 Thank you very much, Amos. So firstly, I'd like to appreciate Amos and his staff to give me such a good opportunity to present my research. I really enjoy meeting some symposium and building this area. Actually, this is my first visit for Lawrence. In my presentation, I'm going to talk about cell line establishment in sarcoma research. As he said, my specialty is cancer protonics. And I'm still learning, investigating cancer proteome. The reason why I needed to establish cell lines in this field is quite interesting. And it will be relevant to your study. In this century, cancer cell lines has been increasing. The importance of cancer cell line has been increasing year by year because of two reasons. So firstly, owing to the technology development, we can easily obtain the data of protonics or transcriptomes of the patient. And by integrating those global data with the clinical pathological data, we can create many hypothesis. And to prove that hypothesis, we require the patient-derived cancer models, such as cell lines. This is the first reason. And the second reason why we need the cancer cell line is that in this century, we have more anti-cancer drugs. In the previous century, we had a very limited number of anti-cancer drugs. For example, when I was a medical student, we had just 10 or 20 anti-cancer drugs. So we didn't have to learn so many about chemotherapy. But in this century, we have a separate hundred anti-cancer drugs, mostly molecular targeting drugs. And we are expecting to predict the response to treatment by examining the mutational status of the drug-able genes. However, the prediction is not always perfect. And we have to establish a correlation between the mutation status and the response to treatment. And the best way is the clinical trials. But the clinical trials are always difficult to perform. So we need some cancer models, such as cell lines. For these two reasons, the importance of the cancer cell line has been increasing year by year in this century. So in my talk, I'm going to talk about the cellular establishment of sarcomas. You may think that cell lines are easily available from the public cell banks, but it's not so true, especially in the field of rare cancers. And I think many of you already know something about rare cancers. So I just confirmed the concept of rare cancers. So rare cancers are defined according to the extremely low incidence of the patients. When the number of the patient number of the people who newly diagnosed as certain malignancies is less than six by 100,000 per year, we call that malignancies as rare cancers. So this definition is quite unique because usually malignancies are defined according to their original organs or their original or molecular background. But in the case of rare cancers, they are defined according to the number of the patient. So because of this definition, many malignancies are classified into this category. According to the definition of rare cancer net, we have 198 different malignancies in this category. You can see that we have a lot of different type of malignancies in this field. And because they are defined just as the number of the patient, they do not have any common molecular background. And all rare cancers behave differently. So the study of rare cancer is quite complex. And this slide demonstrates a demonstration of malignancies. So the X axis, I plot the malignancies and the Y axis, I plot the incidence of the individual malignancies. You can see that there are small number of malignancies with a lot of patients. And we can also have many malignancies with small number of the patient. So in the case of rare cancer, all those are number of the individual rare cancer is very small because we have so many different rare cancers. Rare cancers are not so rare. According to the statistical study in Asian country or European countries, approximately 20% of the cancer patients suffer from rare cancers. So rare cancers are not rare and the study of rare cancer is quite important to improve the health welfare of our society. Then also the total number of the patient with the rare cancer is not so small because the number of individual rare cancer is very small, the prognosis of the patients in this field is quite poor because the treatment for individual rare cancers is quite limited. This slide demonstrates the prognosis for the rare cancer patients and the common cancer patients. You can see that after diagnosis, at any point, like one year or three or five year, all the way the survival rate is shorter in rare cancers than that in common cancers. Then according to the statistical study in the United States and Europe, 25% of all cancer, 20% of all cancer deaths is responsible to the rare cancers. And making diagnosis is very difficult in the case of rare cancers. Because of the small number of the patient, pathologists cannot have the experience about making diagnosis of rare cancers. In this study, the pathologist in the central hospital distributes the pathological slides of rare cancers to the pathologists in the community hospitals. Then try to see how they can make correct diagnosis for the rare cancer patients. And you can see that in 43% cases, the pathologists in the local hospital made long diagnosis. So based on the long diagnosis, the doctors cannot achieve the best treatment for the patient. And clinical trials are especially difficult to conduct in rare cancers. And as you know, the clinical trials cost a lot of time and effort and money. And the market for the rare cancer patient is quite small. So the pharmaceutical companies hesitate to make a drug for the rare cancer patients. So a good example is that in Japan, we have 100,000 new patients with lung cancers every year. And in contrast about Oshiro Sarakoma, we have only 300 every year. In the case of Oshiro Sarakoma, we have just 40 patients annually. So if the drug company develops the drugs for those patients, they cannot recover the investment. So the drugs for the rare cancer patients are quite limited. In Japan, currently, we have more than 100 anti-cancer drugs approved for the treatment. And this slide demonstrates how drastically we became to have new anti-cancer drugs in this century. In the last century, as you can see, the number of the anti-cancer drugs was quite limited, but we still use many of them. In this century, we have so many anti-cancer drugs and mostly they are developed for the major cancers like lung cancers or colorectal cancers or liver cancers. So the molecular drugs written by these red characters are developed for sarcomas, only two. And then I will talk about sarcomas. And sarcomas have more than 100 different subtypes with different clinical behaviors, but only two drugs were developed in the last 20 years. Then, as I said, rare cancers consist of many different type of malignancies. And this slide demonstrates localization of rare cancers. And among them, I have been focusing on this category, the malignancies from connective tissues, namely sarcomas. It is just because of my personal communication. In the last 20 years, I have many medical doctors for sarcomas in my laboratory. So I continue the study of sarcoma proteomics in my laboratory. Then I'm talking about sarcomas overview. So sarcomas are quite challenging malignancy because of diversity, complexity, and reality. So sarcomas derived from the connective mesenchymal tissues like bones, ribbit, and connective tissue, so meaning that sarcomas can occur almost everywhere in human body. So the medical doctors in the different field see the patient with sarcomas. And reflecting the original tissues, sarcomas has many different historical subtypes like more than 100. And this classification has been changing. And I will talk about that later. And also, sarcoma occur almost everywhere in human body and consist of more than 100 different historical subtypes. So total number of the patient with sarcomas is quite small. In Japan, approximately 3,500 patients, 3,500 people are newly diagnosed as sarcomas annually. Then, to see the molecular background of this disease and to develop the biomarkers for the therapeutic strategies, I have been conducting a proteomic study in the National Cancer Center. I started to work in the National Cancer Center in 2001. And since then, we develop a lot of different proteomics modalities, such as large format 2D ditch and reverse phase protein array and mass spectrometry. And I will show you some example about the result of the proteomic study for sarcomas. So firstly, we try to see if we can classify the sarcomas using proteomic data. It was almost 20 years ago, and we had very nice results. Using the proteomic data, we can classify the sarcomas. So using the hierarchical clustering analysis, we found that sarcomas are naturally classified according to their proteomic background. That classification was almost close to the historical classification. So obviously, proteomic data reflect the histological appearance of sarcomas. Then, for the next step, we try to develop the biomarkers to predict the response to the new adjuvant treatment. In the case of osteosarcoma, medical doctors always treat the patient with chemotherapy before the surgical operation. And when the patient responds to the chemotherapy well, their prognosis is very nice. Actually, five years of average rate exceeds 70%. But if they do not respond to the new adjuvant chemotherapy, their prognosis is quite poor. And the doctors cannot predict the response of the new adjuvant. So all the patient receives the chemotherapy before a surgical operation. And many patients with osteosarcoma are children. And the children suffer from the side effect after the treatment. So we try to avoid the unnecessary chemotherapy by developing the predictive biomarker. So in this study, we obtained the biopsy specimen for the patient before chemotherapy. And we conducted the proteomic study and found the proteins which are through the expression level are highly associated with the response to the new adjuvant treatment. So we validate this result using the additional cases by Western blotting and in histochemistry. And this is one of the result of the validation study. So this patient shows over expression of peroxial reduction too. And we expected the poor response to the treatment. But we cannot change the protocol because this is standard chemotherapy. And according to our prediction, the patient didn't respond well to the new adjuvant chemotherapy. So this patient had larger tumor after the treatment. So this is one of the examples of the predictive biomarker in sarcoma. And in this case, we try to develop the prognostic biomarker in new sarcoma. So in this case, we use the surgical specimens for the proteomic study and found that the nucleophosamine was highly correlated with the prognosis of the patient. When the patient didn't show when the patient of nucleophosamine negative tumor, their prognosis was quite high, quite nice. Instead, if they had positive, their prognosis is quite poor. So this is a very nice example of the prognostic biomarker in new sarcoma. And we also try to develop the prognostic biomarker in gastrointestinal stromal tumor. And I just omitted the detail but the validation study was very successful. We examined more than 700 cases in the seven different hospitals for the validation