Biology subjects

Tabouret, E.

Publications and source records attributed to Tabouret, E..

4 recordsLinked to original sources

bioRxiv2026

Morphologic intratumoral heterogeneity from routine whole-slide histopathology is prognostic for survival in primary central nervous system lymphoma: development in the LOC Network and international external validation

Background: Clinical scores incompletely capture outcomes in primary central nervous system lymphoma (PCNSL). We quantified morphologic heterogeneity in pretreatment hematoxylin and eosin (H\&E) whole slides. Patients and methods: Three independent cohorts of immunocompetent, HIV- and EBV-negative patients treated recently were analyzed: LOC 2023 (122 slides), phase III BLOCAGE-01 (245 slides; NCT02313389), and external Barcelona (BCN; 41 slides). UNI embeddings, prototype learning, spatial metrics, and elastic-net Cox regression defined ITH-C. Results: Models achieved bootstrap-corrected concordance of 0.797--0.834. Age-, sex-, and KPS-adjusted ITH-C HRs were 1.29 (95\% CI 1.01--1.64), 1.27 (1.07--1.51), and 2.13 (1.35--3.37), respectively. Adding ITH-C increased MSKCC C-index from 0.671 to 0.717, 0.560 to 0.593, and 0.588 to 0.706. Spatial transcriptomics linked ITH-C to immune programs. Conclusions: Routine H\&E encodes prognostic spatial heterogeneity in PCNSL. ITH-C complements clinical scores, supporting prospective risk stratification.

bioinformatics↗

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↗

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↗

bioRxiv2020

An AI-powered blood test to detect cancer using nanoDSF

We describe a novel cancer diagnostic method based on plasma denaturation profiles obtained by a non-conventional use of Differential Scanning Fluorimetry. We show that 84 glioma patients and 63 healthy controls can be automatically classified using denaturation profiles with the help of machine learning algorithms with 92% accuracy. Proposed high throughput workflow can be applied to any type of cancer and could become a powerful pan-cancer diagnostic and monitoring tool from a simple blood test.

cancer biology↗