How Genomics Will Change the Way We Treat Cancer Patients | George Vasmatzis | TEDxMinneapolis

How Genomics Will Change the Way We Treat Cancer Patients | George Vasmatzis | TEDxMinneapolis

the first time I encountered cancer was when I was five years old we I grew up in a immigrant neighborhood in Thessaloniki Greece we were living in this second-floor apartment and I was looking outside the window you know and reaching out and looking at the world outside it was a beautiful world fascinating world kids were playing soccer the mothers were going shopping in the square the fathers were going to to work I remember this young man he must have been about 20 years old he was walking in front of the house wearing this white uniform going to this Military Academy medical school it was very difficult to get to that school so he was the pride of the neighborhood one day my mother was talking to a neighbor of yours down the street and I remember the sad look in here in her face when she found out that the young man died of cancer the bad disease as they called it that look remained with me the rest of my life I'm sure like me most of you have encountered cancer many times your neighbors your friends family both my parents died of cancer in the early 70s and those were some of the worst times of my life when I was 20 years old I came to the United States to study Electrical Engineering that was the the field on the brink at a time the PCs were coming out Steve Jobs was trying to introduce the mega doses in the universities so I studied electric engineering for a few years both bachelor's and master's but I kept having that longing to work on on a medical field to somehow use my engineering skills perhaps in in biology and medicine maybe I can understand cancer better so I went from my PhD to Boston University where there was a new school in biomedical engineering and that's where I met charge delici the guy on the left Charles sugars before I met him he fought to start the Human Genome Project he and others thought that the only way we could really move forward with medicine and by understanding biology is by uncovering the secrets that they're hidden in the human genome so it was a very ambitious project most people thought it can be done it was too expensive and too time-consuming to finish this you know three billion letters of code but Charles thought that the the project will push new technologies to come forward and engineers to come and work with the problem and it will be cheaper eventually cheaper and faster to do it well he was right he put the first three thirty million dollars as we just told me earlier for the project but the actual project cost about two billion dollars best two billion dollars we ever spend if you ask me much much more important that the PC and that's coming from an electrical engineer so charge the lessee and Jim Cornette they're both here today mentored me through my transition from engineering to biomedical sciences but it was when I went when I ate that I got into this new field called bioinformatics which is tasked with this enormous problem to try to read all the information that's coming out of the human genome and genomics experiments so what is the human genome imagine a small library with about three thousand books the size of the Bible Bible has about a million letters so it's cranberry makers three billion letters this way and this books are stacked in two different books elves representing the chromosomes chromosomes one to twenty two and x and y all this information is in the middle of a cell actually there are two identical cells of it's almost identical sets of information one comes from your mother won't come to your father inside there just in case some of the information in one part is wrong the cell can use information from the other cell so if you have little discrepancies somewhere there you can use the other self to read it of course if you're missing the other self that's probably not a good idea well this is what happens to cancer cell the cancer changes that information deletes information or change that information in a way to make the cell become more aggressive so what do I mean by that imagine that the cell is like a city like Minneapolis where the library is right in the middle of the city and every worker in the city has to tap into that library to figure out what they do so we don't need a governor here we just have this library to do it so it's a library information system and if the information is correct you get the right information you're a policeman and you know what the crimes are or the the murders or you know you know where to go in the factories of them if you are snow plow plow driver in a snowy day it happened you figure out what time you need to get your tracks out and with highways to concentrate on if that information is wrong or missing with our traffic mess so that's what's happening in cells in cancer cells the information is missing this is a genome of a cancer patient all the chromosomes are represented here chromosome 1 on top in this box and when you have a little gray dot that means you have that part of information correct but if you have red dots or blue dots something is wrong this is a normal genome so this cancer genome and chromosome 6 has a big deletion that means a lot of those cells from chromosome 6 which is gone or it has an amplification on X chromosome which means that there was duplicated information and we know that's not good or in that case back there you have exchange of information between chromosomes between chromosomes 2 and 16 in that case it's like taking little paragraphs or books from one chromosome and put them on the other you that with romance story and you end up with a zombie story so all this is not good this is the cancer genome of a different patient notice that it is completely different than the other one maybe there is a deletion on chromosome 6 so there is some you know commonality here but but it was quite different not the other one I showed you and we've done thousands of those more than a thousand that Mayo Clinic alone and we're finding that those genomes are different from one patient to another so that becomes a big problem right we have to become detectives now and figure out what is going on with all the information we are getting and if there are any commonalities and how we can use these commonalities to understand how to treat our patient better those common things we call them biomarkers especially if they are associated with a clinical outcome this is a different page this was a patient that had a very aggressive cancer and went on when he came to Mayo he came out you know out of Hospice but there was an inhibitor that this patient took and pretty much went back to work and after we analyzed the genome we found out exactly why this gene over there called alq was a good target for that inhibitor and we could figure it out by doing this genomic analysis so this is something we couldn't do three or four years ago this is really really new data and new technologies new power that we have there is an oncologist at Mayo Arizona his name is Rajesh Bora that already is using this type of technologies and he's seen 10 to 20% of the patients that now can go and find their lives back people that they didn't have any chances any options now they have options with the Buddhist type of technologies so how do we do that how can we do this we need the following technologies first first of all we need pathologists really good trained pathologist who know how to pick up the right cells from the fluid tumor and so that we can interrogate ourselves we need molecular biologists like Steven Lin here who are taking that those those molecules and they can