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- 1. Biomarkers for personalized anti-cancer therapy Rianne Fijten Department 1
- 2. Introduction Drug 1 Cured Standard Trial and Treatment Drug 2 error Drug 3 Not cured Cancer Treatment By predefined biomarkers for drug sensitivity Genetic Higher Personalized Profiling Choose chance Treatment Drug best drug on being sensitivity cured Department 2
- 3. Research Question Can biomarkers be defined for personalized anti-cancer therapy with use of predictive modeling of drug sensitivity? Department 3
- 4. Project Available data types • Panel of tumor derived cell lines corresponding to diverse tissue types, which has been subject to extensive NCI60 drug molecular phenotypic and pharmacological sensitivity characterization panel • Data: – baseline (untreated) metabolic and transcriptional profiles from 58 cell lines – Growth inhibition data from an array of 118 drugs 1. Cavill et al. 2009 PloS Comp Department 4
- 5. Project Available data types 1 NCI60 drug sensitivity panel Patient tumor profiling data • Chemotherapy responses of individual cancer patients 1. Cavill et al. 2009 PloS Comp Department 5
- 6. Project Methodology • Drug-sensitivity associated Defining pathways Available biomarkers data types for drug • Biomarkers: Most important sensitivity genes or metabolites in those 1 pathways NCI60 drug sensitivity panel 1. Cavill et al. 2009 PloS Comp Department 6
- 7. Project Methodology Defining Available biomarkers data types for drug sensitivity 1 NCI60 drug sensitivity panel Development of predictive models 1. Cavill et al. 2009 PloS Comp Department 7
- 8. Project Methodology 1 Defining Available biomarkers data types for drug sensitivity 1 NCI60 drug sensitivity panel Development of predictive models Patient tumor profiling data Testing predictive models 1. Cavill et al. 2009 PloS Comp Department 8
- 9. Project Methodology 1 Defining Available biomarkers data types for drug sensitivity 1 NCI60 drug sensitivity Aspired outcome panel Development of predictive models Happy patients Patient tumor profiling data Testing Possibly predictive clinical use models 1. Cavill et al. 2009 PloS Comp Department 9
- 10. See you in London! • Are there questions? Department 10
Notas del editor
- Nowadays, most cancer therapy is still a standard procedure that is similar for every patient with a type of tumor. However, this is not always beneficial because, even though the type of the tumor is similar between patients, each tumor is different on molecular level and will therefore respond differently to chemotherapeutic drugs. Another therapy would therefore be better: personalized cancer therapy. This is inidividualized therapy specifically set up for the patient. The standard procedure goes as follows: Several drugs will be tested with trial and error and the best performing drug is chosen. This can be very time consuming and can have adverse effects on the patient. Also, a patient may be cured if the right drug is found, but it can also be that none of the drug are effective, which leads to another attempt with other drugs (feedback loop). Personalized cancer therapy will begin with genetic profiling of the tumor. Because tumors are different and therefore respond differently toward certain drugs, this genetic profiling can predict which drug will work or will not work. The most effective drug can then be administered and fight the tumor. In order to predict how well a drug will perform, biomarkers for sensitivity for that specific drug or group of drugs will need to be defined that can be found using the genetic profiling.
- The research question is therefore: Can biomarkers be defined for personalized anti-cancer therapy with use of predictive modeling of drug sensitivity?
- The project will be set up as follows: Two types of data will be available: Drug sensitivity data from the NCI60 cell line panel, which is a cell line panel containing a set of 59 human cancer cell lines derived from brain, blood and bone marrow, breast, colon, kidney, lung, ovary, prostate and skin, and clinical patient data. The NCI60 data can be used to define biomarkers for specific chemotherapeutic drug. These can then be used to develop predictive models that would eventually be able to predict drug sensitivity for clinical data. When the models have been developed, the patient data can be used to test the effectiveness of the models. The aspired outcome of this project is, of course, that cancer can be treated earlier with the right drugs from the start and hopefully cure patients earlier and more effectively. Note that the defining of biomarkers already has been performed (to some extent), so the senior project will focus on the development of the predictive models.
