Molecular Mechanisms in Malignant Lymphomas - Demonstrators of Personalized Medicine

Description:

The joint project "MMML Demonstrators" deals with improvements in the diagnosis and therapy of lymphoma and consists of seven subprojects. In lymphoma, the so-called diffuse large cell B-cell lymphomas (DLBCL) are responsible for the highest number of deaths. Although the disease is curable in principle, approximately one third of patients still die. However, the expression of certain genes in tumor cells and surrounding tissues can be used to diagnose certain subgroups of these tumors and, in particular, to identify high-risk patients. Detailed knowledge of the biology of these tumors allows the measured gene expression pattern to be used to select an optimal, adapted therapy option. The present joint project will use a new technique for gene expression measurement, which should significantly reduce the workload and costs for a molecular diagnosis. The partners will establish this new technique for routine diagnostics and validate it both with improved histological methods and in the clinic. At the same time, the measured gene expression patterns will be used in a computer model to predict possible therapies. The focus is on the interaction of tumor cells with the surrounding tissue. At the end of the project, the findings will be combined in a web portal and made available to physicians and scientists. The insights gained in this project are thus a first step towards molecular-biological diagnostics and personalised therapy of lymphomas.

Programme: This Project is not associated with a Programme

LHA-ID: 7UACP8PCK2-4

Funding codes:
  • BMBF

Public web page: https://www.sys-med.de/de/demonstratoren/mmml-demonstrators/

Human Diseases: Diffuse large b-cell lymphoma

Leipzig Health Atlas PALs: Rainer Spang, Markus Löffler

Project Coordinators: No Project coordinators for this Project

Project start date: 1st Jan 2015

Project end date: 31st Dec 2018

Project Hierarchy

Related items

Powered by
(v.1.9.1)
Copyright © 2008 - 2019 The University of Manchester and HITS gGmbH
Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig