 Welcome to MOOC course on Introduction to Proteogenomics. In today's lecture, we have an industry expert Dr. Mukesh Jayaswal who will talk about advancement in cancer genomics. He will also give a brief introduction and overview of cancer genomics followed by recent applications of genomics in the area of cancer research. Dr. Jayaswal will talk about challenges of doing cancer research especially accurate diagnosis of cancer. As a result, the cancer is becoming double burden and how by using new technologies like next generation sequencing technologies, one could try to provide better diagnosis and treatment strategies. He will also talk about different strategies of treatment for example, the conventional chemotherapy, radiation therapy and various type of drugs which have been used for cancer treatment. But more focus will be in which way one could start using new diagnostic tools by utilizing NGS technology. So, let us welcome Dr. Mukesh Jayaswal. I am going to give little drive how Illumina do the cancer genomics. Today's agenda I am going to give brief introduction of cancer genomics and how it is utilized for the campaign diagnostic and how it is used for the treatment part. So application part and then some introduction. So, let us start with some introduction. Cancer is basically if you see in the life lifespan of any woman out of three one going to be have a cancer and man is one. So, in your lifestyle, lifetime to every three women going to every one woman out of three going to be a cancer and every one man out of two going to be have cancer right. Fourteen and fourteen million new cases coming every year right and eight million death every year and thirty two million basically is living with cancer right. So, it is a big number right it is a global data it is not Indian data it is a global data, but every year we getting number of people adding in there right. So, it is very important how to diagnose the cancer and then the treatment right, but good thing is that also of this figure actually nowadays technologies advances in such a way right. We increase the lifespan of the cancer patient ten years right. So, out of this is the data like out of like fifty percent of the cancer overall cancer ten half of the patient basically alive till ten year of the cancer treatment right. So, the time life that the frame is increasing and it this is very for different cancer type like cancer if you test this cancer it is basically sixty nine to ninety eight percent vary, but see the lung cancer is still is like three to five percent right. So, if you see this is the more is better for treatment this is has the less treatment right. So, we need to really work out which is the best biomarker for the diagnostic and what with the better treatment possibility right. So, like if you start with like very early stage how we basically do the cancer care initially like very early stage surgery and radiation chemotherapy right, ninety forties now still be doing chemotherapy right, but now after the discovery of genomics right 2000 we start targeted sequencing right, targeted drugs right and now is the novel drug therapy college immunotherapy right. So, so, Illumina focus is basically this part really help the cancer patient for the targeted therapy and followed by the novel immunotherapy. So, I am going to cover these initially like when is there is a cancer people say this is a lung cancer right, breast cancer, but now because of this technologies this organs go to molecular level right, when there is a lung cancer these are subsets of the genes based subsets of the genes which get mutated and they are differential mutation some organ has different type of mutations some has different right. So, now we can say if you have a lung cancer these are the subsets of the genes which get mutated right and these are multiple it is not one now it is a multiple it start from the one gene now is going to be a several gene for one once cancer cancer type and some are those are common also some are common also right. So, coming to the one example see the lung cancer right see 2003 we have Keras only now 2016 we have like 17 different gene added right and these are basically all with the discovery phase and some are basically in the clinical trials also right they are drugs available for that because of the discovery of new genes which are mutated we find out a targeted therapy for that and we have several drugs available for the treatment only important thing you have to do proper diagnostic at right time right. So, I will explain some example so it may be multiple multiple also so if you see the rapid increase of the drugs also see here 511 deaths are in the late clinical trials. So, drugs are coming for the cancer with NGS this is significantly increased right. If you see the country wise if you see the US number see here this light blue is available drugs for the treatment of different different cancer type. So, US have 14 different targeted therapy for the for the treatment of these cancer but see India right now is I think it is not in number but see the China is the they are increasing well also and 6 target therapy is there. So, I think we are still in the discovery phase but I think coming future we going to be come somewhere in this number right. So, what is how we detect the mutations that is really important I just taking the very basic things what is the mutation in the gene right it can be multiple format. So, if you go gene DNA variation is a copy number is a single nucleotide variation that is called a SNP that means one base change if you see this is DNA see this is the one base change which is called a SNP right. Another format DNA variation is translocation right these are normal chromosomes and some part of the chromosome break out and it translocate to each other right