrophages (p = 0.12). SD: 60, 120.  The number of macrophages (green) along the vnc (outlined by black dotted line in the schematic on the left) shows no significant difference between the control and (D) macrophages that express DfosDN or (E) either of 2 RNAi lines against Dfos. (D) DfosDN p = 0.88, 0.99, >0.99. 1Dfos RNAi (TRiP HMS00254) p = 0.21, 0.06, 0.11, 0.072, 0.033, 0.30, 0.56. 2Dfos RNAi (TRiP JF02804) p = 0.34, 0.15, 0.83, 0.27, 0.47, 1.0, 0.45. (D) SD: Ctrl 3, 3, 3, 0.8; DfosDN 6, 3, 0.7. (E) SD: Ctrl 6, 3, 3, 3, 2, 0.3; 1Dfos RNAi 6, 3, 3, 3, 2, 2, 0.3; 2Dfos RNAi 6, 2, 3, 2, 3, 1, 0.4.  Macrophage numbers in the pre-gb (see schematic at left) are increased compared to the control for lines expressing (F) DfosDN or (G) one of 2 different UAS-Dfos RNAi constructs in macrophages under srpHemo-GAL4 control. (F) p = 0.04, SD: 19, 29. (G) 1Dfos RNAi p < 0.0009, 2Dfos RNAi p < 0.0001. SD: 12, 9, 14. (H) Macrophage numbers in the gb are not significantly altered compared to the control upon overexpression of Dfos in macrophages (p = 0.14). SD: 22, 14. (I) Macrophage numbers in the gb for lines expressing one of 2 different UAS-Dfos RNAi constructs in macrophages under srpHemo-GAL4 control and lines, which additionally express UAS-GFP. Control vs. 1mac>Dfos RNAi (TRiP HMS00254) or Control vs. 2mac>Dfos RNAi (TRiP JF02804), p < 0.0001. 1mac>Dfos RNAi vs. 1 + GFPmac>Dfos RNAi or 2mac>Dfos RNAi vs. 2 + GFPmac>Dfos RNAi, p > 0.99. SD: 33, 47, 34. The effect of each Dfos RNAi was eliminated upon simultaneous expression of another UAS construct. Macrophages are labeled using either srpHemo-Gal4 driving UAS-GFP or srpHemo-H2A::3xmCherry. “mac>” indicates srpHemo-GAL4 driver expressing UAS constructs specifically in macrophages. Histograms show mean ± SEM ***p < 0.005, **p < 0.01, *p < 0.05. Unpaired t test was used for statistics, except for G, I, which used one-way ANOVA. The number of embryos analyzed for that genotype is shown within each column in the graphs. In D, n = 6 embryos for the control and n = 9 for Dfos DN. In E, n = 9 embryos for control, 15 and 11 for Dfos RNAis. Scale bar in A: 10 μm. The data underlying the graphs can be found in (A) Dfos protein (green) is detected with an antibody in macrophages (magenta) in embryos from the stages as indicated. (B-I) Quantification in mid St 12 embryos. (B) The number of macrophages (green) in the pre-gb zone (outlined by a black dotted line in the schematic on the left) showed no significant change in (TIF)Click here for additional data file.S2 Fig2Dfos macrophages entering the gb (outlined by the dashed line). Time in minutes shown in the top right corner of each image. (C) Quantification of macrophage speed shows a significant reduction in the speed of 2Dfos macrophages in the pre-gb zone and at gb entry, but none in the head. Regions analyzed indicated in left schematic. Speed in head: control = 2.59 μm/min, 2Dfos = 2.68 μm/min, p = 0.40; speed in pre-gb = 3.38 μm/min, 2Dfos = 2.47 μm/min, p = 2.38e-06; speed in gb entry: control = 2.35 μm/min, 2Dfos = 1.62 μm/min, p = 0.0003. Macrophages are labeled using srpHemo-H2A::3xmCherry. Histograms show mean ± SEM. ****p < 0.0001, ***p < 0.005, **p < 0.01, *p < 0.05. Unpaired t test was used for statistics. The number of analyzed macrophages for each genotype shown within each graph column. Tracks were obtained from movies of 3 embryos each for control and mac>DfosDN for pre-gb entry in A, 4 each for gb entry in A, 3 each for the vnc in A, 4 each of control and 4 2Dfos embryos for head and pre-gb in C, and 3 embryos each for gb entry in C. Scale bars: 10 μm. The data underlying the graphs can be found in (A) Quantification reveals that the directional persistence of macrophages expressing DfosDN (0.58) is unchanged (0.56) in the pre-gb area (p = 0.66) but decreased during gb entry (0.65) (0.72), p = 0.038 and along the vnc (0.54) compared to the control (0.61), p = 0.00026. Left schematic shows pre-gb area in yellow, gb entry outlined in solid line. Boxed area in right schematic shows analyzed area of vnc. (B) Movie stills showing wild-type and (TIF)Click here for additional data file.S3 FigDhc36C 0.02, CG14204 0.03, CG42402 0.04, CR43767 0.046, TM4SF 0.03, CG42260 0.0011, cher 0.046, GstT4 0.018, Xrp1 0.0011, Tspo 0.046, CG31337 0.046. Frl, DAAM, dia, capu all >0.99.  