Fátima Al-Shahrour, from the CNIO in Madrid, came last week to the PRBB to give a talk entitled “Bioinformatics challenges for personalized medicine”. She explained what they do at her Translational Bioinformatics Unit in the Clinical Research Programme. And what they do is both exciting and promising.
They start with a biopsy of a tumour from a cancer patient who has relapsed after some initial treatment – they concentrate mostly in pancreatic cancer, but it would work with any, in principle. From this sample, they derive cell lines, but also – and they are quite unique in this – they generate a personalised xenograft. That is, they implant the human tumour in an immunocompromised mouse, creating an ‘avatar’ of the patient. After passing it from one mouse to another (they do about 60 mice per patient), they extract the tumour to analyse it by exome sequencing (and sometimes gene expression data, etc). They then have about 8 weeks to find, using bioinformatics, druggable targets that they then test on the avatar. Those drugs that work on the mouse are then given to the patient.
The advantages of this system are many and obvious: not only the in vivo model can be used to validate the hypothesis generated by the genetic analysis, but we basically have a personalised cancer model for a patient in which we can try as many drugs as we want. It can be cryopreserved, so we have unlimited access to the sample. And, since cancer is not a disease we can cure yet, but instead patients must keep checking out for possible relapses, metastasis, or resistances to treatment, keeping the mouse in parallel with the patient can help predicting how the patient will react to all these: whether he will develop resistance to the drug, which other mutations might appear, etc.
But there are several disadvantages, too. One is hinted in Fátima’s talk title: the bioinformatics analysis of the tumours to find which mutations are important (drivers) in the disease and which can have drugs that affect them is challenging, not the least because an individual cancer genome can have hundreds to thousands of mutations.
Perhaps the biggest barrier is that, at the moment, making these avatars is inefficient, very expensive and slow. And since the patients who are benefit from this technology are already in a very bad clinical condition, many of them don’t get to live enough to enjoy those benefits. But there are some successful cases, and Fátima mentioned a couple. In one case, a man with pancreatic cancer who was treated with mitomycin after all the tests in his avatar, survived more than 5 years, when he had been given 1 year at the most.
So there is hope in the field of personalised medicine, despite the fact that this is still not standard, and won’t probably be for the near future. And, as someone in the audience mentioned, in an ideal future, we might even have personalised prevention, according to our genetic makeup. Wouldn’t that be great?
A report by Maruxa Martinez, Scientific Editor at the PRBB
An interview published in Ellipse, the monthly magazine of the PRBB.
Vivek Malhotra was born in India 50 years ago and received his formal education in England. After graduating from Oxford, he went to the US as a postdoc at Stanford. He was a professor at the University of California in San Diego where he has spent most of his life. Married to a Basque biologist, in 2008 he came to the PRBB where he coordinates the Cell and Developmental Biology programme of the CRG.
What differences are there between here and the US?
Americans are goal oriented and very driven. They want to solve problems whatever the cost. They are aggressive and critical. And that’s how they have managed to advance so much. I have the feeling that in Spain people are scared of criticising. Consequently they cannot deal with criticism very well. Healthy criticism is essential for change and success.
Are we talking about science?
Criticism is essential in all aspects of life, but especially important for science. As the Greek philosopher Thales said, biology, unlike maths, is not complete, accurate, and permanent. It is open to interpretation, today’s proposal may need to be revised later on based on new knowledge and one should be willing to accept that.
Why did you come to Barcelona?
After 23 years in California I was bored. And even though I took a salary cut I am very happy here. At the CRG, I am able to do science at the same level I used to. I can see myself staying here for the rest of my career. The only thing that scares me is the general ’laissez faire’ attitude to the long-term potential of basic science. Spain needs to invest more in education, long-term and at all levels: school, university and research centres. There are now good research centres in Spain, but far too few. Jordi Camí deserves a lot of credit for building up the PRBB. If we had 2 or 3 more Jordis who could build 2 or 3, or even one more centre like this in the next 5 years, it would be terrific.
What is the best advice you have ever received?
“Work on something you think you might be able to solve in your lifetime”. I have followed this suggestion and focused on key aspects of protein secretion. We have made significant discoveries, some of which could lead to the development of therapeutics for chronic obstructive pulmonary diseases. Drug development, however, is not for me. I dislike the corporate aspect of science.
