Optimization of treatment strategy

The purpose of this study was to predict the survival time of patients with malignant glioma after radiotherapy with high accuracy by considering additional clinical factors and optimize the prescription dose and treatment duration for individual patient by using a machine learning model. A total of 35 patients with malignant glioma were included in this study. The candidate features included 12 clinical features and 192 dose–volume histogram (DVH) features. The appropriate input features and parameters of the support vector machine (SVM) were selected using the genetic algorithm based on Akaike’s information criterion, i.e. clinical, DVH, and both clinical and DVH features. The prediction accuracy of the SVM models was evaluated through a leave-one-out cross-validation test with residual error, which was defined as the absolute difference between the actual and predicted survival times after radiotherapy. Moreover, the influences of various values of prescription dose and treatment duration on the predicted survival time were evaluated. The prediction accuracy was significantly improved with the combined use of clinical and DVH features compared with the separate use of both features (P < 0.01, Wilcoxon signed rank test). Mean ± standard deviation of the leave-one-out cross-validation using the combined clinical and DVH features, only clinical features and only DVH features were 104.7 ± 96.5, 144.2 ± 126.1 and 204.5 ± 186.0 days, respectively. The prediction accuracy could be improved with the combination of clinical and DVH features, and our results show the potential to optimize the treatment strategy for individual patients based on a machine learning model

1,1′-Di-tert-butyl-2,2′,3,3′,4,4′,5,5′-octa­ethyl-1,1′-bis­tannole

The title compound, [Sn2(C4H9)2(C12H20)2], has two 1-stannacyclo­penta­diene skeletons related by inversion symmetry located at the mid-point of the Sn—Sn bond [2.7682 (2) Å]. Thus, the asymmetric unit comprises one half-mol­ecule. The planarity of the stannacyclo­penta­diene ring is illustrated by the dihedral angle of 0.3 (1)°, defined by the C4 and C—Sn—C planes. To avoid steric repulsion, the two stannole rings are oriented in an anti fashion through the Sn—Sn bond. These structural features are similar to those of other bis­tannoles

Tertiary Lymphoid Tissues Are Microenvironments with Intensive Interactions between Immune Cells and Proinflammatory Parenchymal Cells in Aged Kidneys

三次リンパ組織による腎障害メカニズムの解明: 慢性腎臓病の新たな治療標的候補を同定. 京都大学プレスリリース. 2023-08-08.[Significance Statement] Ectopic lymphoid structures called tertiary lymphoid tissues (TLTs) develop in several kidney diseases and are associated with poor renal prognosis. However, the mechanisms underlying TLT expansion and their effect on renal regeneration remain unclear. The authors report that single-nucleus RNA sequencing and validation experiments demonstrate that TLTs potentially amplify inflammation in aged injured kidneys. Lymphocytes within TLTs promote proinflammatory phenotypes of the surrounding proximal tubules and fibroblasts within the TLTs via proinflammatory cytokine production. These proinflammatory parenchymal cells then interact with immune cells by chemokine or cytokine production. Such cell-cell interactions potentially increase inflammation, expand TLTs, and exacerbate kidney injury. These findings help illuminate renal TLT pathology and suggest potential therapeutic targets. [Background] Ectopic lymphoid structures called tertiary lymphoid tissues (TLTs) develop in several kidney diseases and are associated with poor renal prognosis. However, the mechanisms that expand TLTs and underlie exacerbation of kidney injury remain unclear. [Methods] We performed single-nucleus RNA sequencing (snRNA-seq) on aged mouse kidneys with TLTs after ischemia-reperfusion injury. The results were validated using immunostaining, in situ hybridization of murine and human kidneys, and in vitro experiments. [Results] Using snRNA-seq, we identified proinflammatory and profibrotic Vcam1⁺ injured proximal tubules (PTs) with NFκB and IFN-inducible transcription factor activation. VCAM1⁺ PTs were preferentially localized around TLTs and drove inflammation and fibrosis via the production of multiple chemokines or cytokines. Lymphocytes within TLTs expressed Tnf and Ifng at high levels, which synergistically upregulated VCAM1 and chemokine expression in cultured PT cells. In addition, snRNA-seq also identified proinflammatory and profibrotic fibroblasts, which resided within and outside TLTs, respectively. Proinflammatory fibroblasts exhibited STAT1 activation and various chemokine or cytokine production, including CXCL9/CXCL10 and B cell–activating factor, contributing to lymphocyte recruitment and survival. IFNγ upregulated the expression of these molecules in cultured fibroblasts in a STAT1-dependent manner, indicating potential bidirectional interactions between IFNγ-producing CXCR3⁺ T cells and proinflammatory fibroblasts within TLTs. The cellular and molecular components described in this study were confirmed in human kidneys with TLTs. [Conclusions] These findings suggest that TLTs potentially amplify inflammation by providing a microenvironment that allows intense interactions between renal parenchymal and immune cells. These interactions may serve as novel therapeutic targets in kidney diseases involving TLT formation

