 Eric Green, Director of the National Human Genome Research Institute, and I want to welcome all of you to this annual lectureship, the Jeffery M. Trent Lecture in Cancer Research. I'm going to give a general introduction to this lecture series, and then I'll turn over the podium to our Deputy Scientific Director, Paul Liu, who will introduce today's speaker. I have the pleasure of saying a few remarks about this lectureship and the person that this lectureship is named after, and that's Jeff Trent. The story goes as follows. If you go back in time, the intramural program of NHGRI has not been around forever, by any means, and in fact 23 years ago it really only existed as an idea, but Jeff Trent was brought here to essentially build the intramural program. He was brought here jointly when Francis Collins came here as then the Director of the Institute and was asked to create an intramural program. That is not an easy thing to do when it doesn't exist at all. He had to start from scratch, recruiting a number of people, getting space, getting staff, getting everything organized, and what I would say is he did it a spectacular way. Good fortune of joining the effort, not in 1993 when Jeff arrived and some of the first investigators arrived, some of which are actually in the audience. I arrived a year later, but was very fortunate to be able to join what was already a growing and incredibly exciting place to be an investigator doing research in, and a lot of the credit for that really goes to Jeff. He was able to not only recruit good people, but to put together an organization and a style for intramural program that I think has served it extremely well as it has progressed through the years now actually in its third Director of the Intramural Program. So Jeff was the Scientific Director from about 1993 to 2002. At that time he departed and became the Founding President and Research Director of the Translational Genomics Research Institute in TGen in Phoenix, Arizona, and then had a similar opportunity to build science spectacular out there in the desert. And I'll leave it to others to talk and you could read more about TGen and there are some great things that have happened since then. What I would say is I feel very fortunate to have watched Jeff lead the intramural program and I think I learned a lot, as did all of us who are research investigators in the intramural program during his stewardship of the program. And then I was fortunate enough to then be appointed to be his successor and I served as the Scientific Director of NHGRI from 2002 until just about six years ago when I got this new job. But what I would say is one of the very first things I did back in 2003 shortly after becoming the Scientific Director was to honor what I thought was a very valuable legacy that Jeff had left behind in terms of his mark on the intramural program and being the founding Scientific Director and we established this lectureship in his name. And so just, and meanwhile we've had no problem getting truly outstanding scientists to be honored by coming and giving the annual Jeff Trent lecture. Just to give you a flavor of people like Janet Rowley, Lee Hartwell, Harold Varmus, Mike Stratton, Eric Lander, Brian Drewker, Carol Greider, Charles Sawyer, Chris Amos, Bert Vogelstein, Steven Chanick, among that list are three Nobel Laureates and multiple members of the National Academy, needless to say. I think people in the community also have deep admiration for Jeff and for what he did here and are absolutely willing to say yes when we invite them to give this annual lecture. And sometimes what's also great about this lecture is that it gives an excuse for Jeff to come back and visit us for a day and spend time with us and indeed this is one of the years he's been able to do it. So Jeff is here along with his wife, Dee, and a pleasure to have you here and thanks so much. So that's the history of the lectureship and I'd like to turn this over to our Deputy Scientific Director, Paul Lu, who's going to have the pleasure of introducing this year's Jeff Trent lecture. Paul. It is truly my great pleasure to introduce John Carpenter. First I would not say Dan Kessner, who is the current scientific director, said he's regret that he couldn't be here. He's actually in Australia, you know, this is 13 hours ahead of us and so he couldn't give this introduction. John probably don't need introduction too many in this audience since he was one of the first recruited by Jeff into his lab as a postdoc fellow and then a senior research fellow when John graduated from Ohio State University with his PhD and he came here working in the Jeff's lab for about six years and then he became a tenure track independent investigator in 2000. Then he left NIH, went to TGM, became the professor at the Division of Translational Genomics and the Division of Integrated Cancer Genomics and also became the deputy director of basic research in 2012. Only recently he moved to the University of South California, become the chair of the Department of Translational Genomics and also newly formed Institute of Translational Genomics. John has made many seminal contributions to cancer genetics and genomics and he has published over 150 papers. Many of them highly cited. I just checked this morning, one of them was cited more than a thousand times and which is quite impressive. He has several patents and he's a very busy person, he's on so many committees and he served NIH on study sections and other advisory roles and it's a really great pleasure to welcome back. Thanks Paul. Eric, I didn't know about that list. That's kind of scary. Well, I think I can say honestly that you know no matter how far my career goes I don't think there could be a more honorable place that I'd like to be than right here standing at the podium. I've given this lecture today, I have so many friends and colleagues in the audience and a number of them who've you know been incredibly supportive and have played very critical roles in some of the scientific discoveries that we've made through the years and I won't call names because I don't want to miss any names but to all of you I just want to say thanks again. It's been a fun ride. I remember one of the Harry Potter movies they were driving through London in a double-decker bus and it was going all over the place and the driver said in a very Caribbean way it's going to be a bumpy ride and I wish people had told me that before I started because it has been a bumpy ride but I wouldn't trade it for anything. I have had the opportunity again to work with a lot of amazing scientists and just want to say before I get started that I am I'm presenting this this on behalf of a lot of great people. I don't take singular credit for a single thing that I've done. It's just not my approach to getting things done. I was sort of raised in the culture