purpose. And immunohistochemistry will use the high correlation between the expression of fetching and prognosis of the patient with this tumor. Then this is just an ordinary course of proteomic study. I mean, using biomarker resources, we achieve the proteomic study and we try to identify the proteins by which we can predict the clinical behaviors of patients. And after that, we are always required to perform the functional validation study. And at this step, we need the cell lines. Then I always encounter difficulty to find adequate cell lines for the validation purpose. So empirically, I know that we need more sarcoma cell lines. So I investigate the contents of public cell marks by hand manually. Then I found cell cells at that time. So it was almost five years ago. So I retrieved the information from the cell house and achieved the meta-analysis. How many sarcoma cell lines are available from the cell banks? So this work was quite difficult because the name of sarcoma is very valuable because the diagnostic criteria has been changing in the last 20 years. Especially when we became to have the molecular data, the classification has drastically changed every three or four years. So we use the criteria by WHO at that time, and then try to see how many sarcoma cell lines are available. So during this step, we omitted the duplicate cell lines. For example, some cell lines appeared in cell cells repeatedly because those cell lines are transfected with many genes. So we unite those cell lines in a single one. So this is a summary of our results. So as a total, you can have the sarcoma with this number. So cell lines with publications, the number of those sarcoma 571 plus 108, and the cell line is available from cell banks in 108 plus 36. So this 108, 108 sarcoma cell lines can be used for the research for sarcomas. You may think that 108 was a huge number. Actually, it's not, because we have more than 100 historically different sarcomas, which shows the different clinical behaviors. And the limited number of sarcomas are repeatedly subjected for the cell lines. So this is a summary of the histological classification of the cell lines, and how many cell lines are established for each sarcoma. And you can see that the top three sarcomas, we have so many cell lines, like osteosarcoma, labdomyo sarcoma, and ewing sarcomas. And other cell lines, we have just several. And the sarcomas out of this list, they didn't have any cell lines. So when we investigate those sarcomas, we always encounter difficulty for the functional study. And I don't know why these three sarcomas, we have so many cell lines. So one key is that these three sarcomas are children sarcomas. So I think pediatricians focus on the establishment of the cell lines, or the cells from children can be easily established for cell lines. So anyway, so we have so many sarcomas, but we just 108 in cell banks on publication. So definitely we need more cell lines at some time, or even now. Then at that time, I found that we have a vicious cycle in the rare cancer study because we cannot have enough clinical materials for the research. We do not have cancer models. And without having cancer models, we cannot conduct any experiments in the laboratory. So we cannot expect good research outcome, and nobody invest, or nobody give us research fund. Then nobody create new cancer model. So we have to change this situation. So if we start to establish new patient and derived the cancer models, we can change this situation. Once we have a nice cancer models, more number of people will study rare cancers. Then we can expect more investment in this field. Then somebody will create new cancer models. With this idea, I started to establish cell lines of rare cancers. It was 2012. Before that, I asked the researcher to give me cell lines. So I sent email repeatedly, and I got no response. So I decided to make cell lines by myself. So since then, almost every week, I receive the two more tissue sample from the hospitals and try to establish cell lines or general grafts. And at the same time, I also do some proteomics or genomic study for the established cancer models. So this is the list of the cell lines established in my laboratory. At the beginning, we couldn't establish cell lines at all. Actually, I had no experience about primary tissue culture even now. So we had a very difficult time. But we improved the research conditions or I hired good people for the cell line establishment. And recently, we can establish so many cell lines annually. And then we have the list in the cell cells. With the name of NCC sarcoma cell line panel. Then by using the established cell lines, we are now currently conducting so-called pharmacoproteogenomic study. So in the pharmacoprotegenomic study, by using patient-derived cancer model, we screen the drug for the anti-tumor effects. And at the same time, using the cancer model, we also examine the molecular background as a proteomic-genomic level. And by combining these results, we can identify novel anti-cancer drugs as well as the predictive biomarkers. So I purchased the molecular targeting drug, which were approved by FDA as many as possible and examine the anti-tumor effects by using the established cell lines. At the same time, I also investigate the mutational status of drug-able genes by using the technique of the next-generation sequencing, Wasnip array. And I can see that several mutations which could be drug-able in the different type of malignancies. And I also confirmed amplification, which are already reported in certain sarcomas. Then I combined the results of drug screening and the proteomic study. And unfortunately, the