OCT 30, 2014 12:00 PM PDT

Breast-Predict: Leveraging the Power of Systems Medicine Towards Personalized Cancer Therapy

  • Chief Scientific Officer at OncoMark, Professor of Cancer Biology, University of Dublin
      Prof. Gallagher originally graduated from the Department of Biochemistry, UCD in 1993 with a 1st Class Joint Honors degree in Molecular Genetics and Biochemistry. Subsequently, he obtained a PhD in Molecular Oncology from the Cancer Research UK Beatson Laboratories in Glasgow. In 1997, he moved to Paris to undertake a Marie Curie Individual Fellowship at Rhone-Poulenc Rorer (currently Sanofi-Aventis). Afterwards, he returned to Ireland upon receipt of an Enterprise Ireland Post-Doctoral Fellowship (1999-2000) and, subsequently, a Marie Curie Return Fellowship (20002001). In 2001, he was employed in a permanent capacity as College Lecturer at UCD within the former Department of Pharmacology. In 2005, he was appointed Senior Lecturer within the UCD School of Biomolecular and Biomedical Science, promoted to Associate Professor of Cancer Biology in 2006 and Full Professor in 2014. From September 2009-August 2011, Prof. Gallagher was the Vice-Principal of Research and Innovation at the UCD College of Life Sciences. He is also a Conway Fellow at the UCD Conway Institute. In 2007, he co-founded OncoMark Ltd., which is a private company centred on the development and application of biomarker panels and associated technologies, on both tissues and biological fluids (www.oncomark.com). Prof. Gallagher is currently the Chief Scientific Officer (CSO) at OncoMark. A major focus of his research work is the identification and validation of candidate biomarkers of breast cancer and melanoma, with particular emphasis on translation of transcriptomic and proteomic datasets into clinically relevant assays.    Prof. Gallagher has received a number of awards based on his research work to date, including the BACR/AstraZeneca Young Scientist Frank Rose Award in 2004, the St. Lukes Silver Medal Award in 2008 and the NovaUCD 2011 Innovation Award. Prof. Gallagher has had productive collaborative interactions with a variety of other industrial partners throughout his research.   


    Although the incidence of breast cancer is steadily increasing, mortality rates are decreasing. This means that the majority of women with breast cancer now survive, making it even more important to tailor therapy appropriately, reducing toxicity and long-term side-effects. Some patients still succumb despite early intervention, and improved stratification approaches and more diverse treatment options are required.

    This presentation will outline the benefits of a collaborative, inter-disciplinary approach to address key challenges in breast cancer, in particular in relation to the personalisation of therapy. A working case model will be provided of a virtual Collaborative Cancer Research Centre, BREAST-PREDICT (www.breastpredict.com), which tackles clinical needs with respect to the development of more individualised therapies for breast cancer. The BREAST-PREDICT model incorporates the diverse skill sets of several disciplines, including biological, mathematical, computational, pharmaco-epidemiological and systems medicine approaches, in order to determine how to treat individual breast cancer patients according to the particular characteristics of their own cancer.

    BREAST-PREDICT is consolidating existing breast cancer biobank and data resources, and making these available for research projects. Pharmaco-epidemiology approaches are being employed to determine the effects of previous drug exposures on outcome, and multi-omic analyses are being performed on longitudinal samples from primary and metastatic tumours, in order to map the molecular evolution of breast cancer. The group is also leveraging these resources in order to identify new therapeutic targets and combinatorial treatment strategies for specific subtypes, and to develop new tools for improved prediction of patient outcome and response to treatment. The presentation will outline the benefit of this approach and how it can be used to fast-track progress towards personalised therapy in breast cancer.

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