Biology subjects

Lapins, M.

Publications and source records attributed to Lapins, M..

5 recordsLinked to original sources

bioRxiv2025

Morphological cell profiling for drug repurposing against SARS-CoV-2 infection

Antiviral drug discovery has traditionally focused on targeting viral proteins, while host-directed strategies remain largely underexplored. Here, present a systematic drug repurposing strategy leveraging morphological profiling to identify host-targeting antivirals. Our image-based approach combines viral protein immunostaining with high-content Cell Painting analysis to simultaneously assess viral replication and provide in-depth analysis of host cell responses. By screening 5,275 repurposable drugs against SARS-CoV-2 infected cells, we identified compounds that reversed the infected cell phenotype, including ones not detected by conventional cytopathicity and antibody-based assays. A counter-screen excluded compounds whose antiviral activity was likely driven by drug-induced phospholipidosis (DIPL). Pathway enrichment analysis of compounds validated by both Cell Painting dose-response and DIPL assays, revealed host processes frequently hijacked by viruses, including innate immune responses and kinases. Among the top hits, both novel candidates, such as serdemetan, and previously reported broad-spectrum antivirals, such as sunitinib, were identified. Our approach constitutes an adaptable and scalable platform suited for diverse viral pathogens and cell systems. We provide a resource of open access screening data, images, and automated analysis pipelines to advance both antiviral discovery and pandemic preparedness.

microbiology↗

bioRxiv2024

Combined inhibition of MDM2 and PARP lead to a synergistic anti-tumoral response in p53 wild-type rhabdomyosarcoma models

Targeting MDM2-p53 interaction to enhance p53 activity represents a promising antitumoral strategy for p53 wild-type pediatric tumors, including soft-tissue sarcomas. However, results from early-phase clinical trials in hematological and solid cancers have shown limited efficacy of MDM2 inhibitors, underscoring the necessity to explore more effective combinations with other agents. In this study, we provide results from a 22-drug combination screening demonstrating the therapeutic potential of combining siremadlin (MDM2 inhibitor) and olaparib (PARP inhibitor) for treating p53 wild-type rhabdomyosarcoma (p53 WT RMS). Cell survival, cell death, and apoptosis analysis revealed synergistic effects of combining siremadlin plus olaparib in vitro. The combination of both drugs led to a significant increase in p53 activity, as evidenced by p53 accumulation and K382 acetylation, along with an increased expression of bona fide p53 targets. Furthermore, treatment with both drugs resulted in significant reduction of tumor growth and increased mice overall survival when compared to single treatments and control in cell line-derived orthotopic xenograft models. Overall, our study demonstrates, for the first time, the synergistic effect of combining siremadlin plus olaparib in inhibiting p53 WT RMS tumor growth in vitro and in vivo. Our findings support the potential to study the combination of both drugs in clinical trials and warrants further investigation in other tumors with similar molecular features.

cancer biology↗

bioRxiv2022

Morphological profiling of environmental chemicals enables efficient and untargeted exploration of combination effects

Environmental chemicals are commonly studied one at a time, and there is a need to advance our understanding of the effect of exposure to their combinations. Here we apply high-content microscopy imaging of cells stained with multiplexed dyes (Cell Painting) to profile the effects of Cetyltrimethylammonium bromide (CTAB), Bisphenol A (BPA), and Dibutyltin dilaurate (DBTDL) exposure on four human cell lines; both individually and in all combinations. We show that morphological features can be used with multivariate data analysis to discern between exposures from individual compounds, concentrations, and combinations. CTAB and DBTDL induced concentration-dependent morphological changes across the four cell lines, and BPA exacerbated morphological effects when combined with CTAB and DBTDL. Combined exposure to CTAB and BPA induced changes on the ER, Golgi apparatus, nucleoli and cytoplasmic RNA in one of the cell lines. Different responses between cell lines indicate that multiple cell types are needed when assessing combination effects. The rapid and relatively low-cost experiments combined with high information content makes Cell Painting an attractive methodology for future studies of combination effects. All data in the study is made publicly available on Figshare. HighlightsO_LIAssessment of combination effects of BPA, CTAB and DBTDL on four human cell lines C_LIO_LIMorphological profiling/Cell Painting captures dose and combination dependent effects C_LIO_LIBPA exacerbated morphological effects when combined with CTAB and DBTDL. C_LIO_LICell models of diverse origin are needed when profiling environmental chemicals C_LI

pharmacology and toxicology↗

bioRxiv2021

A rapid phenomics workflow for the in vitro identification of antiviral drugs

BackgroundThe current COVID-19 pandemic has highlighted the need for new and fast methods to identify novel or repurposed therapeutic drugs. Here we present a method for untargeted phenotypic drug screening of virus-infected cells, combining Cell Painting with antibody-based detection of viral infection in a single assay. We designed an image analysis pipeline for segmentation and classification of virus-infected and non-infected cells, followed by extraction of morphological properties. ResultsWe show that the methodology can successfully capture virus-induced phenotypic signatures of MRC-5 human lung fibroblasts infected with Human coronavirus 229E (CoV-229E). Moreover, we demonstrate that our method can be used in phenotypic drug screening using a panel of nine host- and virus-targeting antivirals. Treatment with effective antiviral compounds reversed the morphological profile of the host cells towards a non-infected state. ConclusionsThe method can be used in drug discovery for morphological profiling of novel antiviral compounds on both infected and non-infected cells.

pharmacology and toxicology↗

bioRxiv2019

Evaluation of gene expression and phenotypic profiling data as quantitative descriptors for predicting drug targets and mechanisms of action

Profiling drug leads by means of in silico and in vitro assays as well as omics is widely used in drug discovery for safety and efficacy predictions. In this study, we evaluate the performance of machine learning models trained on data from gene expression and phenotypic profiling assays, with models trained on chemical structure descriptors, for prediction of various drug mechanisms of action and target proteins. Models for several hundred mechanisms of actions and targets were trained using data on 1484 compounds characterized in both gene expression using L1000 profiles, and phenotypic profiling with cell painting assay. The results indicate that the accuracy of the three profiling technologies varies for different endpoints, and indicate a clear potential synergistic effect if these methods are combined. We also study the effect of predictive accuracy of data from different cell lines for L1000 profiles, showing that the choice of cell line has a non-negligible effect on the predictive accuracy. The results strengthen the idea of integrated approaches for predicting drug targets and mechanisms of action in preclinical drug discovery.

bioinformatics↗