Klinke:Research - Revision history

David J. Klinke II: /* Summary of Research Program */

David J. Klinke II — Thu, 10 Nov 2011 15:01:09 GMT

Summary of Research Program

←Older revision		Revision as of 15:01, 10 November 2011
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	=== Summary of Research Program ===		=== Summary of Research Program ===
	'''		'''
-	[[Image:Klinke-ResearchSummary.jpg\|~~thumb~~\|left\|Schematic diagram of research program.]]	+	[[Image:Klinke-ResearchSummary.jpg\|350px\|left\|Schematic diagram of research program.]]
	An antibody is naturally produced by the body to recognize and bind to a specific molecular pattern. An antibody can also be engineered commercially to attach itself to a specific molecular pattern associated with cancer cells. These commercially produced antibodies are called monoclonal antibodies and comprise one of the largest classes of cancer drugs. [http://www.gene.com/gene/products/information/oncology/herceptin/ Herceptin] is a commonly known example. The clinical response to these molecularly targeted drugs are thought to occur through two mechanisms - a direct effect on cancer cells and an indirect effect whereby the drugs label the cancer cells so that immune cells can destroy the cancer cells. The relative importance of these two mechanisms in humans is unknown. While these drugs have a remarkable effect in certain groups of patients, de novo (i.e., a patient should respond but they don't) and acquired (i.e., they initially respond but over a period of time the drug loses efficacy) resistance to these drugs is a persistent problem.		An antibody is naturally produced by the body to recognize and bind to a specific molecular pattern. An antibody can also be engineered commercially to attach itself to a specific molecular pattern associated with cancer cells. These commercially produced antibodies are called monoclonal antibodies and comprise one of the largest classes of cancer drugs. [http://www.gene.com/gene/products/information/oncology/herceptin/ Herceptin] is a commonly known example. The clinical response to these molecularly targeted drugs are thought to occur through two mechanisms - a direct effect on cancer cells and an indirect effect whereby the drugs label the cancer cells so that immune cells can destroy the cancer cells. The relative importance of these two mechanisms in humans is unknown. While these drugs have a remarkable effect in certain groups of patients, de novo (i.e., a patient should respond but they don't) and acquired (i.e., they initially respond but over a period of time the drug loses efficacy) resistance to these drugs is a persistent problem.

David J. Klinke II: /* CAREER: Interrogating Antagonistic Mechanisms of Signaling Cross-talk in Natural Killer Cells */

David J. Klinke II — Thu, 01 Sep 2011 14:51:07 GMT

CAREER: Interrogating Antagonistic Mechanisms of Signaling Cross-talk in Natural Killer Cells

←Older revision		Revision as of 14:51, 1 September 2011
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	'''Funding source: National Science Foundation''' <br>		'''Funding source: National Science Foundation''' <br>