of team science by folks like Jeff Trent and Francis Collins by bringing together you know enough smart brains you can get a lot of incredible things done and so through my career I've done a lot of work both on the germline genetic side the cell biology side as well as cancer genomics and tumor profiling and I could talk about a lot of different things but I really want to you know bring to bear some of the work that we've done and some of the concepts that we're seeing moving forward and how aspects of population and tumor heterogeneity have significant impacts on cancer genome science and and clinical phenotypes I'm going to spend a lot of time again in cancer and in the new medical paradigm of precision medicine here again focusing mainly on the work we've done in in the oncology space and I affiliate both with the University of Southern California as chair of the new Department of Translational Genomics but also maintain a relatively strong relationship with with Jeff and the team at TGen as an adjunct faculty member there. I know it's not ACR but I always like to do this and you know there are some financial disclosures I'm one of the founders of a shine analytics which is a clinical sequencing laboratory and I'll discuss off-label use of several FDA approved drugs including penatinib, isopinib, erlotinib and pertuzumab. So getting right to business I think you know the my presentation will be sort of sectioned based on you know looking at historical studies and some of the work that we've done and looking at population heterogeneity as a function of cancer genome science and then I'll go into some aspects of tumor heterogeneity and how that can influence our interpretation of data that's being used both in the research space as well as in the clinical space through precision medicine. So and thinking about population heterogeneity I think we we want to focus on phenotypic differences that we see and looking at sort of global cancer statistics for incidents and death rates and men and women and seeing the common cast of characters for incidents being prostate and breast and lung and colon and some other diseases that we don't look at very commonly because they're a little bit more rare like bile duct cancer, clangial carcinoma and then looking at death rates again, lung cancer still being a very significant contributor to cancer deaths even with the advancements in smoking cessation and prostate and breast of course and colon and then we start seeing tumor types that actually come off as being kind of rare like pancreatic and again this bile duct cancer I'm gonna talk a little bit about the work we're doing in that space but then when we focus on and look at cancer incidents and death rates and African-Americans or blacks we we see a similar picture where we see prostate and breast and colon but then we see things like Bob that cancer actually float up a little higher to the top of the list and looking at looking at men, African-American men and it actually happens to be the fourth most most common cancer in that group it's not that far down the female list either but again just you know thinking about you know there are some commonalities when we look broadly at cancer statistics but there are some differences and these things that we tend to look at as cancer health disparities where diseases like prostate cancer are about twice as commonly diagnosed in African-American men and although breast cancer is more common in white women the cancers can be detected a bit earlier and have more aggressive biologies in African-American women and I'll start off you know talking about you know these concepts of race and ancestry and I see Vince Bonham at least he was sitting in this in the audience there and Vince has really spearheaded a ton of work and really trying to educate the population on these differences and that these two things are not necessarily the same and there's a really complex interplay between the two of these things where race is being a social construct and and and I think Francis has called it a proxy of sorts and is much more related to social and societal related factors where we have and then we have ancestry which is real genetics and biology and is associated with ancestral genetic material that's passed through individuals and again there's an interplay here where undoubtedly you know individuals of you know that have common ancestral backgrounds can definitely have societal clustering and and higher in interactions and and can have more ethnic similarities but then you can also look at ancestry we can have individuals who have very similar genetic ancestries but have very different cultural lifestyles and so these two things there's a complex interplay there but I really want to focus on you know how we look at these things and and and primarily again thinking about genetic ancestry and principal components analyses and individuals like Rick Kittles and others have really spearheaded a lot of this work and understanding that there are very specific genetic alleles that have very high very different frequencies in different populations a gene and allele and Duffy is is one of the more sort of the poster child of of these ancestry informative markers that that that we we can use to actually been individuals based on true genetic ancestry rather than sort of racial cultural or ethnic similarities but again undoubtedly there's an interplay here between race and and society and constructs and ancestry and how they impact phenotypes and diseases and you know several questions can be asked can genetic ancestry be associated with biology and phenotype and the answer is undoubtedly an astounding yes I think we can think of a condition or disease such as sickle cell anemia and I and I you know take a moment to you know make the fact that we have to be careful also about characterizing phenotypes everything's not a disease some things are just conditions and it's a condition of an individual in one environment versus another one again sickle cell is a perfect example where individuals who live in a highly malaria infested area carrying out a little actually have it's beneficial because those individuals can live to ages to reproduce individuals who have a normal ill will be affected and can die from malarial infections you take those individuals out of that environment put them in an environment where there's no malaria all of a sudden they they have a disease so we have to be careful about that and salt retention and hypertension hypertension is another classic example and then we have like diseases and truly deleterious phenotypes like cancer that can be definitely a related more to genetic ancestry rather than race and but race of course without a doubt and I know if there's social scientists in the audience I am not the biologist who believes that these differences we see an