Identifying network control elements in breast cancer oncogenic transformation via whole transcriptome analysis

Objective

Understanding tumorogenesis is a prerequisite to designing rational cancer therapies. Tumorogenesis, and systems biology generally, requires its own set of tools for dealing with masses of high-throughput data. I have demonstrated such abilities over the years, both in the task of single handedly integrating disparate data into the microenvironment of the mammalian thymus as well as in the integration of genome-wide data into biologic understanding through concepts of network and signalling pathways. I approach systems biology with training/research in mathematics, physics, computer science, immunology, and tumor and stem-cell biology. I recently devised a metric for characterizing cancer cells based gene pathways as the basic unit of measurement; the pathway metric was able to detect a cancer signature with 98% success, irrespective of tissue origin, grades, stages and patient clinical data. The metric also predicted patient survival. Representing a sample through its pathway profile served as a powerful tool for classification, but it also enabled process reduction to discover essential molecular mechanisms.
I am now on a tenure-track process of establishing my own lab. The technological revolution in molecular biology makes it possible to follow the process of oncogenic transformation at a whole transcriptome scope, in high resolution and at relatively low cost, through RNA sequencing using next generation, massive parallel, sequencing technology. Previously, I showed how genome-wide measurements can be integrated into scientific understating of stem-cell differentiation. I will now apply this whole-transcriptome approach to study controlled oncogenic transformation in vitro. The ultimate aim is to uncover specific processes that are amenable to specific, rational drug targeting of the tumor.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.

• medical and health sciences basic medicine immunology
• medical and health sciences clinical medicine oncology breast cancer
• natural sciences biological sciences genetics RNA transcriptomes
• natural sciences computer and information sciences
• natural sciences biological sciences molecular biology

Keywords

Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)

• Breast Cancer
• Health sciences
• Natural sciences
• Systems biology
• Transcriptome
• oncogenic transformation
• signaling pathways

Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

• FP7-PEOPLE - Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

• PEOPLE-2007-4-3.IRG - Marie Curie Action: "International Reintegration Grants"

Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

FP7-PEOPLE-IRG-2008
See other projects for this call

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

MC-IRG - International Re-integration Grants (IRG)

Coordinator