		+	[[Image:SEM-B16F0-Exosome.TIF\|thumb\|right\|A scanning electron micrograph of exosomes - nanoscale structures - obtained from a melanoma cancer cell line that are thought to play a role in cell-to-cell communication.]]
	This NSF award by the Biotechnology, Biochemical and Biomass Engineering program supports work to improve our fundamental understanding of how cancer cells escape the cytotoxic action of monoclonal antibodies. Monoclonal antibodies comprise one of the largest classes of cancer drugs that target molecules unique to cancer cells. However, the emergence of resistance to molecular targeted therapies is an increasing, and poorly understood, problem. Without improved understanding of how cancer cells resist the action of molecular targeted therapies, designing effective treatments will remain limited. To improve ultimately the effectiveness of mAbs as cancer drugs, we propose a conceptually novel approach that combines aspects of cellular engineering, immunology, cancer biology, and computationally intensive model-based inference. The research objectives are integrated with educational objectives that aim to promote cross-disciplinary communication among experts and to improve the ability of scientists and engineers to communicate scientific concepts, like how theory and computation are used in scientific practice, effectively with the lay public. It is expected that these aims will have an impact that ranges from local to international. At the local level, the proposed research will provide interdisciplinary training opportunities for graduate and undergraduate students at the interface between multiple disciplines, including biochemical engineering, cancer biology, molecular biology, immunology, and pharmacology. The proposed education aims will also focus outward to create scientists and engineers that can collaborate more effectively across disciplines and, more importantly, that can convey what they do and it's importance to the lay public. Finally, the fundamental fruits of this research may be applied to improve therapies for cancer, a disease that, in developed countries, kills one in three.		This NSF award by the Biotechnology, Biochemical and Biomass Engineering program supports work to improve our fundamental understanding of how cancer cells escape the cytotoxic action of monoclonal antibodies. Monoclonal antibodies comprise one of the largest classes of cancer drugs that target molecules unique to cancer cells. However, the emergence of resistance to molecular targeted therapies is an increasing, and poorly understood, problem. Without improved understanding of how cancer cells resist the action of molecular targeted therapies, designing effective treatments will remain limited. To improve ultimately the effectiveness of mAbs as cancer drugs, we propose a conceptually novel approach that combines aspects of cellular engineering, immunology, cancer biology, and computationally intensive model-based inference. The research objectives are integrated with educational objectives that aim to promote cross-disciplinary communication among experts and to improve the ability of scientists and engineers to communicate scientific concepts, like how theory and computation are used in scientific practice, effectively with the lay public. It is expected that these aims will have an impact that ranges from local to international. At the local level, the proposed research will provide interdisciplinary training opportunities for graduate and undergraduate students at the interface between multiple disciplines, including biochemical engineering, cancer biology, molecular biology, immunology, and pharmacology. The proposed education aims will also focus outward to create scientists and engineers that can collaborate more effectively across disciplines and, more importantly, that can convey what they do and it's importance to the lay public. Finally, the fundamental fruits of this research may be applied to improve therapies for cancer, a disease that, in developed countries, kills one in three.

David J. Klinke II: /* Cell Heterogeneity and Emergent Trastuzumab Resistance in Breast Cancer */

David J. Klinke II — Thu, 01 Sep 2011 14:48:42 GMT

Cell Heterogeneity and Emergent Trastuzumab Resistance in Breast Cancer

←Older revision		Revision as of 14:48, 1 September 2011
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	'''		'''
		+
	=== CAREER: Interrogating Antagonistic Mechanisms of Signaling Cross-talk in Natural Killer Cells ===		=== CAREER: Interrogating Antagonistic Mechanisms of Signaling Cross-talk in Natural Killer Cells ===
	'''Yueting Wu, Kisheon Alexander''' <br>		'''Yueting Wu, Kisheon Alexander''' <br>

David J. Klinke II: /* CAREER: Interrogating Antagonistic Mechanisms of Signaling Cross-talk in Natural Killer Cells */

David J. Klinke II — Thu, 01 Sep 2011 14:45:04 GMT

CAREER: Interrogating Antagonistic Mechanisms of Signaling Cross-talk in Natural Killer Cells

←Older revision		Revision as of 14:45, 1 September 2011
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	'''		'''
	=== CAREER: Interrogating Antagonistic Mechanisms of Signaling Cross-talk in Natural Killer Cells ===		=== CAREER: Interrogating Antagonistic Mechanisms of Signaling Cross-talk in Natural Killer Cells ===
-	'''Yueting Wu''' <br>	+	'''Yueting Wu, Kisheon Alexander''' <br>
	'''Collaborators: Jonathan Bramson, McMaster University, Hamilton, ON''' <br>		'''Collaborators: Jonathan Bramson, McMaster University, Hamilton, ON''' <br>
	'''Funding source: National Science Foundation''' <br>		'''Funding source: National Science Foundation''' <br>

David J. Klinke II: /* CAREER: Interrogating Antagonistic Mechanisms of Signaling Cross-talk in Natural Killer Cells */

David J. Klinke II — Thu, 01 Sep 2011 14:44:00 GMT

CAREER: Interrogating Antagonistic Mechanisms of Signaling Cross-talk in Natural Killer Cells

