Molecular look inside cancer to help a friend in need
Cancer. That dreaded word. No one ever wants to hear it. We all know how deadly cancer can be. So when I found out that a friend of mine was diagnosed with a recurrent form of epithelioid sarcoma, my heart sank. Because I know this woman, and I really like her; she has a kind heart, and is always sporting great smile. I felt so helpless. But I study the use of next-generation sequencing all the time and I already knew that the use of genome sequencing has had a valuable impact in the molecular understanding of different cancer types, including selecting the proper treatment type. I did not hesitate for a moment and I let my friend know what I knew, what I believed.
Then I have gone on an odyssey of trying to find as much information for her benefit as possible.
Obviously my first task was to look up information about epithelioid sarcoma. It is a very rare cancer. It makes up about 1% of all soft tissue sarcomas, which themselves account for only 1% of cancers. Soon it became apparent how rare it actually is. So I decided to do what I can do best and analyze the latest findings in the scientific literature.
As it happens, a paper was published not that long ago investigating the molecular background of epithelioid sarcomas, research that was spearheaded by Dr. Torsten Nielsen of UBC, and the British Columbia Cancer Agency in beautiful Vancouver, Canada.
Although a timely publication for the benefit of my friend, the news was good and bad. It turns out that epithelioid sarcomas are characterized by a heavy mutational load which might impede the ability to find targeted therapy, and did not identify specific unifying mutations. But the study was done on only seven specimens, and these were already collected from three different medical institutions. As already mentioned, that is a truly rare form of cancer. However, the study further confirmed what was previously observed, that these type of tumours are typically characterized by a mutation of SMARCB1 gene leading to its loss of function.
SMARCB1, also called the INI1 gene, is part of the chromatin remodelling complex, a complex that regulates access to DNA for its expression. Say what?
Let us start from beginning. Your DNA lurking inside your cells, if it were to be unfolded into a straight line, would be approximately 2 meters in length. Hey, that’s taller than most of us! That is because our genomes are made up of approximately 6 billion nucleotide bases (the code), and each base is 3.4 nanometers in length, or 3.4 X 10-10 meters (for comparison, even your flimsiest of thinnest hairs would still be at least 10 times bigger in size). So if you make this back of the napkin calculation, you end up with about 2 meters. And that’s a lot to pack into your tiny cell! One way you can achieve that is by winding the DNA around molecules like a yarn around a spool. Do this over and over and eventually you end up with your genome looking like a giant yarn ball that your unruly but irresistibly cute cat got a hold of!
This messy DNA yarn ball, with all of the biological molecules tossed into the mix to nicely pack it all up is referred to as chromatin. It minimizes the space required for this giant biological code, it protects the DNA from damage (like when you take a vacation in Chernobyl), and regulates which sections of the genome can be accessed for biological interpretation by your cell (referred to as expression). And obviously how the genome expression occurs has to be highly regulated. If you mess it up, you can end up with cancer.
Which brings me back to SMARCB1. I contacted the authors of the publication, and Dr. Nielsen was kind enough to answer in detail, and with very precise information, regarding the potential treatment of epithelioid sarcoma. “We had been hoping to find consistent targetable pathways in this disease, but did not find anything consistent beyond the known loss of SMARCB1” said Dr. Nielsen. He pointed to the Epizyme pharmaceutical company involved in the development of a novel therapeutic specifically designed to target the effects of cell disregulation due to loss of SMARCB1. This was a very good lead , and as it later turned out, great timing on account of the completion of Phase 1 clinical trials demonstrating the effects of the drug. This would be one important option to consider for my friend.
Another fortuitous publication was a clinical demonstration of the utility molecular profiling of tumours in a large, complex and detailed study at the Icahn School of Medicine at Mount Sinai.
This publication was a treasure trove of valuable technical information, and I studied it for days with multiple reads. That is not surprising, considering that one of the principal investigators was Dr. Rong Chen who has been involved in some phenomenal research lately. He was involved in the recent development of a repository of genetic variations (termed variants for short) based on the sequencing of more than 150 000 individuals to validate disease-associated mutations.
He was also involved in building a centralized storage of published genetic variants. We are dealing with some mind boggling numbers here! In total, nearly 30 million abstracts were investigated, including over 3 million publications, to produce a database of 473 million variants.
Crucially, he and his colleagues developed a pipeline to seek disease variant pairs which at the moment are still poorly understood. I think I am some secret closet fan of his work because look how many of his articles I studied in the past! Any of these publications deserve a thorough write up in their own right.
The study employed 46 patients who were analyzed with a multitude of available technologies, including whole genome sequencing, whole exome sequencing (looking at genes only), transcriptome sequencing (sequencing of all of the RNA produced from DNA available for expression and which are the precursors to produce proteins in the cell), targeted gene panels (so sequencing a subsection of exome, here specifically targeting genes involved in cancer development) as well as microarray analysis (method of capturing specific DNA fragments).
Yes, I just mentioned the top of the line possible molecular investigative diagnostics, and if you throw proteomics into the mix (which the authors did not, a measure of which proteins and in what quantity they are produced in the tumour cells), then you are talking about the best possible analysis that is currently available. If it fits your budget as we are talking about thousands of dollars here. But still only a fraction of what it costs to treat cancer. Cancer can now be analyzed with a multitude of powerful technologies: whole genome and exome sequencing, transcriptome sequencing, targeted gene panels, microarray analysis and proteomics.
