Biology subjects

Konishi, H.

Publications and source records attributed to Konishi, H..

8 recordsLinked to original sources

bioRxiv2024

Targeting fatty acid synthase suppresses tumor development in NF2/CDKN2A-deficient malignant pleural mesothelioma

Malignant pleural mesothelioma (MPM) is an uncommon yet deadly cancer linked to asbestos exposure. The lack of effective early diagnosis and treatment leads to reduced life expectancy among patients with MPM. This study is aimed to identify a novel molecular target inhibitor to develop more effective therapeutics for MPM. Our drug screening assay showed that the fatty acid synthase (FASN) inhibitor cerulenin demonstrates strong and selective anti-proliferative properties against NF2/CDKN2A(p16)-deficient MPM cells, surpassing the effects of cisplatin or pemetrexed. FASN protein is frequently detected in NF2/p16-deficient MPM tumor-derived tissues (15/15, 100%), but rarely in NF2/p16-intact MPM tumors (8/25, 32%). Notably, cerulenin administration successfully reduced the growth of NF2/p16-deficient MPM tumors in xenografted mice. Cerulenin inhibits mitochondrial fission by targeting dynamin-related protein 1 (DRP1) in NF2/p16-deficient cells. Moreover, the disruption of the FASN gene leads to increased ubiquitination of DRP1. These findings suggest that FASN might play a role in the tumorigenesis of MPM cells through the regulation of mitochondrial dynamics. This research offers a novel perspective on the potential development of precision medicine for MPM.

cancer biology↗

bioRxiv2024

Discovery of anti-SARS-CoV-2 S2 protein antibody CV804 with broad-spectrum reactivity with various beta coronaviruses and analysis of its pharmacological properties in vitro and in vivo

SARS-CoV-2 pandemic alerts us that spillovers of various animal coronaviruses to human in the future may bring us enormous damages. Thus, there is a significant need of antibody-based drugs to treat patients infected with previously unseen coronaviruses.CV804 against the S2 domain of the spike protein, which is less prone to mutations. CV804 shows not only broad cross-reactivities with representative 20 animal-origin coronaviruses but also with diseases-associated human beta coronaviruses including SARS-CoV, MERS-CoV, HCoV-OC43, HCoV-HKU1 and mutant strains of SARS-CoV-2. Other than that, the main characteristics of CV804 are that it has strong antibody-dependent cellular cytotoxicity (ADCC) activity to SARS-CoV2 spike protein-expressed cells in vitro and completely lacks virus-neutralization activity. Comprehensively in animal models, CV804 suppressed disease progression by SARS-CoV-2 infection. Structural studies using HDX-MS and point mutations of recombinant spike proteins revealed that CV804 binds to a unique epitope within the highly conserved S2 domain of the spike proteins of various coronaviruses. Based on the overall data, we suggest that the non-neutralizing CV804 antibody recognizes the conformational structure of the spike protein expressed on the surface of the infected cells and weakens the viral virulence by supporting host immune cells attack through ADCC activity in vivo. CV804 epitope identified in this study is not only useful for the design of pan-corona antibody therapeutics but also to design next-generation coronavirus vaccines and antiviral drugs.

microbiology↗

bioRxiv2022

Molecular engineering of emicizumab to improve hemophilia A treatment

Emicizumab, a factor (F)VIIIa-function mimetic bispecific antibody (BsAb) to FIXa and FX, has become an indispensable treatment for people with hemophilia A (PwHA). Although emicizumab is very potent, long-term outcomes from the clinical studies suggest that a small proportion of PwHA still experiences bleeds. Additionally, non-clinical studies indicate that the maximum cofactor activity of emicizumab is lower than international standard activity (100 IU/dL of FVIII). An increased cofactor activity BsAb would benefit such patients. Here, we report NXT007, a BsAb binding FIXa and FX developed through further engineering of emicizumab. Emicizumab has a common light chain, but through advances in antibody engineering, we were able to create a more potent BsAb with two new non-common light chains. After extensive optimization of the heavy and light chains, the resulting BsAb, NXT007, exerted in vitro thrombin generation (TG) activity in hemophilia A plasma equivalent to 100 IU/dL of FVIII when triggered by tissue factor. NXT007 demonstrated potent hemostatic activity in an acquired hemophilia A model in non-human primates at a much lower dosage than emicizumab, consistent with an around 30-fold dose shift in the in vitro TG activity between NXT007 and emicizumab. Moreover, together with Fc engineering that enhanced FcRn binding and reduced in vivo clearance, we demonstrate that NXT007 could be effective at a much lower dosage with a longer dosing interval compared to emicizumab. These non-clinical results suggest that NXT007 could maintain a non-hemophilic range of coagulation potential in PwHA and provides a rationale for its clinical testing.

bioengineering↗

bioRxiv2022

LUZP1 regulates the constriction velocity of the contractile ring during cytokinesis

There has been a great deal of research on cell division and its mechanisms; however, its processes have not yet been entirely elucidated. To find novel proteins that regulate cell division, we performed the screening using siRNAs and/or the expression plasmid of the target genes and identified leucine zipper protein 1 (LUZP1). Recent studies have shown that LUZP1 interacts with various proteins and stabilizes the actin cytoskeleton; however, the function of LUZP1 in mitosis is not known. In this study, we found that LUZP1 colocalized with the chromosomal passenger complex (CPC) at the centromere in metaphase and at the central spindle in anaphase and that these LUZP1 localizations were regulated by CPC activity and kinesin family member 20A (KIF20A). Mass spectrometry analysis identified that LUZP1 interacted with death-associated protein kinase 3 (DAPK3), one regulator of the cleavage furrow ingression in cytokinesis. In addition, we found that LUZP1 also interacted with myosin light chain 9 (MYL9), a substrate of DAPK3, and comprehensively inhibited MYL9 phosphorylation by DAPK3. In line with a known role for MYL9 in the actin-myosin contraction, LUZP1 suppression accelerated the constriction velocity at the division plane in our timelapse analysis. Our study indicates that LUZP1 is a novel regulator for cytokinesis that regulates the constriction velocity of the contractile ring.