←Older revision		Revision as of 14:44, 1 September 2011
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	'''		'''
	=== CAREER: Interrogating Antagonistic Mechanisms of Signaling Cross-talk in Natural Killer Cells ===		=== CAREER: Interrogating Antagonistic Mechanisms of Signaling Cross-talk in Natural Killer Cells ===
-	'''~~To be recruited~~''' <br>	+	'''Yueting Wu''' <br>
	'''Collaborators: Jonathan Bramson, McMaster University, Hamilton, ON''' <br>		'''Collaborators: Jonathan Bramson, McMaster University, Hamilton, ON''' <br>
	'''Funding source: National Science Foundation''' <br>		'''Funding source: National Science Foundation''' <br>
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	'''		'''
		+
	=== Dendritic Cell Heterogeneity in Toll-like receptor 4 Signaling ===		=== Dendritic Cell Heterogeneity in Toll-like receptor 4 Signaling ===
	'''Priyanka Dixit, Huanling Liu, Ning Cheng''' <br>		'''Priyanka Dixit, Huanling Liu, Ning Cheng''' <br>

David J. Klinke II: /* Summary of Research Program */

David J. Klinke II — Sun, 05 Jun 2011 04:08:55 GMT

Summary of Research Program

←Older revision		Revision as of 04:08, 5 June 2011
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	'''		'''
	[[Image:Klinke-ResearchSummary.jpg\|thumb\|left\|Schematic diagram of research program.]]		[[Image:Klinke-ResearchSummary.jpg\|thumb\|left\|Schematic diagram of research program.]]
-	An antibody is naturally produced by the body to recognize and bind to a specific molecular pattern. ~~Antibodies~~ can also be engineered commercially to attach itself to specific molecular ~~patterns~~ associated with cancer cells. These commercially produced antibodies are called monoclonal antibodies and comprise one of the largest classes of cancer drugs. Herceptin is a commonly known example. The clinical response to these molecularly targeted drugs are thought to occur through two mechanisms - a direct effect on cancer cells and an indirect effect whereby the drugs label the cancer cells so that immune cells can destroy the cancer cells. The relative importance of these two mechanisms in humans is unknown. While these drugs have a remarkable effect in certain groups of patients, de novo (i.e., a patient should respond but they don't) and acquired (i.e., they initially respond but over a period of time the drug loses efficacy) resistance to these drugs is a persistent problem.	+	An antibody is naturally produced by the body to recognize and bind to a specific molecular pattern. An antibody can also be engineered commercially to attach itself to a specific molecular pattern associated with cancer cells. These commercially produced antibodies are called monoclonal antibodies and comprise one of the largest classes of cancer drugs. [http://www.gene.com/gene/products/information/oncology/herceptin/ Herceptin] is a commonly known example. The clinical response to these molecularly targeted drugs are thought to occur through two mechanisms - a direct effect on cancer cells and an indirect effect whereby the drugs label the cancer cells so that immune cells can destroy the cancer cells. The relative importance of these two mechanisms in humans is unknown. While these drugs have a remarkable effect in certain groups of patients, de novo (i.e., a patient should respond but they don't) and acquired (i.e., they initially respond but over a period of time the drug loses efficacy) resistance to these drugs is a persistent problem.

