Biology subjects

Lacoux, C.

Publications and source records attributed to Lacoux, C..

4 recordsLinked to original sources

bioRxiv2026

Single-cell transcriptomics reveals a differential response of human bronchial epithelial cell-types to cadmium chloride

Exposure of cells or tissues to chemical compounds can be analyzed through transcriptomic signatures, which can be used to classify chemical agents. This information can also enrich Adverse Outcome Pathways (AOP). Transcriptional signatures have generally been obtained using "bulk" analysis, by which the global gene expression pattern of an entire tissue is determined. Although this approach has been useful in toxicology, some information is lost, especially when tissues containing multiple cell types are considered. With the advent of single-cell transcriptomics (scRNA-seq), it is now possible to obtain higher resolution, cell type-specific responses in complex tissues. The aim of the present study was to evaluate the added value of scRNA-seq in analysis of the acute response of human bronchial epithelial cells grown at the air/liquid interface (ALI) to a known toxic compound, CdCl2, with well described transcriptional signatures of exposure. Fully differentiated mucocilliary epithelia obtained from three independent donors were exposed to 10 {micro}M CdCl2 and scRNA-seq analysis was performed on a total of 18255 cells to obtain cell type-specific signatures. Our results show that the contribution of each cell type to the overall transcriptomic bulk response varies. For example, the classical heavy metal detoxification response was only detected in multiciliated and secreting cells, while absent in basal cells. The data demonstrate that scRNA-seq provides high-resolution transcriptional signatures with unexpected features. This added information is likely to have implications for the refinement of AOPs and could serve as a basis for a new generation of tests in predictive toxicology.

pharmacology and toxicology↗

bioRxiv2023

A workflow combining single-cell CRISPRi screening and a supervised autoencoder neural network to detect subtle transcriptomic perturbations induced by lncRNA Knock-Down

Single-cell CRISPR-based transcriptome screens are potent genetic tools for concomitantly assessing the expression profiles of cells targeted by a set of guides RNA (gRNA), and inferring target gene functions from the observed perturbations. However, due to various limitations, this approach lacks sensitivity in detecting weak perturbations and is essentially reliable when studying master regulators such as transcription factors. To overcome the challenge of detecting subtle gRNA induced transcriptomic perturbations and classifying the most responsive cells, we developed a new supervised autoencoder neural network method. Our Sparse supervised autoencoder (SSAE) neural network provides selection of both relevant features (genes) and actual perturbed cells. We applied this method on an in-house single-cell CRISPR-interference-based (CRISPRi) transcriptome screening (CROP-Seq) focusing on a subset of long non-coding RNAs (lncRNAs) regulated by hypoxia, a condition that promote tumor aggressiveness and drug resistance, in the context of lung adenocarcinoma (LUAD). The CROP-seq library of validated gRNA against a subset of lncRNAs and, as positive controls, HIF1A and HIF2A, the 2 main transcription factors of the hypoxic response, was transduced in A549 LUAD cells cultured in normoxia or exposed to hypoxic conditions during 3, 6 or 24 hours. We first validated the SSAE approach on HIF1A and HIF2 by confirming the specific effect of their knock-down during the temporal switch of the hypoxic response. Next, the SSAE method was able to detect stable short hypoxia-dependent transcriptomic signatures induced by the knock-down of some lncRNAs candidates, outperforming previously published machine learning approaches. This proof of concept demonstrates the relevance of the SSAE approach for deciphering weak perturbations in single-cell transcriptomic data readout as part of CRISPR-based screening.

bioinformatics↗

bioRxiv2021

Processing body dynamics drive non-genetic MEK inhibitors tolerance by fine-tuning KRAS and NRAS translation

Overactivation of the Mitogen-activated protein kinase (MAPK) pathway is a critical driver of many human cancers. However, therapies targeting this pathway have proven effective in only a few cancers, as cancers inevitably develop resistance. Puzzling observations suggest that MAPK targeting fails in tumors due to early compensatory RAS overexpression, albeit by unexplained mechanisms. We identified a novel mechanism of drug tolerance to MEK inhibitors (MEKi) that involves Processing Bodies (PBs), a membraneless organelle (MLO). MEKi promoted translation of the oncogenes KRAS and NRAS, which in turn triggered BRAF phosphorylation. This overexpression, which occurred in the absence of neotranscription, depended on PB dissolution as the source of the RAS mRNA. Moreover, in response to MEKi removal, the process was dynamic as PBs rapidly reformed and reduced MAPK signaling. These results highlight a dynamic spatiotemporal negative feedback loop of MAPK signaling via RAS mRNA sequestration. Furthermore, we observed a phenotype with a low number of PBs along with strong KRAS and NRAS induction capacities. Overall, we describe a new intricate mechanism involving PBs in the translational regulation of essential cellular signaling pathways like MAPKs, paving the way for future therapies altering MLO and thereby improving targeted cancer therapies.

cancer biology↗

bioRxiv2021

Blockade of pro-fibrotic response mediated by the miR-143/-145 cluster prevents targeted therapy-induced phenotypic plasticity and resistance in melanoma

Lineage dedifferentiation towards a mesenchymal-like state is a common mechanism of adaptive response and resistance to targeted therapy in melanoma. Yet, the transcriptional network driving this phenotypic plasticity remains elusive. Remarkably, this cellular state displays myofibroblast and fibrotic features and escapes MAPK inhibitors (MAPKi) through extracellular matrix (ECM) remodeling activities. Here we show that the anti-fibrotic drug Nintedanib/BIBF1120 is active to normalize the fibrous ECM network, enhance the efficacy of MAPK-targeted therapy and delay tumor relapse in a pre-clinical model of melanoma. We also uncovered the molecular networks that regulate the acquisition of this resistant phenotype and its reversion by Nintedanib, pointing the miR-143/-145 pro-fibrotic cluster as a driver of the therapy-resistant mesenchymal-like phenotype. Upregulation of the miR-143/-145 cluster under BRAFi/MAPKi therapy was observed in melanoma cells in vitro and in vivo and was associated with an invasive/undifferentiated profile of resistant cells. The 2 mature miRNAs generated from this cluster, miR-143-3p and miR-145-5p collaborated to mediate phenotypic transition towards a drug resistant undifferentiated mesenchymal-like state by targeting Fascin actin-bundling protein 1 (FSCN1), modulating the dynamic crosstalk between the actin cytoskeleton and the ECM through the regulation of focal adhesion dynamics as well as contributing to a fine-tuning of mechanotransduction pathways. Our study brings insights into a novel miRNA-mediated regulatory network that contributes to non-genetic adaptive drug resistance and provides proof-of-principle that preventing MAPKi-induced pro-fibrotic stromal response is a viable therapeutic opportunity for patients on targeted therapy.

cancer biology↗