Optimizing MET-Targeted Therapy for Lung Cancer Personalized Treatment
Posted November 19, 2010
Patrick Ma, M.D., M.Sc., Cleveland Clinic Taussig Cancer Institute, Cleveland, Ohio
Lung cancer is the leading cause of cancer death in both men and women. Targeted therapies that focus on molecular and cellular changes that are specific to lung cancer have shown some success, such as the use of erlotinib in metastatic lung cancer that targets the cancer-associated protein epidermal growth factor receptor. However, all initial responders to this targeted drug eventually progress and succumb to resistant recurrent disease. For targeted therapy to be ultimately successful and improve patient survival and long-term outcome, two critical steps need to be achieved: (1) Enhancement of the initial tumor therapeutic response to the treatment regimen (overcome de novo resistance), and (2) abolishment of the mechanism of tumor-resistant-escape to therapy that forms the basis of future resistant disease relapse (overcome acquired resistance). Dr. Patrick Ma, recipient of a Fiscal Year 2009 Lung Cancer Research Program Promising Clinician Award, will address these two issues in his investigation of the MET receptor as a therapeutic target in lung cancer. Preliminary findings from Dr. Ma's laboratory demonstrate that tumors can escape the effects of a MET inhibitor during a brief window of time in which molecular changes occur, thus making them resistant to treatment. Dr. Ma will combine molecular imaging of small animals with immunohistochemical analysis to investigate the potential use of clinical MET inhibitor drug XL184 as an avenue for personalized targeted lung cancer therapy. Specifically, he will also study the role of MET mutations as the molecular factors that may predict response and resistance to the inhibitor drug. Additionally, the cell signaling pathways that determine cell fate when tumors are treated with MET inhibitor will be explored. This project will provide improved strategies to diminish early tumor resistance in tumor cells and offer a novel way to improve long-term clinical outcome and survival in lung cancer patients.
Links:
Public and Technical Abstracts: Optimizing MET-Targeted Therapy for Lung Cancer Personalized Treatment
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Enabling Highly Sensitive Detections of Multiple Lung Cancer Biomarkers Using Nanoparticles
Posted November 10, 2010
Ming Su, Ph.D., University of Central Florida, Orlando, Florida
Early detection of lung cancer is crucial for treatment and survival. Although there are over one hundred biomarkers associated with lung cancers, a major challenge exists for biomarker-based early detection of lung cancers because most biomarkers are not effective, have low concentrations, exist at different stages, and need extensive effort to prepare samples. One approach to enhance diagnostic accuracy is to use multiple lung cancer biomarkers, where even if each biomarker has low power, their combination can provide accurate information. To detect cancer biomarkers, a number of nanoparticles with unique optical, electric, magnetic, or electrochemical properties have been used. Further, nanoparticle-based detections have achieved extremely high sensitivity via the conversion of biological recognition events into measurable physical signals that can be amplified. Nanoparticle-based methods are limited, however, due to their low multiplicity, as only one or several types of biomarkers can be detected at one time, and screening one sample for multiple biomarkers requires extensive time and effort. Thus, to enhance detection, Dr. Ming Su, recipient of a Fiscal Year 2009 Lung Cancer Research Program Concept Award, will develop a new technique for highly sensitive detection of multiple protein biomarkers using encapsulated phase change nanoparticles of differing metals or alloys as thermal barcodes. It is anticipated that the high multiplicity, sensitivity, and reliability of the unique alloy nanoparticles will allow the early detections of multiple cancer biomarkers in small amounts of sample, thereby ensuring effective treatment of lung cancer patients.
Figure: Protein biomarker (2) detection using encapsulated phase change nanoparticles (3) and magnetic bead separation (1)
Links:
Public and Technical Abstracts: Encapsulated Solid-Liquid Phase Change Nanoparticles as Thermal Barcodes for Highly Sensitive Detections of Multiple Lung Cancer Biomarkers
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