Quantification of the macrophage numbers in (D) the pre-gb zone and (E) along the vnc from embryos expressing RNAi against cher (KK 107451), or TM4SF in macrophages (KK 102206) driven by srpHemo-Gal4 shows no significant alteration. The number in the column in (D) corresponds to the number of embryos analyzed. Control vs. cher RNAi p = 0.33. Control vs. TM4SF RNAi p = 0.05. Control vs. cher/TM4SF RNAi p = 0.67. (D) SD: 20, 20, 19, 13. For (E), n = 13 embryos for control and n = 15 for each cher RNAi and TM4SF RNAi. Control vs. cher RNAi p = 0.97 for T1, p = 0.33 for T2, p = 0.88 for T3. Control vs. TM4SF RNAi p = 0.52 for T1, p = 0.76 for T2, p = 0.35 for T3. SD: ctrl 6.5, 5.4, 0.6; cher RNAi 5.0, 3.3, 0.8; TM4SF RNAi 4.4, 4.9, 1.9. (F-I) q-PCR analysis of mRNA extracted from the bones of mice that are wild type, tg for MHC c-fos, viral 3′ UTR, and those in which c-fos transgenesis has led to an OS. Analysis of mRNA expression shows that (F) higher Fos levels in OS correlate with higher levels of (G) the glutathione S transferase Gstt3, and (H) the slit receptor Eva1c, but not (I) Tspo. Bone and OS RNA isolated from the same transgenic mouse, n = 4 mice per group, age 5 to 6 months. p-values = 0.86, 0.0028, 0.0013 in (F), 0.79, 0.0001, 0.0003 in (G), 1.0, 0.054, 0.049 in (H), 0.37, 0.33, 0.040 in (I). SD: 0.7, 0.6, 2.6 in (F); 0.2, 0.3, 1.1 in (G); 0.4, 0.2, 1.5 in (H); 0.1, 0.2, 0.2 in (I). Histograms show mean ± SEM ***p < 0.005, **p < 0.01, *p < 0.05. Unpaired t test or one-way ANOVA with Tukey post hoc were used for statistics of quantifications. Significance is based on adjusted p-values. The data underlying the graphs can be found in (A-C) Comparative mRNA expression levels as determined from RNA sequencing analysis of FACS-sorted wild-type macrophages and those expressing DfosDN, n = 3 biological replicates.  Genes down-regulated in macrophages expressing DfosDN are shown, separated into those with (A) strong and (B) moderate expression in wild-type macrophages. (C) Expression levels of Drosophila formin family genes are unchanged. Fold enrichment is normalized. p-values: (TIF)Click here for additional data file.S4 FigsrpHemo-moe::3xmCherry expressing either CD8::GFP (ctrl) or DfosDN in macrophages. Left western blot also contains w- lane. Original uncropped western blots can be found in 1Dfos or 2Dfos embryos completely rescued the macrophage gb invasion defect. p-values: Control vs. 1Dfos or vs. 2Dfos p = 0.0004 or p = 0.0055, respectively; Control vs. 1 mac>DiaCADfos or vs. 2 mac>DiaCADfos p > 0.999; 1Dfos vs. 1 mac>DiaCADfos p = 0.0005; 2Dfos vs. 2 mac>DiaCADfos p = 0.035. SD: 20, 23, 18, 19, 7.8.  There was no significant change in the number of macrophages in (C) the pre-gb zone or (D) along the vnc in embryos expressing either of 2 different RNAi lines against dia expressed in macrophages. Pre-gb: Control vs. 1dia RNAi p = 0.54, Control vs. 2dia RNAi p = 0.77. vnc: Control vs. 1dia RNAi p = 0.99, Control vs. 2dia RNAi p = 0.95. RNAi1 = TRiP HMS05027, RNAi2 = TRiP HMS00308. (C) SD: 9, 12, 13. (D) SD: Ctrl 5.2, 6.4, 2.5, 0.4; 1dia RNAi 5.6, 6.8, 1.7, 0.2; 2dia RNAi 5.1, 4.9, 2.1, 0.6.  