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- Creators: Ros, Robert
Description
Despite significant advances in digital pathology and automation sciences, current diagnostic practice for cancer detection primarily relies on a qualitative manual inspection of tissue architecture and cell and nuclear morphology in stained biopsies using low-magnification, two-dimensional (2D) brightfield microscopy. The efficacy of this process is limited by inter-operator variations in sample preparation and imaging, and by inter-observer variability in assessment. Over the past few decades, the predictive value quantitative morphology measurements derived from computerized analysis of micrographs has been compromised by the inability of 2D microscopy to capture information in the third dimension, and by the anisotropic spatial resolution inherent to conventional microscopy techniques that generate volumetric images by stacking 2D optical sections to approximate 3D. To gain insight into the analytical 3D nature of cells, this dissertation explores the application of a new technology for single-cell optical computed tomography (optical cell CT) that is a promising 3D tomographic imaging technique which uses visible light absorption to image stained cells individually with sub-micron, isotropic spatial resolution. This dissertation provides a scalable analytical framework to perform fully-automated 3D morphological analysis from transmission-mode optical cell CT images of hematoxylin-stained cells. The developed framework performs rapid and accurate quantification of 3D cell and nuclear morphology, facilitates assessment of morphological heterogeneity, and generates shape- and texture-based biosignatures predictive of the cell state. Custom 3D image segmentation methods were developed to precisely delineate volumes of interest (VOIs) from reconstructed cell images. Comparison with user-defined ground truth assessments yielded an average agreement (DICE coefficient) of 94% for the cell and its nucleus. Seventy nine biologically relevant morphological descriptors (features) were computed from the segmented VOIs, and statistical classification methods were implemented to determine the subset of features that best predicted cell health. The efficacy of our proposed framework was demonstrated on an in vitro model of multistep carcinogenesis in human Barrett's esophagus (BE) and classifier performance using our 3D morphometric analysis was compared against computerized analysis of 2D image slices that reflected conventional cytological observation. Our results enable sensitive and specific nuclear grade classification for early cancer diagnosis and underline the value of the approach as an objective adjunctive tool to better understand morphological changes associated with malignant transformation.
ContributorsNandakumar, Vivek (Author) / Meldrum, Deirdre R (Thesis advisor) / Nelson, Alan C. (Committee member) / Karam, Lina J (Committee member) / Ye, Jieping (Committee member) / Johnson, Roger H (Committee member) / Bussey, Kimberly J (Committee member) / Arizona State University (Publisher)
Created2013
Description
This work demonstrated a novel microfluidic device based on direct current (DC) insulator based dielectrophoresis (iDEP) for trapping individual mammalian cells in a microfluidic device. The novel device is also applicable for selective trapping of weakly metastatic mammalian breast cancer cells (MCF-7) from mixtures with mammalian Peripheral Blood Mononuclear Cells (PBMC) and highly metastatic mammalian breast cancer cells, MDA-MB-231. The advantage of this approach is the ease of integration of iDEP structures in microfliudic channels using soft lithography, the use of DC electric fields, the addressability of the single cell traps for downstream analysis and the straightforward multiplexing for single cell trapping. These microfluidic devices are targeted for capturing of single cells based on their DEP behavior. The numerical simulations point out the trapping regions in which single cell DEP trapping occurs. This work also demonstrates the cell conductivity values of different cell types, calculated using the single-shell model. Low conductivity buffers are used for trapping experiments. These low conductivity buffers help reduce the Joule heating. Viability of the cells in the buffer system was studied in detail with a population size of approximately 100 cells for each study. The work also demonstrates the development of the parallelized single cell trap device with optimized traps. This device is also capable of being coupled detection of target protein using MALDI-MS.
ContributorsBhattacharya, Sanchari (Author) / Ros, Alexandra (Committee member) / Ros, Robert (Committee member) / Buttry, Daniel (Committee member) / Arizona State University (Publisher)
Created2013
Description
Breast cancer cell invasion is a highly orchestrated process driven by a myriad of complex microenvironmental stimuli. These complexities make it difficult to isolate and assess the effects of specific parameters including matrix stiffness and tumor architecture on disease progression. In this regard, morphologically accurate tumor models are becoming instrumental to perform fundamental studies on cancer cell invasion within well-controlled conditions. In this study, the use of photocrosslinkable hydrogels and a novel, two-step photolithography technique was explored to microengineer a 3D breast tumor model. The microfabrication process presented herein enabled precise localization of the cells and creation of high stiffness constructs adjacent to a low stiffness matrix. To validate the model, breast cancer cell lines (MDA-MB-231, MCF7) and normal mammary epithelial cells (MCF10A) were embedded separately within the tumor model and cellular proliferation, migration and cytoskeletal organization were assessed. Proliferation of metastatic MDA-MB-231 cells was significantly higher than tumorigenic MCF7 and normal mammary MCF10A cells. MDA-MB-231 exhibited highly migratory behavior and invaded the surrounding matrix, whereas MCF7 or MCF10A cells formed clusters that were confined within the micropatterned circular features. F-actin staining revealed unique 3D protrusions in MDA-MB-231 cells as they migrated throughout the surrounding matrix. Alternatively, there were abundance of 3D clusters formed by MCF7 and MCF10A cells. The results revealed that gelatin methacrylate (GelMA) hydrogel, integrated with the two-step photolithography technique, has great promise in creating 3D tumor models with well-defined features and tunable stiffness for detailed studies on cancer cell invasion and drug responsiveness.
ContributorsSam, Feba Susan (Author) / Nikkhah, Mehdi (Thesis advisor) / Ros, Robert (Committee member) / Smith, Barbara (Committee member) / Arizona State University (Publisher)
Created2015