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Biomechanics of Cancer Cells: Malignancy Detection Using Mechanophenotyping Tools
The ultimate goal of this project is to enable the detection of circulating tumor cells, a type of cell present in cancer patients from early stages of the disease, through the use of microfluidics and novel optical technology.
Metastasis is the main cause of cancer-related mortality. It is the multi-step process whereby cancer cells enter the vascular or lymphatic systems, travel to distant tissues through these networks, and exit, giving rise to secondary tumors. As a cell acquires this metastatic potential, there are corresponding changes in the cytoskeletal structure that result in characteristic biomechanical phenotypes.
Despite major progress in the study of the mechanisms that govern cancer metastasis and in the development of new therapies for its treatment, early-detection remains the most effective strategy for reducing cancer-related deaths. Until now, however, only a few described early-detection methods are effective enough for clinical use. Many of these techniques focus on circulating tumor cells (CTCs), which are cells found in the bloodstream that have detached from the primary tumor site and represent an intermediate stage of the metastatic dissemination.
In the proposed project, we aim to develop a system to mechanically characterize complex cell mixtures and enable detection of rare individuals, such as CTCs. With this aim, we have coupled next generation imaging sensors to a microscope equipped with a real-time deformability cytometry (RT-DC) microfluidic system (Otto et al., 2015). This system entails marker-free mechanical characterization of large cell populations based on the deformations of cells pumped through a microfluidic capillary.
At the initial stages of the project, the selected student will estimate the mechanical properties of established metastatic and non-malignant cell lines. Once their properties are known, he or she will analyze cell mixtures containing known proportions of metastatic and non-malignant cells. In parallel, he or she will develop new algorithms for the detection and segmentation of the images acquired with the imaging sensors. Once the performance of the detection algorithms allows us to unequivocally detect small populations of mechanically altered cells, blood samples containing CTCs from cancer patients will be analyzed.
Metastasis is the main cause of cancer-related mortality. It is the multi-step process whereby cancer cells enter the vascular or lymphatic systems, travel to distant tissues through these networks, and exit, giving rise to secondary tumors. As a cell acquires this metastatic potential, there are corresponding changes in the cytoskeletal structure that result in characteristic biomechanical phenotypes.
Despite major progress in the study of the mechanisms that govern cancer metastasis and in the development of new therapies for its treatment, early-detection remains the most effective strategy for reducing cancer-related deaths. Until now, however, only a few described early-detection methods are effective enough for clinical use. Many of these techniques focus on circulating tumor cells (CTCs), which are cells found in the bloodstream that have detached from the primary tumor site and represent an intermediate stage of the metastatic dissemination.
In the proposed project, we aim to develop a system to mechanically characterize complex cell mixtures and enable detection of rare individuals, such as CTCs. With this aim, we have coupled next generation imaging sensors to a microscope equipped with a real-time deformability cytometry (RT-DC) microfluidic system (Otto et al., 2015). This system entails marker-free mechanical characterization of large cell populations based on the deformations of cells pumped through a microfluidic capillary.
At the initial stages of the project, the selected student will estimate the mechanical properties of established metastatic and non-malignant cell lines. Once their properties are known, he or she will analyze cell mixtures containing known proportions of metastatic and non-malignant cells. In parallel, he or she will develop new algorithms for the detection and segmentation of the images acquired with the imaging sensors. Once the performance of the detection algorithms allows us to unequivocally detect small populations of mechanically altered cells, blood samples containing CTCs from cancer patients will be analyzed.
1. Conduct a literature review, focusing on cancer mechanics, circulating tumor cell detection, and cell segmentation (10%).
2. Optimize and further design experimental protocols for the analysis of cell lines, complex cell mixtures, and blood samples (40%).
3. Develop segmentation algorithms to analyze the deformability data collected with the RT-DC system (25%).
4. Write a final report / thesis (25%).
1. Conduct a literature review, focusing on cancer mechanics, circulating tumor cell detection, and cell segmentation (10%). 2. Optimize and further design experimental protocols for the analysis of cell lines, complex cell mixtures, and blood samples (40%). 3. Develop segmentation algorithms to analyze the deformability data collected with the RT-DC system (25%). 4. Write a final report / thesis (25%).
Unai Silvan PhD E-mail: unai.silvan@hest.ethz.ch Institute for Biomechanics, ETH Zürich, Professorship Jess Snedeker
Unai Silvan PhD E-mail: unai.silvan@hest.ethz.ch Institute for Biomechanics, ETH Zürich, Professorship Jess Snedeker