Biology subjects

Sonoshita, M.

Publications and source records attributed to Sonoshita, M..

6 recordsLinked to original sources

bioRxiv2026

Co-targeting an AMPK--MAPK axis reprograms CAFs and suppresses PDAC

Pancreatic ductal adenocarcinoma (PDAC) is a fatal cancer characterized by limited therapeutic options and a highly treatment-resistant tumor microenvironment. Beyond tumor-intrinsic genetic alterations, growing evidence indicates that host-microbiome interactions influence cancer progression through microbial metabolites. However, how microbiome-derived metabolites influence oncogenic signaling in PDAC remains unclear. Here, integrated profiling revealed a consistent reduction of the microbial metabolite acetic acid in fecal samples from treatment-naive patients with PDAC and in a genetically defined Drosophila model recapitulating key PDAC driver alterations. Acetic acid activates AMP-activated protein kinase, and pharmacological activation of this pathway together with inhibition of mitogen-activated protein kinase signaling suppressed tumor growth in fly and mouse models. Combined pathway targeting restored AMPK activity and suppressed cancer-associated fibroblast activation. These findings identify a microbiome-associated metabolic vulnerability in PDAC and suggest that coordinated targeting of metabolic and oncogenic signaling may restrain tumor progression and improve therapeutic strategies.

cancer biology↗

bioRxiv2025

Alternative Anastrozole Target CYP4V2 Impairs Neurons in Preclinical Models of Inherited Tauopathy

Tauopathies, including Alzheimer disease, are neurodegenerative diseases characterized by the pathological aggregation of the microtubule-associated protein Tau (MAPT). This study explores the neuroprotective properties of anastrozole, a clinical Aromatase inhibitor, in both a Drosophila tauopathy model expressing human MAPTR406W and isogenic pairs of human induced pluripotent stem cell-derived cortical neurons expressing MAPT mutations. The Aromatase inhibitor anastrozole, initially identified in a Drosophila MAPTR406W drug screen, reduced oxidative stress and Tau phosphorylation in cultured cortical neurons. Its protective effects were not mediated by Aromatase activity or cholesterol metabolism: screening in Drosophila identified CYP4V2 as a potential off-target. Knockdown of CYP4V2 in MAPTR406W neurons recapitulated protection against oxidative stress-induced cell death. These findings position anastrozole and its offtarget CYP4V2 as novel therapeutic avenues for primary tauopathies and potentially Alzheimers disease and related dementias by reducing Tau phosphorylation and susceptibility to oxidative stress.

neuroscience↗

bioRxiv2024

Identifying simultaneous inhibition of riboflavin metabolism and MEK as a novel therapeutic strategy for pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) remains a formidable challenge with a survival rate of approximately 10%, largely due to the lack of diagnostic and therapeutic options. To identify novel therapeutic targets for PDAC, we previously developed a Drosophila melanogaster model, the 4-hit fly, which mimics the alterations in KRAS, TP53, CDKN2A, and SMAD4 genes observed in PDAC. Through whole-body genetic screening using the 4-hit model, we identified riboflavin (RF) metabolism as a novel potential therapeutic target for PDAC. Additionally, transcript levels of four out of five genes that are involved in RF metabolism were elevated in human PDAC compared to non-tumor tissues. Roseoflavin (RoF), an antimetabolite of RF, resulted in a variety range of metabolic changes, decreased mitochondrial respiratory chain activity, and suppressed proliferation in cultured PDAC cells. Furthermore, the combination of RoF with the MEK inhibitor drug trametinib significantly suppressed the growth of human PDAC xenografts compared to either treatment alone. These findings underscore that dual targeting of RF metabolism and MEK represents a novel therapeutic strategy for PDAC.