	The research projects described below focus on different aspects of this problem, as summarized in the graphic. The award from the National Cancer Institute focuses on understanding how cancer cells get around the therapeutic action of the antibody by re-wiring their internal circuitry (i.e., How do malignant cells interpret these biochemical signals?). This internal circuitry governs how a cell processes information and makes decisions (i.e., whether it proliferates, doesn't do anything, or dies). The CAREER award from the National Science Foundation focuses on understanding how cancer cells escape the action of these drugs by interfering with the immune response (i.e., What biochemical signals do cells use to communicate?). The award from the National Institute of Allergy and Infectious Disease focuses on understanding how immune cells interpret all of these biochemical signals. A common theme in these projects is the combination of targeted experiment and model-based inference. Model-based inference is the process of encoding our prior knowledge of how cells interpret biochemical signals in the form of a mathematical model. The model is then used to test whether our prior knowledge is consistent with the experimental data. Model-based inference is a key tool as biological systems exhibit intrinsic uncertainty - due to either ethical constraints or due to technical limitations of the available experimental techniques. By combining experimental study with model-based inference, we hope to obtain greater fidelity in understanding how these systems work than could be obtained using either technique in isolation.		The research projects described below focus on different aspects of this problem, as summarized in the graphic. The award from the National Cancer Institute focuses on understanding how cancer cells get around the therapeutic action of the antibody by re-wiring their internal circuitry (i.e., How do malignant cells interpret these biochemical signals?). This internal circuitry governs how a cell processes information and makes decisions (i.e., whether it proliferates, doesn't do anything, or dies). The CAREER award from the National Science Foundation focuses on understanding how cancer cells escape the action of these drugs by interfering with the immune response (i.e., What biochemical signals do cells use to communicate?). The award from the National Institute of Allergy and Infectious Disease focuses on understanding how immune cells interpret all of these biochemical signals. A common theme in these projects is the combination of targeted experiment and model-based inference. Model-based inference is the process of encoding our prior knowledge of how cells interpret biochemical signals in the form of a mathematical model. The model is then used to test whether our prior knowledge is consistent with the experimental data. Model-based inference is a key tool as biological systems exhibit intrinsic uncertainty - due to either ethical constraints or due to technical limitations of the available experimental techniques. By combining experimental study with model-based inference, we hope to obtain greater fidelity in understanding how these systems work than could be obtained using either technique in isolation.

	'''		'''
		+
	=== Cell Heterogeneity and Emergent Trastuzumab Resistance in Breast Cancer ===		=== Cell Heterogeneity and Emergent Trastuzumab Resistance in Breast Cancer ===
	'''Yogesh Kulkarni, Vivian Suarez''' <br>		'''Yogesh Kulkarni, Vivian Suarez''' <br>

David J. Klinke II at 13:39, 13 April 2011

David J. Klinke II — Wed, 13 Apr 2011 13:39:25 GMT

←Older revision		Revision as of 13:39, 13 April 2011
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	'''		'''
	=== CAREER: Interrogating Antagonistic Mechanisms of Signaling Cross-talk in Natural Killer Cells ===		=== CAREER: Interrogating Antagonistic Mechanisms of Signaling Cross-talk in Natural Killer Cells ===
-	'''To be ~~hired~~''' <br>	+	'''To be recruited''' <br>
	'''Collaborators: Jonathan Bramson, McMaster University, Hamilton, ON''' <br>		'''Collaborators: Jonathan Bramson, McMaster University, Hamilton, ON''' <br>
	'''Funding source: National Science Foundation''' <br>		'''Funding source: National Science Foundation''' <br>

David J. Klinke II at 13:37, 13 April 2011

David J. Klinke II — Wed, 13 Apr 2011 13:37:44 GMT

←Older revision		Revision as of 13:37, 13 April 2011
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	{{Klinke}}		{{Klinke}}
-	~~[[Image:Klinke_overview1.tif\|400px\|right]]~~
-	How do we translate observations obtained in model systems, such as inbred mouse strains and cell lines, to improve patient outcomes? Can we develop predictive models to help tailor treatment strategies to the individual patient? These two questions help frame the research efforts in the Klinke lab. Within this context, we have focused on applied questions related to how tumors use direct and indirect methods to create a favorable environment for tumor growth. To address these challenging questions, we combine classical engineering tools, such as dimensional analysis and chemical kinetics, with the experimental tools of molecular and cellular biology. In addition, we have created some new tools to minimize the impact of bias on our statements of belief in how we think these systems operate. This synthesis of molecular and cellular biology with computational tools to model and predict system behavior may be classified as systems biology.
-	~~<br> <br>~~
-
	'''		'''
	=== Summary of Research Program ===		=== Summary of Research Program ===

