Prediction of combination therapies based on topological modeling of the immune signaling network in multiple sclerosis.

ABSTRACT:

Background

Multiple sclerosis (MS) is a major health problem, leading to a significant disability and patient suffering. Although chronic activation of the immune system is a hallmark of the disease, its pathogenesis is poorly understood, while current treatments only ameliorate the disease and may produce severe side effects.

Methods

Here, we applied a network-based modeling approach based on phosphoproteomic data to uncover the differential activation in signaling wiring between healthy donors, untreated patients, and those under different treatments. Based in the patient-specific networks, we aimed to create a new approach to identify drug combinations that revert signaling to a healthy-like state. We performed ex vivo multiplexed phosphoproteomic assays upon perturbation

SUBMITTER: Bernardo-Faura M 

PROVIDER: S-EPMC8284018 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature