Whole genome sequencing of spermatocytic tumours

Speaker: Anne Goriely
Department: Josephine Nefkens Institute
Subject: Whole genome sequencing of spermatocytic tumours
Location: Erasmus MC
Date: 28-06-2017
Author: Renée van der Winden

Anne Goriely came to talk to us about her work on spermatocytic tumours. In her talk she first gave a lot of background information before going into detail about her latest findings. She started by giving us some information on spermatocytic tumours. These testicular tumours are very rare and mostly occur in older men. They are slow growing, but can become extremely large (3-30 cm in diameter). Luckily, the prognosis is usually very good. The cell of origin for these tumours is an adult spermatogonia. This is interesting, since the germline usually does not mutate because that is evolutionarily very disadvantageous. These mutations occur through a copy error during stem cell division and the mutation rate increases with age, which explains why these tumours are usually found in older men.

Seminar 7
Mutations found in relation to age (Goriely et al., 2017)

Next, Goriely brought up Apert syndrome. This disorder only has a paternal origin and the mutation causing it is spontaneous, which means it has to have occurred during spermatogenesis. It was found that the higher the age of the father, the more likely it was that the offspring would have the disorder. This is called the paternal age effect. Apert syndrome shares this feature with other disorders. It also turns out that only gain-of-function mutations are enriched with age. This can be beneficial for the current generation, but harmful for the next. That is why they are called ‘selfish mutations’.

Goriely’s lab searched for these selfish mutations in testis. To do so they made slices of testis and stained them. They found that there was a higher level of staining in some testicular tubes, which indicated mutated spermatogonia. These selfish clones can spread over large areas of the testis and different clones can be found in the same testis. It is even possible for mutated and non-mutated clones to be side by side in a tube. Some of these mutations are strong and thus lead to impaired spermatogenesis, but this is not the case for all mutations. It turns out that these selfish clones are more numerous with increasing age and that all men have them. In that sense they can be compared to moles on the skin.

Lastly, Goriely pointed out that when a distribution was made of the occurrence of spermatocytic tumours versus age, it turned out to be bimodal. Moreover, spermatocytic tumours are rare, while selfish mutations are common. This led to the belief that there might be a second source for these tumours. At this point whole genome sequencing was used to determine that aneuploidy occurs in the testis. Hypotheses connected to this finding are that aneuploidy comes before the selfish mutation and thus they might be passenger mutations. Thus aneuploidy might drive tumorigenesis. Moreover, aneuploidy can cause a gene imbalance, causing meiosis to fail so that the cell re-enters mitosis. This can lead to the giant tumours observed.

I thought this seminar was very easy to follow due to all the background information given. I liked the topic of the talk, but I do feel that for a large part of the talk we kept coming back to the same conclusion: that mutation rate goes up with age. I would be interested to see if the hypotheses given are true and what might then be done to help treatment of these tumours.


Molecular and functional heterogeneity in the human haematopoietic stem cell compartment

Speaker: Elisa Laurenti
Department: Cambridge Stem Cell Institute, University of Cambridge, Cambridge
Location: Erasmuc MC Rotterdam
Date: Juni 12, 2017
Author: Teun Huijben

Elisa Laurenti has been interested in stem cells during her entire academic carrier. After doing a PhD and PostDoc in this field, she now has her own lab at Cambridge, where she studies the heterogeneity in the human haematopoietic stem cell (HSC) compartment. In this one hour she introduced us to the field and explained the research she has performed in the last years.

The main point of Elisa’s talk was that where we all think of stem cells as just stem cells, there is actually a large heterogeneity between them. By quantifying the differences between the different HCSs, she hopes to define distinct subsets with different functions, characteristics and detectable markers within the broad HSC-pool.

By single-cell analysis, Elisa found two distinct subsets of haematopoietic stem cells: long-term HSCs (LT-HSC) and short-term HSCs (ST-HSCs). They are characterized by just two surface markers: LT-HSCs express high levels of CDf49 and low levels of CD90, where ST-HSCs have opposite expression levels. The functional difference between them is that LT-HSCs divide very rarely, and ST-HSCs divide more often.

