Yoshiaki Kariya

RANKL subcellular trafficking and regulatory mechanisms in osteocytes

The receptor activator of the NF‐κB ligand (RANKL) is the central player in the regulation of osteoclastogenesis, and the quantity of RANKL presented to osteoclast precursors is an important factor determining the magnitude of osteoclast formation. Because osteoblastic cells are thought to be a major source of RANKL, the regulatory mechanisms of RANKL subcellular trafficking have been studied in osteoblastic cells. However, recent reports showed that osteocytes are a major source of RANKL presentation to osteoclast precursors, prompting a need to reinvestigate RANKL subcellular trafficking in osteocytes. Investigation of molecular mechanisms in detail needs well‐designed in vitro experimental systems. Thus, we developed a novel co‐culture system of osteoclast precursors and osteocytes embedded in collagen gel. Experiments using this model revealed that osteocytic RANKL is provided as a membrane‐bound form to osteoclast precursors through osteocyte dendritic processes and that the contribution of soluble RANKL to the osteoclastogenesis supported by osteocytes is minor. Moreover, the regulation of RANKL subcellular trafficking, such as OPG‐mediated transport of newly synthesized RANKL molecules to lysosomal storage compartments, and the release of RANKL to the cell surface upon stimulation with RANK are confirmed to be functional in osteocytes. These results provide a novel understanding of the regulation of osteoclastogenesis.

LXR Alpha Transactivates Mouse Organic Solute Transporter Alpha and Beta via IR-1 Elements Shared with FXR

PurposeRecently identified organic solute transporter (Ost) α and β are located on the basolateral membrane of enterocytes and may be responsible for the intestinal absorption of many substrates including bile acids. In the present study, the mechanism governing the transcriptional regulation of their expression was investigated.Methods and ResultsTo clarify the transcriptional regulation of Osts, reporter gene assays were performed using mouse Ostα/β promoter-luciferase reporter constructs. Co-transfection of the constructs with farnesoid X receptor (FXR) and retinoid X receptor α (RXRα) or liver X receptor α (LXRα) and RXRα into Caco-2 cells induced the transcriptional activities of both Ost α and β and further increases were observed following treatment with each agonist. Sequence analyses indicated the presence of IR-1 regions in Ostα and Ostβ promoters, which was confirmed by the finding that the deletion of IR-1 sequences abolished the response to FXR and LXRα. Furthermore, mutations in IR-1 reduced the FXR- and LXRα-dependent transactivation of Ostα/β. Together with the detection of direct binding of FXR/RXRα and LXRα/RXRα to the IR-1 elements, the presence of functional FXRE/LXRE was revealed in the promoter region of both Ostα and Ostβ. In addition, the stimulatory effect of FXR/RXRα and LXRα/RXRα on Ostα, but not on Ostβ, was further enhanced by HNF-4α.ConclusionsIt was concluded that LXRα/RXRα transcriptionally regulate mouse Ostα/β via IR-1 elements shared with FXR/RXRα. Exposure to FXR/LXRα modulators may affect the disposition of Ostα/β substrates.

Function of OPG as a traffic regulator for RANKL is crucial for controlled osteoclastogenesis

The amount of the receptor activator of NF‐κB ligand (RANKL) on the osteoblastic cell surface is considered to determine the magnitude of the signal input to osteoclast precursors and the degree of osteoclastogenesis. Previously, we have shown that RANKL is localized predominantly in lysosomal organelles, but little is found on the osteoblastic cell surface, and consequently, the regulated subcellular trafficking of RANKL in osteoblastic cells is important for controlled osteoclastogenesis. Here we have examined the involvement of osteoprotegerin (OPG), which is currently recognized as a decoy receptor for RANKL, in the regulation of RANKL behavior. It was suggested that OPG already makes a complex with RANKL in the Golgi apparatus and that the complex formation is necessary for RANKL sorting to the secretory lysosomes. It was also shown that each structural domain of OPG is indispensable for exerting OPG function as a traffic regulator. In particular, the latter domains of OPG, whose physiologic functions have been unclear, were indicated to sort RANKL molecules to lysosomes from the Golgi apparatus. In addition, the overexpression of RANK‐OPG chimeric protein, which retained OPG function as a decoy receptor but lost the function as a traffic regulator, inhibited endogenous OPG function as a traffic regulator selectively in osteoblastic cells and resulted in the upregulation of osteoclastogenic ability despite the increased number of decoy receptor molecules. Conclusively, OPG function as a traffic regulator for RANKL is crucial for regulating osteoclastogenesis at least as well as that as a decoy receptor.

