L'application de la métabolomique à la détermination de biomarqueurs sériques facilitant le pronostic du choc septique et du carcinome hépatocellulaire par la spectrométrie de masse et par la spectrométrie résonance magnétique nucléaire
Auteur / Autrice : | Zhicheng Liu |
Direction : | Philippe Savarin |
Type : | Thèse de doctorat |
Discipline(s) : | Chimie |
Date : | Soutenance le 06/02/2017 |
Etablissement(s) : | Sorbonne Paris Cité |
Ecole(s) doctorale(s) : | École doctorale Galilée (Villetaneuse, Seine-Saint-Denis) |
Partenaire(s) de recherche : | Laboratoire : Laboratoire Chimie bioorganique, biophysique et biomatériaux pour la santé (Villetaneuse, Seine-Saint-Denis) |
Jury : | Président / Présidente : Laurence Le Moyec |
Examinateurs / Examinatrices : Laurence Le Moyec, Patrick Emont, Christophe Junot, Mohamed N. Triba, Guowang Xu | |
Rapporteurs / Rapporteuses : Patrick Emont, Christophe Junot |
Mots clés
Résumé
A cascade of metabolomic studies have been developed in the recent decade. The application of metabolomics in the clinical field has been shown to be promising since even subtle physiological changes can be revealed by a metabolomic study which determines variations in the metabolome.Personalized clinical care is currently proposed for almost all the diseases, however, it is still difficultto be executed for the scarce of clinical biomarkers. This thesis work concerns the applications of both ¹H NMR-based and MS-based metabolomics in the determination of potential serumbiomarkers which help to improve personalized diagnosis and prognosis. It is composed by twoprincipal parts. The first part of the work aims to find out metabolite biomarkers predicting themortality of septic shock before clinical intervention and first 12 hours after hospitalization using NMR-based and LC-MS-based metabolomic methods respectively. The goal of the second part of the work is to seek potential biomarkers predicting the recurrence of HCC before and after RFA treatment. Our findings not only show that both the two applied techniques were useful for the discovery of novel clinical biomarkers, but also show that the two techniques are complementary