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Molecular phenotyping empowers drug discovery: a proof-of-concept study

ABSTRACT: Today, novel candidate therapeutics are identified in an environment which is intrinsically different from the clinical context in which they are ultimately evaluated. We present a strategy that allows biological relevance to be assessed in the early stages of drug discovery. Using molecular phenotyping and an in vitro model of diabetic cardiomyopathy, we show that by quantifying pathway reporter gene expression, molecular phenotyping can cluster compounds based on pathway profiles and dissect associations between pathway activities and disease phenotypes simultaneously. Molecular phenotyping identified a class of calcium-signaling modulators that can reverse disease-regulated pathways and phenotypes, which was validated by structurally distinct compounds of relevant classes. The technique was applicable to compounds with a range of binding specificities and detected false-positive hits missed by classical phenotypic assays. Our results advocate application of molecular phenotyping in drug discovery, promoting biological relevance as a key selection criterion early in the drug development cascade.

ORGANISM(S): Homo sapiens

PROVIDER: GSE89972 | GEO | 2017/05/24

SECONDARY ACCESSION(S): PRJNA354350

REPOSITORIES: GEO

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Homo sapiens

Project description:Molecular phenotyping empowers drug discovery: a proof-of-concept study

| PRJNA354350 | ENA

Compressed phenotypic screening empowers scalable biological discovery (PDAC screens)

Project description:High-throughput phenotypic screens leveraging biochemical perturbations and high-content readouts are poised to advance therapeutic discovery, yet they remain constrained by limitations of scale. To address this, we establish a method of pooling exogenous perturbations followed by computational deconvolution to compress a screen’s required sample, labor, and financial input. We benchmark the approach with a bioactive small molecule library and a high-content imaging readout, demonstrating the feasibility and increased efficiency of compressed experimental designs compared to conventional approaches. To prove generalizability, we apply compressed screening in two different biological discovery campaigns. In the first, we use early-passage pancreatic cancer organoids to map transcriptional responses to alibrary oftumor-microenvironmentrecombinant protein ligands. We uncover reproducible phenotypic shifts induced by specific ligands that are distinct from canonical reference signatures and uniquely correlate with clinical outcome.In the second, we examine the modulatory effects of a known mechanism of action chemical compound library on primary human peripheral blood mononuclear cell immune responses. Through contrastive analyses, we identify molecules that potentiate and/or inhibit cell-type specific transcriptional features, uncover pleiotropic effects for individual compounds across diverse cell types, and realize a systems-level view of drug responses. In sum, our approach empowers phenotypic screens with information-rich readouts to advance drug discovery efforts as well as basic biological inquiry.

2024-05-13 | GSE267243 | GEO

Targeted therapy for LIMD1-deficient non-small cell lung cancer subtypes: a Proof-of-Concept synthetic lethal study

Project description:An early event in lung oncogenesis is loss of the tumour suppressor gene LIMD1 (LIM domains containing 1); this encodes a scaffold protein, which binds multiple binding partners to suppress tumourigenesis via a number of different mechanisms. Approximately 45% of non-small cell lung cancers (NSCLC) are deficient in LIMD11, yet this subtype of NSCLC has been overlooked in preclinical and clinical investigations. Defining therapeutic targets in these LIMD1 loss-of-function patients is difficult due to a lack of ‘druggable’ targets, thus alternative approaches are required. To this end, we performed the first drug repurposing screen to identify synthetic lethal compounds with LIMD1 loss in lung cancer cells. PF-477736 was shown to selectively target LIMD1 deficient cells in vitro through inhibition of multiple kinases, inducing cell death via apoptosis. Furthermore, PF-477736 is effective in treating LIMD1-/- tumors in subcutaneous xenograft models, with no significant effect in LIMD1+/+ cells. We have identified a novel drug tool with significant preclinical characterization that serves as an excellent candidate to explore and define LIMD1-deficient cancers as a new therapeutic subgroup of critical unmet need.

2022-02-16 | PXD023674 | Pride

Shah2020 - Predicting liver cytosol stability of small molecules.

Project description:The human liver cytosol stability model is used for predicting the stability of a drug in the cytosol of human liver cells, which is beneficial for identifying potential drug candidates early during the drug discovery process. If a drug compound is quickly absorbed, it may not reach the intended target in the body or become toxic. On the other hand, if a drug compound is too stable, it could accumulate and cause detrimental effects. The authors use an NCATS dataset of 1450 compounds screened in vitro in mouse and human cytosol fractions. Compounds were classified as stable (half-life > 30min) or unstable (half-life ≤ 30 min). Note that authors report the dataset was biased towards stable compounds. Model Type: Machine learning model. Model Relevance: Predicts probability of a compound stability due to liver cells metabolism. Model Encoded by: Pauline (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos9yy1

2024-04-22 | MODEL2404220005 | BioModels

Exploring kidney allograft rejection: A proof-of-concept study using spatial transcriptomics

Project description:In this proof-of-concept study, spatial transcriptomics combined with public single-cell RNA sequencing data were used to explore the potential of this technology to study kidney allograft rejection. We aimed to map gene expression patterns within diverse pathological states by examining biopsies classified across non-rejection, T cell-mediated acute rejection, and interstitial fibrosis and tubular atrophy (IFTA). Our results revealed distinct immune cell signatures, including those of T and B lymphocytes, monocytes, mast cells, and plasma cells, and their spatial organization within the renal interstitium. We also mapped chemokine receptors and ligands to study immune-cell migration and recruitment. Finally, our analysis demonstrated differential spatial enrichment of transcription signatures associated with kidney allograft rejection across various biopsy regions. Interstitium regions displayed higher enrichment scores for rejection-associated gene expression patterns than did tubular areas, which had negative scores. This implies that these signatures are primarily driven by processes unfolding in the renal interstitium. Overall, this study highlights the value of spatial transcriptomics for revealing cellular heterogeneity and immune signatures in renal transplant biopsies, and demonstrates its potential for studying the molecular and cellular mechanisms associated with rejection. However, certain limitations must be borne in mind regarding the development and future applications of this technology.