sarcomas, with so-called drug-able mutation, didn't respond to the corresponding molecular targeting drug. So, but these results are quite concordant with the clinical observations. For example, EGF receptor mutations are often observed in osteosarcomas. But osteosarcomas never responds to Imachinip. Or we can say the same thing for other combination. For example, B-luck mutations are also observed in many sarcomas, but they are not responsible for molecular targeting drugs. So we can establish the combination between the genetic mutation and response to the molecular targeting drug by using cell line in high-slip way. Then once we have some nice concordance, we can go to the clinical study. Then in the clinical, in the drug screening, we usually we screen more than 200 anti-cancer drugs approved by the FDA. Then we found certain drugs shows very nice anti-tumor effects for many of the established cell lines. And we are now confirming this result using the xenoblasts, patient-derived xenoblasts. So this is a list of the histology for which we could establish cell lines. So I always have some questions. So what is the factors for the successful cell line establishment? But currently I don't have any answer to that question. For example, for certain sarcomas, we repeatedly establish the cell lines. For example, giant cell tumor bone. But the giant cell tumor bone is not so malignant. Usually, this tumor do not make distant metastasis and the prognosis of the patient is quite nice. But instead, malignant perforal nerve cis tumor, this is very malignant sarcomas. Then the other one, yeah, so I mean the malignant potential in vivo does not determine the success rate of cell line establishment. So I need to continue this study. So I will retire in five years from National Cancer Center. But definitely I cannot complete this project. I have more than 100 sarcomas for cell line establishment. So I hope my students or my staff continue my project after five years. Then in addition to sarcomas, we have so many rare cancers. So but I prove that it's not so difficult to establish cell line of rare cancers. So I hope to expand this study by somebody and to have more cell lines for rare cancers because we may have the similar situation in all rare cancers. And we also have the different similar situation even in common cancer. So this slide demonstrates the molecular background lung adenocarcinoma. So lung adenocarcinomas are definitely common cancers. And we have so many cell lines of lung cancer. But when we look into the molecular background of those cell lines, there is actually we need to have more than more cell lines. You can see that the molecular background are quite complex in this tumor. And actually backgrounds are a little bit different between Japan and the United States. The previously, the molecular background didn't so much at all in the clinical practice. But nowadays, because we have molecular targeting drugs and the medical doctor decides the serobility strategy according to the molecular profile, we need the cell lines with unique combination genetic profiles. So in that sense, we need more cell lines with the detailed data of genome and proteome. So this is the last slide of my presentation. I hope the cell cells to provide us the information to decide which cell lines we have to establish further. So currently, definitely we need more cell lines and the priority should be determined according to the clinical requirement. So I hope cell cells provides the information about that. Thank you very much for your attention. So time for questions. Thanks for this interesting talk. I would have a question concerning the proteogenomics approach that you showed. Have you been looking predominantly for mutations or are you as well looking for, for example, for gene fusion or novel transcripts of known oncogenes in this approach? Okay, so we have some gene panel test. We call that NCC-onco panel. In NCC-onco panel, we examine the drug or mutation for 120 genes as well as the fusion genes. So we use NCC-onco panel for all established cell lines. In addition to that, we also started the whole exon sequencing for the cell lines. Yeah, I was wondering if you do the bottom-up approach for proteomics, whether you can find as well, you know, peptides which are unique for certain fusions or so on. Yeah, yeah, actually that is what we are doing. So currently we will purchase the newest mass spectrometer in our institute. So the newest one will cover almost all the protein in the single experiment. So I hope to combine the protein data and the gene data to find more drugable mutation over the proteins reflecting the mutation status. Thanks a lot. Thank you for the talk. I'm curious about the methodology and the success rate. How, what is the success rate of going from organoid to make a cell line or from a xenograph to make cell line? Do you use the same medium? What are the conditions there? Thank you. I'd like to optimize the tissue culture medium, but the tissue culture medium should be optimized according to the historical subtypes. But currently I just have a single type of cell culture. So which include local inhibitor and several growth factors. And the success rate of cell lines in approximately 25% in average. But it largely depend on the historical subtypes. For example, in the case of giant cell tumor of bone, success rate is close to 100%. But in contrast for Angiosarcoma, Angiosarcoma is quite malignant sarcomas, but success rate was 0%. So it's difficult to explain these disorders. And all cells, all cell lines we make a spheroid in the U-shaped 96th cell plate. So all cell lines can make a spheroid. Okay. Thank you.