Biology subjects

Pasquier, E.

Publications and source records attributed to Pasquier, E..

12 recordsLinked to original sources

bioRxiv2026

Microdomes: Micro-engineered Microdome arrays enable standardised and shear-free 3D biology with full-spectrum optical imaging compatibility

Three-dimensional cellular models such as organoids and spheroids hold major promise for developmental biology, disease modelling and precision medicine, yet their large-scale production and analysis remain constrained by handling-induced shear stress, sample fragility, positional instability and limited compatibility with advanced imaging workflows. Here, we introduce Microdomes, dense arrays of open-top, dome-shaped microcavities. Each cavity holds a single specimen in its own miniature aquarium, accessed through a narrow apical opening that admits cells, medium, matrix and staining reagents while shielding it from the shear generated during routine pipetting. Each Microdomes chip accommodates more than 100 spheroids or organoids, supporting diverse cell types, co-culture formats and both matrix-free and matrix-embedded culture. All specimens are retained through prolonged culture, repeated medium exchange, fixation and immunostaining. Because every specimen occupies a fixed, addressable position against a thin transparent film, the same spheroid can be relocated and re-imaged over weeks of culture and across microscopes, from array-wide overviews to subcellular details, without transfer, embedding or other perturbation. Microdomes also support AI-based automated segmentation, from whole-spheroid outlines to individual nuclei in 3D, using common image analysis software. Microdomes thereby turn each array into a self-contained quality control unit, providing specimen-level traceability that organoid production pipelines currently lack.

cell biology↗

bioRxiv2026

Deletion of Ferritin Heavy Chain Limits Tumor Growth and Promotes Iron-Dependent Stress in Medulloblastoma

Iron is essential for tumor proliferation and metabolic adaptation but becomes cytotoxic when unbuffered, creating a potential metabolic vulnerability. Ferritin, a conserved iron-storage complex, limits labile iron and establishes the upper threshold of iron tolerance in cancer cells. Here, we report the first ferritin heavy chain (FTH) knockout in a brain tumor model system. Although FTH loss was tolerated under basal conditions through adaptive remodeling of iron metabolism, it exposed profound vulnerabilities under iron stress. FTH deficiency lowered the threshold for iron toxicity, sensitizing medulloblastoma (MB) cells to both canonical ferroptosis and a mechanistically distinct iron-dependent cell death pathway. Oxidative iron stress impaired tumor growth and prolonged survival in orthotopic xenografts, whereas vitamin C-induced iron reduction triggered a selective, iron-dependent, but non-ferroptotic elimination of MB-like cells in tumor organoids. Notably, sensitivity to iron toxicity correlated strongly with cellular phenotype, with mesenchymal-like cells displaying greater susceptibility than epithelial-like counterparts. Collectively, these findings identify ferritin as a central regulator of iron tolerance in MB and establish iron toxicity, not via iron deprivation, as a therapeutically exploitable vulnerability. More broadly, this work provides a mechanistic framework for targeting iron metabolism through modulation of ferritin-dependent iron buffering and iron redox homeostasis in cancers. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=170 SRC="FIGDIR/small/739635v1_ufig1.gif" ALT="Figure 1000"> View larger version (53K): org.highwire.dtl.DTLVardef@1c499a4org.highwire.dtl.DTLVardef@431c70org.highwire.dtl.DTLVardef@2b5borg.highwire.dtl.DTLVardef@11e9ac1_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2026

Reverse molecular pharmacology identifies the non-canonical axis of IRAK as a chemoresistance factor in neuroblastoma

Owing to chemoresistance, the prognosis of relapsed neuroblastoma is dismal with less than 10% of patients surviving after 5 years. We developed a reverse molecular pharmacology approach that is based on high-throughput drug screening coupled with chemo-informatic and transcriptomic analyses. This led to the identification of IRAK1 as a key chemoresistance factor in neuroblastoma. By performing functional and pharmacological drug combination screens targeting IRAK1, we revealed a synergy between IRAK1 inhibition/silencing and BET, EGFR and mTOR inhibitors as well as microtubule-targeting agents. The synergistic combination of microtubule-targeting agent, vincristine and IRAK inhibitors was then confirmed in tumor spheroids, patient-derived tumoroids and a syngeneic orthotopic mouse model. Mechanistically, IRAK inhibition potentiated the pro-apoptotic and cell cycle arrest properties of vincristine via a pathway involving the PIDDosome complex rather than its canonical MyDDosome axis. Altogether, this study represents a proof-of-concept of our reverse molecular pharmacology approach to quickly develop biology-guided drug combinations, that could be applied to any other human diseases.

cancer biology↗

bioRxiv2024

A new nanoDSF approach to anti-tubulin compounds screening revealed novel MTAs among approved drugs.