First off, let us discuss the report that was provided to patients and their treating physicians as this reflects what any cancer-stricken individual will be able to expect when testing themselves using genomic technologies. In the first instance, it included the list of discovered somatic mutations (meaning they were not inherited but rather originated postnatally in the cancer cells).
On average, more than 100/specimen were found, and could be categorized into 5 tiers:
- Variants in genes involved in the patient’s specific cancer development;
- Pan-cancer genes (those found in many cancers);
- Genes known to play a role in other cancers;
- Genes in the COSMIC database but not known to be associated with any cancers (it is a database of all somatic mutation previously discovered in cancers, whether its function is known or not;
- All other somatic mutations.
The report also included the prediction of drug response based on previously identified variants associated with tumor sensitivity or resistance to either definitive therapies (FDA-approved), or all others including experimental drugs in clinical trials. If drugs are in the clinical development, the information such as inclusion/exclusion criteria, trial location and open/close date information is provided.
Another important piece of information delivered is the prediction of drug toxicity based on the patient’s germline variants (those we are born with and carry in all of our cells), and genomic alterations according to either FDA labeling or published literature. Such genomic based information can help select an optimal drug, dosing, and even treatment duration.
Finally, the potential prognostic implication was provided based on variants previously associated with clinical outcomes such as overall survival or recurrence-free survival. So that is a wealth of potential information, and crazily enough, most people in the world don’t know anything about it! But how useful is this stuff really? This is truly a hot topic of debate right now.
Remarkably, this study showed that the use of such information allowed for therapeutic recommendations to be made for 91% of patients, and this is quite consistent with what has been observed in other recent studies. However, this also underscores the fact that no useful information might come from such elaborate studies (and at a great cost, so a person has to take their chances).
For the four patients who could not obtain any recommendations, it was due to the fact that no informative mutations were discovered, with only 2.5 cancer-related somatic mutations obtained per patients. Kind of weird that you would need more cancer mutations to figure out how to fight it. Furthermore, for two of these individuals, no transcriptome data was available due to lack of a sample. Shows you how one set of data can complement and augment another.
In addition, even if sample is obtained, this study also indicates what possible pitfalls could be observed with data generation. A sufficient DNA amount was available in 91% of patients to carry out exome sequencing. For the rest, other approaches had to be relied upon. Of those where exome or genome sequencing was performed, nearly 20% of the time multiple attempts were required to succeed, including 7.3% samples being re-sequenced to yield more depth for enhanced analysis, events that would only drive the cost further in obtaining data.
One would expect that similar statistics could be observed in other laboratories which simply reflect the nature of samples being dealt with. However, what studies such as these indicate is how rapidly this field of science is moving forward, and the more people will be involved in having their cancer analyzed in such manner, the more likely potential solutions will be found. It is hard not to keep hopes up when personalized anti-cancer vaccines are already being assessed in clinical trials.
Another important value of this publication was the technical comparison of such exhaustive genomic profiling compared to data obtained from less intensive technologies, such as microarray and targeted gene panels. It provided valuable information to advise my friend with in terms of her options, including the minimal tests that could be undertaken to commence obtaining information of value. In particular, the authors compared their profiling approach with several commercially available cancer gene panels.
The value of genome profiling was investigated in multiple ways, but I will focus only on the mean number of actionable alterations, or those genomic events based on which treatment can be attempted. The commercially available cancer gene panels were able to identify on average between 0.65-2.6 such alterations as compared to 4.9 by the study methods employed by the authors. This included 1.5 somatic mutations, 0.6 copy number alteration (where the quantity of particular gene is affected), 2.2 germline mutations, and 0.7 alterations affecting gene expression. So much more in-depth data could be obtained.
Ultimately, I contacted authors of the study as well, and once again, Dr. Eric Schadt was kind enough to answer, providing very valuable information. He was able to point out a company that was commercially involved in performing similar in-depth studies of cancer samples, but also including the coveted proteomics information. This truly opened up many potential options for my friend to move forward in attempting to treat her difficult cancer case. All of these options were delivered to her to inform her oncologist in order to determine the best course of action.
What was the final outcome? Truly the best one could hope for! Her cancer went into remission and my friend was able to avoid these complex and expensive tests. Instead, she focused on healthy eating and healthy living, the stewards of keeping cancer at bay, and has been in no need of treatment since. While scientific information can be of great benefit, the best story always is when your body can find own means to combat cancer disease. For all others, powerful options now exist that we can all hope will succeed in driving complete cancer remission and even a cure! Only time will tell, with the involvement of many more patients.
If you are interested in information on cancer DNA testing, contact us, we can point you and your oncologist in right direction. If you like this type of analysis, we have lots more coming, so be sure to check back in the future or sign up. And if you think someone you know could use this article, the share button is just a click away. You never know how someone’s life could be affected.
This article has been produced by Merogenomics Inc. and edited by Kerri Bryant. Reproduction and reuse of any portion of this content requires Merogenomics Inc. permission and source acknowledgment. It is your responsibility to obtain additional permissions from the third party owners that might be cited by Merogenomics Inc. Merogenomics Inc. disclaims any responsibility for any use you make of content owned by third parties without their permission.
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