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Esophageal adenocarcinoma (EAC) is one of the most lethal and fastest growing cancers in the United States. Its onset is commonly triggered by metaplastic transformation of normal squamous esophageal epithelial cells to Barrett's esophagus (BE) cells in response to acid reflux. BE patients are believed to progress through non-dysplastic metaplasia

Esophageal adenocarcinoma (EAC) is one of the most lethal and fastest growing cancers in the United States. Its onset is commonly triggered by metaplastic transformation of normal squamous esophageal epithelial cells to Barrett's esophagus (BE) cells in response to acid reflux. BE patients are believed to progress through non-dysplastic metaplasia and increasing grades of dysplasia prior to EAC. Conventional cancer diagnostic tools rely on bulk-cell analyses that are incapable of identifying intratumoral heterogeneity or rare driver cells that play important roles in cancer progression. An improved single-cell method of cancer diagnosis would overcome this challenge by detecting cancer initiating cells before they progress into untreatable stages. In this study, using EAC as a model, we attempted to identify a more effective method of cancer diagnosis. We quantified the single- and bulk-cell mRNA expression of genes that have been proposed to be instrumental in the progression of EAC through BE. Quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR) analysis was performed on human primary cells to measure the mRNA expression levels of BE- and EAC-associated genes. Our results showed high levels of heterogeneity of CDX2 and TFF3 at the single-cell resolution in human BE and EAC samples. Additionally, while expression of VEGF is generally low at the bulk-cell level, our results showed that a few, rare cells had significantly higher VEGF expression levels than the majority of cells in the EAC sample. In conclusion, we have affirmed that EAC cancer cells, as well as BE cells, show high levels of heterogeneity. Based on the VEGF gene expression pattern, single-cell analysis could potentially be more effective for identifying rare, but essential cells for cancer progression, which could then be targeted for treatment. Future studies will focus on analyzing human samples from thousands of normal and cancer subjects to validate the use of single-cell profiling in cancer.
ContributorsHaeuser, Kelsey Lynn (Author) / Tran, Thai (Thesis director) / Kelbauskas, Laimonas (Committee member) / Gao, Weimin (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2013-12
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Description
In the past decades, single-cell metabolic analysis has been playing a key role in understanding cellular heterogeneity, disease initiation, progression, and drug resistance. Therefore, it is critical to develop technologies for individual cellular metabolic analysis using various configurations of microfluidic devices. Compared to bulk-cell analysis which is widely used by

In the past decades, single-cell metabolic analysis has been playing a key role in understanding cellular heterogeneity, disease initiation, progression, and drug resistance. Therefore, it is critical to develop technologies for individual cellular metabolic analysis using various configurations of microfluidic devices. Compared to bulk-cell analysis which is widely used by reporting an averaged measurement, single-cell analysis is able to present the individual cellular responses to the external stimuli. Particularly, oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) are two key parameters to monitor heterogeneous metabolic profiles of cancer cells. To achieve multi-parameter metabolic measurements on single cells, several technical challenges need to be overcome: (1) low adhesion of soft materials micro-fabricated on glass surface for multiple-sensor deposition and single-cell immobilization, e.g. SU-8, KMPR, etc.; (2) high risk of using external mechanical forces to create hermetic seals between two rigid fused silica parts, even with compliance layers; (3) how to accomplish high-throughput for single-cell trapping, metabolic profiling and drug screening; (4) high process cost of micromachining on glass substrate and incapability of mass production.

In this dissertation, the development of microfabrication technologies is demonstrated to design reliable configurations for analyzing multiple metabolic parameters from single cells, including (1) improved KMPR/SU-8 microfabrication protocols for fabricating microwell arrays that can be integrated and sealed to 3 × 3 tri-color sensor arrays for OCR and ECAR measurements; (2) design and characterization of a microfluidic device enabling rapid single-cell trapping and hermetic sealing single cells and tri-color sensors within 10 × 10 hermetically sealed microchamber arrays; (3) exhibition of a low-cost microfluidic device based on plastics for single-cell metabolic multi-parameter profiling. Implementation of these improved microfabrication methods should address the aforementioned challenges and provide a high throughput and multi-parameter single cell metabolic analysis platform.
ContributorsSong, Ganquan (Author) / Meldrum, Deirdre R. (Thesis advisor) / Goryll, Michael (Committee member) / Kelbauskas, Laimonas (Committee member) / Wang, Hong (Committee member) / Arizona State University (Publisher)
Created2017