Publications associées à Exosome-inspired targeting of cancer cells with enhanced affinity

Publications associées (32)

Ru(II)-Arene Complexes of Curcumin and Bisdesmethoxycurcumin Metabolites

Paul Joseph Dyson, Farzaneh Fadaei Tirani, Mouna Hadiji

Curcuminoids and their complexes continue to attract attention in medicinal chemistry, but little attention has been given to their metabolic derivatives. Here, the first examples of (arene)Ru(II) complexes with curcuminoid metabolites, tetrahydrocurcumin ...

Amer Chemical Soc2024

Development of cysteine cathepsin inhibitors combined with cell type-specific delivery for the treatment of B-cell lymphoma and solid tumors

Aaron Simone Petruzzella

Cysteine cathepsins proteases are enzymes that play essential physiological roles, but their activity is also associated to different aspects of cancer progression and to the development of other diseases. Therefore, cysteine cathepsins are relevant and pr ...

EPFL2024

Characterization of the gut-bone marrow axis through bile acid signaling

Alejandro Alonso Calleja

Communication between the intestine and other organs such as the lungs, brain or bones is mediated by several metabolites, like short-chain fatty acids or bile acids, that relay information about nutritional and microbiota status. Bile acids are endogenous ...

EPFL2024

Exploration and modulation of mechanical cues for enhanced cancer immunotherapy

Armand Kurum

The advent of immunotherapy, such as immune checkpoint blockade (ICB) and adoptive transfer of cytotoxic lymphocytes, has transformed the clinical care of cancer. However, a significant proportion of patients are resistant to immunotherapy or experience re ...

EPFL2024

Plasmonic Nanostructures for Photocatalysis: Material, Photonic and Electronic Effects

Fateme Kiani Shahvandi

Plasmonic photochemistry has a large potential to replace energy-intensive chemical processes with low-temperature, low-pressure light-driven chemical reactions. Plasmonic nanostructures have emerged as promising photocatalysts with exceptional and tunable ...

EPFL2024

Metabolically enhanced CAR T cells efficiently clear solid tumors in mice

Li Tang

Chimeric antigen receptor (CAR) T cells in the solid tumor microenvironment enter a partially dysfunctional state called T cell exhaustion. Interleukin (IL)-10-producing CAR T cells retain their metabolic fitness, resist T cell exhaustion and display unpre ...

Nature Portfolio2024

From Sequence to Dynamics to Function: Computational Design of Allostery and Ligand Selectivity in G-Protein Coupled Receptors

Mahdi Hijazi

The phenomenon of allostery, a general property in proteins that has been heralded as "the second secret of life" remains elusive to our understanding and even more challenging to incorporate into protein design. One example of allosteric proteins with gre ...

EPFL2024

Accessible and highly observable gastrointestinal organoid model systems for studying host-pathogen interactions

Moritz Hofer

Traditional cell cultures have long been fundamental to biological research, offering an alternative to animal models burdened by ethical constraints and procedural intricacies, often lacking relevance to human physiology and disease. Moreover, their inabi ...

EPFL2024

A Cluster of Evolutionarily Recent KRAB Zinc Finger Proteins Protects Cancer Cells from Replicative Stress–Induced Inflammation

Didier Trono, Priscilla Turelli, Sandra Eloise Kjeldsen, Evaristo Jose Planet Letschert, Filipe Amândio Brandão Sanches Vong Martins, Olga Marie Louise Rosspopoff, Cyril David Son-Tuyên Pulver, Romain Forey, Florian Huber

Heterochromatin loss and genetic instability enhance cancer progression by favoring clonal diversity, yet uncontrolled replicative stress leads to mitotic catastrophe and inflammatory responses that promote immune rejection. KRAB domain-containing zinc fin ...

2024

Bioengineering functional organoid models across scales

Tania Hübscher

The last two decades have seen the development of organoid models for many different tissues and organs. Organoids are three-dimensional organ-mimetics derived from stem or progenitor cells comprising various specialized cell types, resembling the architec ...

EPFL2024

Deciphering the nature of cell state transitions in single cells using quantitative modeling of temporal dynamics

Alex Russell Lederer

Cells are the smallest operational units of living systems. Through synthesis of various biomolecules and exchange of signals with the environment, cells tightly regulate their composition to realize a specific functional state. The transformation of a cel ...

EPFL2024

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

Cytokine-armed dendritic cell progenitors for antigen-agnostic cancer immunotherapy

Ali Ghasemi

Dendritic cells (DCs) are specialized myeloid cells with the ability to uptake, process, and present antigens to T lymphocytes. They also generate cytokine and chemokine gradients that regulate immune cell trafficking, activation, and function. Monocyte-de ...

EPFL2024

Machine learning-aided generative molecular design

Philippe Schwaller, Jeff Guo

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

Nature Portfolio2024

Antibody-peptide conjugates for targeted inhibition of cysteine proteases

Elisa Oricchio

We developed a rational approach to design peptide-based covalent inhibitors and coupled the inhibitors with antibodies for cell-specific delivery. We used this platform to generate antibody-peptide inhibitor conjugates (APICs) that target a family of prot ...

Nature Portfolio2024

Solvation Free Energies from Machine Learning Molecular Dynamics

Nicola Marzari, Nicéphore Arthur François Bonnet

The present work proposes an extension to the approach of [Xi, C; et al. J. Chem. Theory Comput. 2022, 18, 6878] to calculate ion solvation free energies from first-principles (FP) molecular dynamics (MD) simulations of a hybrid solvation model. The approa ...

Amer Chemical Soc2024

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Ksenia Briling

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

EPFL2024

Next-Generation Modeling of Cancer Using Organoids

Wouter Richard Karthaus, Jillian Rose Love

In the last decade, organoid technology has become a cornerstone in cancer research. Organoids are long-term primary cell cultures, usually of epithelial origin, grown in a three-dimensional (3D) protein matrix and a fully defined medium. Organoids can be ...

Cold Spring Harbor Lab Press, Publications Dept2024

Distinct ultrastructural phenotypes of glial and neuronal alpha-synuclein inclusions in multiple system atrophy

Henning Paul-Julius Stahlberg, Marta Di Fabrizio, Amanda Jennifer Lewis, Domenic Burger

Multiple System Atrophy is characterized pathologically by the accumulation of alpha-synuclein (aSyn) into glial cytoplasmic inclusions (GCIs). The mechanism underlying the formation of GCIs is not well understood. In this study, correlative light and elec ...

2024

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