Miraca Holdings Inc., a Japan-based holding company in the healthcare sector, recently announced that its affiliate Innogenetics N.V. in Ghent (Belgium) had changed its name to Fujirebio Europe N.V. The name change is the next logical step in an integration process that was launched by the acquisition in September 2010 of Innogenetics N.V. by Fujirebio Inc., a subsidiary of Miraca Holdings. Fujirebio is recognized as a key player in oncology for routine and novel IVD markers. Th e name change confirms Fujirebio’s strong commitment to the introduction of the Lumipulse immunoanalyser range in laboratories across Europe. The Lumipulse G1200 was presented to the European market for the first time in Italy in November 2011 and this fully automated chemiluminescent enzyme immunoassay (CLEIA) system is now available to laboratories in Spain and will soon be available in Germany and France.

For more than 100 years, researchers have been unable to explain why cancer cells contain abnormal numbers of chromosomes, a phenomenon known as aneuploidy. Many believed aneuploidy was simply a random by-product of cancer.

Now, a team at Harvard Medical School has devised a way to understand patterns of aneuploidy in tumours and predict which genes in the affected chromosomes are likely to be cancer suppressors or promoters. They propose that aneuploidy is a driver of cancer rather than a result of it.
‘If you look at a cancer cell, it looks like an unholy mess with gene deletions and amplifications, chromosome gains and losses, like someone threw a stick of dynamite into the cell. It seems random, but actually previous work has shown that there is a pattern to which chromosomes and chromosome arms are altered—and that means we can understand that pattern and how or if it drives cancer,’ said senior author Stephen Elledge, Gregor Mendel professor of Genetics and of Medicine at HMS and professor of medicine at Brigham and Women’s Hospital.

‘What we have done is to propose a new theory about how this works and then prove it using mathematical analysis,’ he said.
For decades since the ‘oncogene revolution,’ cancer research has focused on mutations—changes in the DNA code that abnormally activate genes that promote cancer, called oncogenes, or deactivate genes that suppress cancer. The role of aneuploidy—in which entire chromosomes or chromosome arms are added or deleted—has remained largely unstudied.

Elledge and his team, including research fellow and first author Teresa Davoli, suspected that aneuploidy has a significant role to play in cancer because missing or extra chromosomes likely affect genes involved in tumour-related processes such as cell division and DNA repair.

To test their hypothesis, the researchers developed a computer program called TUSON (Tumour Suppressor and Oncogene) Explorer together with Wei Xu and Peter Park at HMS and Brigham and Women’s. The program analysed genome sequence data from more than 8,200 pairs of cancerous and normal tissue samples in three pre-existing databases.

They generated a list of suspected oncogenes and tumour suppressor genes based on their mutation patterns—and found many more potential cancer drivers than anticipated. Then they ranked the suspects by how powerful an effect their deletion or duplication was likely to have on cancer development.

Next, the team looked at where the suspects normally appear in chromosomes.

They discovered that the number of tumour suppressor genes or oncogenes in a chromosome correlated with how often the whole chromosome or part of the chromosome was deleted or duplicated in cancers. Where there were concentrations of tumour suppressor genes alongside fewer oncogenes and fewer genes essential to survival, there was more chromosome deletion. Conversely, concentrations of oncogenes and fewer tumour suppressors coincided with more chromosome duplication.

When the team factored in gene potency, the correlations got even stronger. A cluster of highly potent tumour suppressors was more likely to mean chromosome deletion than a cluster of weak suppressors.
Since 1971, the standard tumor suppressor model has held that cancer is caused by a ‘two-hit’ cascade in which first one copy and then the second copy of a gene becomes mutated. Elledge argues that simply losing or gaining one copy of a gene through aneuploidy can influence tumour growth as well.

‘The loss or gain of multiple cancer driver genes that individually have low potency can add up to have big effects,’ he said.

‘It’s a terrific study,’ said Angelika Amon, a professor of biology at Massachusetts Institute of Technology who was not involved in the project. ‘These novel algorithms of identifying tumour suppressors and oncogenes nicely provide an explanation of how aneuploidies evolve in cancer cells, and the realisation that subtle changes in the activity of many different genes at the same time can contribute to tumorigenesis is an exciting and intriguing hypothesis.’

These findings also may have answered a long-standing question about whether aneuploidy is a cause or effect of cancer, leaving researchers free to pursue the question of how. Harvard Medical School

A study by researchers in Nottingham has identified seven distinct types of breast cancer, a discovery which could lead to new and improved prognostic tests for patients with the disease.
The findings could revolutionise the way in which breast cancer patients are treated by giving clinicians more detailed information about a patient’s breast cancer type and helping them create a more personalised treatment plan, avoiding over or under-treatment.
Dr Green said: ‘With an increasing number of treatment options available for breast cancer patients, decision making regarding the choice of the most appropriate treatment method is becoming increasingly complex. Improvements in care and outcome for patients with breast cancer will involve improved targeting of effective therapies to appropriate patients.
‘Equally important should be improvement in parallel strategies to avoid unnecessary or inappropriate treatment and side effects.’
Breast cancer is a biologically complex disease and each tumour can have very different properties, so the more information that doctors have about each patient’s cancer, the better they can plan treatments. Currently just two proteins are tested for as standard in breast cancer cells (known as biomarkers): the oestrogen receptor (ER), and human epidermal growth factor receptor 2 (HER2), alongside information about the tumour size, spread and grade.
Dr Green and colleagues, who also included Professor Ian Ellis in the Division of Oncology and Jon Garibaldi and Daniele Soria in the University’s School of Computer Science, wanted to see if, by testing for more biomarkers, but keeping the number of biomarkers as low as possible to make an affordable test a realistic proposition, they could devise categories that better reflect the diversity of breast cancer and, importantly, better predict how a patient’s cancer is likely to progress.
Using tissue that now forms part of the Breast Cancer Campaign Tissue Bank, the team tested 1073 tumour samples and from these, 997 (93%) fitted perfectly into one of seven classes, whereas 76 (7%) had mixed characteristics and couldn’t be put into a distinct category. They then verified these classes in another 238 tumour samples.
The seven classes are defined by different combinations and levels of ten biomarkers found in breast cancer cells. These biomarkers include ER and HER2, the two biomarkers currently tested for in clinics, but also others that are not currently tested for, such as p53, cytokeratins, HER3 and HER4.
To test whether the new classes could give doctors more information about prognosis, Dr Green’s team compared the classes to survival outcomes from the patient samples. Each of the seven classes was found to have its own unique survival outcome. This indicates that the classes can tell us more about prognosis and help doctors to fine-tune treatment plans to improve survival.
Importantly, the technology required to measure protein biomarkers in tumour samples is already in place in most pathology laboratories across the UK, whereas newly developed genetic profiling tests such as Oncotype DX need to be sent to specialist laboratories, which brings additional costs. University of Nottingham