outcome or health disparities are specifically linked to biology some of these things are associated with with socioeconomic factors such as poverty access to health care environments and some behaviors that might be associated with diets or lifestyles and and then this complex again this complex interplay between genetic ancestry and race but I want to walk through a few examples where you know we can start looking at ancestry or race and how it can influence disease risk and ancestry or race and how it might influence disease outcomes and the first example will be work that was done in lymphoma by group out of the ACS where they published a paper looking at disparities in the adoption of of the use of rituximab in patients with diffuse large B cell lymphoma where in the early 2000 was shown it was shown that adding this anti CD 20 antibody rituximab to chop therapy significantly improved both complete responses and and overall response in patients with lymphoma but they then went on to show that there was a disparity in the adoption and use showing that individuals who were African-American which were less like and much less likely to get a rituximab added to their chemo therapeutic regimen and then they were able to go on and show that individuals who had insurance versus those who are uninsured were less likely or more likely to get access to this blockbuster drug so in this case one can actually almost say that there's really no genetic ancestry associated with this disparity in outcome these disparities in outcome or or access to these drugs it's purely access to care and another example which I get really excited about is work that was done in pediatric leukemia Junyang and Mary Rowling the group out of St. Jude's and this is to me one of the real strong studies that that really sort of made a true link between ancestry and biology and a disease and I think it should be always known as one of the the first seminal examples of this so we know that ALL five-year survival rates are really high most these kids do do pretty well but not all of them do and there definitely some ethnic or racial differences in survival and outcome with purse poor overall survival scene and out among African-American kids and kids of at the time let's you know we're you know Hispanic ethnicity we can use various phrases Latino compared to European Americans or Asians and so June performed a genome-wide association studying on about 2,500 kids who'd been diagnosed with ALL and it's important to know that the treatment regimen tends to include initial induction therapy which can be quite intense and then condolent consolidation or intensification to really try to drive the cancer into remission and then after remission there's then given maintenance and during maintenance in some cases what they'll do is they'll do a real intense infusion for a month or two and this is called delayed intensification that occurs at the start of maintenance therapy and this will be important as I as I talk about summarize the rest of the study so he performed principal components analysis from AFI 500k data on these kids and if you look at the kids the sort of genetic contribution individuals with the the red this is European genetic contribution Africans are in gray the African chromosomal material or genetic ancestry green is Asian and then the blue is Native American and this is where the analysis got really really interesting he was a actually able to show that kids that had greater than 10% Native American ancestry based on their PCA had a much higher probability of relapse after therapy and this is relapse after after induction I mean after maintenance and so you can you can look here and and and see even kids who self-reported as white but had greater than 10% Native American ancestry also had a much greater probability of relapse and then when you looked at outcomes based on therapy when you looked at kids who did not get delayed intensification during maintenance there was a significant increase in probability especially when you looked at kids with greater than 10% Native American ancestry but when you looked at the kids who all got a delayed intensification you can almost completely eliminate the disparity so if you have a kid who comes in they take greater than 10% Native American ancestry perhaps that child should always get delayed intensification as part of their their maintenance therapy so again is this real cool association between genetic ancestry and a clinical outcome but through more of a social economic approach and making sure that they get the appropriate therapy you can completely eliminate that disparity so I think this is a great example of how we can think about ancestry and population heterogeneity and its influence on on disease risk and outcome and then I want to switch gears and talk a little bit about a little bit about the work that we've done in multiple myeloma in my lab and in collaboration with you know scientists from from various institutions I'll walk through that so myeloma being a disease of plasma cells with a very well-known molecular pathogenesis and from normal B cell the monoclonal gamopathy of undetermined significance or pre malignant B cell disease through full-blown myeloma with the primary genetic lesion being defined by translocations at the IgH locus on chromosome 14 to a series of oncogenes and downstream progression events including deletion of chromosome 13 or chromosome 13 monosome, asthmatic mutations in RAS, RAS genes in FGFR and other secondary events such as amplification of C-May. It tends to be a disease of aging meaning that the median age of diagnosis around 70 about 30,000 newly diagnosed cases 10 about 10-11,000 deaths per year. We've seen this incredible development of blockbuster drugs particularly the immunomodulatory inhibitors or or imids such as linalidomide and proteasome inhibitors such as Bortezimib and more recently carfilzimib. The five-year overall survival rate before the use of these drugs was only about 37% and it's increased to almost 50% because of the development of these incredible drugs but also of an importance is that multiple myeloma actually happens to represent one of the most significant cancer-held disparities looking at incidence rates in males it actually has the second highest rate ratio rate race ratio between African-Americans and Europeans both in males and females and in looking at death rates the rate ratio is also among the top killers for both African-American men and women so it's been a very disease of quite a bit of interest for my research program where we've got some hypotheses that we're trying to test one being although mortality disparities have decreased on the outcome side there's a still a consistent disparity in incidence rate and and that along with this historical difference in mortality could suggest a possible