David J. Klinke II at 22:23, 12 April 2011

David J. Klinke II — Tue, 12 Apr 2011 22:23:57 GMT

←Older revision		Revision as of 22:23, 12 April 2011
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	=== Summary of Research Program ===		=== Summary of Research Program ===
	'''		'''
-	[[Image:Klinke-ResearchSummary.jpg\|~~300px~~\|~~right~~\|Schematic diagram of research program.]]	+	[[Image:Klinke-ResearchSummary.jpg\|thumb\|left\|Schematic diagram of research program.]]
	An antibody is naturally produced by the body to recognize and bind to a specific molecular pattern. Antibodies can also be engineered commercially to attach itself to specific molecular patterns associated with cancer cells. These commercially produced antibodies are called monoclonal antibodies and comprise one of the largest classes of cancer drugs. Herceptin is a commonly known example. The clinical response to these molecularly targeted drugs are thought to occur through two mechanisms - a direct effect on cancer cells and an indirect effect whereby the drugs label the cancer cells so that immune cells can destroy the cancer cells. The relative importance of these two mechanisms in humans is unknown. While these drugs have a remarkable effect in certain groups of patients, de novo (i.e., a patient should respond but they don't) and acquired (i.e., they initially respond but over a period of time the drug loses efficacy) resistance to these drugs is a persistent problem.		An antibody is naturally produced by the body to recognize and bind to a specific molecular pattern. Antibodies can also be engineered commercially to attach itself to specific molecular patterns associated with cancer cells. These commercially produced antibodies are called monoclonal antibodies and comprise one of the largest classes of cancer drugs. Herceptin is a commonly known example. The clinical response to these molecularly targeted drugs are thought to occur through two mechanisms - a direct effect on cancer cells and an indirect effect whereby the drugs label the cancer cells so that immune cells can destroy the cancer cells. The relative importance of these two mechanisms in humans is unknown. While these drugs have a remarkable effect in certain groups of patients, de novo (i.e., a patient should respond but they don't) and acquired (i.e., they initially respond but over a period of time the drug loses efficacy) resistance to these drugs is a persistent problem.

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	'''Funding source: PhRMA Foundation, National Cancer Institute''' <br>		'''Funding source: PhRMA Foundation, National Cancer Institute''' <br>

