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In July 2014 the European Translational Research Network in Ovarian Cancer (EUTROC), held its annual conference in London. High on its agenda was cancer's resistance to established drugs.

Cancer is a complex disease. It arises from random "errors" in our genes, which regulate the growth of cells that make-up our bodies. Error-laden cells either die or survive, and multiply as a result of complex changes that scientists don't fully understood.
 
Translational medicine
Translational medicine is a rapidly growing discipline in biomedical research, which benefits from a recent technological revolution that allows scientists to monitor the behaviour of everyone of our 25,000 genes, identify almost every protein in an individual cell, and work to improve cancer therapies.
 
Ovarian cancer is the forth most common form of cancer in women, after breast, lung and bowel cancer. Each year, in the UK some 7,000 people are diagnosed with ovarian cancer, in the US it's 240,000. Most women are diagnosed once the cancer has spread beyond the ovaries, which makes treatment challenging, and mortality rates high. Only 10% of women diagnosed with ovarian cancer at the latest stage survive more that five years. 
 
 
Molecular profiling
EUTROC employs a multi-disciplinary, collaborative, "bench-to-bedside" approach in order to expeditiously discover new therapies, which tailor medical treatment to the specific characteristics of specific cancers: personalised medicine.
 
Cancers are like people: not all are alike, and when examined at a molecular level they show that their genetic makeup is very different. Clinicians use molecular profiling to examine the genetic characteristics of a person's cancer as well as any unique biomarkers, which enables them to identify and create targeted therapies designed to work better for a specific cancer profile.
 
Combatting cancer resistance
Personalising treatment to target errors in specific cancers at the point of diagnosis fails to address the fact that cancers mutate in response to treatment. Even drugs that are initially effective may become ineffective as the cancer returns and re-establishes its ability to grow and spread. Cancer often behaves like a taxi navigating a way round a localised traffic jam

 

An approach to combat this is to treat a cancer with one target drug, and if the cancer returns with newly developed resistance, identify how that resistance occurred and target that with another drug, and so on, until the cancer and its resistances are beaten.  This is similar to accepting that a local traffic jam may be bypassed, and finding and blocking all the ways around the jam.
 
Another approach is to target and block something critical for the survival of a specific cancer. This is similar to blocking a strategic point that controls all the traffic coming in and leaving a city. For example, taxi drivers clogging up Trafalgar Square and bringing London to a standstill. But scientists are a long way from achieving this because researchers don't know whether such targets in relations to cancers exists, and even if they did, they don't know whether they can be blocked effectively. And, even if such targets were discovered and were blocked, scientists still don't know what would be the side effects of doing so. 
 
Takeaways
For personalised medicine to be successful, clinicians and scientists need to track the evolutionary trajectories of cancers in patients through sequential episodes of treatment and relapse. Besides being a major clinical and scientific challenge, this is also a significant informational and communication challenge, which networks such as EUTROC are addressing.
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joined 10 years, 5 months ago

Euan Stronach

Senior Investigator, GlaxoSmithKline

Euan gained a first class honours in Molecular Biology followed by a PhD in Medical Genetics from the University of Aberdeen.

In 2000 he joined Prof Hani Gabra and his team at the, then Imperial Cancer Research Fund now Cancer Research UK, unit in Edinburgh as a postdoctoral fellow.

From there he moved to Imperial College in 2003 where he ran the Molecular Therapy Lab within the Ovarian Cancer Action Research Centre. 

Since 2015 he is a Senior Investigator at GlaxoSmithKline.

Eaun is a Honorary Senior Lecturer at Imperial College London.


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Ioannis Pandis

Research Associate, Imperial College London

Dr Ioannis Pandis received a Ph.D. degree in Biological Chemistry from the BSRC “Al. Fleming” Institute in Athens, Greee in 2012.

From 2012, he has been working as a research associate at Imperial College. He is in the Discovery Science Group working on the European Innovatice Medicine Initiative (IMI), eTRIKs project, which is aimed at developing a translational information and knowledge management systems.

His personal interest is the development of bioinformatic applications enabling applied biomedical research, with a particular focus on genome regulation analysis.


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joined 10 years, 5 months ago

Ugo Cavallaro

Principal Investigator, European Institute of Oncology

Dr Cavallaro is a cell biologist and molecular oncologist interested in the biological mechanisms that underlie cancer development.