genetic role or biological role for these disparities and we've set out to determine if somatic events in tumors that are associated have been associated with poor outcome in myeloma through other studies might be enriched in tumors from African-American patients. We had a large series of about 250 tumors that we profiled in collaboration with the Broad Institute who performed genome sequencing my lab did and and in collaboration with Jeff we did a bunch of work in developing gene expression information and copy number data from from these tumors using array technologies all the data is available publicly through a portal within our interestingly interestingly within our cohort there are about 15 16 African American patients about 180 European American patients and what we wanted to do is to look at these regions of the genome that had been previously associated with our poor outcome or high-risk disease to see if there were any differences in the frequency of these events and tumors derived from African-American and European-American papers and Angie Baker as a staff scientist in my lab I was lead author on this paper which was a seminal study that was the first to report a biological and genomic analysis of tumors from African-American patients in comparing to tumors from European-American patients and just looking at the results of the copy number I won't go through everything in detail but one thing that jumped out at us was one Q gain which is a highly associated with a high-risk disease actually happened to be more frequent in tumors from European-American patients than African-American patients it reached statistical significance and after correction it went away but it was still pretty close and that was an indication that are we thinking about it the wrong way could African American patients actually have tumors that are more associated with favorable outcome and if they got the right drugs maybe they'd actually end up doing better and looking at you know some other like the Arkansas high-risk gene expression profile we didn't see much of a difference there we looked at 14 Q breakpoints we also saw here that tumors from European-American patients were more likely to have breakpoints at 14 Q than African-American patients again suggesting that perhaps African-American patients have tumors that are more associated with favorable outcome and in talking to lots of hemonic hematologist oncologists who treat myeloma patients they all tend to say that African-American patients do better when they get the image and the and the proteasome inhibitors so in this case we believe that African-Americans may have tumors that are more associated with favorable outcome and if they get the appropriate drugs and perhaps they might actually do as well or better but there's still this historical difference in incidents which could suggest that there might be an inherited factor involved in a more frequent development of multiple myeloma in these patients we've now since begin to apply deeper whole genome sequencing technologies to analyzing these tumors and of course they're awesome because we can do very comprehensive genomic interrogation point mutations across the exome or genome cop make we can deduce copy number changes identified grocery arrangements and if we have RNA of course we can do all sorts of cool transcriptional analyses and just a few slides about the work we're doing another study through the multiple myeloma research foundation which I think is it could be a model for cancer genome science going forward this is a longitudinal study it's not taking it's not performing genomic analysis and taking a snapshot of a single sample from a single tumor single tumor in this study we're actually recruiting patients at diagnosis pre-treatment and we've recruited a thousand patients and we're profiling all of these tumors normal tumor pairs tumors have been enriched for a whole genome whole exome and RNA sequencing all of the patients will go on one of three treatment regimens and then at relapse we're collecting tumors and profiling there as well so we can really get a sense of the natural history of these tumors during the course of therapy and this study is really being driven by a really talented scientist at TGEN named Jonathan Keats who I share the PI ship with and Winnie Liang who runs a collaborative sequencing center at TGEN and comparing this study to all of the other TCGA and large cancer genome studies we've generated more data than all except the next-gen sequence data it's for all except the breast cancer studies and just looking at you know the the distribution of RNA exome and whole genome again this being a compass and this being breast so we've generated quite a bit of data for this project already and these data will be made publicly available on one of the postdocs in my lab Zarko Munoilovich has been has taken this data and run music analysis to look at the mutational status of myeloma tumors and looking at the landscape and again we've published some papers previously on the the somatic landscape of myeloma in a smaller data set and but overall the mutation frequencies are pretty similar and we know what the most commonly mutated genes are but what this study empowered us to do is to be able to look at over a hundred African-American tumors making it the largest study today and over 500 600 or so tumors from your European American patients and what we've now done instead of just using self-identified race we've begun to extract genetic ancestry information from this and so this is a principal components analysis done by Zarko where we took first anchored our PCA using a thousand genomes populations focusing on the Yorubin of Ibadan Nigeria the African-American population from Southwest the CEP or the CEU from Utah the Mexican from LA and the Hong Chinese and so here are the different groups here's the Yorubin and the Brown the CEP the the Mexican from from Los Angeles and the Hong and the African Americans here you can see this sort of distribution or continuum through a sort of the we know the admixture between African and European chromosomes and then we can overlay our myeloma patients here in blue where we have our European self-identified patients and those that self-identify as African American and then patients that kind of fall in between different areas of the principal components and then begin to look at mutation differences based on the PCA so African Americans that have higher degrees of African ancestry versus those more centrally distributed in the continuum and then look at the differences and so this is just looking at you know the genetic alterations across a series of commonly mutated genes and some interesting things have popped out for instance looking at you know p53 mutations are much more common in tumors from European American patients than from African