Regulatory Mechanisms of RANKL Presentation to Osteoclast Precursors

It is important to understand the molecular mechanisms regulating osteoclast formation, as excess activation of osteoclasts is associated with various osteopenic disorders. Receptor activator of nuclear factor kappa B (RANKL) is a central player in osteoclastogenesis. Recent findings suggest that osteocytes are the major supplier of RANKL to osteoclast precursors. It has also been suggested that osteocyte cell death upregulates the RANKL/osteoprotegerin (OPG) ratio in viable osteocytes adjacent to apoptotic osteocytes in areas of bone microdamage, thus, contributing to localized osteoclast formation. Indeed, viable osteocytes can provide RANKL through direct interactions with osteoclast precursors at osteocyte dendritic processes. In addition, OPG tightly regulates RANKL cell surface presentation in osteocytes, which contributes to the inhibition of RANKL signaling, as well as the decoy receptor function of OPG. By contrast, the physiological role of RANKL in osteoblasts is yet to be clarified, although similar mechanisms of regulation are observed in both osteocytes and osteoblasts.

Rab27a and Rab27b are involved in stimulation-dependent RANKL release from secretory lysosomes in osteoblastic cells.

The quantity of the receptor activator of NF‐κB ligand (RANKL) expressed at the cell surface of osteoblastic cells is an important factor regulating osteoclast activation. Previously, RANKL was found to be localized to secretory lysosomes in osteoblastic cells and to translocate to the cell surface in response to stimulation with RANK‐Fc‐conjugated beads. However, the in vivo significance of stimulation‐dependent RANKL release has not been elucidated. In this study we show that small GTPases Rab27a and Rab27b are involved in the stimulation‐dependent RANKL release pathway in osteoblastic cells. Suppression of either Rab27a or Rab27b resulted in a marked reduction in RANKL release after stimulation. Slp4‐a, Slp5, and Munc13‐4 acted as effector molecules that coordinated Rab27a/b activity in this pathway. Suppression of Rab27a/b or these effector molecules did not inhibit accumulation of RANKL in lysosomal vesicles around the stimulated sites but did inhibit the fusion of these vesicles to the plasma membrane. In osteoblastic cells, suppression of the effector molecules resulted in reduced osteoclastogenic ability. Furthermore, Jinx mice, which lack a functional Munc13‐4 gene, exhibited a phenotype characterized by increased bone volume near the tibial metaphysis caused by low bone resorptive activity. In conclusion, stimulation‐dependent RANKL release is mediated by Rab27a/b and their effector molecules, and this mechanism may be important for osteoclast activation in vivo.

Vps33a Mediates RANKL Storage in Secretory Lysosomes in Osteoblastic Cells

Previous studies have indicated that the amount of RANKL expressed on the cell surface of osteoblasts or bone marrow stromal cells (BMSCs) is considered an important factor determining the extent of osteoclast activation. However, subcellular trafficking of RANKL and its regulatory mechanisms in osteoblastic cells is still unclear. In this study, we showed that RANKL is predominantly localized in lysosomal organelles, but little is found on the cell surface of osteoblastic cells. We also showed that RANKL is relocated to the plasma membrane in response to stimulation with RANK‐Fc–coated beads, indicating that the lysosomal organelles where RANKL is localized function as secretory lysosomes. In addition, using a protein pull‐down method, we identified vacuolar protein sorting (Vps)33a as interacting with the cytoplasmic tail of RANKL. Furthermore, knockdown of Vps33a expression reduced the lysosomal storage of RANKL and caused the accumulation of newly synthesized RANKL in the Golgi apparatus, indicating that Vps33a is involved in transporting RANKL from the Golgi apparatus to secretory lysosomes. We also showed that suppression of Vps33a affects the cell surface expression level of RANKL and disrupts the regulated behavior of RANKL. These results suggest that RANKL storage in secretory lysosomes is important to control osteoclast activation and to maintain bone homeostasis.

