EMID2 is a novel biotherapeutic for aggressive cancers identified by in vivo screening

BACKGROUND

New drugs to tackle the next pathway or mutation fueling cancer are constantly proposed, but 97% of them are doomed to fail in clinical trials, largely because they are identified by cellular or in silico screens that cannot predict their in vivo effect.

METHODS

We screened an Adeno-Associated Vector secretome library (> 1000 clones) directly in vivo in a mouse model of cancer and validated the therapeutic effect of the first hit, EMID2, in both orthotopic and genetic models of lung and pancreatic cancer.

RESULTS

EMID2 overexpression inhibited both tumor growth and metastatic dissemination, consistent with prolonged survival of patients with high levels of EMID2 expression in the most aggressive human cancers. Mechanistically, EMID2 inhibited TGFβ maturation and activation of cancer-associated fibroblasts, resulting in more elastic ECM and reduced levels of YAP in the nuclei of cancer cells.

CONCLUSION

This is the first in vivo screening, precisely designed to identify proteins able to interfere with cancer cell invasiveness. EMID2 was selected as the most potent protein, in line with the emerging relevance of the tumor extracellular matrix in controlling cancer cell invasiveness and dissemination, which kills most of cancer patients.

A method for in vivo evaluation of α-glucosidase inhibition using Drosophila

The development of α-glucosidase inhibitors is essential for the prevention of type II diabetes. Previous research has investigated in vitro inhibition using isolated α-glucosidase, which may not accurately reflect physical processes. The method presented in this study aims to establish a rapid and inexpensive in vivo method to study the inhibition of α-glucosidase activity using Drosophila as a model organism. This method can be used to calculate the IC50 value of compounds of interest for inhibition of α-glucosidase activity. The method established in this study can be used for in vivo screening of anti-diabetic compounds. •A rapid and inexpensive in vivo method to study the inhibition of α-glucosidase activity.•This method can be used to calculate the IC50 value of compounds of interest for inhibition of α-glucosidase activity.•This is a useful method for in vivo screening of anti-diabetic compounds.

In Vivo Screening Method for the Identification and Characterization of Prokaryotic, Metabolite-Responsive Transcription Factors

In prokaryotes, transcription factors (TFs) are of uttermost importance for the regulation of gene expression. However, the majority of TFs are not characterized today, which hampers both the understanding of fundamental processes and the development of TF-based applications, such as biosensors, used in metabolic engineering, synthetic biology, diagnostics, etc. One way of analyzing TFs is through in vivo screening, enabling the study of TF-promoter interactions, ligand inducibility, and ligand specificity in a high-throughput fashion. Here, an approach is described for the selection and cloning of TF-promoter pairs, the development of a reporter system, and the measurement and analysis of fluorescent reporter assays. Furthermore, the importance of a suitable inducible plasmid system is illustrated together with prospective adaptations to modify a reporter system's output signal. The given approach can be used for the investigation of native, heterologous, or even artificially created TFs in Escherichia coli, and can be extended toward use in other microorganisms.

Efficient Method to Identify Synthetic Riboswitches Using RNA-Based Capture-SELEX Combined with In Vivo Screening

Synthetic riboswitches are a promising tool for conditional gene expression. In vitro selected aptamers used as binding domains for the design of RNA-based switches have to exhibit excellent binding affinity as well as ligand binding-induced structural changes. Selection via Capture-SELEX favors the enrichment of aptamers which exhibit both characteristics. For the Capture-SELEX, an RNA pool is used that gets immobilized onto a capture oligonucleotide by hybridization. Addition of the ligand frees the aptamers by their binding to the ligand, resulting in the release from the capture oligonucleotide through structural changes. These sequences get reverse transcribed, PCR amplified, and used for the following selection rounds. In this publication, we present a detailed protocol for Capture-SELEX, followed by screening in yeast to identify aptamers suitable for the design of synthetic riboswitches.

Barcoding Technology for Multiplexed Analysis of Metastatic Ability In Vivo

DNA barcoding allows the quantitative, biomarker-free tracking of individual cell populations in mixed/heterogeneous cell pools. Here, we describe a multiplexed in vivo screening platform based on DNA barcoding technology to interrogate compound libraries for their effect on metastatic seeding in vivo. We apply next-generation sequencing (NGS) technology to quantitatively analyze high-throughput compound screening in mice. Up to 96 compounds and controls can be screened for their effect on metastatic ability in a single mouse.

Identification of 2-(2'-fluoro-[1,1'-biphenyl]-2-yl)acetamide as a Sodium Valproate-like broad spectrum anti-epileptic drug candidate

By further optimizing compound A [2'-fluoro-N-methyl-[1,1'-biphenyl]-2-sulfonamide], we identified DSP-0565 [2-(2'-fluoro-[1,1'-biphenyl]-2-yl)acetamide, 17a] as a strong, broad-spectrum anti-epileptic drug (AED) candidate. Our efforts mainly focused on finding an alternative polar group for the sulfonamide in order to improve ADME profile of compound A including good metabolic stability and no reactive metabolic production. This led to the identification of biphenyl acetamide as a new scaffold for development of broad-spectrum AED candidates. DSP-0565 showed anti-convulsant activity in various models (scPTZ, MES, 6 Hz and amygdala kindling) with good safety margin, and was therefore selected as a clinical candidate.