cell biology↗

bioRxiv2020

Deep Texture Representations as a Universal Encoder for Pan-cancer Histology

Cancer histological images contain rich biological and clinical information, but quantitative representation can be problematic and has prevented direct comparison and accumulation of large-scale datasets. Here we show that deep texture representations (DTRs) produced by a bilinear Convolutional Neural Network, express cancer morphology well in an unsupervised manner, and work as a universal encoder for cancer histology. DTRs are useful for content-based image retrieval, enabling quick retrieval of histologically similar images from optimally area selected datasets of 7,175 cases from The Cancer Genome Atlas. Via comprehensive comparison with driver and clinically actionable gene mutations, we have successfully predicted 309 combinations of genomic features and cancer types from hematoxylin and eosin-stained images at high accuracy (AUC > 0.70 and q < 0.02). With its mounting capabilities on accessible devices such as smartphones, DTR-based encoding for cancer histology has a potentially strong impact on global equalization for cancer diagnosis and targeted therapies.

cancer biology↗

bioRxiv2019

Tandem paired nicking promotes precise genome editing with scarce interference by p53

Targeted knock-in mediated by double-stranded DNA cleavage is accompanied by unwanted insertions and deletions (indels) at on-target and off-target sites. A nick-mediated approach scarcely generates indels but exhibits reduced efficiency of targeted knock-in. Here, we demonstrate that tandem paired nicking, a method for targeted knock-in involving two Cas9 nickases that create nicks at the homologous regions of the donor DNA and the genome in the same strand, scarcely creates indels at the edited genomic loci, while permitting the efficiency of targeted knock-in largely equivalent to that of the Cas9 nuclease-based approach. Tandem paired nicking seems to accomplish targeted knock-in via DNA recombination analogous to Hollidays model, and creates intended genetic changes in the genome without introducing additional nucleotide changes such as silent mutations. Targeted knock-in through tandem paired nicking neither triggers significant p53 activation nor occurs preferentially in p53-suppressed cells. These properties of tandem paired nicking demonstrate its utility in precision genome engineering.

molecular biology↗

bioRxiv2018

Luigi: Large-scale histopathological image retrieval system using deep texture representations

BackgroundAs a large number of digital histopathological images have been accumulated, there is a growing demand of content-based image retrieval (CBIR) in pathology for educational, diagnostic, or research purposes. However, no CBIR systems in digital pathology are publicly available.\n\nResultsWe developed a web application, the Luigi system, which retrieves similar histopathological images from various cancer cases. Using deep texture representations computed with a pre-trained convolutional neural network as an image feature in conjunction with an approximate nearest neighbor search method, the Luigi system provides fast and accurate results for any type of tissue or cell without the need for further training. In addition, users can easily submit query images of an appropriate scale into the Luigi system and view the retrieved results using our smartphone application. The cases stored in the Luigi database are obtained from The Cancer Genome Atlas with rich clinical, pathological, and molecular information. We tested the Luigi system by querying typical cancerous regions from four cancer types, and confirmed successful retrieval of relevant images.\n\nConclusionsThe Luigi system will help students, pathologists, and researchers easily retrieve histopathological images of various cancers similar to those of the query image.

pathology↗

bioRxiv2017

Capturing the Difference in Humoral Immunity between Normal and Tumor Environments from RNA Sequences of B-Cell Receptors Using Supervised Machine Learning

The recent success of immunotherapy in treating tumors has attracted increasing interest in research related to the adaptive immune system in the tumor microenvironment. Recent advances in next-generation sequencing technology enabled the sequencing of whole T-cell receptors (TCRs) and B-cell receptors (BCRs)/immunoglobulins (Igs) in the tumor microenvironment. Since BCRs/Igs in tumor tissues have high affinities for tumor-specific antigens, the patterns of their amino acid sequences and other sequence-independent features such as the number of somatic hypermutations (SHMs) may differ between the normal and tumor microenvironments. However, given the high diversity of BCRs/Igs and the rarity of recurrent sequences among individuals, it is far more difficult to capture such differences in BCR/Ig sequences than in TCR sequences. The aim of this study was to explore the possibility of discriminating BCRs/Igs in tumor and in normal tissues, by capturing these differences using supervised machine learning methods applied to RNA sequences of BCRs/Igs.\n\nRNA sequences of BCRs/Igs were obtained from matched normal and tumor specimens from 90 gastric cancer patients. BCR/Ig-features obtained in Rep-Seq were used to classify individual BCR/Ig sequences into normal or tumor classes. Different machine learning models using various features were constructed as well as gradient boosting machine (GBM) classifier combining these models. The results demonstrated that BCR/Ig sequences between normal and tumor microenvironments exhibit their differences. Next, by using a GBM trained to classify individual BCR/Ig sequences, we tried to classify sets of BCR/Ig sequences into normal or tumor classes. As a result, an area under the curve (AUC) value of 0.826 was achieved, suggesting that BCR/Ig repertoires have distinct sequence-level features in normal and tumor tissues.\n\nTo the best of our knowledge, this is the first study to show that BCR/Ig sequences derived from tumor and normal tissues have globally distinct patterns, and that these tissues can be effectively differentiated using BCR/Ig repertoires.

bioinformatics↗