Training in Cancer Biology: Focus on Tumour Escape Mechanisms

SCHEME: PRIDE

CALL: 2016

DOMAIN: BM - Life Sciences, Biology and Medicine

FIRST NAME: Simone

LAST NAME: Niclou

INDUSTRY PARTNERSHIP / PPP: No

INDUSTRY / PPP PARTNER:

HOST INSTITUTION: LIH

KEYWORDS: Tumour escape, tumour resistance, metastasis, tumour microenvironment, proteomics, onco-genomics, tumour biomarkers, tumour heterogeneity, computational biology, data integration, biological networks

START: 2016-10-15

END: 2023-04-14

WEBSITE: https://www.lih.lu

Submitted Abstract

Cancer is still in many instances an incurable disease with a growing number of affected patients in all societies. High quality training of young scientists and research-oriented medical staff is a prerequisite for developing improved cancer therapies and patient care. The CANBIO DTU will provide state-of-the-art training in cancer biology covering molecular mechanisms of tumour progression, treatment resistance, biomarker discovery, therapeutic applications in pre-clinical disease models, as well as building computational disease models to facilitate innovative translational research. The overall focus of the research programmeme is on tumour escape mechanisms, thus addressing the increasingly important clinical problem of tumour progression and recurrence. We will study induced escaped mechanisms meaning the development of resistance mechanisms against treatment, including resistance to cytotoxic agents and targeted therapies. Furthermore, the intrinsic escape mechanisms of tumours based on their genetic heterogeneity and their amazing capacities to evade immune surveillance, to metastasize and to adapt to diverse niches will be investigated. A key asset of this DTU is its diversified and long standing expertise of the supervisors in cancer research, academic training and in clinical treatment of cancer patients, as well as their track record in joint research and training activities. Thus the training will range from the analysis of large scale molecular data (genome, proteome, transcriptome, metabolome) to phenotypic data (cell and organ behaviour) and to the study of whole organisms (patients, patient-based animal models). Additionally, specific training programmemes will be provided that aim at integration of these different data types using bioinformatics and computational systems biology approaches. Thus, the PhD candidates in this DTU will acquire an in depth understanding of the complexity of cancer and associated research questions, as well as a vast set of transferable skills that will adequately prepare them for their next career step.

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