American patients and TP53 loss of mutations are significantly associated with poor outcome in myeloma so again these data suggesting that African Americans might have tumors that have associated with more favorable outcome and then all these mutations that are more common in tumors derived from from individuals with African African ancestry versus European ancestry and some of the genes of interest we're looking at is patch D3 not well well characterized gene but with a very significant difference and I think this group is really interesting because even though we have a lower number of African of tumors from individuals African ancestry we still see these significant differences we've got almost over 600 tumors here and so these frequencies should be pretty stable over time so again for the first time really understanding somatic differences in tumors from individuals based on on on ancestry and again you know looking at the Zarko looking at the pathways that might be more more differentially regulated in individuals in tumors from individuals from these different ancestral populations so again being among the first to really look at this in in depth at the tumor biology and relationship to genetic ancestry and our data again would suggest that these African American patients may have tumors with features associated with favorable outcomes so if they get the the right therapies they actually may have better outcomes but again we have not addressed the issues related to incidents and are hoping to do so through genome-wide association studies in tumors from African American patients using our whole exome data from Compass or performing high-density SNP array experiments and GWAS analysis to see if we can identify genetic variants that might be associated with this increase in and incidence in myeloma so hopefully you know this you know this this review period is sort of walks you through you know some some aspects of how ancestry can either influence disease risk or or outcomes and it could be race or ancestry two examples where access is clearly driving the disparities where there is a diffuse B cell infoma multiple myeloma and then one example where I think ancestry and biology actually is driving outcome disparity in ALL but you can eliminate that disparity by making sure kids get a very specific treatment regimen as part of their clinical management so now I want to shift gears a little bit and talk about some of the work we've done in precision medicine precision oncology again there's a lot I can talk about we've we've run a number of clinical trials a melanoma standup to cancer study with Jeff and study in glioblastoma with Prados in the group Mike Prados in the group at UCSF and or the study in triple negative breast cancer we've done with Joyce O'Shaughnessy at Baylor but again yet again I really want to focus on how population and tumor heterogeneity can influence our interpretation of data related to precision medicine and you know this slide just showing you know the fact that you know targeted therapeutics are therapeutics are here to stay and the more we understand about the genomic landscape of tumors we can provide novel targets to drug developers who can then develop drugs that specifically that hit specific very specific genomic alterations in these tumors and I think one of the things that you know really is awesome is the fact that these drugs don't have to be you know indicated for a single disease type we know a matnip works both in BCR able positive CML as well as kit and PDGFR mutated gist and you know we've seen activity with EGFR inhibitors both non small cell lung cancer and colon cancer and more recently we've seen the development of PARP inhibitors and and and work that we did with Rulsh and I and Ken Pienta showing that BRCA2 homozygous deletions occur at frequencies higher than we would have once thought in and castration resistant prostate cancer and these tumors respond to PARP inhibitors and it was a fast-track expedited approval of elaborate for the treatment of subset of castration resistant prostate cancers and then you know I'd be remiss to not say that this this new sort of it's really not new but a newly adopted approach of immune checkpoint inhibitors treatment modality and targets like PD1 or PDL1 on the tumors PD1 or CTCLA4 in the T cells and and the incredible outcomes that we're seeing with these immune checkpoint inhibitors doesn't work for everybody but in those tumors where it does work and we have some biomarkers where it might work like hypermutation expression of these biomarkers or the expression of neoantigens. So this growing laundry list of genomic alterations and targeted therapies has led us to this new revolution of precision medicine and where we can profile a tumor identify the appropriate alterations and then perhaps select a targeted therapy for that patient's cancer. These events of course are these genes are mutated by various mechanisms. We know the oncogenes in many cases can be amplified or mutated or overexpressed tumor suppressors deleted mutated or hypermethylated and we also know that some of these genes are altered by breakpoints translocations leading to the the generation of oncogenic fusions that can also be targeted. So you know through collaborations a lot of folks at TGEN and in partnership primarily with my good friend and colleague David Craig just you know I mean God I can't see enough awesome things about David and the work that he's done to help build this out but building out this algorithm and this was and I have to give credit to you know the stand up to cancer team that helped us derive this and submit a exemption for device to the FDA in support of our Jeff's stand up to cancer study but you know starting with patient and doc and consent and biopsy collection and of specimens and sending those specimens through quality assessment of the analytes and sequencing and bioinformatics analysis and then essentially merging the somatic information to the drug space and then generating these reports holding molecular tumor boards to vet that information and then provide what we feel is the most appropriate therapy for that patient based on the molecular profile. Part of this was building out an incredibly standardized and validated platform part of which was the creation of a controlled access clinical portal again this is David Craig my just tremendous friend and colleague where each patient can you know a clinical research nurse can go in and create a new patient fill out the form with with with a controlled lexicon and vocabulary standardized clinical annotations and then from this be able to generate auto-generated report that can be used as part of the molecular tumor boards and the sequencing I don't get any money from Illumina but I have their machine here just want to make sure that's that said and then we have