Transcriptional analysis of LT-HSCs and ST-HSCs didn’t give any results, they both showed the same expression landscapes. One explanation for this could be that both cells are very quiescent and therefore not transcriptionally active. The solution Elisa and her colleagues found was to activate the cells and then analyse their transcriptomes. Once activated, the cells start in quiescence, which is a ’sleeping’ state, and are then activated. The ST-HSCs are activated earlier than LT-HSCs, which is another functional difference between them.

To activate the in vitro cultured HSCs, they are transplanted into living mice or into in vitro cultured tissues. Both activated cells are analyzed by single RNA-seq and microarrays. By doing this, they found at least 34 genes that are differently expressed between two subsets. CDK6 appeared to have to most distinct difference in expression between the two groups and was the best gene to indicate whether a cell is ST-HSC or LT-HSC. Surprisingly, treatment with CDK6 determined the state of the cells: over-activation of CDK6 resulted in a faster activation and a CDK6 inhibitor resulted in slower activation.

However, next to this direct effect by changing the expression level of CDK6, also long-term effects were measured. When CDK6 was over-expressed, LT-HSCs gained a positive competitive advantage over SC-HSCs over the long term. In other words, they outnumbered the ST-HSCs. This can be explained by the fact that CDK6 stimulates activation of the cells. ST-HSCs already activate quite fast, so stimulating activation results in activation of all ST-HSC. They all start differentiating and no ST-HSC will be left. LT-HSCs on the other hand, activate more slowly and will remain abundant in the HSC-pool, and will eventually dominate over the ST-HSCs in number.

In the remainder of the time, Elisa told about her current research in further defining subsets of haematopoietic stem cells by finding new markers that characterize distinct groups. Her talk emphasized once more the difficulties we face when looking at stem cells, or molecular biology in general; tissues are very heterogenous and we do not yet know a lot about all their differences. However, her talk was very clear and she is obvious an important person in this field.

Methylation analysis and NGS as basis for classification and grading of brain tumors

Speaker: Andreas von Deimling             

Department: Josephine Nefkens Institute for Oncology

Subject: Methylation analysis and NGS as basis for classification and grading of brain tumors

Location: Erasmus MC

Date: 25-01-2017

Author: Renée van der Winden

Today Andreas von Deimling came in to talk to us about his team’s research in the diagnosis and grading of brain tumors. They have developed a method to classify the methylation patterns of tumors into distinct tumor subtypes. It was already known that methylation could distinguish four subgroups in medulloblastoma and it now turns out this also works for a lot of other types of brain tumors. During his talk Deimling often compared the result of methylation classification with that of WHO. Currently, WHO can distinguish 90 subtypes of brain tumors and methylation classification can distinguish 82 of those 90. What is very useful about methylation classification, is that methylation patterns in tumors turn out to be very stable. So the pattern in an early tumor is roughly the same as that in a tumor in a later stage.

To perform the classification a patients methylation pattern is run through approximately 10,000 decision trees which all point to a certain tumor subtype. To find which type is the right one, you simply have to pick the type on which most decision trees landed. As a supplement to this method, Deimling and his team also look at copy number variations in the tumor cells. A diagnosis like this takes around ten days to complete. It is then integrated with the diagnosis from WHO to give as accurate a diagnosis as possible. About 75% of the diagnoses overlap, which shows the methylation classification is reliable. In about 12% of the cases the methylation method yields a change in the diagnosis compared to WHO, these are of course the cases that are most interesting and show the best use of the methylation classification. Then there is 12% which does not give a match and less than 1% in which methylation classification is misleading.

As an example, Deimling talked about meningioma’s. Right now, mitosis is counted to distinguish between grade I, II and III tumors, which vary in aggressiveness. This is very arbitrary. Methylation classification can help to distinguish between these grades which leads to better treatment of the patients.