Systems‐based understanding of pharmacological responses with combinations of multidisciplinary methodologies

The importance of systems-based pharmacological approaches to drug discovery and development has increasingly been recognized. This reviews summarizes recent advances in the development of systems pharmacology and introduces the methods used for analysis. To understand the cellular response at the molecular level, pathway maps must be prepared to show how the function of the constituent molecules within cells are linked and integrated to form molecular networks. First, the methods used to prepare these pathway maps, such as databases, knowledge bases and software platforms, are introduced. Then the mathematical theories used to analyse the behavior of molecular networks are summarized. To quantitatively predict cellular responses, simulations are performed that are based on the rate equations for each reaction within the pathway map. If the number of reactions described in the pathway map is small, and if the parameter values for the rate constants are available, it is possible accurately to simulate the behavior of the molecular networks. However, to analyse complex maps, mathematical abstraction is required. Such abstraction methods are important to integrate cellular responses and to understand tissue/organ and in vivo pharmacological/toxicological responses. The scope and limitations of the methods are also discussed.

Elucidation of the molecular mechanisms underlying adverse reactions associated with a kinase inhibitor using systems toxicology

Background/Objectives:Targeted kinase inhibitors are an important class of agents in anticancer therapeutics, but their limited tolerability hampers their clinical performance. Identification of the molecular mechanisms underlying the development of adverse reactions will be helpful in establishing a rational method for the management of clinically adverse reactions. Here, we selected sunitinib as a model and demonstrated that the molecular mechanisms underlying the adverse reactions associated with kinase inhibitors can efficiently be identified using a systems toxicological approach.Methods:First, toxicological target candidates were short-listed by comparing the human kinase occupancy profiles of sunitinib and sorafenib, and the molecular mechanisms underlying adverse reactions were predicted by sequential simulations using publicly available mathematical models. Next, to evaluate the probability of these predictions, a clinical observation study was conducted in six patients treated with sunitinib. Finally, mouse experiments were performed for detailed confirmation of the hypothesized molecular mechanisms and to evaluate the efficacy of a proposed countermeasure against adverse reactions to sunitinib.Results:In silico simulations indicated the possibility that sunitinib-mediated off-target inhibition of phosphorylase kinase leads to the generation of oxidative stress in various tissues. Clinical observations of patients and mouse experiments confirmed the validity of this prediction. The simulation further suggested that concomitant use of an antioxidant may prevent sunitinib-mediated adverse reactions, which was confirmed in mouse experiments.Conclusions:A systems toxicological approach successfully predicted the molecular mechanisms underlying clinically adverse reactions associated with sunitinib and was used to plan a rational method for the management of these adverse reactions.

Systems Pharmacology of Tyrosine Kinase Inhibitor-Associated Toxicities

Tyrosine kinase inhibitors (TKIs) are designed to exhibit marked efficacy against cancer progression, based on accumulated molecular knowledge. The administration of TKIs is associated with much lower general toxicities (such as pancytopenia and gastrointestinal tract disturbance) than the administration of classical cytotoxic anti-tumor agents. However, TKIs provoke certain adverse reactions, which cannot be explained by the molecular mechanisms known at the time of drug development. Unfortunately, these unfavorable events often force the discontinuation of TKI treatment, with a typical worsening of therapeutic outcomes. Therefore, elucidating the molecular mechanisms behind TKI-related adverse reactions is a critical task in current and future chemotherapeutic drug management. Here, we provide a concrete mechanistic investigation of the adverse reactions of erlotinib, a TKI prototype, using a systems pharmacology-based approach. The molecular mechanism of erlotinib remains largely unknown, probably because there has been no unbiased drug analysis or account taken of the information available in numerous archives. In this study, we separated the mechanism of skin inflammation, a prominent erlotinib-mediated adverse reaction, into multiple pharmacokinetic/pharmacodynamic layers constituting drug responses. Importantly, an examination of the candidate mechanisms associated with each layer effectively extracted mechanisms from a myriad of contenders, enabling the design of polished “wet” experiments for further confirmation. This strategy is conceptually applicable to drugs other than erlotinib, and might facilitate the mechanistic exploration of the adverse reactions of cancer drugs in general.