scholarly journals Gene Expression Music Algorithm-Based Characterization of the Ewing Sarcoma Stem Cell Signature

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Martin Sebastian Staege
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Stem Cell ◽  
Cell Lines ◽  
Microarray Data ◽  
Ewing Sarcoma ◽  
Correlation Coefficients ◽  
Music Algorithm ◽  
Dna Microarray Data

Gene Expression Music Algorithm (GEMusicA) is a method for the transformation of DNA microarray data into melodies that can be used for the characterization of differentially expressed genes. Using this method we compared gene expression profiles from endothelial cells (EC), hematopoietic stem cells, neuronal stem cells, embryonic stem cells (ESC), and mesenchymal stem cells (MSC) and defined a set of genes that can discriminate between the different stem cell types. We analyzed the behavior of public microarray data sets from Ewing sarcoma (“Ewing family tumors,” EFT) cell lines and biopsies in GEMusicA after prefiltering DNA microarray data for the probe sets from the stem cell signature. Our results demonstrate that individual Ewing sarcoma cell lines have a high similarity to ESC or EC. Ewing sarcoma cell lines with inhibited Ewing sarcoma breakpoint region 1-Friend leukemia virus integration 1 (EWSR1-FLI1) oncogene retained the similarity to ESC and EC. However, correlation coefficients between GEMusicA-processed expression data between EFT and ESC decreased whereas correlation coefficients between EFT and EC as well as between EFT and MSC increased after knockdown of EWSR1-FLI1. Our data support the concept of EFT being derived from cells with features of embryonic and endothelial cells.

scholarly journals Highly efficient Runx1 enhancer eR1-mediated genetic engineering for fetal, child and adult hematopoietic stem cells

2021 ◽  
Author(s):  
Cai Ping Koh ◽  
Avinash Govind Bahirvani ◽  
Chelsia Qiuxia Wang ◽  
Tomomasa Yokomizo ◽  
Cherry Ee Lin Ng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Stem Cell ◽  
Genetic Engineering ◽  
Developmental Stages ◽  
Genetic Element ◽  
Malignant Diseases ◽  
Hematopoietic Stem ◽  
Gene Ablation

A cis-regulatory genetic element which targets gene expression to stem cells, termed stem cell enhancer, serves as a molecular handle for stem cell-specific genetic engineering. Here we show the generation and characterization of a tamoxifen-inducible CreERT2 transgenic (Tg) mouse employing previously identified hematopoietic stem cell (HSC) enhancer for Runx1, eR1 (+24m). Kinetic analysis of labeled cells after tamoxifen injection and transplantation assays revealed that eR1-driven CreERT2 activity marks dormant adult HSCs which slowly but steadily contribute to unperturbed hematopoiesis. Fetal and child HSCs which are uniformly or intermediately active were also efficiently targeted. Notably, a gene ablation at distinct developmental stages, enabled by this system, resulted in different phenotypes. Similarly, an oncogenic Kras induction at distinct ages caused different spectrums of malignant diseases. These results demonstrate that the eR1-CreERT2 Tg mouse serves as a powerful resource for the analyses of both normal and malignant HSCs at all developmental stages.

scholarly journals Investigation of the expression of RIF1 gene on head and neck, pancreatic and brain cancer and cancer stem cells

2016 ◽  
Vol 39 (6) ◽  
pp. 43 ◽  
Author(s):  
Hacer E GursesCila ◽  
Muradiye Acar ◽  
Furkan B Barut ◽  
Mehmet Gunduz ◽  
Reidar Grenman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pancreatic Cancer ◽  
Stem Cells ◽  
Stem Cell ◽  
Cancer Stem Cells ◽  
Head And Neck ◽  
Cell Line ◽  
Cell Lines ◽  
Cancer Cell ◽  
Cancer Cell Lines