What is a normal day for you?
I walk to work, which takes about 25 minutes. This gives me time to focus on the key issues for the day. When I get to work I talk to the people in my lab, and in fact I keep on doing that all day. On average every 10 mins I abandon the computer and walk around the lab and my floor, and generally bother people by repeatedly asking if they have anything new. Most people hide when they see me coming but the brave and passionate ones take the bait and we have fun talking. I do not have a set routine but I try to communicate regularly with my friends both here and in the US. My iPhone is always on. If I am awake at 3am and come up with a useful idea I send an email right away to my lab members. So there is no time limit for work. However, I am learning to keep my evenings free for my family.
This interview was published in the PRBB monthly newspaper, Ellipse.
You can also read an earlier post about his talk here.
Figuring out how the brain works is the obsession of Rodrigo Quian, professor at the University of Leicester (UK). This challenge led him to apply his physics training and a PhD in maths to neuroscience. With the discovery of the “Jennifer Aniston neurone”, or concept cells, it seems we have taken a step towards the understanding of memory.
How can we “see” neurones?
We work on patients with epilepsy requiring hippocampus surgery. As part of this they have electrodes attached to the brain for several hours. This allows us to talk to them and detect how the neurones respond to stimuli we present them with.
Why the Jennifer Aniston neurone?
We did experiments where we showed patients people close to them like relatives and celebrities. The first neurone I found responded to pictures of Jennifer Aniston. It was a shock to discover that somewhere in the brain are neurones that respond in such a specific way to abstract concepts.
Did it only respond to photos?
It responded to various photos of Aniston, images as different in colour and format as we were able to find. The same with her name when written or spoken. Specifically, to the ‘concept’ of Jennifer Aniston. We found neurones that responded to different famous people depending on the person. The only neurones that did not respond were in an autistic patient.
One neurone per concept?
If I could find one neurone that responded to Jennifer Aniston, there must be more because if it was the only one, the probability of me finding it among the thousands of neurones in that area is practically zero. There has to be a network of neurones that encode a concept. These concept cells can quickly generate associations, so there are neurones that respond to two concepts, but they are always related to one another. This is a key mechanism for generating memories. I think they are the building blocks of memory and the link between perception and memory. This is a radically different idea to what was believed until now, that the basis of memory was distributed networks of millions of neurones.
Can you locate complex thoughts like phobias?
Often a complex thought is an association of simple thoughts. My old mentor at Caltech, Christof Koch, said it was necessary to break down the difficult problem of consciousness into related problems that are simpler and easier to attack. The consciousness of self is a very complex thing. One must first understand how the flow of consciousness works. That is, that one thing makes me think about another thing and that about another and so on. This can be studied in the neurones generating associations between two concepts and, from the moment we have made this association, we can see if the neurone also responds to the association and encodes it. In a few tests we have found that these concept cells begin to respond to the association we have created.
What other experiments are you working on?
We want to know if neurone response changes according to the presentation of the stimulus, for example the exposure time to the photos. The results demonstrate that neural response is closely related to the conscious perception of the patient. That is, if the patient believes that he has seen something, then the neurone is activated. In fact, it is even possible to predict beforehand when neurones will be activated and know what image a patient is looking at only from the neurone records.
The 5th Open Day at the Barcelona Biomedical Research Park (PRBB) opens this edition of El·lipse, the park’s monthly newspaper.
Other news include the celebration of the CRG 10th anniversary, new proteins important for cell division or for tumour growth, how stem cell dysfunction links cancer and ageing or a new drug against skin cancer. You will also learn about the “Jennifer Aniston” neurone from Rodrigo Quian, from the University of Leicester (UK), or about the effects of radiations from mobile phones on our health, a subject that Elisabeth Cardis (CREAL) and her group are studying.
The Computer-Assisted Drug Design (CADD) laboratory of the GRIB is devoted to the area of drug design and development. Directed by Manuel Pastor, who started the group 10 years ago at the IMIM, it includes pharmacists, biologists, chemists, and a mathematician. “We also had a telecommunications engineer at one point. Our research needs experts in both science and programming”, justifies Pastor.
