Lysophosphatidic acid stimulates the proliferation and motility of malignant pleural mesothelioma cells through lysophosphatidic acid receptors, LPA1 and LPA2

金沢大学がん研究所分子標的がん医療研究開発センターLysophosphatidic acid (LPA) is one of the simplest natural phospholipids. This phospholipid is recognized as an extracellular potent lipid mediator with diverse effects on various cells. Although LPA is shown to stimulate proliferation and motility via LPA receptors, LPA1 and LPA2, in several cancer cell lines, the role of LPA and LPA receptors for malignant pleural mesothelioma (MPM) has been unknown. MPM is an aggressive malignancy with a poor prognosis and the incidence is increasing and is expected to increase further for another 10-20 years worldwide. Therefore, the development of novel effective therapies is needed urgently. In this study, we investigated the effect of LPA on the proliferation and motility of MPM cells. We found that all 12 cell lines and four clinical samples of MPM expressed LPA1, and some of them expressed LPA2, LPA3, LPA4 and LPA5. LPA stimulated the proliferation and motility of MPM cells in a dose-dependent manner. Moreover, LPA-induced proliferation was inhibited by Ki16425, an inhibitor of LPA1, and small interfering RNA against LPA1, but not LPA2. Interestingly, LPA-induced motility was inhibited by small interfering RNA against LPA2, but not LPA1, unlike a number of previous reports. These results indicate that LPA is a critical factor on proliferation though LPA1, and on motility though LPA2 in MPM cells. Therefore, LPA and LPA receptors, LPA2 as well as LPA1, represent potential therapeutic targets for patients with MPM. © 2008 Japanese Cancer Association

Intensification therapy with anti-parathyroid hormone-related protein antibody plus zoledronic acid for bone metastases of small cell lung cancer cells in severe combined immunodeficient mice

金沢大学附属病院がん高度先進治療センターBone metastases occur in more than one-third of patients with advanced lung cancer and are difficult to treat. We showed previously the therapeutic effect of a third-generation bisphosphonate, minodronate, and antiparathyroid hormone-related protein (PTHrP) neutralizing antibody on bone metastases induced by the human small cell lung cancer cell line, SBC-5, in natural killer cell-depleted severe combined immunodeficient mice. The purpose of our current study was to examine the effect of the combination of PTHrP antibody and zoledronic acid, which has been approved to treat bone metastases, against bone metastases produced by SBC-5 cells expressing PTHrP. Treatment with PTHrP antibody and/or zoledronic acid did not affect the proliferation of SBC-5 cells in vitro. Repeated treatments with either PTHrP antibody or zoledronic acid inhibited the formation of osteolytic bone metastases of SBC-5 cells but had no effect on metastases to visceral organs. Importantly, combined treatment with PTHrP antibody and zoledronic acid further inhibited the formation of bone metastases. Histologic assays showed that, compared with either PTHrP antibody or zoledronic acid alone, their combination decreased the number of tumor-associated osteoclasts and increased the number of apoptotic tumor cells. These findings suggest that this novel dual-targeting therapy may be useful for controlling bone metastases in a subpopulation of small cell lung cancer patients. Copyright © 2009 American Association for Cancer Research.全文公開20100

Hematopoietic cell-derived IL-15 supports NK cell development in scattered and clustered localization within the bone marrow

骨髄のNK細胞の分化に造血細胞が産生するIL-15が必須である --2種類の局在を示すNK細胞の新規分化モデル--. 京都大学プレスリリース. 2023-09-20.Natural killer (NK) cells are innate immune cells critical for protective immune responses against infection and cancer. Although NK cells differentiate in the bone marrow (BM) in an interleukin-15 (IL-15)-dependent manner, the cellular source of IL-15 remains elusive. Using NK cell reporter mice, we show that NK cells are localized in the BM in scattered and clustered manners. NK cell clusters overlap with monocyte and dendritic cell accumulations, whereas scattered NK cells require CXCR4 signaling. Using cell-specific IL-15-deficient mice, we show that hematopoietic cells, but not stromal cells, support NK cell development in the BM through IL-15. In particular, IL-15 produced by monocytes and dendritic cells appears to contribute to NK cell development. These results demonstrate that hematopoietic cells are the IL-15 niche for NK cell development in the BM and that BM NK cells are present in scattered and clustered compartments by different mechanisms, suggesting their distinct functions in the immune response

