Biomedical subjects

Olivier Elemento

Publications and source records attributed to Olivier Elemento.

7 recordsLinked to original sources

PubMed2026

A Real-Time Image-Based Co-Culture Assay to Quantify Tumor-Infiltrating Lymphocyte-Mediated Apoptotic Killing of Patient-Derived Tumor Organoids.

Understanding the functional capacity of tumor-infiltrating lymphocytes (TILs) to recognize and eliminate autologous tumor cells is central to advancing personalized immunotherapy. The goal of this method is to provide an image-based, live-cell imaging protocol that measures TIL-mediated, caspase-3-dependent apoptotic killing against patient-derived tumor organoids (PDTOs) in real time. This method integrates established procedures for isolation and expansion of PDTOs and TILs with a standardized three-dimensional co-culture system and automated fluorescence-based apoptosis detection. Tumor organoids are plated in imaging-compatible 96-well plates and labeled with a red tumor marker, while expanded TILs are added at defined effector-to-target ratios in the presence of a caspase-3 activated green fluorescent substrate. Co-cultures are imaged every 4 h using a live-cell analysis system to capture phase-contrast and dual-fluorescence channels. Quantitative image analysis identifies red-positive tumor structures and calculates the proportion of red/green double-positive apoptotic tumor objects over time. Appropriate technical and biological replicates are incorporated, along with baseline, spontaneous apoptosis, negative and positive killing controls to ensure assay rigor. By preserving tumor heterogeneity within the PDTOs' three-dimensional architecture while enabling longitudinal quantification, this protocol provides a physiologically relevant system for functionally profiling patient-specific tumor-TIL interactions and investigating immunomodulatory agents that augment anti-tumor immunity.

Humans↗

PubMed2025

Worldwide Innovative Network (WIN) Consortium in Personalized Cancer Medicine: Bringing next-generation precision oncology to patients.

The human genome project ushered in a genomic medicine era that was largely unimaginable three decades ago. Discoveries of druggable cancer drivers enabled biomarker-driven gene- and immune-targeted therapy and transformed cancer treatment. Minimizing treatment not expected to benefit, and toxicity-including financial and time-are important goals of modern oncology. The Worldwide Innovative Network (WIN) Consortium in Personalized Cancer Medicine founded by Drs. John Mendelsohn and Thomas Tursz provided a vision for innovation, collaboration and global impact in precision oncology. Through pursuit of transcriptomic signatures, artificial intelligence (AI) algorithms, global precision cancer medicine clinical trials and input from an international Molecular Tumor Board (MTB), WIN has led the way in demonstrating patient benefit from precision-therapeutics through N-of-1 molecularly-driven studies. WIN Next-Generation Precision Oncology (WINGPO) trials are being developed in the neoadjuvant, adjuvant or metastatic settings, incorporate real-world data, digital pathology, and advanced algorithms to guide MTB prioritization of therapy combinations for a diverse global population. WIN has pursued combinations that target multiple drivers/hallmarks of cancer in individual patients. WIN continues to be impactful through collaboration with industry, government, sponsors, funders, academic and community centers, patient advocates, and other stakeholders to tackle challenges including drug access, costs, regulatory barriers, and patient support. WIN's collaborative next generation of precision oncology trials will guide treatment selection for patients with advanced cancers through MTB and AI algorithms based on serial liquid and tissue biopsies and exploratory omics including transcriptomics, proteomics, metabolomics and functional precision medicine. Our vision is to accelerate the future of precision oncology care.

Humans↗

PubMed2021

GCN2 kinase activation by ATP-competitive kinase inhibitors.

Small-molecule kinase inhibitors represent a major group of cancer therapeutics, but tumor responses are often incomplete. To identify pathways that modulate kinase inhibitor response, we conducted a genome-wide knockout (KO) screen in glioblastoma cells treated with the pan-ErbB inhibitor neratinib. Loss of general control nonderepressible 2 (GCN2) kinase rendered cells resistant to neratinib, whereas depletion of the GADD34 phosphatase increased neratinib sensitivity. Loss of GCN2 conferred neratinib resistance by preventing binding and activation of GCN2 by neratinib. Several other Food and Drug Administration (FDA)-approved inhibitors, such erlotinib and sunitinib, also bound and activated GCN2. Our results highlight the utility of genome-wide functional screens to uncover novel mechanisms of drug action and document the role of the integrated stress response (ISR) in modulating the response to inhibitors of oncogenic kinases.