is called a translocation. Then there is some part of the DNA inserted or deleted in the part that call insertion deletion inversion and sometime the some part of the chromosome is it duplicated or deleted that is a copy number changes. So, there are multiple variants occur in the DNA it may be format of single copy SNP format CNV insertion deletion. So, we need to detect this type of mutation very in very accurate way right that is how Illumina helps to the cancer patient for the detection of these variants plus also through the campaign in diagnostic we also prescribe the treatments right if you go for the RNA variants. So, DNA is DNA we talked about RNA variant means sometime the genes are fused RNA fusion right sometime the the expression of genes is changed right. So, we need to change look also the thing for the treatment of the cancer. So, these are multiple form of variation in the RNA format to detect these variation we do two approaches one is the whole genome sequencing approach that means you are sequencing whole genome right that means you you are sequencing all 24 chromosome pair right chromosome 1 to X and Y right to do this you need. So, what sequencing does it reads chromosome number 1 1 time 2 3 all the time it generates 3 GB data when you when you when you sequence all the chromosomes right all the chromosomes 3 GB, but if you read 3 times 30 times that means 3 GB multiplied 30 90 GB data is required to sequence genome in 30 times means for the accurate read right what happened right when you start reading you start one time you add some error right. So, we do multiple reads right. So, for human genome is recommended you read 30 times. So, for one human genome that means you are going to generate 90 GB data and which is can be done in a lamina platform only from high sick to Nova sick right I will tell little little all on that. So, another approach is targeted therapy targeted sequencing that means you are not targeting your genome you are targeting only the small portion of genome let us call it targeted therapy. Suppose your cancer patient has multiple gene spread on different chromosomes what you do during the library preparation you only pull down these parts of the chromosome arrest is removed right and these red circle one is captured there is a different way of capture I will take you can detail how we capture that thing after capturing what we do we do the sequencing is the same calculation if you do targeted sequencing and read by 100 times 100 x means 100 time that means you generate that much data suppose this all red part of the DNA is total target size is 15 MB if you read 100 times that means you require 5 GB data that is why simple calculation is totally depend on how much sequencing data is required basically it comes upon what is your target design what is your target size if your target size is 50 KB only you want to do 100 sequencing you required only 5 GB data. So, depending on your target depending on your application you might require different type of sequencer. So, these are the Illumina sequencer it start from the very low data output it is called IC ICs on generate only 1.2 GB data that means it is good for single gene like BRCA 1, BRCA 2 right very small panel right many see it generate around 7.5 GB data maximum my seek 15 GB data next seek is 120 GB data is all depends is high throughput is totally depend on what you want to do sequencing suppose if you want to do exome sequencing means the part of the DNA which which express their gene right. So, for one exome data it required 5 GB data right. So, if you choose my seek you can do only 3 samples because 15 GB divided by 5. So, total 3 samples by if you go next seek 200 120 GB that mean divided by 5 you can do around 6 around 20 to 30 samples right. Then high seek these are the high seek series per we we are not basically selling this one now we have a nova seek nova seek generate like 6 GB data means 6000 GB data that means you can do around 500 exome 2400 genome in one run. So, capacity of the sequencing is really increased by the Illumina technology right I think none of the platform here in in in any any player we can do this much data generation like 6 GB data and these type of the sequencer like nova seek really help the community for the cancer care because you need to do very deep sequencing to see that variant right because there is two type of variant one time germline variant which inherited to the mother and father right one is somatic which is generate doing your life lifestyle right and their frequency of frequency of detection is very low 0.01 percent that means to detect that variant you need to go for high x read like 5000 x read you need to go 2000 as read right for that you need to give at least have the bigger sequencer to get this data right. So, Illumina what is Illumina is platform benefit is the quality the quality of data is basically very high the Q30 is is 99.9 0.9 percent that means that means Illumina sequencing incorporate one error in thousand base pair. So, really really high sequencing data right then we do parent sequencing I think this is something very important when you go for the somatic machine detection coverage is very high. So, there is a multiple feature which Illumina basically has a very good very good sequencing platform for the data generation and actually total human genome 90 percent data is done by the Illumina right. So, because of these these this technology it is the for the case cancer patient the different collaboration with the Illumina these are the collaboration people use these technology for the cancer care right. So, one is Lex Luxo, Bristol Mayor right IBM Watson these are the collaboration which basically use Illumina technology for the campaign diagnostic. So, I am giving from this point I am going to