How has myeloma treatment become more personalized based on genetics?

[Music] how has myeloma treatment become more personalized based on genetics so for many diseases there is a unifying genetic trigger that drives that cancer forward so in diseases like cml we know that a translocation between the ninth chromosome and the 22nd chromosome engineers something in the cell that drives cml forward and blocking that actually prevents someone's cml or chronic myelogenous leukemia get from getting worse multiple myeloma unfortunately is a very genomically unstable or genomically heterogeneous disease someone's myeloma may be driven by a variety of different genetic abnormalities what we have the ability to nowadays is do sequencing to find out in an individual which pathways may be active which may be driving the cancer forward and from this we may be able to draw from other drugs and other diseases so for example some people's myeloma may be driven by a mutation called a b raf mutation or a ras mutation b raf and ras are these pathways inside cells that allow them to survive so when the body tells the cancer cell to die these pathways are kind of turned on automatically so the cell says i don't have to listen to you and i can continue to grow but we can take drugs from other diseases like melanoma or colon cancer if someone has a myeloma that's driven by b-raf or nras or k-ras we can take a drug from another disease give it to an individual who has a myeloma that's driven by one of these pathways block the pathway and their myeloma may regress from a drug that was never designed to be used in myeloma to begin with there's a very exciting drug called venetoclax which is an oral bcl2 inhibitor bcl2 is something that's expressed on a lot of b cells b cells can be things like myeloma but b cells are also things like lymphoma and venetoclax is a drug that's already approved in lymphoma but we're now finding that there are subsets of myeloma patients where this drug may be very active and it's very active in two big groups one group over expresses this protein called bcl2 but another group is people who have another type of translocation between two different genetic arms so people have a translocation between the 11th and the 14th chromosome may be highly responsive to this drug venetoclax so we're being very aggressive at identifying an individual's myeloma and finding what drugs may specifically target them and drugs like venetoclax are becoming more and more used in this patient population we haven't really bought in to risk stratification so there are very few trials that have said this is a very high risk patient we're going to do this or this is an extremely low risk patient will not treat them so intensively and yet even clinically you can recognize these very high risk patients by extra extramodillary disease plasma cell leukemia some cytogenetic abnormalities and so there really is a purpose in this trying to work on high-risk disease and so there's this thing called um yeah systems biology where really you take as much information as you can you take the images the genetics the proteins mash them all together and try and come out of that with a way of addressing this problem so there's the puzzle in front of you it's a jigsaw um it's not they're not all of the same and what you want to do is to split that jigsaw into its individual pieces and so there are big projects out there have been done like this myeloma genome project which has brought everything together and what it shows you is that the genetics are super complicated and you might say too complicated we can never get to grips with that but actually this driver idea versus a passenger idea is something that you should all be aware of because while there's lots of passenger events that get carried along by the driver there's only limited driver events so there may only be six genetic lesions that determine how a patient's myeloma behaves and so this is what we're trying to find driver variants that push the disease forward or drive it along and carry these passengers with them and so what we need is big data more information and we need a team of geeks who are prepared to sit there and struggle with this problem and come up with the drivers that we can use to segment the disease into its individual components and as time has moved on computer technology and analysis platforms have got better and so you can use the computer to do the thinking for you and the using these integrative learning approaches you can generate segments of myeloma and so it's quite clear that they're only limited segments probably six maybe more but we're starting to get to what these segments are and so it's like pulling out the patients from the overall group who you should treat differently and so as diagnostics have got better so we've seen cytogenetics metaphases eye fish and now mutation panels it's very easy to turn a genetic test around in a week and separate that puzzle into the three distinct groups and that's all personalized medicine is about at this stage is separating and segmenting the disease so the question then for genetics is if we can understand this biology of unique characteristics is it possible to treat individuals rather than groups of myeloma patients and so we take a step back and say well what makes every individual unique their genetics that is the genes that make up you and your traits make you individually unique likewise your tumor the myeloma tumor probably has a lot of unique genetic characteristics that make it an individually unique myeloma and as a result we better understand that unique characteristics so that we can better treat individuals so myeloma genetics is pretty complicated we know that there's variation among patients and that variation is genetic variation their tumor cells have chromosomal abnormalities that may be different from one patient to another those chromosomal abnormalities may impact how aggressive the disease is how it responds to therapy we also know that genes can be mutated how genes are mutated may impact how you respond to a therapy how aggressive your disease is we also know that within one individual's individual's tumor population there may be genetic clusters of cells that differ so that some of them respond to therapy and some of them don't and they contribute to the relapse so the idea on this is to have a better idea of predictions by using genetics as biomarkers that is a signpost it's a signpost that says if you have this type of genetic pattern here are the options that might work for you here are the options that may not work for you so a lot of genetics now is trying to target the identification of useful information that is associated with how aggressive the disease is and which therapies might be best for that particular genetic abnormality that leads to individualized therapy the whole idea of not treating everybody as one group of myeloma patients but treating them as individual is going to be dependent on our ability to characterize every individual's tumor's genetic characteristics and this is a research field we are at a point now where we're getting better insight on the biology of myeloma and we're starting to see how these may influence therapeutic choices and many of you as patients are getting genetic testing done and that genetic testing will tell your oncologist how aggressive your disease might be how aggressive the therapy might need to be and it's even giving the oncologist some information about which therapies might be the best therapies for you it's a continuing field of research to get better and better at doing this and the proof of that is 20 years ago before we had this kind of information myeloma patients would live three or four years and that was kind of an average lifetime for a myeloma patient now with the new therapies our ability to target those therapies better patients are living much longer we're getting much more long-term survivors because we have better effective therapies and better ways of defining which therapies might work with individuals and it's all based on our understanding of your genome and the genetic information that that we're getting on every individual how is myeloma treatment personalized to genetic markers now and what may the future of precision medicine in myeloma be segments you can then put treatments to each of those segments so we've heard these before and i want to come back to them so the 414 myeloma 15 of all cases it does well if you give it lots of proteasome inhibition so you might want to focus carphylsemib onto the 414s the 1114 a relatively good risk group it responds to this drug called venetoclax and really the other groups don't respond to venetoclax so you suddenly have a tool where if you want to use venetoclax in the clinic you need a diagnostic and then you need to treat those patients with that kind of therapy and there's venetoclax and there's the responses so uh you get 40 responses if you have the 11 14 if you don't have the 11 14 the response rates are kind of much less we're going to utilize the immune system and leaf did a good job of showing that but we have all of those targets each of these numbers is a different target that's on the surface of the myeloma cell that you can target your antibodies against all your car t's but life doesn't work like one size fits all it works like some patients won't respond to car t's and we won't understand why and so we need technologies to look at the immune system and this kind of technique called site off allows you to look at the whole immune system in one go so you can expect us to try and personalize immunotherapy using kind of immune segmentation rather than molecular segmentation further you all will i know hate having bone marrow tests so you can combine blood biopsies with diagnostic panels and then everybody in the country could have a rather cheap diagnostic tests get the result back in real time and adjust their therapy in real time and then use that panel to monitor disease over time further to that approach imaging technology is becoming so powerful that you can extract what are called radiomic features from these plasmacytomas just from the imaging data and some of those features correlate with prognosis so as time moves on our rather crude approaches will become increasingly sophisticated and it'll make the information quicker more robust and patients lives [Music] better