p-Medicine: From data sharing and integration via VPH models to personalized medicine

The Worldwide innovative Networking in personalized cancer medicine (WIN) initiated by the Institute Gustave Roussy (France) and The University of Texas MD Anderson Cancer Center (USA) has dedicated its 3rd symposium (Paris, 6–8 July 2011) to discussion on gateways to increase the efficacy of cancer diagnostics and therapeutics (http://www.winconsortium.org/symposium.html). Speakers ranged from clinical oncologist to researchers, industrial partners, and tools developers; a famous patient was present: Janelle Hail, a 30-year breast cancer survivor, founder and CEO of the National Breast Cancer Foundation, Inc. (NBCF). The p-medicine consortium found this venue a perfect occasion to present a poster about its activities that are in accordance with the take home message of the symposium. In this communication, we summarize what we presented with particular attention to the interaction between the symposium’s topic and content and our project.

[1]  Fabrice Andre,et al.  Implications of personalized medicine—perspective from a cancer center , 2011, Nature Reviews Clinical Oncology.

[2]  G. Misener,et al.  Short Communication , 1990, American Potato Journal.

[3]  Y. Pekarsky,et al.  Reprogramming of miRNA networks in cancer and leukemia. , 2010, Genome research.

[4]  Yudong D. He,et al.  Gene expression profiling predicts clinical outcome of breast cancer , 2002, Nature.

[5]  L. Hood,et al.  Predictive, personalized, preventive, participatory (P4) cancer medicine , 2011, Nature Reviews Clinical Oncology.

[6]  David Gavaghan,et al.  The virtual physiological human: tools and applications II , 2009, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[7]  David Cameron,et al.  A stroma-related gene signature predicts resistance to neoadjuvant chemotherapy in breast cancer , 2009, Nature Medicine.

[8]  Hyunsoo Kim,et al.  Single-nucleotide polymorphisms inside microRNA target sites influence tumor susceptibility. , 2010, Cancer research.

[9]  Leroy Hood,et al.  Systems biology, proteomics, and the future of health care: toward predictive, preventative, and personalized medicine. , 2004, Journal of proteome research.

[10]  M. Cronin,et al.  A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. , 2004, The New England journal of medicine.

[11]  Marco Viceconti.  The Virtual Physiological Human , 2007, ERCIM News.

[12]  L. Garraway,et al.  Clinical implications of the cancer genome. , 2010, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[13]  Juri G. Gelovani,et al.  Methodological and practical challenges for personalized cancer therapies , 2011, Nature Reviews Clinical Oncology.

[14]  T. Eberlein.  A Multigene Assay to Predict Recurrence of Tamoxifen-Treated, Node-Negative Breast Cancer , 2006 .

[15]  Gabriella Pravettoni,et al.  P5 medicine: a plus for a personalized approach to oncology , 2011, Nature Reviews Clinical Oncology.

[16]  David Gavaghan,et al.  The virtual physiological human: tools and applications I , 2009, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[17]  Charles Auffray,et al.  Predictive, preventive, personalized and participatory medicine: back to the future , 2010, Genome Medicine.