Mapping cancer’s ‘social networks’ opens new approaches to treatment

Cancer Research UK-funded scientists have designed a computer model that applies techniques used to analyse social networks to identify new ways of treating cancer, according to research published in PLOS Computational Biology. The model analyses the unique behaviours of cancer-causing proteins – spotting what makes them different from normal proteins, and mapping out molecular targets for new potential drugs that could be developed to treat cancer.

Scientists at The Institute of Cancer Research, London, compared proteins inside cells to members of an enormous social network, mapping the ways they interact. This allowed them to predict which proteins will be most effectively targeted with drugs.The researchers have made this map publicly available. It could provide drug discovery scientists with a shortcut to finding new drugs for many different types of cancer.

The team found that there are many molecular pathways that interact to affect the development of cancer. Cancer-causing proteins that have already been successfully targeted with drugs tended to have particular ‘social’ characteristics that differ from non-cancer proteins – suggesting that previously unexplored cancer proteins with similar characteristics could also make good drug targets.

‘Hub-like’ proteins which ‘communicate’ with lots of other proteins – like a super-Facebook user with thousands of friends – were more likely to cause cancer.This information could provide a wide range of potential targets for drug development.

Study leader Dr Bissan Al-Lazikani, Team Leader in Computational Biology and Cancer Research UK-funded scientist at The Institute of Cancer Research, London, said: “Our study is the first to identify the rules of social behaviour of cancer proteins and use it to predict new targets for potential cancer drugs. It shows that cancer drug targets behave very differently from normal proteins and often have a complex web of social interactions, like a Facebook super-user.

Finding new targets is one of the most important steps in drug discovery. But it can be a lengthy, expensive process. The map that we’ve made will help researchers design better new drugs, more quickly, saving time and money. It also sheds light on how resistance to treatments may occur, and in just a few years could help doctors choose the best drug combinations to suit individual patients.”
Nell Barrie, Cancer Research UK’s senior science information manager said: “Thanks to research, cancer survival has doubled in the last 40 years. But we urgently need to develop better, more effective treatments so that in the future no one has to fear a cancer diagnosis. Research like this, that’s made publicly available, will help speed up crucial advances in drug discovery to save more lives from cancer.

Mitsopoulos et al. Distinctive Behaviors of Druggable Proteins in Cellular Networks.  PLoS Comput Biol. 2015; 11(12): e1004597. doi:10.1371/journal.pcbi.1004597 [Article]

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New smart robot accelerates cancer treatment research

A new smart research robot accelerates research on cancer treatments by finding optimal treatment combinations. 

Complex diseases like cancer are almost exclusively treated by combining several different drugs. These combinations are typically composed from drugs that show an effect on their own, but do not necessarily constitute the best possible combinations. The new robot system finds optimal treatment combinations and was developed by a research group led by Dr Mats Gustafsson, Professor of Medical Bioinformatics at Uppsala University.

We have built a robot system that plans and conducts experiments with many substances, and draws its own conclusions from the results. The idea is to gradually refine combinations of substances so that they kill cancer cells without harming healthy cells‘, says Dr Claes Andersson, also a leading scientist in the project.

Instead of just combining a couple of substances at a time, the new lab robot has the ability to handle on the order of a dozen drugs simultaneously. The aim for the future is to be able to handle many more, preferably hundreds.

We are now one among the few laboratories in the world with this type of lab robot. However, so far researchers have only used the systems to look for combinations that kills the cancer cells, not taking the side effects into account‘, says Mats Gustafsson.

The next step in the development is to make the robot system more automated and smarter. The current version still involves a few manual steps that could be automated. The scientists also want to build more prior knowledge into the guiding algorithm of the robot, for example, prior knowledge about drug targets and disease pathways.

For patients with the same cancer type returning multiple times, sometimes the cancer cells develop resistance against the pharmacotherapy used. The new robot systems may also become important in the efforts to find new drug compounds that make these resistant cells sensitive again.

An article about the robot system was presented today in Scientific Reports, and is part of a doctoral thesis on drug combinations, recently defended by Dr Muhammad Kashif.

Kashif et al. In vitro discovery of promising anti-cancer drug combinations using iterative maximisation of a therapeutic index. Sci Rep. 2015;5:14118. doi: 10.1038/srep14118 [Article]

New general concept for the treatment of cancer

A team of researchers from five Swedish universities, led by Karolinska Institutet and the Science for Life Laboratory, have identified a new way of treating cancer. The concept is presented in the journal Nature and is based on inhibiting a specific enzyme called MTH1, which cancer cells, unlike normal cells, require for survival. Without this enzyme, oxidized nucleotides are incorporated into DNA, resulting in lethal DNA double-strand breaks in cancer cells.

To accelerate the development of this treatment principle and to proceed with clinical trials in patients as quickly as possible, we are working with an open innovation model. Even before publication, we have sent out MTH1 inhibitors to a range of research groups worldwide“, says Thomas Helleday, holder of the Söderberg Professorship at Karolinska Institutet, who heads the study.