again David's team building out just incredible bioinformatics framework to support all of everything from data collection data management data analysis secondary analysis generation and annotation of the information creating the reports that can then be vetted by the tumor board and and an incredible establishment of a relationship with Dell computing a lot of work hard work that Jeff did that has supplied us with an incredible high performance computing environment to support this work and and then you know the process of comparing each patient somatic tumor profile to a relational database developed by Jeff Kieffer and and more recently Sarah Byron I'm using her heuristic programs and and and algorithms to match the the mutation profile with the drug gene relation database and we can sort of modify the or tune the pharmacopeia however we want based on the study to generate reports that'll have the drug other information like is there an oral formulation for the drug sometimes it's really important the alteration driving that relationship is it a positive or negative indication and whether or not there are clinical trials available we built a CLIA lab fully validate validated so it's CLIA certified Kappa credited I have to give credit to Jeanine Lubello and Lisa Bombard Greerden who were the lab directors Mary Ellen Ahern who was the lab manager who helped us build this this clinical laboratory and so and Jeff and Pat had to submit this document to the FDA in support of their clinical trial and I have a picture of their faces before and after this process and I think there were a number of babies born some divorces and and a few people quit after that this document was submitted but boy the the overall benefits of having this in place have been tremendous for us because you know we feel like we're thought leaders in this space and being able to validate a platform such that it meets the the rigorous and stringent guidelines for CLIA, Kappa and the FDA. A number of papers have been published on on on methodologies as well as the results of some of these trials the triple negative breast cancer study being the first and was the most cited paper in molecular cancer therapeutics in 2014 amazing study led by Sarah Byron with Mike Prados and Galeo Blastoma even on the pediatric side work with Lenny Sender at the at Children's Hospital Orange County led by my postdoc Troy McEcheran recently promoted to to intervene assistant professor and I'm going to talk a lot a lot about the studies we've done in Calangio carcinoma and of course the work that Jeff and Pat are leading in and looking at B BRAF V6 non-V BRAF V600 mutated melanomas and even some some papers related to methods and for validation we just had this in nature reviews and just sort of reviewing the translation of RNA sequencing into the clinic. We have this paper where we have a set of synthetic oligos that mimic oncogenic fusions that can be used spiked into a sample in a clinical lab and used to validate the detection of oncogenic fusions from RNA seek data and then just a week or two ago this came out in collaboration with Illumina as well as a Marco Mars group in Vancouver where we have a normal tumor cell line pair Kolo 829 where we've all sequenced this in a clinical laboratory setting and actually developed a set of truth variants that can be used or compared to in any clinical laboratory to put this cell on peer forward as a somatic reference standard for clinical sequencing. And so now moving on to population heterogeneity I think one of the issues we face in precision medicine today is the fact that you know in many cases we want to just be able to use a tumor sample because it in using this method we you know we really don't in fear with the clinical standards and approaches in pathology labs right we're not asking them to give us a piece of fresh tissue and sort of alter their their day-to-day workflows and but some feel that requesting a sample and some feel that requesting a sample for constitutional DNA is not always feasible and complicates or slows the testing and but you know there may be high risk of false positives and this is kind of where I want to focus this talk several and this is very important I think from the pop from the population standpoint as some populations have higher genetic variation so much like much more likely to have private variants in their genome and those private variants can sometimes trigger drug rules and we've seen it many times in just some examples and I'm not going to name labs I'm just going to say lab e lab a and lab b this lab doing somatic analysis on the same tumor or the same DNA that was used for tumor only analysis where this lab had normal tumor new or was able to state specifically that that was a really a germline BRCA mutation and looking at the variants of undetermined significance on this list almost 10 to 12 of these variants actually were germline variants they were had nothing to do with these were not tumor acquired somatic mutations another case called rectal cancer same situation another patient with metastatic triple negative breast cancer where our lab detected a frame shift mutation and pick 3r1 which is therapeutically actionable happened to be missed by the other lab we won't go into that very much but there were two other mutations on the front page of that report one of which triggered a drug rule and interestingly we were able to show because we did normal to appear that that actually was a germ those two were germline variants one of these genes notch even though it didn't trigger drug rule here later could have would have which would have been the use of gamma secretase inhibitors for which the one of the side effects is incredible a diarrhea diarrhea and so we want to make sure that we're doing this appropriately and that individuals again from populations that have higher degrees of genetic variation where data may not necessarily be in the public databases for filtering can have more more of these false positives on their reports and so it's work done by Rebecca Halpern in David's lab and and Zarko in my lab and we took a series of patients we had African-Americans European-Americans and performed principal components analysis and looked at the number of mutations that would have been sort of from a tumor only analysis if you just use filtering using publicly available snip data showing that you would have had a much higher number of false positives and individuals who have higher degrees of African ancestry versus individuals of European ancestry and looking at the number of two of mutations again the average being 242 here versus 125 and and then looking at European versus African-American these tables not right but essentially what we're seeing here is that if you were African-American there would be an average of 240 variants on average versus 125 if you