give some of the example how basically these are used for the application for the cancer care. So, this is the how the patient journey start right if you see the very important right what type of therapy you are going to give the patient this is really important thing and for this diagnostic is very important. So, nowadays there is a multiple sample size may be plasma may be FFP tissues right. So, nowadays people use ISC QPCR and NGS also, but there is some drawbacks when you go for the real-time PCR or ISC because at a time you can do only one gene right, but for the cancer is the multiple gene required you need to go for very high throughput sequencer to do the NGS right. So, this is this is where the Illumina works start what type of therapy you need to give to the patient and then monitoring. So, for this one depending upon the customer right depending on the if there is a regional hospital they do very small panels right 5 to 15 genes some are bigger clinical trials right they do 500 gene panels some are doing whole exome or whole genome sequencing and they do different approaches to identify the cancer what was the cause of that right. So, we have a complete solution for the library prep instrumentation informatics part which tells you like what with the targeted therapy what could and what with how you and there is lots of clinical trial going on and these instrument is also IVD approved. So, that means you can directly imply into the IVD mode with research. So, I am telling this one is really because this is the NOVA 6 series is generated 6 TB data but is can virtually sequence any genome any targeted panel any method and any skill right. So, this technology basically people using to use for a targeted therapy let me show some example this is the ICIC these are two DX model of the Nesic and Mycic some applications right. So, this is the genes basically this is around the 34 common gene 34 common gene which is expressed in most of the cancer type different cancer type and these are common right and these are basically germline germline mutations which are 34 gene. And if you see the Breca here is basically common in 50 50 type of the cancer that means that means you can there is a question right if somebody doing a single gene panel and somebody doing the multiple gene panel the accuracy for the multiple genes much better because it doing the multiple gene and these are common markers for all. So, it makes sense you do the multiple gene. So, what cancer gene does is basically regulate the cell proliferation DNA repair and other function. So, if you see this is the hereditary gene this is like 114 gene which are overlapping with a somatic cancer right and overall is around 500 gene basically which is involved in the cancer means involved in the cancer. So, it is already well studied right some are hereditary some are cancer somatic and both are overlapping some extent like 45 genes are overlapping. So, we try to design a one comprehensive panel right to and it can be come from different organ also to detect the these mutations one comprehensive not not one one comprehensive panel. So, this is one example this is done by the strand in India this strand in Bangalore. So, they use a multiple gene panel which is TST 15 as a 15 gene panel and they studied this thing in the breast cancer and ovarian cancer right and they identified that the there is a 51 pathogenic mutation which are common in the breast cancer and ovarian cancer right. So, it is a value if you value that if you do the multiple gene if you do one day maybe you miss it let us see the example. Suppose there is a colon cancer and you get a tissue for the for the diagnostic right and you do only one test Keras right and if it is negative if it is positive that is ok it is a therapy available right it is negative you have to other another another test is BRAF right if it is getting it is another test right and RAS right, but if you do these tests it takes 21 days and amount of tissue basically gets more you need every time you need fresh tissue and the cost of the per test is also added. So, that means if you have one common panel which can do multiple thing and all the mutation your therapy must be better right that is how the campaigning diagnostic or precise precise treatment done there is a patient multiple target means all all type of cancer one test if you get something mutated there is a different different informatics part and you your campaign diagnostic treatments available right. So, it is very important when what what panel you basically using. So, Illumina has a multiple multiple cancer panel also. So, if you we have the comprehensive cancer panel we have a hotspot cancer panel smaller panel also the multiple cancer panel I will go one detail one by one. Let me tell you how we make the library like up to this point I told you we have the different cancer panels right, but how we make the libraries right that is a very important part. So, we use a Nexta DNA flex library preparation right in this this is the very very easy process it takes only 10 nanogram of DNA any type of tissues FFP tissues usually the cancer type is a long time you get going to have FFP tissues and to make this library is only 6.5 hours. So, it is very easy right and it is cost effective also. So, how we make it. So, just to see this is the your targeted DNA right which you want to target right. So, this is the transposier base enzyme it fragmented DNA the smaller fragment right see. So, now this adding the adapters at this this is the target you we want to sequence and this is the adapter which is going to bind in the alumina flow cells and indexes. If you see because we do the targeted sequencing. So, that means you need have to have a probe which captures that target right. So, this is the blue color is the probe is