Biology subjects

Lagadec, C.

Publications and source records attributed to Lagadec, C..

4 recordsLinked to original sources

bioRxiv2024

Development of Molecular Digital Twins Based on Ambient Ionization Mass Spectrometry Imaging for Real-Time Application in Oncological Surgery

Cancer surgery is a fundamental component of oncology treatment, its quality significantly impacts patient outcomes, influencing both relapse rates and survival. However, achieving this customization is contingent upon early collection of robust molecular data during surgery, providing accurate information for diagnosis, prognosis, and delineating surgical margins. The introduction of digital twin (DT) technology has recently opened a new era of precision and effectiveness in cancer surgery. Expanding from its successful implementations in the industrial sector, DT concept has evolved into a highly promising breakthrough in healthcare. Therefore, our study goal is on creating DT by using accurate and high-throughput molecular data obtained through mass spectrometry imaging. We developed a machine-learning-based pipeline that allow to depict infiltration of cancer cells into normal tissue that offer precise delineation of tumor margins thanks to SpiderMass. This process also enables the prediction of relative presence of bacterial strains in tumoral and healthy mammary glands.

bioengineering↗

bioRxiv2024

Spatial self-organization of cancer stem cell niches revealed by live single-cell imaging

Phenotypic plasticity is a major factor of tumor heterogeneity and treatment resistance. In particular, cancer stem cells (CSCs) represent a small subpopulation within tumors with self-renewal and tumor-forming capabilities. Understanding reprogramming, maintenance, and lineage properties of CSCs requires dedicated tools to disentangle the respective influences of phenotypic inheritance and cell-cell interactions. Here we set up ultra-wide field microscopy of breast cancer cell lines expressing a stemness fluorescent reporter for several days. The fluorescent reporter distinguishes three phenotypes: cancer stem cells (CSCs), cancer differentiated cells (CDCs) and intermediate/transiting cancer cells (iCCs). Spatial statistics indicate significant zonation, aka phenotypic niches, with CSC clustering near each other but away from CDCs. Surprisingly, single cell time series reveal spontaneous reprogramming events from CDC to CSC even in unperturbed populations. We identify that such transitions are prone to arise during the cell cycle. Moreover, lineage analysis shows that the phenotype is partially inherited from ancestor cells. However, such heredity is not sufficient to explain the spatial properties of the cell population, which also depend on cell-cell interactions. Indeed, we identified that phenotypic transitions of cancer cells are influenced by the phenotypic state of neighboring cells. Reprogramming into CSCs is respectively promoted and inhibited by the presence of CSCs and CDCs in the neighborhood. Altogether, our results disentangle how phenotypic inheritance and intercellular interactions orchestrate the spatio-temporal self-organization of cancer cell heterogeneity, maintaining a subpopulation of CSCs within niches.

systems biology↗

bioRxiv2023

Single-cell Electrochemical Aptasensor Array

Despite several demonstrations of electrochemical devices with limits of detection (LOD) of 1 cell/mL, the implementation of single-cell bioelectrochemical sensor arrays has remained elusive due to the challenges of scaling up. In this study, we show that the recently introduced nanopillar array technology combined with redox-labelled aptamers targeting epithelial cell adhesion molecule (EpCAM) is perfectly suited for such implementation. Combining nanopillar arrays with microwells determined for single cell trapping directly on the sensor surface, single target cells are successfully detected and analyzed. This first implementation of a single-cell electrochemical aptasensor array, based on Brownian-fluctuating redox species, opens new opportunities for large-scale implementation and statistical analysis of early cancer diagnosis and cancer therapy in clinical settings. For Table of Contents only O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=73 SRC="FIGDIR/small/532912v2_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@2f8bddorg.highwire.dtl.DTLVardef@187886corg.highwire.dtl.DTLVardef@10d9f8dorg.highwire.dtl.DTLVardef@1661cfe_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2020

Robot-Assisted SpiderMass for in vivo Real-Time Topography Mass Spectrometry Imaging

Mass Spectrometry Imaging (MSI) has shown to bring invaluable information for biological and clinical applications. However, conventional MSI is generally performed ex vivo from tissue sections. Here, we develop a novel MS-based method for in vivo mass spectrometry imaging. By coupling the SpiderMass technology - that provides in vivo minimally invasive analysis - to a robotic arm of high accuracy, we demonstrate that images can be acquired from any surface by moving the laser probe above the surface. By equipping the robotic arm with a sensor, we are also able to both get the topography image of the sample surface and the molecular distribution, and then and plot back the molecular data, directly to the 3D topographical image without the need for image fusion. This is shown for the first time with the 3D topographic MS-Based whole-body imaging of a mouse. Enabling fast in vivo MSI bridged to topography pave the way for surgical applications to excision margins.

biochemistry↗