put them into high-throughput technologies like this one which is a lot of sequencing in arrays when Charles started the human genome project 30 years ago we could sequence one fragment with a thousand dollars in about week now we can sequence a hundred million of those fragments with the same money and time so our ability to figure out what is going to the cells is a hundred million times better now and finally we get all this information it's multiple libraries of information which you cannot go and read by by I obviously so you need computers and algorithms to understand what this information is really telling you and that's what I do I write algorithms to understand that information and somehow linked it with biological information 15 years ago I found myself exactly what I wanted to be at Mayo Clinic one of the best clinical institutions in the world and finally I could maybe try to do what I was trained to do what I was trying to do since I was little the person who hired me is Frank Prendergast he was one of the first leaders at Mayo Clinic who understood or realized that the genomics are going to tend to change medicine and how we treat patients and early on in my career John Seville who was also very curious to see how genomics will influence his own field which was pathology the three of us shared the same vision that after we do the genomics of patients we will be able to find these biomarkers and biomarkers will help us reduce over treatment for example or do better under treatment studies or even know how to target the right patient whether I died track so we developed this program well marker discovery program within the center of individualized medicine to do just that find the next biomarkers that we would need to treat patients better what we realized very early is that the only way we can do that is with teams of investigators that one person alone cannot do this because it's just too complex too difficult to do it and the teams would require all these disciplines that I'm showing here the clinicians the pathologists who will actually ask the right questions you know for finding the biomarkers the molecular biologists the the the decision about fermentations who will analyze all this information and we also realize that those teams would have to operate that our patient needs and patients here are extremely important if it wasn't for brave patients that would come to us and say yes we want to help you do this we want to participate that was extremely important for us to have the patients and also the benefactors that would come and give us resources to be able to do those things the teams also took advantage of all the resources that a big institution like Mayo has for example an integrated practice a large amount of samples with annotated samples that they have the right information them wolves one of the best reference laboratory is that where we can take the biomarkers and quickly develop the test and launch it and and offer it to the patients so what do those biomarkers do I'm gonna give you a couple of examples here in prostate cancer one of the biggest problems that Jeff carves a urologist in the team is we don't know how to treat a patient that comes with a post biopsy some patients need surgery but some patients don't need it really like for example this is a prostate these are all prostate and this is a slice of a prostate and this is the country the big ugly cancer that needs to be taken out here long another prostate that has a very small cancer and when they took it out they're thinking what's to do we really need to take this out thirty five thousand fifty thousand dollars surgery and all the morbidity issues that that patient might have the change of life the quality of life we really need to do that it turns out that if you look at the 200,000 surgeries of the world that were done in prostate cancer every year about a hundred thousand didn't need to do the surgery if you multiply that with fifty thousand that's five billion dollars we can save the system we can come up with a with a way to figure that out at the BIOS level so we don't go to surgery so what we did is we took answers from indolent intermediate and aggressive cancers we did the genomes of those and we look for those biomarkers that could classify patients either on the left or on the right and then came up with a model where we can apply those biomarkers and we can tell the new patient if they have low risk for aggressive disease or high and send them to surgery in a different project marie-christine debris and other pathologies wanted to know in lung cancer when there are patients with that they have two tumors in their lungs like in this case and there are two tumors in those lungs if those are independent or metastasis of one another if they were metastases in one one another that's probably aggressive disease high stage disease and it's likely not going to benefit from surgery but they if they're independent that could be a stage one disease it's one of them they can probably go to surgery and perhaps be cured by that so it's extremely important to figure out if those two tumors are related or independent from each other well it turns out that whole genome sequences can contain on the top is a patient that had independent tumors were on the bottom obviously it doesn't take an oncology degree to see that those two patterns are kind of similar right so the patient below will have to go to chemotherapy or the patient on top can go to surgery now we're developing a test where we can do this now for our patients and even further what we have realized many times that a lot of the DNA the altered DNA from the cancer ends up in the blood of the patient and that opens up a lot of interesting opportunities like for example we could take a tumor out figure out what are the alterations and the breakpoints on that patient and then go into the blood and monitor that patient so if this if it was if a surgery was done we can figure out this way if the patient relapses earlier but there's another much more interesting application for this which has to do with therapy a patient with aggressive cancer which which is starting to metastasize cost about half a million dollars to the system right now and many times this is because all policies try some chemo therapies and it takes months before they know that it's working a system like that can tell us if the patient is responding to therapy and if it's not responding therapy we can stop the therapy earlier save money to the system and perhaps send the patient to a different therapy which is more targeted in that case so I try to give you some examples of how we can use genomics to change skinca practice I think we are at war with cancer we're not winning that war yet but what we've done with genomics we are started understanding how cancer things and finally I think we're winning some battles and that we shall not be done without people like charged the lessee Jim Cornette Frank Prendergast who actually gave their lives to work on this and binging to NIH to to universities and to clinical institutions and also for me I wouldn't be here if my mother didn't put this thing in me in my mind so I hope that is a smile in your face right now thank you

5 thoughts on “How Genomics Will Change the Way We Treat Cancer Patients | George Vasmatzis | TEDxMinneapolis”

  1. Efharisto! I hope we can find a cure for cancer soon. I want my father to survive this battle. Hopefully we can discover some method to really dig deeper into this deadly illness. My prayers go out to all of us who have cancer in our lives, either with loved ones or ourselves. And I pray it will not continue taking lives.

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