Recent research from University of Copenhagen sheds light on previously unknown facts about muscular dystrophy at molecular level. The breakthrough is hoped to improve future diagnosis and treatment of the disease. Researchers have developed a method that will make it easier to map the proteins that have an important kind of sugar monomer, mannose, attached. This is an important finding, as mannose deficiency can lead to diseases such as muscular dystrophy.
About 3,000 people in Denmark suffer from one of the serious muscle-related diseases that come under the heading of muscular dystrophy. Some patients diagnosed with muscular dystrophy die shortly after birth, others become severely retarded and develop eye problems, while certain groups are confined to life in a wheelchair. Common to all muscular dystrophy sufferers is the difficulty of their muscle cells to attach themselves to each other and to the surrounding tissue. However, little is actually known about the root causes of the disease.

New basic research from University of Copenhagen now offers insight into previously unknown facts about muscular dystrophy that may improve future diagnosis and treatment of the disease.

‘Our new research findings may shed light on some of the cellular processes that take place in connection with, for example, muscular dystrophy. This is important information because it is crucial for us to gain as detailed an understanding as possible about the individual cell components. Although the journey from the current basic research to any potential treatment options or diagnostic tools is a long one, our discoveries give grounds for optimism,’ says postdoc Malene Bech Vester-Christensen – who carried out the new experiments from her base at the Faculty of Health and Medical Sciences, University of Copenhagen, and has since taken up a research position at Novo Nordisk.
The new method developed by researchers makes it easier to map the proteins that The protein previously associated with muscular dystrophy is a so-called glycoprotein – a protein with chains of sugar molecules attached. The special kind of sugar attached to these glycoproteins is called mannose. A functional pathway for binding mannose to the proteins is key to the functioning of the human organism, and genetic defects in the process that attaches mannose to the proteins – known as O-mannosylation – can lead to diseases such as muscular dystrophy.

‘To date, only one single protein has been identified and characterised where the mannose deficiency on the protein leads to muscular dystrophy, but our method enables us to faster identify many new proteins that have mannose attached and therefore potentially play a key role for the disease,’ says Adnan Halim, who is associated with the research project and a postdoc with the Danish National Research Foundation, Copenhagen Center for Glycomics. University of Copenhagen

A pilot study by a multi-disciplinary team of investigators at Georgetown University suggests that a simple dot test could help doctors gauge the extent of dopamine loss in individuals with Parkinson’s disease (PD).

‘It is very difficult now to assess the extent of dopamine loss — a hallmark of Parkinson’s disease — in people with the disease,’ says lead author Katherine R. Gamble, a psychology PhD student working with two Georgetown psychologists, a psychiatrist and a neurologist. ‘Use of this test, called the Triplets Learning Task (TLT), may provide some help for physicians who treat people with Parkinson’s disease, but we still have much work to do to better understand its utility,’ she adds.

Gamble works in the Cognitive Aging Laboratory, led by the study’s senior investigator, Darlene Howard, PhD, Davis Family Distinguished Professor in the department of psychology and member of the Georgetown Center for Brain Plasticity and Recovery.

The TLT tests implicit learning, a type of learning that occurs without awareness or intent, which relies on the caudate nucleus, an area of the brain affected by loss of dopamine.

The test is a sequential learning task that does not require complex motor skills, which tend to decline in people with PD. In the TLT, participants see four open circles, see two red dots appear, and are asked to respond when they see a green dot appear. Unbeknownst to them, the location of the first red dot predicts the location of the green target. Participants learn implicitly where the green target will appear, and they become faster and more accurate in their responses.

Previous studies have shown that the caudate region in the brain underlies implicit learning. In the study, PD participants implicitly learned the dot pattern with training, but a loss of dopamine appears to negatively impact that learning compared to healthy older adults.
‘Their performance began to decline toward the end of training, suggesting that people with Parkinson’s disease lack the neural resources in the caudate, such as dopamine, to complete the learning task,’ says Gamble.

In this study of 27 people with PD, the research team is now testing how implicit learning may differ by different PD stages and drug doses.

‘This work is important in that it may be a non-invasive way to evaluate the level of dopamine deficiency in PD patients, and which may lead to future ways to improve clinical treatment of PD patients,’ explains Steven E. Lo, MD, associate professor of neurology at Georgetown University Medical Center, and a co-author of the study.

They hope the TLT may one day be a tool to help determine levels of dopamine loss in PD. EurekAlert