Two further examples of line profiles used for the determination of the membrane-to-cytoplasmic ratios in cher RNAi, or TM4SF RNAi as shown in the schematic in E. Line length approximately 8 μm. Blue lines indicate mean GFP intensity on the membrane and in cytoplasm. Histograms show mean ± SEM ***p < 0.005, **p < 0.01, *p <0.05. One-way ANOVA with Tukey post hoc was used for statistics of quantification. The number in each column corresponds to the number of analyzed embryos. “mac>” indicates srpHemo-GAL4 driver expressing UAS constructs in macrophages. Macrophages are labeled using srpHemo-H2A::3xmCherry. The data underlying the graphs can be found in (A) Three western blots probed with an mCherry antibody of St 11 embryo extracts from (TIF)Click here for additional data file.S5 FigsrpHemo-Gal4 (“mac>”) driving UAS-LifeActGFP. White stars indicate the tip of each actin protrusion. Scale bar 5 μm. (B) Microtubules are labeled with srpHemo-Gal4 driving UAS-CLIP::GFP. Spatially matched stills of the first macrophage expressing DfosDN and control extending protrusions into the gb slightly before entering with the body of the cell. As DfosDN macrophages have a delay in entry, the stills from the DfosDN movie are from a later developmental time point than the control. (C) Quantification of macrophage maximum length and maximum width shows that DfosDN expressing macrophages are 23% longer and 12% thinner than wild-type macrophages inside the gb (indicated in schematic above by dashed box). Control vs. DfosDN maximum length p = 0.0005, SD: 3.4, 5.7; control vs. DfosDN maximum width p = 0.0025, SD: 1.3, 1.0. (D) Quantification of the maximum length and maximum width of macrophages in the pre-gb zone (indicated in schematic by dashed box) shows that macrophages expressing DfosDN are 9% shorter and 9% thinner than wild-type macrophages. Control vs. DfosDN maximum length p = 0.0095, SD: 2.2, 2.0; control vs. DfosDN maximum width p = 0.005, SD: 2.3, 1.9. (E) Overexpression of UAS-Lam in macrophages through srpHemo-Gal4 (mac>) causes no change in their number in the gb compared to the control. p = 0.65, SD: 15, 18. Histograms show mean ± SEM ***p < 0.005, **p < 0.01, *p < 0.05. Unpaired t test was used for statistics of quantification. The number of measurements per genotype is shown in each columns. The data underlying the graphs can be found in (A) Representative image showing actin protrusions of the first macrophage entering the gb in the control and in lines expressing DfosDN in macrophages. Actin was visualized by (TIF)Click here for additional data file.S6 FigProposed interactions of proteins at the cell cortex in wild-type macrophages during gb infiltration as shown in (TIF)Click here for additional data file.S1 MoviesrpHemo-H2A::3xmCherry are imaged while entering the gb in control embryos (left) and embryos in which macrophages express DfosDN (right). Time in minutes is indicated in the upper right corner. Scale bar: 10 μm. DfosDN, dominant negative version of Dfos; DN, dominant negative; gb, germband.Movies corresponding to stills shown in (AVI)Click here for additional data file.S2 MoviesrpHemo-Gal4 driving UAS-GFP::nls are imaged during their migration along the segments of the vnc in control embryos (left) and embryos in which DfosDN is expressed in macrophages (right). Time in minutes is indicated in the upper right corner. Scale bar: 10 μm. DfosDN, dominant negative version of Dfos; vnc, ventral nerve cord.Movies corresponding to stills shown in (AVI)Click here for additional data file.S3 MoviesrpHemo-Gal4 driving UAS-GFP::nls are imaged while entering the gb in control embryos (left) and 2Dfos mutant embryos (right). Time is indicated in minutes. Scale bar: 10 μm. gb, germband.Movies corresponding to stills shown in (AVI)Click here for additional data file.S4 MoviesrpHemo-Gal4 driving UAS-LifeAct::GFP is imaged during gb entry in control embryos (left) and embryos with macrophages expressing DfosDN (right). Note the extended protrusion of the DfosDN expressing macrophages. Time is indicated in minutes. Scale bar: 10 μm. DfosDN, dominant negative version of Dfos; gb, germband.Movies corresponding to stills shown in (AVI)Click here for additional data file.S5 MoviesrpHemo-Gal4 driving UAS-CLIP::GFP. They are imaged during gb entry in control embryos (left) and embryos with macrophages expressing DfosDN (right). Note the extended shape of the DfosDN expressing macrophages. Time is indicated in minutes. Scale bar: 10 μm. DfosDN, dominant negative version of Dfos; gb, germband.Movies corresponding to stills shown in (AVI)Click here for additional data file.