N-alkyl-[1,1'-biphenyl]-2-sulfonamide derivatives as novel broad spectrum anti-epileptic drugs with efficacy equivalent to that of sodium valproate

In order to develop phenyl sulfonamides as a novel class of anti-epileptic drugs (AED) for both general and partial seizure, we initiated in vivo screening of our chemical library in the mice MES and sc-PTZ models and found compounds 1 and 2 as lead compounds. Optimization of 1 and 2 led to the discovery of compound 21, which showed potent anticonvulsant effect in MES, scPTZ and rat amygdala kindling models. These findings indicate that compound 21 could be a useful new broad spectrum AED like sodium valproate and provide an opportunity to struggle current therapy-resistant epilepsy.

Simple N,N-dimethyl phenylsulfonamides show potent anticonvulsant effect in two standard epilepsy models

Optimization of the previously reported benzothiazine analogue A led to the identification of compound 1, which showed anti-convulsant activity in two golden standard animal models of seizure, the MES and scPTZ models. Structure-activity relationship investigation of compound 1 revealed compounds 2, 6 and 19 as attractive anti-epileptic drug (AED) candidates with potent anticonvulsant effect in both the MES and scPTZ models. As these compounds are structurally different from existing AEDs, determination of their mechanism of actions could provide clues to understanding current therapy-resistant seizures. Moreover, these simple phenylsulfoneamide compounds could be good starting points for searching broad spectrum AEDs by such in vivo screening.

Computational insight into the chemical space of plant growth regulators

An enormous technological progress has resulted in an explosive growth in the amount of biological and chemical data that is typically multivariate and tangled in structure. Therefore, several computational approaches have mainly focused on dimensionality reduction and convenient representation of high-dimensional datasets to elucidate the relationships between the observed activity (or effect) and calculated parameters commonly expressed in terms of molecular descriptors. We have collected the experimental data available in patent and scientific publications as well as specific databases for various agrochemicals. The resulting dataset was then thoroughly analyzed using Kohonen-based self-organizing technique. The overall aim of the presented study is to investigate whether the developed in silico model can be applied to predict the agrochemical activity of small molecule compounds and, at the same time, to offer further insights into the distinctive features of different agrochemical categories. The preliminary external validation with several plant growth regulators demonstrated a relatively high prediction power (67%) of the constructed model. This study is, actually, the first example of a large-scale modeling in the field of agrochemistry.

Discovery of benzothiazine derivatives as novel, orally-active anti-epileptic drug candidates with broad anticonvulsant effect

In order to develop novel anti-epileptic drugs that are effective for both general and partial seizure, we conducted in vivo screening of our chemical library in the mice MES and sc-PTZ models and found the benzothiazine 1 as lead compound. Optimization of this compound led to the discovery of compound 7b, which showed potent anticonvulsant effect in the MES, scPTZ and rat amygdala kindling models. Since the chemical structure of 7b is different from that of any existing AED, it is suggested that 7b may have unique mechanism of action for relieving both partial and generalized epilepsy.

Continuous-flow C. elegans fluorescence expression analysis with real-time image processing through microfluidics

The nematode Caenorhabditis elegans has become an essential model organism in neuroscience research because of its stereotyped anatomy, relevance to human biology, and capacity for genetic manipulation. To solve the intrinsic challenges associated with performing manual operations on C. elegans, many automated chip designs based on immobilization-imaging-release approaches have been proposed. These designs are prone to limitations such as the exertion of physical stress on the worms and limited throughput. In this work, a continuous-flow, high-throughput, automated C. elegans analyzer based on droplet encapsulation and real-time image processing was developed to analyze fluorescence expression in worms. To demonstrate its capabilities, two strains of C. elegans nematodes with different levels of expression of green fluorescent protein (GFP) were first mixed in a buffer solution. The worms were encapsulated in water-in-oil droplets to restrict random locomotion. The droplets were closely packed in a two-layer polydimethylsiloxane (PDMS) platform and were flowed through a narrow straight channel, in which a region of interest (ROI) was defined and continuously recorded by a frame acquisition device. Based on the number of pixels counted in the selected color range, our custom software analyzed GFP expression to differentiate between two strains with nearly 100% accuracy and a throughput of 0.5 seconds/worm.

Development of a Drosophila melanogaster spliceosensor system for in vivo high-throughput screening in myotonic dystrophy type 1

Alternative splicing of pre-mRNAs is an important mechanism that regulates cellular function in higher eukaryotes. A growing number of human genetic diseases involve splicing defects that are directly connected to their pathology. In myotonic dystrophy type 1 (DM1), several clinical manifestations have been proposed to be the consequence of tissue-specific missplicing of numerous genes. These events are triggered by an RNA gain-of-function and resultant deregulation of specific RNA-binding factors, such as the nuclear sequestration of muscleblind-like family factors (MBNL1–MBNL3). Thus, the identification of chemical modulators of splicing events could lead to the development of the first valid therapy for DM1 patients. To this end, we have generated and validated transgenic flies that contain a luciferase-reporter-based system that is coupled to the expression of MBNL1-reliant splicing (spliceosensor flies), to assess events that are deregulated in DM1 patients in a relevant disease tissue. We then developed an innovative 96-well plate screening platform to carry out in vivo high-throughput pharmacological screening (HTS) with the spliceosensor model. After a large-scale evaluation (>16,000 chemical entities), several reliable splicing modulators (hits) were identified. Hit validation steps recognized separate DM1-linked therapeutic traits for some of the hits, which corroborated the feasibility of the approach described herein to reveal promising drug candidates to correct missplicing in DM1. This powerful Drosophila-based screening tool might also be applied in other disease models displaying abnormal alternative splicing, thus offering myriad uses in drug discovery.