Evaluation of the Pichia pastoris expression system for the production of GPCRs for structural analysis

<p>Abstract</p> <p>Background</p> <p>Various protein expression systems, such as <it>Escherichia coli </it>(<it>E. coli</it>), <it>Saccharomyces cerevisiae </it>(<it>S. cerevisiae</it>), <it>Pichia pastoris </it>(<it>P. pastoris</it>), insect cells and mammalian cell lines, have been developed for the synthesis of G protein-coupled receptors (GPCRs) for structural studies. Recently, the crystal structures of four recombinant human GPCRs, namely β₂adrenergic receptor, adenosine A_2areceptor, CXCR4 and dopamine D3 receptor, were successfully determined using an insect cell expression system. GPCRs expressed in insect cells are believed to undergo mammalian-like posttranscriptional modifications and have similar functional properties than in mammals. Crystal structures of GPCRs have not yet been solved using yeast expression systems. In the present study, <it>P. pastoris </it>and insect cell expression systems for the human muscarinic acetylcholine receptor M2 subtype (CHRM2) were developed and the quantity and quality of CHRM2 synthesized by both expression systems were compared for the application in structural studies.</p> <p>Results</p> <p>The ideal conditions for the expression of CHRM2 in <it>P. pastoris </it>were 60 hr at 20°C in a buffer of pH 7.0. The specific activity of the expressed CHRM2 was 28.9 pmol/mg of membrane protein as determined by binding assays using [³H]-quinuclidinyl benzilate (QNB). Although the specific activity of the protein produced by <it>P. pastoris </it>was lower than that of Sf9 insect cells, CHRM2 yield in <it>P. pastoris </it>was 2-fold higher than in Sf9 insect cells because <it>P. pastoris </it>was cultured at high cell density. The dissociation constant (Kd) for QNB in <it>P. pastoris </it>was 101.14 ± 15.07 pM, which was similar to that in Sf9 insect cells (86.23 ± 8.57 pM). There were no differences in the binding affinity of CHRM2 for QNB between <it>P. pastoris </it>and Sf9 insect cells.</p> <p>Conclusion</p> <p>Compared to insect cells, <it>P. pastoris </it>is easier to handle, can be grown at lower cost, and can be expressed quicker at a large scale. Yeast, <it>P. pastoris</it>, and insect cells are all effective expression systems for GPCRs. The results of the present study strongly suggested that protein expression in <it>P. pastoris </it>can be applied to the structural and biochemical studies of GPCRs.</p

JRAB shifts “dancing style” of cell clusters

In fundamental biological processes, cells often move in groups, a process termed collective cell migration. Collectively migrating cells are much better organized than a random assemblage of individual cells. Many molecules have been identified as factors involved in collective cell migration, and no one molecule is adequate to explain the whole picture. Here we show that JRAB/MICAL-L2, an effector protein of Rab13 GTPase, provides the “law and order” allowing myriad cells to behave as a single unit just by changing its conformation. First, we generated a structural model of JRAB/MICAL-L2 by a combination of bioinformatic and biochemical analyses and showed how JRAB/MICAL-L2 interacts with Rab13 and how its conformational change occurs. We combined cell biology, live imaging, computational biology, and biomechanics to show that impairment of conformational plasticity in JRAB/MICAL-L2 causes excessive rigidity and loss of directionality, leading to imbalance in cell group behavior. This multidisciplinary approach supports the concept that the conformational plasticity of a single molecule provides “law and order” in collective cell migration

Evolutionary histories of breast cancer and related clones

乳がん発生の進化の歴史を解明 --ゲノム解析による発がんメカニズムの探索--. 京都大学プレスリリース. 2023-07-28.Tracking the ol' mutation trail: Unraveling the long history of breast cancer formation. 京都大学プレスリリース. 2023-08-31.Recent studies have documented frequent evolution of clones carrying common cancer mutations in apparently normal tissues, which are implicated in cancer development1, 2, 3. However, our knowledge is still missing with regard to what additional driver events take place in what order, before one or more of these clones in normal tissues ultimately evolve to cancer. Here, using phylogenetic analyses of multiple microdissected samples from both cancer and non-cancer lesions, we show unique evolutionary histories of breast cancers harbouring der(1;16), a common driver alteration found in roughly 20% of breast cancers. The approximate timing of early evolutionary events was estimated from the mutation rate measured in normal epithelial cells. In der(1;16)(+) cancers, the derivative chromosome was acquired from early puberty to late adolescence, followed by the emergence of a common ancestor by the patient’s early 30s, from which both cancer and non-cancer clones evolved. Replacing the pre-existing mammary epithelium in the following years, these clones occupied a large area within the premenopausal breast tissues by the time of cancer diagnosis. Evolution of multiple independent cancer founders from the non-cancer ancestors was common, contributing to intratumour heterogeneity. The number of driver events did not correlate with histology, suggesting the role of local microenvironments and/or epigenetic driver events. A similar evolutionary pattern was also observed in another case evolving from an AKT1-mutated founder. Taken together, our findings provide new insight into how breast cancer evolves