Clearly, this new method is useful for the classification of brain tumors, however, because methylation is stable in tumors, it is not very useful for grading the tumors and more research is needed on that topic.
Lastly, Deimling showed us a website on which doctors can easily access the methylation patterns of tumor subtypes. Moreover, since two weeks there is a prototype for a sarcoma classifier, thereby widening the usage of this method.

I thought this seminar was quite easy to follow and I liked the topic. I find it very inspiring that people are working to defeat a disease like cancer, which is lethal in many cases, and succeeding. I might want to join them one day. I loved the fact that Deimling and his team made a website for other doctors to access. It showed me that he really cares about his research and that he wants to help others with it.

Chronic myelomonocytic leukemia: Recent insights in pathogenesis

Speaker: Eric Solary
Subject: Chronic myelomonocytic leukemia: Recent insights in pathogenesis
Location: Erasmus MC
Date: 19-12-2016          

Eric Solary talked to us about his research in chronic myelomonocytic leukemia (CMML). He discussed new and improved ways to diagnose and treat the disease, as well as a new way to make a better prognosis for patients.

The first way to make a diagnosis easier, is to look at the percentage of different peripheral blood monocytes a patient has. It turns out that in CMML patients more than 94% of their monocytes are classical CD14+ and CD16-, while this is less in healthy individuals. It was shown that demethylating agents could return the normal distribution in CMML patients. Moreover, monocyte phenotype could detect MDS, a disease that usually evolves into CMML.

Secondly, looking at the genetic mutations in patients may also help to diagnose them properly. Three genomic signatures for CMML have been found, of which TET2 was the most frequent mutation, occurring in 60% of the cases. Aside from these three, two TET3 mutations have been found that are associated with the TET2 mutation.


seminar-1Figure 1: A chart showing the different mutations in CMML patients


Solary’s lab tried to find a better prognostic method for CMML, but unfortunately they were unsuccessful. There are currently many factors that can be used to make a prognosis, but Solary added a new one: ASXL1 mutation. This mutation is also associated with the disease. Unfortunately, this method does not outperform the prognostic methods that are already being used. However, it also did not do any worse, so it is still useful.

Lastly, new ways of treatment were discussed. Hypomethylating agents help restore the healthy phenotype in patients. However, it turned out that this does not rid the patients of the mutations that they have. Furthermore, hypomethylating factors increase miR-150, a microRNA which has a higher expression in non-classical monocytes. Unfortunately, not all patients responded to this treatment. Looking at the baseline DNA methylation of patients could help distinguish responders from non-responders beforehand, making for a more effective treatment.

I found this seminar quite difficult to follow, but I still found it interesting. I was inspired by the fact that there are still new ways of treatment being found for cancer, even very specific types of cancer like in this case. From listening to this seminar I realized it is important to not only look at new ways of treatment, but also for a better diagnosis and prognosis. I think I might someday like to do research in the field of medicine, so it was very interesting to hear what kind of discoveries are made there.

Speaker: Louis Vermeulen

Department: JNI Oncology

Subject: Stem cell dynamics in homeostasis and cancer of the gut

Location: Erasmus MC

Date: 23-3-16

 Author: Hielke Walinga


A good way to look to cancer in the biological sense is to see it as a process of evolution on the cellular level. A cancer cell is fitter than the healthy cells because it produces more offspring, and is not killed by apoptosis. In this way cancer can better be understood by studying the dynamics between cells and so discover what is responsible for a larger offspring in the cells. The cells that produce offspring in an organism are exclusively the stem cells. Studying stem cell dynamics is therefore very important in a better understanding of cancer. This is what Louis Vermeulen discussed in his seminar on 23 March. Louis Vermeulen has studied the stem cell dynamics of the intestinal stem cells (ISC’s) and proposed a model describing these dynamics and how certain cancer mutations alter these dynamics.

First of all research has shown that colon cancer isn’t a bulk of cells growing very fast, but it looked like these cancer create a bit their own small organized organs. This is, however, simply explained by the fact that these cancers didn’t arise from random cells, but did arise from stem cells. Therefore they grow still in a bit organized manner.