Microtubule Targeting Agents (MTAs) constitute a vital category of tubulin-binding compounds, deployed across anticancer therapies. Despite the array of MTA drugs developed by pharmaceutical entities, the quest for novel efficacious molecules continues unabated. We unveil an innovative in vitro MTA screening methodology employing nano differential scanning fluorimetry (nanoDSF), presenting distinct advantages over known assays. This novel approach not only assesses compound-tubulin binding but also quantitatively analyzes their impact on tubulin polymerization. Proposed nanoDSF assay was rigorously validated using the Prestwick Chemical Library, which encompasses 1,520 approved compounds, successfully identifying all previously known MTAs. Furthermore, this screening has unearthed potential anti-tubulin agents among drugs currently utilized for non-related medical conditions, offering insights into their mechanisms of action in inhibiting cancer cell proliferation and/or inducing cytotoxicity. These discoveries herald new opportunities for drug repositioning involving the newly identified MTAs and substantially streamline the process of screening extensive chemical libraries for MTAs featuring novel chemical structures.

cancer biology↗

bioRxiv2024

A mechanism for telomere-specific telomere length regulation

Telomere length is a critical determinant of telomere function and hence chromosome stability. Critically short telomeres induce cellular senescence and division arrest, which eventually may lead to devastating age-related degenerative diseases. Conversely, maintenance of telomere length is a hallmark of cancer. How telomere set-length is established and molecular mechanisms for telomere-specific length regulation remained unknown. Here we detail a mechanism of a telomere-specific set-length regulation that causes drastic differences in telomere length between individual telomeres in the same cell. Indeed, the results show that telomerase recruitment is modulated in cis in a telomere-specific way. Increased Sir4 abundance on yeast TEL03L subtelomeric heterochromatin leads to a set-length maintenance that is two to three times higher than on any other telomere. Remarkably, the distal 15 kb of TEL03L are sufficient to transfer this telomere specific set-length regulation to another chromosome. Furthermore, a mutation in the telomere boundary element protein Tbf1 allows increased Sir4 binding on all telomeres and hence results in longer set-lengths. The results therefore will force a rethinking of telomere length regulation away from the generalized view that all telomeres are treated the same to a more telomere-specific treatment. HIGHLIGHTSO_LIRegulation of the set-length of telomeric repeats is telomere-specific. C_LIO_LITEL03L on yeast chromosome III displays a set-length regulation that confers an extremely long repeat tract. C_LIO_LITransferring the distal part of TEL03L onto chromosome XV is sufficient to impose the very long set-length regulation. C_LIO_LITelomere-specific tract set-length regulation depends on the alternate telomerase recruitment pathway involving Sir4 and yKU and the chromatin boundary protein Tbf1. C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC="FIGDIR/small/598646v2_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1c3bb52org.highwire.dtl.DTLVardef@13f338forg.highwire.dtl.DTLVardef@51f91aorg.highwire.dtl.DTLVardef@1b95ac0_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2023

BMP2 and BMP7 cooperate with H3.3K27M to promote quiescence and invasiveness in pediatric diffuse midline gliomas

Pediatric diffuse midline gliomas (pDMG) are an aggressive type of childhood cancer with a fatal outcome. Their major epigenetic determinism has become clear, notably with the identification of K27M mutations in histone H3. However, the synergistic oncogenic mechanisms that induce and maintain tumor cell phenotype have yet to be deciphered. In 20 to 30% of cases, these tumors have an altered BMP signaling pathway with an oncogenic mutation on the BMP type I receptor ALK2, encoded by ACVR1. However, the potential impact of the BMP pathway in tumors non-mutated for ACVR1 is less clear. By integrating bulk, single-cell and spatial transcriptomic data, we show here that the BMP signaling pathway is activated at similar levels between ACVR1 wild-type and mutant tumors and identify BMP2 and BMP7 as putative activators of the pathway in a specific subpopulation of cells. By using both pediatric isogenic glioma lines genetically modified to overexpress H3.3K27M and patients-derived DIPG cell lines, we demonstrate that BMP2/7 synergizes with H3.3K27M to induce a transcriptomic rewiring associated with a quiescent but invasive cell state. These data suggest a generic oncogenic role for the BMP pathway in gliomagenesis of pDMG and pave the way for specific targeting of downstream effectors mediating the K27M/BMP crosstalk.

cancer biology↗

bioRxiv2022

Combination drug screen targeting glioblastoma core vulnerabilities reveals pharmacological synergisms

