Publications associées à A streamlined search technology for identification of synergistic drug combinations

Publications associées (33)

In an era of combinatorial immunotherapy: elucidating and targeting mechanisms of systemic immunosuppression in HPV16+ cervical cancer to improve therapeutic vaccine responses

Immunotherapy has revolutionized cancer treatment, yet many patients, including those with cervical cancers induced by high-risk human papillomaviruses such as HPV16, remain unresponsive due to immune evasion mechanisms. While the tumor microenvironment (T ...

EPFL2025

Cyclic Peptides for Drug Development

Christian Heinis, Alexander Lund Nielsen, Xinjian Ji

Cyclic peptides are fascinating molecules abundantly found in nature and exploited as molecular format for drug development as well as other applications, ranging from research tools to food additives. Advances in peptide technologies made over many years ...

Wiley-VCH Verlag GmbH2024

Deconvolution of ex-vivo drug screening data and bulk tissue expression predicts the abundance and viability of cancer cell subpopulations

Alexandre Coudray

Ex-vivo drug sensitivity screening (DSS) allows the prediction of cancer treatment effectiveness in a personalized fashion. However, it only provides a readout on mixtures of cells, potentially occulting important information on clinically relevant cell su ...

EPFL2023

Functionalization of harmonic nanoparticles for drug release and multimodal imaging applications

Adrian Stefan Gheata

Cancer is among the leading causes of death worldwide, and as knowledge of the disease continues to grow there is an increasing interest towards precision medicine: more specifically towards the theranostics field, i.e the development of targeted molecular ...

EPFL2024

Computational drug development for membrane protein targets

Pierre Vogel, Henning Paul-Julius Stahlberg, Shuguang Yuan, Dongchun Ni, Babatunde Edukpe Ekundayo

The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learni ...

2024

The predictive capacity of in vitro preclinical models to evaluate drugs for the treatment of retinoblastoma

Paul Joseph Dyson, Irina Sinenko, Roland Christopher Turnell-Ritson

Retinoblastoma is a rare childhood cancer of the eye. Of the small number of drugs are used to treat retinoblastoma, all have been repurposed from drugs developed for other conditions. In order to find drugs or drug combinations better suited to the improv ...

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD2023

Optimised three-dimensional in vitro retinoblastoma models tailored for drug discovery and clinical translatability

Irina Sinenko

Retinoblastoma, while relatively rare, stands as the most prevalent intraocular cancer. In Switzerland, the survival rate approaches 100%, but it drops to less than 50% in low-income countries. The current treatment options for retinoblastoma rely on a lim ...

EPFL2023

Alchemical analysis of FDA approved drugs

Philippe Schwaller, Daniel Probst

Chemical space maps help visualize similarities within molecular sets. However, there are many different molecular similarity measures resulting in a confusing number of possible comparisons. To overcome this limitation, we exploit the fact that tools desi ...

2023

Deep learning predicts malignancy and metastasis of solid pulmonary nodules from CT scans

Jiancheng Yang

In the clinic, it is difficult to distinguish the malignancy and aggressiveness of solid pulmonary nodules (PNs). Incorrect assessments may lead to delayed diagnosis and an increased risk of complications. We developed and validated a deep learning-based m ...

FRONTIERS MEDIA SA2023

Multitarget-Directed Gallium(III) Tris(acyl-pyrazolonate) Complexes Induce Ferroptosis in Cancer Cells via Dysregulation of Cell Redox Homeostasis and Inhibition of the Mevalonate Pathway

Farzaneh Fadaei Tirani

A series of Ga(Q(n))(3) coordination compounds have been synthesized, where HQ(n) is 1-phenyl-3-methyl-4-RC(=O)-pyrazolo-5-one. The complexes have been characterized through analytical data, NMR and IR spectroscopy, ESI mass spectrometry, elemental analysi ...

AMER CHEMICAL SOC2023

Modeling tumor size dynamics based on real-world electronic health records and image data in advanced melanoma patients receiving immunotherapy

Federico Amato

The development of immune checkpoint inhibitors (ICIs) has revolutionized cancer therapy but only a fraction of patients benefits from this therapy. Model-informed drug development can be used to assess prognostic and predictive clinical factors or biomark ...