like 18 or 19 or big long and it is biotinated right. So, if it is biotinated is bind to this target and you have stepped up in label bead it pulled on only that part right. So, it gets only that part of DNA and this is the enriched part of your DNA that means you have targeted you have enriched only that smaller part of your DNA right. So, that means with this technology you can easily target smaller of the DNA for the sequence. So, it is totally depends upon your design how it can be one gene only it is a 18 merbed long probe but if it is bind to DNA it may be bigger also yeah. So, but we cut the DNA in such a format if you see here here is 150 base pair. So, it cannot be more than 150 base pair for sequencing. Yes. Yes. Indi-hydrography. And we try to make sure you all the part of that gene is covered it might be overlapping probes also right. Suppose, if we do not cover you might lost some part right. So, that is how we do the library prep right. Okay. So, after level I want to show one case study here. In this case study a woman of 68 year old is diagnosed with myelanoma right. June 2011 so it is surgically removed right. After few months is that the cancels metastase it become it is goes to the lymph node and then after two through three months they develop a subcutaneous pulmonary metastasis right. So, after doing surgery also it basically goes is increases not not not not basically cared it is not cured right. So, what doctor did what doctor did doctor ordered a test which covers only two genes and RAS and Keras right. And that detail only three mutations. So, when they when the when they find that there is a no mutation on Biorap and no mutation of NRAs right. So, that is why therapy does not work because you do not cover all the things. Then added at the end NJ test was ordered right. And they find very novel mutation is a different mutation on the Biorap gene this is the kinase domain and this is the mutation type is a totally different mutation right. Now, when they find this mutation in the kinase domain what it did with the help of that chemotherapy they give another targeted therapy to block this one. They give the kinase inhibitors and this is the name of kinase inhibitor right. With the giving of this kinase inhibitor the in few months 30 percent drop and another few months is 30 percent drop. Finally basically the case study is saying that studying only of by the real time PCR a few part of the gene is may not enough because you need to go cover all the all the part of gene right. And after studying getting this type of mutation they find that no you can do one chemotherapy per targeted therapy kinase inhibitor mixed together and is better for the treatment. So, this is one case study how people use the targeted therapy right. So, coming through this the important point right doing one gene is not enough maybe 10 genes not enough because cancer is a bigger is big pathway multiple genes are involved it is not one gene. So, we recently we launched once TST 170 panel. So, we launched one this panel and covers most of the cancer type and is involved to determine the different type of cancer it also did it the copy number variation RNA fusion and all. So, one gene panel ok. So, one last point like I want to share this is the novel therapy by Onco. So, Imno Onco. So, up to this point I showed like there is a comprehensive panel made and different ways of therapy right I do not have to cover all, but let us go this one. Immno therapy is really a very novel way to show like how we going to treat by the immunotherapy. So, if you see here one simple example PDL 1. So, PDL 1 is PD 1 is basically if you go this slide this is the tumours tumours and this is the T cells and the PD 1 is this is pressed in the T cell and PDL 1 is pressed in the tumour cell. Their interaction basically blocks the T cell activation and allow that tumour cell grow right. So, if the doctor give the chemotherapy right it not going to help because T cell is not responding. So, what the best way about the treatment give the double therapy targeted therapy to block this PDL 1 right to block this PDL 1 and give the targeted therapy. It will help the patient to recover fast right because at that time T cell get activated and kill all the cancer environment. So, these are the multiple paper where people use anti PDL 1 for the treatment of the different cancer type. So, if you see the example this is the inhibitor of the PDL 1 if the tissue have the high PDL 1 expression if you give this drug the response is basically better get better at least for the treatment purpose is to 70 70 percent. So, that means you by giving these kind of immunotherapy also it is better for the treatment of the cancer patient right. So, I am stopping here the key home message like targeted therapy basically helping the cancer patient for the for the treatment and we are moving towards the campaigning diagnostic thing right. So, there is a one panel which going to be the say this is kind of mutation you have and this is going to be targeted therapy or targeted drug going to be available in the way and the drugs are numbers are increasing maybe after five year you going to have multiplied drugs slide. So, I think is things are changing with the targeted therapy and this is going so fast. In today's lecture Dr. Mukesh Jaiswal talked about different mutations and variations in the gene which need to be diagnosed primarily and accurately to deal with cancer. We also heard how a specific industry technologies such as Illumina platform is going to provide new strategies to detect variations in DNA and RNA which could be used to select treatment strategies. He also talked about two important approaches that is used by Illumina in cancer genomic studies first whole genome sequencing and second target sequencing. Thank you.