were European American and two and a half or three would have triggered a drug rule in an African-American versus 1.5 of those false positive drug rule triggering variants would have been on your report if in the case of European-Americans so again and this is a statistically significant difference so there's definitely an ancestral bias to this and we've been playing around with optimized and approaches using probabilistic approaches and essentially what we've done is we've sequenced a series of tumors really deep done some dilution series and came to the conclusion that if you have more normal contaminated stroma in the specimen you can use the germline variants because the whether it's tumor or germline germline variants we should have an allele frequency of about 50-50 in a pile up if it's a heterozygous variant but if it's a tumor variant and there's normal contaminated stroma those heterozygous somatic variants will have an allele shift and you can use that information to reduce the number of false positives and if you sequence higher meaning if you have a really high quality sample that's like 90 percent tumor you have to sequence upwards of 1600 to 3200 X to be able to identify these these allele shifts and so we've been able we've played David and Rebecca and the team of essentially came up with some algorithms where if this was a triple negative breast cancer from a Ghana African patient these you know you have you know almost 350 false positives if you use filtering only but if you use our approach you can significantly decrease the number of false positives that would end up on an approach and here Ghana and African European American triple negatives and a patient with glioblastoma that had Latino ancestry so I'm going to use a final few minutes of my presentation to talk about tumor heterogeneity and it's impact on precision medicine I think many of us in cancer have followed the work of Charlie Swanton and the group over at Cambridge and in the UK the Sanger Center where they took a sample from a kidney cancer patient and chopped it up into various pieces and then looked at the regional profile of each of these specimens they also had a chest wall metastasis that they looked at as well they were able to show that one of those specific regions region R4 which was this region had had mutations that were also available in the METS but none of the other lesions from that tumor did suggesting that this tumor sort of set in the middle between the primary and the METS and so they were able to draw these phylogenetic trees just amazing work that showed at the gene expression a level R4 also mimicked the METS more than any of the other from the primary renal lesion and so we've worked out some algorithms so this is one of our compass multiple myeloma patients and Jonathan Keats built out bioinformatics tools that will allow us to look at clonal variants in the tumor so in this particular patient we picked up three different clones this is looking at the sort of the bimodal or trimodal distribution of heterozygous variants which indicate various sub clones and so in this particular patient looking at time point one and time point two the distribution of these clones is pretty similar meaning this clone remain the dominant clone throughout the course of this patient's clinical management yet another patient you see very significant clonal dynamics occurring where at diagnosis you have this red and blue these red and blue clones that are the primary and this low level low line green clone at was also low at this time point but became among the dominant clones and the blue clone goes away over various courses of treatment so this tumor heterogeneity and the shifting and flowing of various clones under various conditions and so on and so on these clones under various therapeutic conditions is going to provide us with information on understanding what mechanisms are associated with response or resistance to the various therapies and then finally work we've done in cholangial carcinoma or bile duct cancer tumors of the bile duct they can curse sporadically or be associated with liver flu infection we're primarily focusing on the sporadics and it can be very difficult to treat we publish this paper with Alan Bryce and Mattesh Borat at the Mayo Clinic in Scottsdale where we showed the integrated genomic characterization and clinical sequencing identified therapeutically actionable context around FGFR and EGFR pathways and treatment one patient with an ERFI-1 homozygous deletion ERFI-1 is a very obscure scourging was not on many of the cancer panels that people were using in clinical laboratories but it's it's critically important because its role is to prevent dimerization of of of herb receptors so it can be among the has to be one of the most important tumor suppressors but understanding this patient at loss hypothesizing that it was it was leading to hyper activation of the herb signaling EGFR signaling tumor before erlotinib tumor after erlotinib this is looking at metabolic activity just a dramatic response because we selected erlotinib because of the hypothesis of EGFR activation we also identified tumors that had FGFR2 oncogenic fusions and translocations treating those patients with FGFR inhibitors looking at dysentometric scans before a ponatinib which is a select FGFR inhibitor and tumor after tumors just melting away in these patients so moving forward and thinking more about the concept of heterogeneity in a different context patient comes in with with advanced clangiocharsenoma sample sent for clinical sequencing looking at the copy number data we saw this event on chromosome 8 which was characterized as as leading to an oncogenic fusion include that that encompassed NRG-1 NRG-1 happens to be the ligand for herb receptors leading to increase that phosphorylation activation again more evidence that in this tumor type there's a context around activated herb receptor signaling and herb fusions have been seen in other tumors not specifically this one but what they showed was that these fusions leading to activation of her 2 and her 3 we also identified yet another ERFI-1 inactivating event in this in this tumor so we had activation of the herb receptor pathway on both sides both activation hyper activation through energy and and and loss of of makes 6 ERFI-1 the discussion of the tumor board focusing around herb receptor signaling not wanting to target any of any of the specific receptors but thinking about targeting multiple receptors by using a drug that would prevent dimerization that drug being protrusion map this is liver cancer before liver cancer after just incredible response to this but it was a transient response there was a progression after several months on on therapy we're actually able to collect a biopsy at progression and looking at the copy number the 8th event went away and