-	[[Image:Klinke-Suarez.JPG\|thumb\|~~left~~\|Prof. Klinke and Vivian Suarez, a graduate student in ChE, identify differentially expressed proteins using 2-D gel electrophoresis.]]	+	[[Image:Klinke-Suarez.JPG\|thumb\|right\|Prof. Klinke and Vivian Suarez, a graduate student in ChE, identify differentially expressed proteins using 2-D gel electrophoresis.]]
	Monoclonal antibodies, such as trastuzumab, are one of the largest categories of new drugs that target specifically molecules that differentiate cancer cells from normal cells. Despite the remarkable clinical efficacy and specificity of these molecularly targeted therapies, acquired and de novo resistance to therapy is an important clinical problem. Understanding emergent resistance to trastuzumab is inhibited by the inability to quantify aberrant cell signaling pathways among heterogeneous populations of breast cancer cells. Thus there is urgent need for multidisciplinary approaches to assess and interpret the clinical importance of cellular heterogeneity within breast cancer tumors. Our long-term goal is to improve the clinical management of cancer by establishing the scientific foundation for a prognostic technology that will identify individuals who will develop resistance to molecularly targeted therapies. The overall objective of this project is to identify unique patterns of signaling proteins associated with drug sensitivity and apply computational tools from chemical kinetics and Bayesian statistics to interpret the significance of these patterns of protein expression. Our central hypothesis is that breast cancer cells that overexpress ErbB2 exhibit heterogeneity in response to trastuzumab. Furthermore, this heterogeneity is due to variations in expression of proteins that influence the ErbB2 signaling pathway. Prior studies identify such proteins that individually correlate with trastuzumab resistance. The challenge is inferring how these proteins act in concert to influence trastuzumab resistance. The rationale that underlies the proposed research is that identifying patterns of signaling proteins that are correlated with sensitivity to trastuzumab will enable measuring these protein patterns at the single-cell level in tumor biopsy samples. The proposed research is innovative as it provides a novel approach that combines cutting-edge techniques in computational systems biology and proteomics to address the pressing issue of emergent resistance to trastuzumab in breast cancer patients.		Monoclonal antibodies, such as trastuzumab, are one of the largest categories of new drugs that target specifically molecules that differentiate cancer cells from normal cells. Despite the remarkable clinical efficacy and specificity of these molecularly targeted therapies, acquired and de novo resistance to therapy is an important clinical problem. Understanding emergent resistance to trastuzumab is inhibited by the inability to quantify aberrant cell signaling pathways among heterogeneous populations of breast cancer cells. Thus there is urgent need for multidisciplinary approaches to assess and interpret the clinical importance of cellular heterogeneity within breast cancer tumors. Our long-term goal is to improve the clinical management of cancer by establishing the scientific foundation for a prognostic technology that will identify individuals who will develop resistance to molecularly targeted therapies. The overall objective of this project is to identify unique patterns of signaling proteins associated with drug sensitivity and apply computational tools from chemical kinetics and Bayesian statistics to interpret the significance of these patterns of protein expression. Our central hypothesis is that breast cancer cells that overexpress ErbB2 exhibit heterogeneity in response to trastuzumab. Furthermore, this heterogeneity is due to variations in expression of proteins that influence the ErbB2 signaling pathway. Prior studies identify such proteins that individually correlate with trastuzumab resistance. The challenge is inferring how these proteins act in concert to influence trastuzumab resistance. The rationale that underlies the proposed research is that identifying patterns of signaling proteins that are correlated with sensitivity to trastuzumab will enable measuring these protein patterns at the single-cell level in tumor biopsy samples. The proposed research is innovative as it provides a novel approach that combines cutting-edge techniques in computational systems biology and proteomics to address the pressing issue of emergent resistance to trastuzumab in breast cancer patients.

David J. Klinke II at 22:23, 12 April 2011

David J. Klinke II — Tue, 12 Apr 2011 22:23:11 GMT

←Older revision		Revision as of 22:23, 12 April 2011
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	=== Summary of Research Program ===		=== Summary of Research Program ===
	'''		'''
-	[[Image:Klinke-ResearchSummary.jpg\|~~thumb~~\|right\|Schematic diagram of research program.]]	+	[[Image:Klinke-ResearchSummary.jpg\|300px\|right\|Schematic diagram of research program.]]
	An antibody is naturally produced by the body to recognize and bind to a specific molecular pattern. Antibodies can also be engineered commercially to attach itself to specific molecular patterns associated with cancer cells. These commercially produced antibodies are called monoclonal antibodies and comprise one of the largest classes of cancer drugs. Herceptin is a commonly known example. The clinical response to these molecularly targeted drugs are thought to occur through two mechanisms - a direct effect on cancer cells and an indirect effect whereby the drugs label the cancer cells so that immune cells can destroy the cancer cells. The relative importance of these two mechanisms in humans is unknown. While these drugs have a remarkable effect in certain groups of patients, de novo (i.e., a patient should respond but they don't) and acquired (i.e., they initially respond but over a period of time the drug loses efficacy) resistance to these drugs is a persistent problem.		An antibody is naturally produced by the body to recognize and bind to a specific molecular pattern. Antibodies can also be engineered commercially to attach itself to specific molecular patterns associated with cancer cells. These commercially produced antibodies are called monoclonal antibodies and comprise one of the largest classes of cancer drugs. Herceptin is a commonly known example. The clinical response to these molecularly targeted drugs are thought to occur through two mechanisms - a direct effect on cancer cells and an indirect effect whereby the drugs label the cancer cells so that immune cells can destroy the cancer cells. The relative importance of these two mechanisms in humans is unknown. While these drugs have a remarkable effect in certain groups of patients, de novo (i.e., a patient should respond but they don't) and acquired (i.e., they initially respond but over a period of time the drug loses efficacy) resistance to these drugs is a persistent problem.