The group’s interests are divided into three main areas. The first is methodological: they have written several programs marketed and are used by many pharmaceutical companies. The most recent one is Pentacle, which allows the creation of models relating the structure with the activity of a compound, as well as the computation of molecular descriptors. “Molecular descriptors are used to convert a real molecule into a computer representation, so they are needed in pretty much all steps of drug development”, explains the head of the group. Another software tool created by the group a few years ago is Shop. “Imagine you have a molecule that has the desired effect, but it cannot be used: because, for example, it’s toxic, or not soluble enough. With Shop you can remove the fragment that causes the problem and substitute it for another that will maintain the same biological activity without the side effect”.
A second research area is structure-based drug design (SBDD), which they apply to the study of schizophrenia. In collaboration with other groups in Santiago de Compostela they are looking at potential drug targets for the disease to try to find new compounds that can bind them.
The most recent and active research area is focused on drug safety. The group coordinates the IMI (Innovative Medicines Initiative) project eTOX, which aims to develop methodologies to predict toxic properties of new compounds in silico (with the help of computers) and as early as possible. “This project involves pretty much all the big pharmaceutical companies in Europe, as well as some of the best European academic groups in cheminformatics”- says Pastor – “Pharma companies have realised that what is making it difficult for them is not the competition, but the intrinsic complexity of the problem. They have run out of easy targets, and the existing methodologies are not working that well finding good drugs for the difficult ones. So they are starting to join forces”.
Another upcoming IMI project Pastor is excited about is OpenPhacts (Open Pharmacological Space). As with eTox, Pastor will collaborate with Ferran Sanz and other GRIB members, to contribute to this project which “will change the scene completely”, promises the head of CADD. “There is a lot of information publically available information that is of interest to pharmaceutical companies: data on compounds, structures and, pathways. But it’´s all dispersed, and the industry is spending huge amounts of money trying to collect and exploit this information. OpenPhacts will bring together make pertinent enquiries, such as: is there a compound similar to this one involved in this specific pathway? The CADD group will contribute by assessing these relevant questions. “The drug companies know what they need, and the technical experts know what can be done. We are the intermediaries, we know about both worlds”, concludes Pastor.
This article was published in the El·lipse publication of the PRBB.
A new article in which the groups of Jordi Mestres and José Yelamos, both at the IMIM, have collaborated, represents an example of how many gaps there are in our knowledge of biological processes, and of the potential danger of this lack of knowledge might cause.
In this case, the focus is small molecules. These are widely used in chemical biology, usually as inhibitors to try to understand the function of specific proteins they target. But despite the fact they are commonly used, we don’t have a complete knowledge of their target profile, and they might have unknown off-target interactions. Therefore the conclusions we get from their effects might include a big confounding effect that is not taken into account.
In this paper published in ACS Chemical Biology Mestres and Yelamos show that this is precisely the case with the PJ34 small molecule, which is used to study the role of the PARP proteins, a family of proteins which play an important role in DNA repair, cell death and proliferation, and in the stabilization of the genome.
The authors have found that PJ34 not only inhibits PARP1, but it also has high affinities for Pim1 (IC50 = 3.7 µM) and Pim2 (IC50 = 16 µM) serine/threonine kinases, which are involved in many of the processes relevant to PARP biology. This result questions the appropriateness of using PJ34 as a chemical tool to probe the biological role of PARP1 and PARP2 at the high micromolar concentrations applied in most studies.
Antolín AA, Jalencas X, Yélamos J, Mestres J. Identification of Pim Kinases as Novel Targets for PJ34 with Confounding Effects in PARP Biology. ACS Chem Biol. 2012 Oct 1;
Complex genetic disorders often involve multiple proteins interacting with each other, and pinpointing which of them are actually important for the disease is still challenging. Many computational approaches exploiting interaction network topology have been successfully applied to prioritize which individual genes may be involved in diseases, based on their proximity to known disease genes in the network.
In a paper published in PLoS One, Baldo Oliva, head of the Structural bioinformatics group at the GRIB (UPF–IMIM) and Emre Guney, have presented GUILD (Genes Underlying Inheritance Linked Disorders), a new genome-wide network-based prioritization framework. GUILD includes four novel algorithms that use protein-protein interaction data to predict gene-phenotype associations at genome-wide scale, and the authors have proved that they are comparable, or outperform, several known state-of-the-art similar approaches.