Synergistic drug combinations are an attractive anticancer strategy but prove challenging to identify. Here we present a stepwise approach consisting in revealing core cancer vulnerabilities and exploiting them through drug combination screen to uncover synergistic treatments for glioblastoma patients. MethodsWe established an innovative method, based on high-throughput screening, target deconvolution and functional genomics, to reveal core vulnerabilities in glioblastoma. Combination drug screen targeting these vulnerabilities was then designed to unveil synergistic associations. The therapeutic potential of the top drug combination was validated in two different clinically-relevant models: an organotypic ex vivo model and a syngeneic orthotopic mouse model of glioblastoma. ResultsLarge-scale monotherapy drug screening identified 83 potent anti-glioblastoma compounds. Target deconvolution using public chemoinformatic databases uncovered 1,100 targets and interactors of the hit compounds. Screening of a focused siRNA library targeting the top 292 drug interactors revealed 22 targetable vulnerabilities, 9 of which were confirmed as core glioblastoma vulnerabilities by mining the CRISPR screen cohort data from the online Cancer Dependency Map portal. Six selective inhibitors of the core vulnerabilities were then screened in combination with a custom-made library of 88 compounds and synergies amongst the 528 tested pairwise combinations were predicted. The combinations of CHK1 / MEK and AURKA / BET inhibitors were highlighted and validated in 3D tumor spheroids. Using an organotypic ex vivo model and a syngeneic orthotopic mouse model, we definitively ascertained the efficacy of dual AURKA / BET inhibition in glioblastoma. ConclusionsCollectively, we uncovered that dual inhibition of BET proteins and aurora kinase A is highly synergistic against GBM. Moreover, our study indicates that our approach to exploit drug poly-pharmacology for the rational design of drug combination screens represent a valuable strategy to discover synergistic treatments against refractory cancers.

pharmacology and toxicology↗

bioRxiv2022

Fusion-negative Rhabdomyosarcoma 3D-organoids as an innovative model to predict resistance to cell death inducers

Rhabdomyosarcoma (RMS) is the main form of soft-tissue sarcoma in children and adolescents. For 20 years, and despite international clinical trials, its cure rate has not really improved, and remains stuck at 20% in case of relapse. The definition of new effective therapeutic combinations is hampered by the lack of reliable models, which complicate the transposition of promising results obtained in pre-clinical studies into efficient solutions for young patients. Inter-patient heterogeneity, particularly in the so-called fusion-negative group (FNRMS), adds an additional level of difficulty in optimizing the clinical management of children and adolescents with RMS. Here, we describe an original 3D-organoid model derived from relapsed FNRMS and show that it finely mimics the characteristics of the original tumor, including inter- and intra-tumoral heterogeneity. Moreover, we have established the proof-of-concept of their preclinical potential by re-evaluating the therapeutic opportunities of targeting apoptosis in FNRMS from a streamlined approach based on the exploitation of bulk and single-cell omics data.

cancer biology↗

bioRxiv2021

CRCM5484: A BET- BDII Selective Compound With Differential Anti-Leukemic Drug Potentiation

Differentially screening the Fr-PPIChem chemical library on the BET BRD4-BDII versus -BDI bromodomains led to the discovery of a BDII selective tetrahydropyridothienopyrimidinone (THPTP)-based compound. Structure-activity relationship (SAR) and hit-to-lead approaches allowed us to develop CRCM5484, a potent inhibitor of BET proteins with a preferential and 475-fold selectivity for the second bromodomain of the BRD3 protein (BRD3-BDII) over its first bromodomain (BRD3-BDI). Its very low activity was demonstrated in various cell-based assays, corresponding with recent data describing other selective BDII compounds. However, screening on a drug sensitivity and resistance-profiling platform revealed its ability to modulate the anti-leukemic activity in combination with various FDA-approved and/or in-development drugs in a cell- and context-dependent differential manner. Altogether, the results confirm the originality of the THPTP molecular mode of action in the BD cavity and its potential as starting scaffold for the development of potent and selective bromodomain inhibitors.

cancer biology↗

bioRxiv2021

Metronomic therapy prevents emergence of drug resistance by maintaining the dynamic of intratumor heterogeneity.