2024-05-02 | GSE245870 | GEO

Proof of concept of blockmiR induced MBNL rescue in Myotonic dystrophy muscle cells

Project description:The symptoms of Myotonic Dystrophy Type 1 (DM1) are multi-systemic and life-threatening. The neuromuscular disorder is rooted in a non-coding CTG microsatellite expansion in the DMPK gene that is correctly transcribed and physically sequesters the MBNL family of proteins. The high-affinity binding occurring between the proteins and the repetitions disallows MBNL proteins from performing their post-transcriptional splicing regulation leading to downstream molecular effects directly related to disease symptoms such as myotonia and muscle weakness. In this study, we build off of previously demonstrated evidence showing that the silencing of miR-23b and miR-218 can increase MBNL1 and 2 protein in DM1 cells. Here we use blockmiR antisense technology to block the binding sites of these miRNAs in order to increase MBNL translation into protein without binding to the microRNAs in DM1 muscle cells. The blockmiRs show therapeutic effects with the rescue of mis-splicing, MBNL subcellular localization, and transcriptomic expression proving that this novel and highly specific strategy could be a potentially viable therapy in Vivo.

2022-07-31 | GSE173359 | GEO

In vitro transcription studies used in a proof of concept whole transcriptome model predition study - MCF7 cells (2 of 4)

Project description:MCF7 cells were exposed in triplicate to three agrichemicals for 24hrs at 8 concentrations and a DMSO vehicle control (0.001, 0.003, 0.01, 0.03, 0.1, 0.3, 1, 3, and 10 μM plus DMSO vehicle controls). While a common set of DMSO controls was used, these CEL files were RMA normalized independently with each of the chemical treated groups. Gene expression was measured on an Affymetrix GeneTitan system. The compounds used were fenbuconazole (a.k.a FENB, CAS # 114369-43-6) a triazole fungicide, imazalil (a.k.a. IMAZ, CAS # 35554-44-0), an azole pesticide, and 2,4-dichlorophenoxyacetic acid (a.k.a. 2,4-D or 2-4-D in file names, CAS # 94-75-7), a chlorophenoxy herbicide.

2018-12-21 | GSE109509 | GEO

In vitro transcription studies used in a proof of concept whole transcriptome model predition study - HepG2 cells (4 of 4)

Project description:HpeG2 cells were exposed in triplicate to three agrichemicals for 24hrs at 8 concentrations and a DMSO vehicle control (0.001, 0.003, 0.01, 0.03, 0.1, 0.3, 1, 3, and 10 μM plus DMSO vehicle controls). While a common set of DMSO controls was used, these CEL files were RMA normalized independently with each of the chemical treated groups. Gene expression was measured on an Affymetrix GeneTitan system. The compounds used were fenbuconazole (a.k.a FENB, CAS # 114369-43-6) a triazole fungicide, imazalil (a.k.a. IMAZ, CAS # 35554-44-0), an azole pesticide, and 2,4-dichlorophenoxyacetic acid (a.k.a. 2,4-D or 2-4-D in file names, CAS # 94-75-7), a chlorophenoxy herbicide.

2018-12-21 | GSE109513 | GEO

In vitro transcription studies used in a proof of concept whole transcriptome model predition study - HepaRG cells (3 of 4)

Project description:HepaRG cells were exposed in triplicate to three agrichemicals for 24hrs at 8 concentrations and a DMSO vehicle control (0.001, 0.003, 0.01, 0.03, 0.1, 0.3, 1, 3, and 10 μM plus DMSO vehicle controls). While a common set of DMSO controls was used, these CEL files were RMA normalized independently with each of the chemical treated groups. Gene expression was measured on an Affymetrix GeneTitan system. The compounds used were fenbuconazole (a.k.a FENB, CAS # 114369-43-6) a triazole fungicide, imazalil (a.k.a. IMAZ, CAS # 35554-44-0), an azole pesticide, and 2,4-dichlorophenoxyacetic acid (a.k.a. 2,4-D or 2-4-D in file names, CAS # 94-75-7), a chlorophenoxy herbicide.

2018-12-21 | GSE109511 | GEO

Chemical proteomics reveals the target landscape of 1,000 kinase inhibitor tool compounds

Project description:Here, we profiled the targets of 1,184 compounds from drug discovery projects in lysates of cancer cell lines using the Kinobeads approach. The resulting 500,000 compound-target interactions are available in ProteomicsDB and we exemplify how this molecular resource may be used for research. We anticipate that this molecular resource will aid drug discovery and chemical biology.

2023-06-23 | MSV000092248 | MassIVE

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