As a proof of principle, the authors have used GUILD to investigate top-ranking genes in Alzheimer’s disease (AD), diabetes and AIDS using disease-gene associations from various sources.
GUILD is freely available for download at http://sbi.imim.es/GUILD.php
Guney E, Oliva B. Exploiting Protein-Protein Interaction Networks for Genome-Wide Disease-Gene Prioritization. PLoS One. 2012;7(9):e43557
David Searls retired three years ago from his position as senior Vice President of Bioinformatics in GlaxoSmithKline. Since then, this computer scientist who spent 16 years in academia and 19 years in industry has gone back to his theoretical studies on linguistic analysis of biological sequences. He was invited to the PRBB and talked to us about drugs and computers.
This interview was published in Ellipse, the monthly magazine of the PRBB.
What part does bioinformatics have in drug development?
It is an essential step along the way. This is because not only drug discovery, but all biology, has become, since the human genome and the high throughput technologies, an information science. It is very data-intensive, and you need computers to analyse that data.
How is the industry crisis affecting the pharmaceutical companies?
The industry is indeed in great difficulty at the moment, as costs are increasing while the number of new drugs is going down. One way the large pharmaceutical companies are adapting is by starting to drop some of their therapeutic areas. Fundamentally, R+D is becoming smaller, due to the merging of companies and the reduction of costs. They are also depending more on in-licensing, i.e. buying drugs at different stages of development from smaller biotech companies or from universities. This way the ideas, the basic science and the early testing, are done by smaller companies while Big Pharma does only the last stage, the clinical trials, which is what they are best at. Basically, a more spread out economic model is being created.
Can bioinformatics help?
Yes, it can. One of the reasons why the cost of developing drugs is so high is that many of the molecules studied as potential drugs aren’t effective, or have undesired side effects. Better use of the information that predicts interactions between molecules can prevent early failure, since the side effects are usually due to interactions between the drug and proteins other than the target.
Another way bioinformatics can help is in drug repositioning, which is taking a drug that has been approved for one disease, and looking for other uses for it. Bioinformatics helps us find other protein interactions of a specific drug target, and predict which processes that target might be involved in, as well as potential effects. The advantage is that we already have data on the safety of the drug, which is one of the most costly procedures.
What will be the role of bioinformatics in personalised medicine?
It is already helping to classify diseases via the analysis of transcriptomics, i.e. which genes are activated in each tissue. This allows us to find subtypes of an apparently homogeneous tumour that are susceptible to different drugs. We can then check the expression pattern of the patients to decide which treatment is best for them. Also, personalised medicine won’t be one drug for one individual, but a combination of drugs for each individual. Again, bioinformatics will help with the prediction of which combinations will be more useful.
The extra finger of the chicken
In this image from the CMRB we can see the induction of an extra finger in the interdigital space of a chicken. This finger has grown thanks to a microsphere (the blue dot in the image) that is covered in Activin A, a molecule with the ability to form cartilage. The microsphere was introduced in the interdigital space of the chicken embryo when it was 5 days old. After incubating it for 3 more days, the Activin A has induced the formation of the finger.
Research on human aging is a hot topic nowadays, due to a growing aging population and the consequent prevalence of aging-associated diseases such as Alzheimer’s, arthritis or cardiovascular diseases. Researchers at the CMRB review the use of human induced pluripotent stem cells (hiPSC) to study the fundamental mechanisms underlying aging in this article published in Current Opinion in Cell Biology.
Indeed, hiPSC-based models of aging and aging-related diseases are facilitating the study of the molecular and cellular mechanisms underlying aging. For example, the use of iPSCs from patients with accelerated aging (like those with Hutchinson–Gilford progeria syndrome) could recapitulate the aging process in vitro much faster than the several decades needed for normal human tissue to age. Also, cell and organ derivatives from patient-specific iPSCs can be transplanted into animal models and the integrated human living materials could provide an opportunity to study human tissue and organ aging or disorders in an in vivo context.
Liu GH, Ding Z, Izpisua Belmonte JC. iPSC technology to study human aging and aging-related disorders. Curr Opin Cell Biol. 2012 Sep 18;