cancer biology↗

bioRxiv2024

Super homotypic targeting by exosome surface engineering

Homotypic targeting is the inherent ability of cells for preferential interaction with cells of similar or identical types, a phenomenon commonly seen in cell adhesion, tissue formation, and immune responses. Unfortunately, its full potential remains largely untapped. Here we introduce an approach to drastically boost the homotypic targeting capabilities of cells via exosomes (nanoscale extracellular vesicles secreted by cells). By engineering exosome surfaces with lanthanides, we amplify specific cell-exosome interactions by more than 25-fold, significantly accelerating the selective capture of exosomes by cells of the same lineage. This substantial enhancement in cellular homophilicity opens up an entirely new class of applications, two of which we showcase here with unprecedented performance: using cells to detect specific exosomes and using exosomes to detect specific cells. The concept of "super homotypic targeting" offers enormous potential to transform cancer diagnostics, immunotherapy, targeted drug delivery, tissue engineering, and vaccine development.

cell biology↗

bioRxiv2024

Flow zoometry of Drosophila

Drosophila serves as a highly valuable model organism across numerous fields including genetics, immunology, neuroscience, cancer biology, and developmental biology. Central to Drosophila-based biological research is the ability to perform comprehensive genetic or chemical screens. However, this research is often limited by its dependence on laborious manual handling and analysis, making it prone to human error and difficult to discern statistically significant or rare events amid the noise of individual variations resulting from genetic and environmental factors. In this article we present flow zoometry, a whole-animal equivalent of flow cytometry for large-scale, individual-level, high-content screening of Drosophila. Our flow zoometer automatically clears the tissues of Drosophila melanogaster, captures three-dimensional (3D) multi-color fluorescence tomograms of single flies with single-cell volumetric resolution at an unprecedented throughput of over 1,000 animals within 48 hours (24 hr for clearing; 24 hr for imaging), and performs AI-enhanced data-driven analysis - a task that would traditionally take months or years with manual techniques. To demonstrate its broad applications, we employed the flow zoometer in various laborious screening assays, including those in toxicology, genotyping, and tumor screening. Flow zoometry represents a pivotal evolution in high-throughput screening technology: previously from molecules to cells, now from cells to whole animals. This advancement serves as a foundational platform for "statistical spatial biology", to improve empirical precision and enable serendipitous discoveries across various fields of biology.

bioengineering↗

bioRxiv2018

Integrated in silico and Drosophila cancer model platform captures previously unappreciated chemicals perturbing a kinase network

Drosophila provides an inexpensive and quantitative platform for measuring whole animal drug response. A complementary approach is virtual screening, where chemical libraries can be efficiently screened against protein target(s). Here, we present a unique discovery platform integrating structure-based modeling with Drosophila biology and organic synthesis. We demonstrate this platform by developing chemicals targeting a Drosophila model of Medullary Thyroid Cancer (MTC) with disease-promoting kinase network activated by mutant dRetM955T. Structural models for kinases relevant to MTC were generated for virtually screening to identify initial hits that were dissimilar to known kinase inhibitors yet suppressed dRetM955T-induced oncogenicity. We then combined features from the hits and known inhibitors to create a hybrid molecule with improved dRetM955T phenotypic outcome. Our platform provides a framework to efficiently explore novel chemical spaces, develop compounds outside of the current inhibitor chemical space, and correct cancer-causing signaling networks to improve disease prognosis while minimizing whole body toxicity.\n\nAUTHOR SUMMARYEffective and safe treatment of multigenic diseases often involves drugs that modulate whole systems by interacting with multiple nodes in pathways and networks, i.e., polypharmacology. Polypharmacology is increasingly appreciated as a potential desirable property of kinase drugs; however, most known drugs that interact with multiple targets have been identified as such by chance, and most polypharmacological compounds are not chemically unique resembling to structures of known kinase inhibitors. The fruit fly Drosophila has been established as a robust screening platform that provides an inexpensive, rapid, and quantitative measure of whole animal drug response, complementing computational approaches. We present a chemical genetics approach that efficiently combines Drosophila with structural prediction and virtual screening, creating a unique discovery platform. We demonstrate the utility of our approach by developing useful small molecules targeting a kinase network in a Drosophila model of Medullary Thyroid Cancer (MTC) driven by the active mutant dRetM955T.

cancer biology↗