Adenosine Triphosphate↗

PubMed2021

OCT2 pre-positioning facilitates cell fate transition and chromatin architecture changes in humoral immunity.

During the germinal center (GC) reaction, B cells undergo profound transcriptional, epigenetic and genomic architectural changes. How such changes are established remains unknown. Mapping chromatin accessibility during the humoral immune response, we show that OCT2 was the dominant transcription factor linked to differential accessibility of GC regulatory elements. Silent chromatin regions destined to become GC-specific super-enhancers (SEs) contained pre-positioned OCT2-binding sites in naive B cells (NBs). These preloaded SE 'seeds' featured spatial clustering of regulatory elements enriched in OCT2 DNA-binding motifs that became heavily loaded with OCT2 and its GC-specific coactivator OCAB in GC B cells (GCBs). SEs with high abundance of pre-positioned OCT2 binding preferentially formed long-range chromatin contacts in GCs, to support expression of GC-specifying factors. Gain in accessibility and architectural interactivity of these regions were dependent on recruitment of OCAB. Pre-positioning key regulators at SEs may represent a broadly used strategy for facilitating rapid cell fate transitions.

Animals↗

PubMed2003

IMGT/PhyloGene: an on-line tool for comparative analysis of immunoglobulin and T cell receptor genes.

IMGT/PhyloGene is an on-line software package for comparative analysis of immunoglobulin (IG) and T cell receptor (TR) variable genes of all vertebrate species, newly implemented in IMGT, the international ImMunoGeneTics information system ((R)). IMGT/PhyloGene is strongly associated with the IMGT gene and allele nomenclature and with the IMGT unique numbering for V-REGION, which directly creates standardized alignments from IMGT reference sequences. IMGT/PhyloGene is the first tool to use the IMGT expertized and standardized data for automated comparative analyses, and the first on-line software package for phylogenetic reconstruction to be integrated to a sequence database. Starting from a standardized alignment of selected sequences, IMGT/PhyloGene computes a matrix of evolutionary distances, builds a tree using the Neighbor-Joining (NJ) algorithm, and outputs various graphical tree representations. The resulting IMGT/PhyloGene tree is then used as a support for studying the evolution of particular subregions, such as the CDR-IMGT (Complementarity Determining Regions) or the V-RS (Variable gene Recombination Signals). IMGT/PhyloGene is freely available at http://imgt.cines.fr.

Databases, Nucleic Acid↗

PubMed2002

An efficient and accurate distance based algorithm to reconstruct tandem duplication trees.

UNLABELLED: The problem of reconstructing the duplication tree of a set of tandemly repeated sequences which are supposed to have arisen through unequal recombination, was first introduced by Fitch (1977, Genetics, 86, 93-104), and has recently received a lot of attention. In this paper, we describe DTSCORE, a fast distance based algorithm to reconstruct tandem duplication trees, which is statistically consistent. As a cousin of the ADDTREE algorithm (Sattath and Tversky, 1977, Psychometrika, 42, 319-345), the raw DTSCORE has a time complexity in O(n(5)), where n is the number of observed repeated sequences. Through a series of algorithmic refinements, we improve its complexity to O(n(4)) in the worst case, but stress that the refined DTSCORE algorithm should perform faster with real data. We assess the topological accuracy of DTSCORE using simulated data sets, and compare it to existing reconstruction methods. The results clearly show that DTSCORE is more accurate than all the other methods we studied. Finally, we report the results of DTSCORE on a real dataset. SUPPLEMENTARY INFORMATION: http://www.lirmm.fr/w3ifa/MAAS/

Chromosome Mapping↗

PubMed2002

Reconstructing the duplication history of tandemly repeated genes.

We present a novel approach to deal with the problem of reconstructing the duplication history of tandemly repeated genes that are supposed to have arisen from unequal recombination. We first describe the mathematical model of evolution by tandem duplication and introduce duplication histories and duplication trees. We then provide a simple recursive algorithm which determines whether or not a given rooted phylogeny can be a duplication history and another algorithm that simulates the unequal recombination process and searches for the best duplication trees according to the maximum parsimony criterion. We use real data sets of human immunoglobulins and T-cell receptors to validate our methods and algorithms. Identity between most parsimonious duplication trees and most parsimonious phylogenies for the same data, combined with the agreement with additional knowledge about the sequences, such as the presence of polymorphisms, shows strong evidence that our reconstruction procedure provides good insights into the duplication histories of these loci.

Algorithms↗