The inside of the intestine consists of a lot of relief, because it is covered with so-called villi. The cells in these villi got lost pretty fast and of course need to be replaced. The stem cells replacing these are located at the bottom between these villi. Replacing is therefore from the bottom to the top. In this well the ISC’s are located in a circle. Not only did these ISC’s replace the cells above them, but it turned out they also replace each other. This is discovered by the use lineage tracing. The stem cells are marked by something which is also visible in their offspring.

After this discovery they tried to model this stochastic dance of replacing. They discovered that their model was sufficient by taking only two parameters, N and λ. N is the number of ISC who participate in the dance and λ is the replacement rate of ISC’s per time unit. It turned out that the dance is so dynamic that there is a good chance that one ISC will replace all the others. This is called fixation, and obviously the fixation chance is the important value which a cancer cell is trying to increase.

When all ISC’s are healthy (i.e. no cancer cells) the chance that one ISC will replace its neighbor is just 50 percent. A cancer cell will of course have a higher chance to do this. When this chance is known the fixation chance can be calculated by the following formula.
Fixatie formule
Image 1: Formula for chance of fixation, Pfix, with the amount of ISC, N, and the increased chance of replacing its neighbor, PR (for neutral drift this is 0.5).

Later research has shown that certain cancer mutations indeed have a bias in this drift. These mutations are: KRASG120, APC+/-, APC-/-. Important to know is the a very frequent cancer mutation, p53R172N, is not creating a bias.

I think this research perfectly shows how mathematical models can give more insight in something biological complex as oncogenesis.

Fixatie evenement
Image 2: This image shows how a fixation event takes place.

New approaches and imaging tools in cancer therapy

JNI Oncology lectures, Erasmus MC Rotterdam, 25.11.15

Title: Can we cure cancer? New approaches and imaging tools

Speaker: Clemens Löwik (Erasmus MC, Rotterdam, The Netherlands)

Author: Edgar Schönfeld


Clemens Löwik’s talk focused on new imaging techniques that are able to augment existing anti-cancer therapies. At the beginning of his talk he raised the question how we can possibly cure cancer. If the original tumor does not have metastasized yet, resection of the tumor cures the patient usually. For metastatic cancers, combination therapy including immunotherapy will most likely result in a cure for many malignancies in the future, according to Löwik. In his talk he introduced three recent developments he was involved in that touch these subjects:

  1. Fluorescent image guided surgery
  2. Photodynamic therapy + immunotherapy
  3. Necrosis as a target for diagnostic imaging & therapy

Fluorescent image guided surgery (FIGS) employs fluorescent dyes to demarcate cancer tissue during an operation. Metastatic cancers are usually treated with a combination of surgery, irradiation and chemotherapy. However, during an operation it can be difficult to distinguish cancerous tissue from healthy tissue. Especially very small metastases can remain undetected. In recent years contrast agents have been developed that fluoresce upon stimulation with near infrared light (NIR), which can penetrate several centimeters through tissue. In the context of an operation, this contrast agent is administered to the patient. A NIR light source is adjusted such that it points onto the surgical area, while a NIR sensitive camera records life images. These life images can be displayed on a monitor or via goggles. Such a system is already in use at the Leiden University Medical Center.

Figure: Setup for a fluorescent image guided surgery


Video: Point-of-view footage of fluorescent image guided surgery; Left: normal image; Right: augmented image


Löwik was also involved in a study in which tumors were eradicated by a combination of photodynamic therapy (PDT) and immunotherapy in mice. A PDT treatment starts by administering a photosensitizing agent to the patient, which stays longer in cancer cells than in healthy tissue. Subsequently the tumor is irradiated with light of a specific wavelength. This triggers the production of reactive oxygen species (ROS) by the photosensitizer, which destroys the tumor cells. The technique is highly selective, does not leave any scars and most importantly, equally affects cancer stem cells. In addition it causes damage to the vasculature in the tumor environment, thereby cutting off the nutrient supply for tumor cells. Above all, PDT in combination with a therapeutic vaccine can cause an immune response which successfully prevents tumor reoccurrence in mice.