Despite recent advances in deciphering cancer drug resistance mechanisms, relapse is a widely observed phenomenon in advanced cancers, mainly due to intratumor clonal heterogeneity. How tumor clones progress and impact each other remains elusive. By better understanding clone dynamics, we could reveal valuable biological insights and unveil vulnerabilities that could be therapeutically exploited. In this study, we developed 2D and 3D non-small cell lung cancer co-culture systems and defined a phenomenological mathematical model. Our results demonstrated a dominant role of the drug-sensitive clones over the drug-resistant ones under untreated conditions. Model predictions and their experimental in vitro and in vivo validations indicated that metronomic schedule leads to a better regulation of tumor cell heterogeneity over time than maximum-tolerated dose schedule, while achieving control of global tumor progression. We finally showed that drug-sensitive clones exert a suppressive effect on the proliferation of the drug-resistant ones through a paracrine mechanism way, which is linked to metabolic cell clone activity. Altogether, these computational and experimental approaches allow assessment of drug schedules controlling drug-sensitive and -resistant clone balance and highlight the potential of targeting cell metabolism to manage intratumor heterogeneity. SignificanceCombined computational and experimental models reveal how drug-sensitive tumor cells exert their dominance over drug-resistant cells and how it impacts optimal chemotherapy scheduling.

cancer biology↗

bioRxiv2020

In silico molecular target prediction unveils mebendazole as a potent MAPK14 inhibitor

The concept of polypharmacology involves the interaction of drug molecules with multiple molecular targets. It provides a unique opportunity for the repurposing of already-approved drugs to target key factors involved in human diseases. Herein, we used an in silico target prediction algorithm to investigate the mechanism of action of mebendazole, an anti-helminthic drug, currently repurposed in the treatment of brain tumors. First, we confirmed that mebendazole decreased the viability of glioblastoma cells in vitro. Our in silico approach unveiled 21 putative molecular targets for mebendazole, including 12 proteins significantly up-regulated at the gene level in glioblastoma as compared to normal brain tissue. Validation experiments were performed on three major kinases involved in cancer biology: ABL1, MAPK1/ERK2 and MAPK14/p38α. Mebendazole could inhibit the activity of these kinases in vitro in a dose-dependent manner, with a high potency against MAPK14. Its direct binding to MAPK14 was further validated in vitro and inhibition of MAPK14 kinase activity was confirmed in live glioblastoma cells. Consistent with biophysical data, molecular modeling suggested that mebendazole was able to bind to the catalytic site of MAPK14. Finally, gene silencing demonstrated that MAPK14 is involved in glioblastoma tumor spheroid growth and response to mebendazole treatment. This study thus highlighted the role of MAPK14 in the anticancer mechanism of action of mebendazole and provides further rationale for the pharmacological targeting of MAPK14 in brain tumors. It also opens new avenues for the development of novel MAPK14/p38α inhibitors to treat human diseases.Significance Statement This study provides a framework to investigate drug polypharmacology by rapidly identifying novel molecular targets of already-approved drugs. It unveils a new mechanism involved in the anticancer activity of anti-helminthic drug, mebendazole, which is currently being repurposed for the treatment of brain tumors. By helping to decipher the mechanism(s) of action of repurposed drugs in their new indications, this approach could contribute to the development of safer and more effective therapeutic strategies in oncology and beyond.Competing Interest StatementThe authors have declared no competing interest.View Full Text

pharmacology and toxicology↗

bioRxiv2018

Predicting synergism of cancer drug combinations using NCI-ALMANAC data

BackgroundDrug combinations are of great interest for cancer treatment. Unfortunately, the discovery of synergistic combinations by purely experimental means is only feasible on small sets of drugs. In silico modeling methods can substantially widen this search by providing tools able to predict which of all possible combinations in a large compound library are synergistic. Here we investigate to which extent drug combination synergy can be predicted by exploiting the largest available dataset to date (NCI-ALMANAC, with over 290,000 synergy determinations).\n\nMethodsEach cell line is modeled using primarily two machine learning techniques, Random Forest (RF) and Extreme Gradient Boosting (XGBoost), on the datasets provided by NCI-ALMANAC. This large-scale predictive modeling study comprises more than 5000 pair-wise drug combinations, 60 cell lines, 4 types of models and 5 types of chemical features. The application of a powerful, yet uncommonly used, RF-specific technique for reliability prediction is also investigated.\n\nResultsThe evaluation of these models shows that it is possible to predict the synergy of unseen drug combinations with high accuracy (Pearson correlations between 0.43 and 0.86 depending on the considered cell line, with XGBoost providing slightly better predictions than RF). We have also found that restricting to the most reliable synergy predictions results in at least two-fold error decrease with respect to employing the best learning algorithm without any reliability estimation. Alkylating agents, tyrosine kinase inhibitors and topoisomerase inhibitors are the drugs whose synergy with other partner drugs are better predicted by the models.\n\nConclusionsDespite its leading size, NCI-ALMANAC comprises an extremely small part of all conceivable combinations. Given their accuracy and reliability estimation, the developed models should drastically reduce the number of required in vitro tests by predicting in silico which of the considered combinations are likely to be synergistic.

bioinformatics↗