- The project will be set up as follows: Two types of data will be available: Drug sensitivity data from the NCI60 cell line panel, which is a cell line panel containing a set of 59 human cancer cell lines derived from brain, blood and bone marrow, breast, colon, kidney, lung, ovary, prostate and skin, and clinical patient data. The NCI60 data can be used to define biomarkers for specific chemotherapeutic drug. These can then be used to develop predictive models that would eventually be able to predict drug sensitivity for clinical data. When the models have been developed, the patient data can be used to test the effectiveness of the models. The aspired outcome of this project is, of course, that cancer can be treated earlier with the right drugs from the start and hopefully cure patients earlier and more effectively. Note that the defining of biomarkers already has been performed (to some extent), so the senior project will focus on the development of the predictive models.
- The project will be set up as follows: Two types of data will be available: Drug sensitivity data from the NCI60 cell line panel, which is a cell line panel containing a set of 59 human cancer cell lines derived from brain, blood and bone marrow, breast, colon, kidney, lung, ovary, prostate and skin, and clinical patient data. The NCI60 data can be used to define biomarkers for specific chemotherapeutic drug. These can then be used to develop predictive models that would eventually be able to predict drug sensitivity for clinical data. When the models have been developed, the patient data can be used to test the effectiveness of the models. The aspired outcome of this project is, of course, that cancer can be treated earlier with the right drugs from the start and hopefully cure patients earlier and more effectively. Note that the defining of biomarkers already has been performed (to some extent), so the senior project will focus on the development of the predictive models.
- The project will be set up as follows: Two types of data will be available: Drug sensitivity data from the NCI60 cell line panel, which is a cell line panel containing a set of 59 human cancer cell lines derived from brain, blood and bone marrow, breast, colon, kidney, lung, ovary, prostate and skin, and clinical patient data. The NCI60 data can be used to define biomarkers for specific chemotherapeutic drug. These can then be used to develop predictive models that would eventually be able to predict drug sensitivity for clinical data. When the models have been developed, the patient data can be used to test the effectiveness of the models. The aspired outcome of this project is, of course, that cancer can be treated earlier with the right drugs from the start and hopefully cure patients earlier and more effectively. Note that the defining of biomarkers already has been performed (to some extent), so the senior project will focus on the development of the predictive models.
- The project will be set up as follows: Two types of data will be available: Drug sensitivity data from the NCI60 cell line panel, which is a cell line panel containing a set of 59 human cancer cell lines derived from brain, blood and bone marrow, breast, colon, kidney, lung, ovary, prostate and skin, and clinical patient data. The NCI60 data can be used to define biomarkers for specific chemotherapeutic drug. These can then be used to develop predictive models that would eventually be able to predict drug sensitivity for clinical data. When the models have been developed, the patient data can be used to test the effectiveness of the models. The aspired outcome of this project is, of course, that cancer can be treated earlier with the right drugs from the start and hopefully cure patients earlier and more effectively. Note that the defining of biomarkers already has been performed (to some extent), so the senior project will focus on the development of the predictive models.
- The project will be set up as follows: Two types of data will be available: Drug sensitivity data from the NCI60 cell line panel, which is a cell line panel containing a set of 59 human cancer cell lines derived from brain, blood and bone marrow, breast, colon, kidney, lung, ovary, prostate and skin, and clinical patient data. The NCI60 data can be used to define biomarkers for specific chemotherapeutic drug. These can then be used to develop predictive models that would eventually be able to predict drug sensitivity for clinical data. When the models have been developed, the patient data can be used to test the effectiveness of the models. The aspired outcome of this project is, of course, that cancer can be treated earlier with the right drugs from the start and hopefully cure patients earlier and more effectively. Note that the defining of biomarkers already has been performed (to some extent), so the senior project will focus on the development of the predictive models.