this blazing amplification of EGFR pops up that wasn't there in the initial tumor right so treat with protrusion map we get rid of the NRG-1 clone this new clone is a reason that has this incredible amplification of EGFR significant response or a lot nib but again it was transient and now we get a third biopsy right so what happens next right you've been on protrusion map had a response you then go on our latin have a response cancer comes back so what happens is this going to change think I ran out of this work knowledge rinse you guys get to see my talk backwards the forwards okay here we go one more can you do one more no I don't one more go forward it shouldn't I am so I like pressed it like 80 times in both directions don't press the button guess what happens the first clone comes back so you've got this clonal ties so protrusion map kills this clone a lot of them kills this clone but the first clone came back but what happens in clinical oncology at progression you never give the the previous treatment because an oncologist mind the patient has failed that treatment right and so we have to take these aspects of tumor heterogeneity in I can't get this move and into context of precision medicine and I think it's complicating our ability to see improved outcomes using you know this incredible clinical approach so in summary population and tumor heterogeneity and genome science and precision college oncology exists there is race and ancestry and they can be related but are not necessarily the same I think I've shown that there may be an enrichment of certain biological factors that can be associated with biology and phenotypes and outcomes research into uncovering these factors will help us better understand a disease etiology within various populations and could provide information on how to better how to best approach clinical man clinical management development of tools and methodologies can help to improve the performance of precision medicine which can have critical impact on clinical interpretation results I think I've shown that particularly in ancestral pop populations that have not undergone significant bottlenecks where there are lots of genetic variants and tumor heterogeneity of course exists and is a confounder in current clinical precision medicine approaches and better tools and methods will allow us to better sample the entirety of a patient's cancer instead of taking snapshots of individual biologies to uncover these clonal aspects of these tumors that are primed taught to induce relapse so in conclusion one more kind of go should I touch the button who cares acknowledgements boy this thing was full of people's names it was all me but you know just you know specifically of course David Craig and and all the work that he's done he's been an incredible collaborator and partner in a lot of this work Jonathan Keats and Willie Winnie Liang and developing a lot of our sequencing infrastructure they are teaching can't can't say enough about the support that Jeff has given me through through the career to have the freedom to approach these high-risk studies that have I believe allowed me to apply you know knowledge in science and genomics to improve clinical care for patients and then our clinical partners Mattesh now and at at Mayo Clinic Pat Laruso at Yale Dan von Hoff and and the group at Scottsdale Health who Dan has been sort of the godfather of precision medicine at TGen and then all of the funding agencies MMRF the prostate cancer foundation Coleman for the cure the Ben and Catherine Ivy Foundation the NIH and the NCI so I'll stop there thank you if there are any I'd love to engage the audience Thomas this new energy one this gene actually localizes at the site of a common copy number variant and we and others have shown that these are sites where the common some breaks and this is correlated to either translocations or sites of copy number changes if you do see change absolute I know absolutely you know there's you know a really interesting observation that we've made in triple negative breast cancer I I don't want to give it away yet because I think it's going to be similar but we've seen breakpoints in a very specific region of the genome encompassing a very important tumor suppressor only tumors from African-American women so far and and and my hypothesis is that there's some genetic haplotype or some some that's that's more frequent in individuals of African ancestry that's leading to these breakpoints occurring at that very specific region of the genome so you know as part of our ongoing studies our hope is to better understand that to be able to you know utilize publicly available data like the data you guys are generating to look at where these breakpoints are occurring and to understand more about the genetic contribution and haplotypes and how they relate to specific alterations occurring specific somatic specific somatic events occurring at specific regions of the genome I think that it's been a lost opportunity in the cancer genome space that there really hasn't been enough integration between the germline community and the somatic community to really understand how the germline influences somatic alterations in cancer and I think that that could be one of the more exciting opportunities for us going forward and understanding cancer initiation and progression and outcomes in different in different groups of people maybe I can ask you a question so for the multiple my loneliest story you mentioned African-Americans they actually have a good favorable prognosis signature but their prognosis you know it's actually worse so have you look at the treatment you know they have received well that's the correlation that's the amazing thing about the compass study is that it's longitudinal and we know treatment up front and we know treatment along the patient's clinical management so we don't yet have that information but we will by the end of the study because we'll have arguably the only data set that will allow us to do that that's powered enough to make those correlations to be able to say if you have these events and you're you have favorable outcome but you didn't get you know these three specific regiments you're likely to do worse and you're likely to do better so we'll be able to make those correlations because of the design of that study if no further questions I just like thank you very much for this wonderful lecture there will be a reception you know right now in the NIH library and as a token of appreciation we're going to give this to John it's a you know aerial photo of a nice and you're welcome to sign this around you know the frames you know this will be in the library you know where it's building 9 that's what I'm doing 9 it's summer right there's history in a basement of building I need to go take a picture of it before they tear it down thanks Paul thanks