In recent decades, the development of new anticancer agents has focused on targeting specific genetic defects in cancer cells. These are often effective initially, but are troubled with rapid resistance emerging. In the current study, the researchers present a general enzymatic activity that all cancers tested rely on and that seems to be independent of the genetic changes found in specific cancers. The research team shows that all the investigated cancer tumours need the MTH1 enzyme to survive. In this way, cancer cells differ from normal cells, which do not need this enzyme.

The concept is built on that cancer cells have an altered metabolism, resulting in oxidation of nucleotide building blocks“, says Thomas Helleday.”MTH1 sanitises the oxidized building blocks, preventing the oxidative stress to be incorporated into DNA and becoming DNA damage. This allows replication in cancer cells so they can divide and multiply. With an MTH1 inhibitor, the enzyme is blocked and damaged nucleotides enter DNA, causing damage and kill cancer cells. Normal cells do not need MTH1 as they have regulated metabolism preventing damage of nucleotide building blocks. Finding a general enzymatic activity required only for cancer cells to survive opens up a whole new way of treating cancer,”

To take the treatment concept to towards a clinical application, the scientists have taken a multidisciplinary collaboration strategy with researchers from five Swedish universities. They have produced a potent MTH1 inhibitor that selectively kills cancer cells in the tumours that have been surgically removed from skin cancer patients. Dr Roger Olofsson Bagge is a surgeon at Sahlgrenska University Hospital, and also affiliated with the Sahlgrenska Academy at the University of Gothenburg:

When we saw that the tumour from one of my melanoma patients who has developed resistance to all the current treatment actually responded very well to the treatment, we were extremely happy. It’s rare that you get to experience and witness such a breakthrough,” he says.

However, a lot of work remains to be done before it is time for clinical trials, which is likely to take at least one or two years, according to Thomas Helleday. In another article published in the same issue of Nature parts of the Swedish research team, together with collaborators in Austria and the UK present results showing that even previously identified substances that kill cancer cells work by inhibiting the MTH1 enzyme, something which has not been realised until now.

That existing anticancer agents hit the MTH1 shows that the concept really works. Now that we understand the mechanism, we can develop very selective inhibitors“, says Thomas Helleday.

Gad et al., (2014). MTH1 inhibition kills cancer by preventing sanitation of the dNTP pool. Nature, EPub Ahead of Print, doi: 10.1038/nature13181 [Abstract]

Huber et al., (2014). Stereospecific targeting of MTH1 by (S)-crizotinib as anticancer strategy. Nature, EPub Ahead of Print, doi: 10.1038/nature13194 [Abstract]

Racial disparities in health care among older male cancer survivors

Older African-American and Hispanic men who have survived cancer are less likely than their white counterparts to see a specialist or receive basic preventive care, such as vaccinations, according to new research from Wake Forest Baptist Medical Center.

Researchers examined racial/ethnic disparities in health care receipt among a nationally representative sample of male cancer survivors. They found that disparities are evident among older, but not younger, cancer survivors, despite their access to Medicare.

Lead author Nynikka Palmer, Dr.P.H., a postdoctoral fellow at Wake Forest Baptist, said they identified 2,714 men 18 and older from the 2006-2010 National Health Interview Survey who reported a history of cancer. The researchers looked at health care receipt in four self-reported measures: primary care visit, specialist visit, flu vaccination and pneumonia vaccination.

“Overall, our results suggest that older minority male cancer survivors may need specific support to ensure they receive necessary post-treatment care,” Palmer said.

The study was recently published online ahead of print in the American Journal of Public Health.

Even when the researchers adjusted for factors that contribute to disparities, such as education and health insurance, they found that African American and Hispanic male cancer survivors 65 years and older may not be receiving appropriate follow-up care and preventive care. Palmer said this is a concern “because regular follow-up care is important to monitor for recurrence, new cancers, and late and long-term effects of cancer and its treatment, particularly for those with more co-morbidities.”

Overall, among older survivors, approximately 39 percent of African-Americans and 42 percent of Hispanics did not see a specialist, compared with 26 percent of older non-Hispanic whites. Likewise, about 40 percent of African-American and Hispanic cancer survivors did not receive the flu vaccination, compared with 22 percent of non-Hispanic white cancer survivors.

Similarly, 51 percent of African-Americans and 59 percent of Hispanic cancer survivors did not report receiving the pneumonia vaccine, compared with 29 percent of non-Hispanic whites.

“These findings are consistent with other reports of health care use among cancer survivors and suggest there may be differences in types of Medicare health plans, supplemental insurance and out-of-pocket costs among older survivors that could be contributing to this disparity,” Palmer said.

Palmer said further study is needed to identify other factors that may influence racial/ethnic disparities among male survivors, such as patients’ beliefs about care after cancer and patient-provider communication.

Palmer et al., (2013). Racial/Ethnic Disparities in Health Care Receipt Among Male Cancer Survivors. Am. J. Public Health103: 1306-1313 [Abstract]