Single cell heterogeneity plays an important role in the onset and progression of a variety of disease pathologies. One of the most notable examples of the impact of heterogeneity in the complexity of a disease is cancer. Traditionally, molecular…
Single cell heterogeneity plays an important role in the onset and progression of a variety of disease pathologies. One of the most notable examples of the impact of heterogeneity in the complexity of a disease is cancer. Traditionally, molecular analyses on cancer-related samples have been performed on bulk populations of cells, with the resultant data only representative of an average of the population, thereby concealing potentially relevant information about individual cells. Performing these studies at the single cell level is proposed to address this issue. However, current methods for the isolation and analysis of single cells often require specialized and expensive equipment that may be prohibitive to labs wishing to perform such analyses. Herein, a method for the isolation and gene expression analysis of single cells is described that (1) relies only on readily available, inexpensive materials, (2) is compatible with phase and fluorescent microscopy, and (3) allows for the ability to track specific cells throughout all measurements. This method utilizes random seeding of single cells on 72-well Terasaki plates (also called microtest plates) that have 20 µl, optically clear flat-bottomed wells in order to circumvent the need for specific hardware for cell isolation. Suspensions of the Barrett’s esophagus epithelial cell line CP-D stably expressing turboGFP and a related, GFP-negative BE cell line, CP-A, were prepared, seeded at a concentration of approximately 1-2 cells/well and incubated overnight. Wells containing single cells were visually identified using phase-contrast and fluorescent microscopy. Single cells were then lysed directly in the well, total RNA was isolated, and RT-qPCR was performed. RT-qPCR results reflected the ability to distinguish between turboGFP-expressing and non-expressing cells that matched previous identification by microscopy. These results indicate that this is a convenient and cost-effective method for studying gene expression in single cells.
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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…
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.
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A major goal of the Center for Biosignatures Discovery Automation (CBDA) is to design a diagnostic tool that detects novel cancer biosignatures at the single-cell level. We designed the Single-cell QUantitative In situ Reverse Transcription-Polymerase Chain Reaction (SQUIRT-PCR) system…
A major goal of the Center for Biosignatures Discovery Automation (CBDA) is to design a diagnostic tool that detects novel cancer biosignatures at the single-cell level. We designed the Single-cell QUantitative In situ Reverse Transcription-Polymerase Chain Reaction (SQUIRT-PCR) system by combining a two-photon laser lysis (2PLL) system with a microfluidic reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) platform. It is important to identify early molecular changes from intact tissues as prognosis for premalignant conditions and develop new molecular targets for prevention of cancer progression and improved therapies. This project analyzes RNA expression at the single-cell level and presents itself with two major challenges: (1) detecting low levels of RNA and (2) minimizing RNA absorption in the polydimethylsiloxane (PDMS) microfluidic channel. The first challenge was overcome by successfully detecting picogram (pg) levels of RNA using the Fluidigm (FD) BioMark™ HD System (Fluidigm Corporation, South San Francisco, CA) for RT-qPCR analysis. This technology incorporates a highly precise integrated fluidic circuit (IFC) that allows for high-throughput genetic screening using microarrays. The second challenge entailed collecting data from RNA flow-through samples that were passed through microfluidic channels. One channel was treated with a coating of polyethylene glycol (PEG) and the other remained untreated. Various flow-through samples were subjected to RT-qPCR and analyzed using the FD FLEXsix™ Gene Expression IFC. As predicted, the results showed that the treated PDMS channel absorbed less RNA than the untreated PDMS channel. Once the optimization of the PDMS microfluidic platform is complete, it will be implemented into the 2PLL system. This novel technology will be able to identify cell populations in situ and could have a large impact on cancer diagnostics.
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In carcinogenesis, intercellular interactions within and between cell types are critical but remain poorly understood. We present a study on intercellular interactions between normal and premalignant epithelial cells and their functional relevance in the context of premalignant to malignant progression…
In carcinogenesis, intercellular interactions within and between cell types are critical but remain poorly understood. We present a study on intercellular interactions between normal and premalignant epithelial cells and their functional relevance in the context of premalignant to malignant progression in Barrett’s esophagus. Using whole transcriptome profiling we found that in the presence of normal epithelial cells, dysplastic cells but not normal cells, exhibit marked down-regulation of a number of key signaling pathways, including the transforming growth factor beta (TGFβ) and epithelial growth factor (EGF). Functional assays revealed both cell types showed repressed proliferation and significant changes in motility (speed, displacement and directionality) as a result of interactions between the two cell types. Cellular interactions appear to be mediated through both direct cell-cell contact and secreted ligands. The findings of this study are important in that they reveal, for the first time, the effects of cellular communication on gene expression and cellular function between premalignant (dysplastic) epithelial cells and their normal counterparts.
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Background: Heterogeneity within cell populations is relevant to the onset and progression of disease, as well as development and maintenance of homeostasis. Analysis and understanding of the roles of heterogeneity in biological systems require methods and technologies that are capable of…
Background: Heterogeneity within cell populations is relevant to the onset and progression of disease, as well as development and maintenance of homeostasis. Analysis and understanding of the roles of heterogeneity in biological systems require methods and technologies that are capable of single cell resolution. Single cell gene expression analysis by RT-qPCR is an established technique for identifying transcriptomic heterogeneity in cellular populations, but it generally requires specialized equipment or tedious manipulations for cell isolation.
Results: We describe the optimization of a simple, inexpensive and rapid pipeline which includes isolation and culture of live single cells as well as fluorescence microscopy and gene expression analysis of the same single cells by RT-qPCR. We characterize the efficiency of single cell isolation and demonstrate our method by identifying single GFP-expressing cells from a mixed population of GFP-positive and negative cells by correlating fluorescence microscopy and RT-qPCR.
Conclusions: Single cell gene expression analysis by RT-qPCR is a convenient means for investigating cellular heterogeneity, but is most useful when correlating observations with additional measurements. We demonstrate a convenient and simple pipeline for multiplexing single cell RT-qPCR with fluorescence microscopy which is adaptable to other molecular analyses.
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