With his research group he discovered a novel interaction between the adhesion molecule NCAM and the receptor tyrosine kinase FGFR, introducing the paradigm that a growth factor receptor can be activated by a non-canonical ligand such as an adhesion molecule (Francavilla et al., J Cell Sci, 2007, and J Cell Biol, 2009).

His group also discovered that the NCAM/FGFR interaction plays a causal role in ovarian cancer, where it also emerged as a potential therapeutic target in preclinical models (Zecchini et al., EMBO Mol Med, 2011).

Another adhesion molecule that is intensively studied in his lab is L1, originally described as a neural adhesion molecule. They reported that L1 is expressed in specific lineages of the hematopoietic compartment, where it regulates immune cell motility and trafficking (Maddaluno et al., J Exp Med, 2009). Furthermore, his group reported that L1 plays a dual, cell context-dependent role in ovarian cancer (Zecchini et al, Cancer Res, 2008).

More recently, his research group became interested in the novel, unexpected role of adhesion molecules in tumor angiogenesis and vascular maturation. These observations led them to propose novel therapeutic target for anti-angiogenic treatments.

He is actively addressing these scientific issues in preclinical models and clinical samples of specific tumor types, such as pancreatic and ovarian carcinoma.

Another area of intense research in his group is the identification and characterisation of ovarian cancer stem cells, namely an elusive subset of transformed cells that is is thought to drive cancer development, dissemination, recurrence and chemoresistance.

Finally, they are actively pursuing the definition of novel ovarian cancer biomarkers and potential targets, combining cutting edge technologies with the use of clinically relevant specimens, taking advantage of a close collaboration with IEO gynecological oncologists


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Robert Zeillinger

Associate Professor and Founder and Head, Molecular Oncology Group, Dep. of Obstetrics and Gynaecology, Medical University of Vienna

Professor Robert Zeillinger is an Associate Professor at the Ludwig Boltzmann Institute for Gynecology and Gynecological Oncology, Department of Obstetrics and Gynecology, University of Vienna.

A graduate in biochemistry, Professor Zeillinger is also the founder and the head of the Molecular Oncology Group at The Department of Obstetrics and Gynaecology at the Medical University of Vienna. The main objectives of the group's research are understanding gynaecological cancers at molecular levels, improving diagnosis and prognosis and defining novel therapeutic targets.

The interdisciplinary group is engaged in various national and international organizations and networks (e.g. TOC – Tumor Bank Ovarian Cancer; EUTROC – European Network for Translational Research in Ovarian Cancer; OCTIPS – Ovarian Cancer Therapy Innovative Models; OVCAD – Ovarian Cancer Diagnosis; Ludwig Boltzmann Gesellschaft – Cluster Translational Oncology).


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joined 10 years, 6 months ago

Yike Guo

Professor of Computing Science

Yike Guo is a Professor of Computing Science in the Department of Computing at Imperial College London. He leads the Discovery Science Group in the department, as well as being the founding Director of the Data Science Institute at Imperial College.

Professor Guo also holds the position of CTO of the tranSMART Foundation, a global open source community using and developing data sharing and analytics technology for translational medicine.

Professor Guo received a first-class honours degree in Computing Science from Tsinghua University, China, in 1985 and received his PhD in Computational Logic from Imperial College in 1993 under the supervision of Professor John Darlington.

He founded InforSense, a healthcare intelligence company, and served as CEO for several years before the company's merger with IDBS, a global advanced R&D software provider, in 2009. He has been working on technology and platforms for scientific data analysis since the mid-1990s, where his research focuses on knowledge discovery, data mining and large-scale data management.

He has contributed to numerous major research projects including: the UK EPSRC platform project, Discovery Net; the Wellcome Trust-funded Biological Atlas of Insulin Resistance (BAIR); and the European Commission U-BIOPRED project. He is currently the Principal Investigator of the European Innovative Medicines Initiative (IMI) eTRIKS project, a €23M project that is building a cloud-based informatics platform, in which tranSMART is a core component for clinico-genomic medical research, and co-Investigator of Digital City Exchange, a £5.9M research programme exploring ways to digitally link utilities and services within smart cities.

Professor Guo has published over 200 articles, papers and reports. Projects he has contributed to have been internationally recognised, including winning the “Most Innovative Data Intensive Application Award” at the Supercomputing 2002 conference for Discovery Net, and the Bio-IT World "Best Practices Award" for U-BIOPRED in 2014. He is a Senior Member of the IEEE and is a Fellow of the British Computer Society.


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