Löwik’s favorite subject however is necrosis. He holds a patent for a method that stains necrotic cells. This involves the use of dyes that cannot enter cells, except if the membrane has lost its integrity. Since almost all tumors have a necrotic core, these dyes can be used for diagnostic purposes. Interestingly, Löwik reported that his team recently developed nanoparticles that can enter the necrotic area of tumors. In doing so, they attack the tumor from the inside.

Each of the presented methods is very promising in my eyes. Above all, fluorescent image guided surgery impresses me deeply. This method can greatly decrease the likelihood of overseeing metastases and thereby make a tumor relapse less likely.

Molecular classification of pediatric brain tumors

Speaker: Marcel Kool

Department: JNI Oncology

Subject: Molecular classification of pediatric brain tumors

reveals new entities

Location: Erasmus MC


Author: Hielke Walinga

Times that only surgery was a treatment for cancer are long over. Very different treatments have been developed and knowing which one to use for a patient can be crucial for the survival of the patient or can prevent severe damage to other tissues near the tumour. Especially very vulnerable tissues like the brain must be treated with the exact right treatment. Therefore some researchers focus on the classification of these tumours. Just like Marcel Kool whose seminar I listened to at 2 September. Marcel Kool tries to classify paediatric (children’s) brain tumours using molecular methods. He gave an overview of the latest discoveries of the field.

Cancer types always used to be classified by their histology (their appearance when viewing it under a microscope). This makes sense, since the way a cancer looks is usually a result from the specific mutations it has. However molecular research has shown that this classification isn’t always correct for guessing the type of cancer.

For example oligo astrocytoma, which looks like a bunch of star like structures, doesn’t exist on the molecular level. It is actually at the molecular level either astrocytoma (star like structure) or oligodendroglia (a bunch of tree like structures).

Another way to distinct different cancer types is to look at the clinical outcome. The survival rate should be a good sign on the different mutations of the tumour, and might be later be linked to something that good help to set a good diagnosis. This classification is done using grades. Higher grades (from one to three) stand for a worse outcome. However molecular research has shown that there is actually no difference between two and three of most types.

To reveal the gene expression the molecular methods that could be used for this research are for example Northern or Southern blotting, however it’s quite hard to obtain enough sample from the tumour, especially because it’s in the brain, to do these kind of research. A better method might be to use NanoString to reveal certain fragments RNA. A method, that’s better to be done, and also studies by Marcel Kool, is actually to reveal DNA methylation. However, it’s left to discussion on how this actually relates to the nature of the tumour.

DNA methylation

An example of a methylation heat map created in a research in which Marcel Kool has cooperated. (Source: Hendrik Sturm, Hotspot Mutations in H3F3A and IDH1 Define Distinct Epigenetic and Biological Subgroups of Glioblastoma, Cancer Cell: Volume 22, Issue 4, 16 October 2012, Pages 425–437)

The research shows a lot of new entities of brain tumours, and the researchers also have been able to link the results to different causes of the cancer. Their distinction almost always came from different pathways that are affected by some kind of mutations. Sometimes they were able to link these together to one certain factor, like the MITF TF of the AT RT tumours. But it also revealed that glioblastoma is a cancer caused by a histone gene mutation. They also were able to link their results to the clinical outcome of the disease. For example, medulastoma has a molecular subgroup (Wnt) which almost always meant a survival for the patient.

To use all these result for the benefit of the patient, the next step would be to create a worldwide database of some sort, which doctors could use by their diagnosis of the patients. Therefore this will be the next step in molecular neuropathology. Actually this has partly already begun and it is called INFORM (INdividualized therapy FOr Relapsed Malignancies in childhood). Still this only focusses on the relapse cases, because they usually have a dismal prognosis.