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      Gene Expression in Single Cells Isolated from the CWR-R1 Prostate Cancer Cell Line and Human Prostate Tissue Based on the Side Population Phenotype

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          Abstract

          Defining biological signals at the single cell level can identify cancer initiating driver mutations. Techniques to isolate single cells such as microfluidics sorting and magnetic capturing systems have limitations such as: high cost, labor intense, and the requirement of a large number of cells. Therefore, the goal of our current study is to identify a cost and labor effective, reliable, and reproducible technique that allows single cell isolation for analysis to promote regular laboratory use, including standard reverse transcription PCR (RT-PCR).

          In the current study, we utilized single prostate cells isolated from the CWR-R1 prostate cancer cell line and human prostate clinical specimens, based on the ATP binding cassette (ABC) transporter efflux of dye cycle violet (DCV), side population assay. Expression of four genes: ABCG2; Aldehyde dehydrogenase1A1 (ALDH1A1); androgen receptor (AR); and embryonic stem cell marker, Oct-4, were determined.

          Results from the current study in the CWR-R1 cell line showed ABCG2 and ALDH1A1 gene expression in 67% of single side population cells and in 17% or 100% of non-side population cells respectively. Studies using single cells isolated from clinical specimens showed that the Oct-4 gene is detected in only 22% of single side population cells and in 78% of single non-side population cells. Whereas, AR gene expression is in 100% single side population and non-side population cells isolated from the same human prostate clinical specimen.

          These studies show that performing RT-PCR on single cells isolated by FACS can be successfully conducted to determine gene expression in single cells from cell lines and enzymatically digested tissue. While these studies provide a simple yes/no expression readout, the more sensitive quantitative RT-PCR would be able to provide even more information if necessary.

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          NIH Image to ImageJ: 25 years of image analysis.

          For the past 25 years NIH Image and ImageJ software have been pioneers as open tools for the analysis of scientific images. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
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            Nature, nurture, or chance: stochastic gene expression and its consequences.

            Gene expression is a fundamentally stochastic process, with randomness in transcription and translation leading to cell-to-cell variations in mRNA and protein levels. This variation appears in organisms ranging from microbes to metazoans, and its characteristics depend both on the biophysical parameters governing gene expression and on gene network structure. Stochastic gene expression has important consequences for cellular function, being beneficial in some contexts and harmful in others. These situations include the stress response, metabolism, development, the cell cycle, circadian rhythms, and aging.
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              Somatic mutation, genomic variation, and neurological disease.

              Genetic mutations causing human disease are conventionally thought to be inherited through the germ line from one's parents and present in all somatic (body) cells, except for most cancer mutations, which arise somatically. Increasingly, somatic mutations are being identified in diseases other than cancer, including neurodevelopmental diseases. Somatic mutations can arise during the course of prenatal brain development and cause neurological disease-even when present at low levels of mosaicism, for example-resulting in brain malformations associated with epilepsy and intellectual disability. Novel, highly sensitive technologies will allow more accurate evaluation of somatic mutations in neurodevelopmental disorders and during normal brain development.
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                Author and article information

                Journal
                101636624
                42834
                Single Cell Biol
                Single Cell Biol
                Single cell biology
                2168-9431
                21 October 2016
                12 September 2016
                September 2016
                24 October 2016
                : 5
                : 3
                : 150
                Affiliations
                [1 ]Department of Pharmacology and Therapeutics, Roswell Park Cancer Institute, Buffalo, NY-14263, USA
                [2 ]Department of Biostatistics, Roswell Park Cancer Institute, Buffalo, NY-14263, USA
                [3 ]Department of Urologic Oncology, Roswell Park Cancer Institute, Buffalo, NY-14263, USA
                Author notes
                [* ] Corresponding author: Wendy J Huss, Ph.D., Department of Pharmacology and Therapeutics, Roswell Park Cancer Institute, Elm and Carlton Streets, Buffalo, NY, 14263, USA, Tel: 716-845-1213; wendy.huss@ 123456roswellpark.org
                Article
                NIHMS824443
                10.4172/2168-9431.1000150
                5076885
                46f3d1ba-6bc2-4eff-ab31-80f208b6d3df

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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                single cells,human prostate clinical specimens,side population assay,abcg2,aldehyde dehydrogenase,androgen receptor

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