A Deep Recurrent Neural Network with Iterative Optimization for Inverse Image Processing Applications

Many algorithms and methods have been proposed for inverse image processing applications, such as super-resolution, image de-noising, and image reconstruction, particularly with the recent surge of interest in machine learning and deep learning methods. As for Computed Tomography (CT) image reconstruction, the most recently proposed methods are limited to image domain processing, where deep learning is used to learn the mapping between a true image data set and a noisy image data set in the image domain. While deep learning-based methods can produce higher quality images than conventional model-based algorithms, these methods have a limitation. Deep learning-based methods used in the image domain are insufficient to compensate for lost information during a forward and backward projection in CT image reconstruction, especially with high noise. This dissertation proposes new iterative reconstruction algorithms implemented by the Recurrent Neural Network (RNN). The RNN is usually used to process sequential data, such as a stock price prediction or natural language processing. In this dissertation, we use the RNN to implement the iterative reconstruction (IR), where the RNN performs an iterative optimization for CT image reconstruction. Besides, we propose new RNN memory cells called Gated Momentum Unit (GMU) and Recurrent FISTA Unit (RFU) to keep the RNN cell preserve a long-term memory. The GMU and GFU are similar to the Long-Short Term Memory (LSTM) and the Gated Recurrent Unit (GMU), in which the RNN cells alleviate a banishing and an exploding gradient problem. The GMU and GFU have simpler network structures than the LSTM and the GRU, and they are particularly designed to accelerate the convergence of the training optimization process. We conducted a simulation study and a real CT image study to demonstrate that these proposed methods achieved the highest Peak Signal to Noise Ratio (PSNR) and Structure Similarity (SSIM). The GMU was evaluated in CT image reconstruction, and the GFU was evaluated in CT Metal Artifact Reduction (CT MAR). Also, we showed these algorithms converged faster than other well-known methods. Furthermore, in the fourth chapter of this dissertation, we discuss how vital image texture is in inverse image processing problems. Many methods have been proposed for these problems; however, the most popular methods, the convolutional neural network (CNN) based methods with a Mean Squared Error (MSE) are known to over-smooth images due to the nature of the MSE. The MSE-based methods minimize Euclidean distance for all pixels between a baseline image and a CNN-generated image and ignore the pixels\u27 spatial information, such as image texture. The chapter of this dissertation proposes a new method based on Wasserstein GAN (WGAN) for inverse problems. We showed that the WGAN-based method was effective in preserving image texture. It also used a maximum likelihood estimation (MLE) regularizer to preserve pixel fidelity. Maintaining image texture and pixel fidelity is an essential requirement in medical imaging. We used PSNR and SSIM to evaluate the proposed method quantitatively. We also conducted first-order and second-order statistical image texture analysis to assess image texture

Simple formula for the interspaces of periodic grating structures self-organized on metal surfaces by femtosecond laser ablation

Self-organized grating structures formed on Mo and Ti metal surfaces irradiated with femtosecond laser pulses at wavelengths of 800 and 400 nm are investigated by electron microscopy. We observe the formation of the self-organized grating structures on the metals irradiated with 400-nm laser pulses at low laser fluence in narrow fluence ranges. The interspaces of the grating structure depend on the wavelength and fluence of the laser. We find that the dependence of the grating interspaces on laser fluence can be explained by a simple formula for induction of a surface-plasma wave through the parametric decay of laser light