2023

Microfluidic device combining hydrodynamic and dielectrophoretic trapping for the controlled contact between single micro-sized objects and application to adhesion assays

Philippe Renaud, Arnaud Bertsch, Clémentine Sophie Sarah Lipp

The understanding of cell-cell and cell-matrix interactions via receptor and ligand binding relies on our ability to study the very first events of their contact. Of particular interest is the interaction between a T cell receptor and its cognate peptide-m ...

ROYAL SOC CHEMISTRY2023

Comparative Evaluation of Lipofectamine and Dendrimer for Transfection of Short RNA Into Human T47D and MCF-10A Cell Lines

Erfan Shirzadi

Purpose: Non-viral transfection approaches are extensively used in cancer therapy. The future of cancer therapy lies on targeted and efficient drug/gene delivery. The aim of this study was to determine the transfection yields of two commercially available ...

2023

Elucidating and modulating regulatory pathways so as to reprogram the immunosuppressive tumor microenvironment for therapeutic benefit

Agnieszka Alicja Chryplewicz

Glioblastoma (GBM) is the most frequent and highly malignant form of brain cancer. New therapeutic regimens are urgently needed as GBM patients present with a minimal response to currently-approved therapies. The goal of this project is to identify new the ...

EPFL2023

The Antioxidant and Proapoptotic Effects of Sternbergia clusiana Bulb Ethanolic Extract on Triple-Negative and Estrogen-Dependent Breast Cancer Cells In Vitro

Natalia Gasilova, Laure Menin

Background: Sternbergia clusiana belongs to the Amaryllidaceae family and is recognized for the valuable biological activity of its major bioactive compounds. The aim of the current is to evaluate the anticancer effects of the ethanolic bulb extract of Ste ...

MDPI2023

Effective Inhibition of TDP-43 Aggregation by Native State Stabilization

Hilal Lashuel, Yllza Jasiqi, Lixin Yang

Preventing the misfolding or aggregation of transactive response DNA binding protein with 43 kDa (TDP-43) is the most actively pursued disease-modifying strategy to treat amyotrophic lateral sclerosis and other neurodegenerative diseases. In this work, we ...

Wiley-VCH Verlag GmbH2024

Development of a novel Chimeric Antigen Receptor (CAR) for its use in Natural Killer (NK) cells for cancer treatment and beyond

Angela Madurga Alonso

The use of CAR technologies has revolutionized cancer treatment. Their unprecedented efficacy against B cell malignancies has opened the doors for a lot of excitement and research in the field. These synthetic receptors are composed of an antigen recogniti ...

EPFL2023

Rational Design of Chemically Controlled Antibodies and Protein Therapeutics

Bruno Emanuel Ferreira De Sousa Correia, Li Tang, Pablo Gainza Cirauqui, Sandrine Madeleine Suzanne Georgeon, Stéphane Rosset, Leo Scheller, Anthony Marchand, Sailan Shui, Lucia Bonati

Protein-based therapeutics, such as monoclonal antibodies and cytokines, are important therapies for various pathophysiological conditions such as oncology, autoimmune disorders, and viral infections. However, the wide application of such protein therapeut ...

2023

Combi-seq for multiplexed transcriptome-based profiling of drug combinations using deterministic barcoding in single-cell droplets

Christoph Merten, Ngoc Hien Du

Anti-cancer therapies often exhibit only short-term effects. Tumors typically develop drug resistance causing relapses that might be tackled with drug combinations. Identification of the right combination is challenging and would benefit from high-content, ...

Nature Research2022

In-Cell Quantification of Drugs by Magic-Angle Spinning Dynamic Nuclear Polarization NMR

David Lyndon Emsley, Pierrick Berruyer, Andrea Bertarello

The determination of intracellular drug concentrations can provide a better understanding of the drug function and efficacy. Ideally, this should be performed nondestructively, with no modification of either the drug or the target, and with the capability ...

AMER CHEMICAL SOC2022