Purpose: Recent studies have shown that cancer stem cells are resistant to chemotherapy. The aim of this study was to compare RIF1 gene expression in head and neck, pancreatic cancer and glioma cell lines and the cancer stem cells isolated from these cell lines. Methods: UT-SCC-74 from Turku University and UT-SCC-74B primary tumor metastasis and neck cancer cell lines, YKG-1 glioma cancer cell line from RIKEN, pancreatic cancer cell lines and ASPC-1 cells from ATCC were grown in cell culture. To isolate cancer stem cells, ALDH-1 for UT-SCC-74 and UT-SCC-74B cell line, CD-133 for YKG-1 cell line and CD-24 for ASPC-1 cell line, were used as markers of cancer stem cells. RNA isolation was performed for both cancer lines and cancer stem cells. RNAs were converted to cDNA. RIF1 gene expression was performed by qRT-PCR analysis. RIF1 gene expression was compared with cancer cell lines and cancer stem cells isolated from these cell lines. The possible effect of RIF1 gene was evaluated. Results: In the pancreatic cells, RIF1 gene expression in the stem cell-positive cell line was 256 time that seen in the stem cell-negative cell line. Conclusion: Considering the importance of RIF1 in NHEJ and of NHEJ in pancreatic cancer, RIF1 may be one of the genes that plays an important role in the diagnoses and therapeutic treatment of pancreatic cancer. The results of head and neck and brain cancers are inconclusive and further studies are required to elucidate the connection between RIF1 gene and these other types of cancers.

scholarly journals EZH2 inhibition in glioblastoma stem cells increases the expression of neuronal genes and the neuronal developmental regulators ZIC2, ZNF423 and MAFB

2021 ◽  
Author(s):  
Bnar Kader ◽  
Rebecca DiStefano ◽  
Katherine L West ◽  
Adam G West
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Stem Cell ◽  
Cell Lines ◽  
Treatment Options ◽  
Underlying Mechanism ◽  
Neuronal Structure ◽  
Expression Of Genes ◽  
Neuronal Genes ◽  
Stem Cell Lines

Glioblastoma multiforme (GBM) is an aggressive brain cancer with a very poor prognosis. It has been shown that GBM stem cells within a GBM tumour have increased resistance to standard therapies, so new approaches are needed to increase the range of treatment options available. Here we use two GBM stem cell lines, representing the classical/pro-neural and mesenchymal GBM subtypes, to investigate the effects of three different EZH2 inhibitors on GBM stem cell survival and gene expression: EPZ6438, GSK343 and UNC1999. EZH2 is the catalytic component of the PRC2 chromatin repressor complex, which represses transcription through methylation of histone H3 at lysine 27. Both cell lines showed significantly reduced colony formation after 48-hour exposure to the inhibitors, indicating they were sensitive to all three EZH2 inhibitors. RNA-seq analysis revealed that all three EZH2 inhibitors led to increased expression of genes related to neurogenesis and/or neuronal structure in both GBM stem cell lines. Chromatin immunoprecipitation (ChIP-Seq) was used to identify potential direct targets of the histone methylation activity of EZH2 that might be driving the increase in neuronal gene expression. Three genes were identified as candidate regulatory targets common to both cell lines: MAFB, ZIC2 and ZNF423. These transcription factors all have known roles in regulating neurogenesis, brain development and/or neuronal function. Through analysis of three different EZH2 inhibitors and two GBM stem cell lines, this study demonstrates a common underlying mechanism for how inhibition of EZH2 activity reduces GBM stem cell proliferation and survival.

Cytometric Profiling of CD133+ Cells in Human Colon Carcinoma Cell Lines Identifies a Common core Phenotype and Cell Type-specific Mosaics

2013 ◽  
Vol 28 (3) ◽  
pp. 267-273 ◽  
Author(s):  
Marica Gemei ◽  
Rosa Di Noto ◽  
Peppino Mirabelli ◽  
Luigi Del Vecchio
Keyword(s):  
Colorectal Cancer ◽  
Stem Cells ◽  
Cancer Stem Cells ◽  
Colon Carcinoma ◽  
Cell Lines ◽  
Carcinoma Cell ◽  
Cell Type ◽  
Carcinoma Cell Lines ◽  
Cell Type Specific

In colorectal cancer, CD133+ cells from fresh biopsies proved to be more tumorigenic than their CD133– counterparts. Nevertheless, the function of CD133 protein in tumorigenic cells seems only marginal. Moreover, CD133 expression alone is insufficient to isolate true cancer stem cells, since only 1 out of 262 CD133+ cells actually displays stem-cell capacity. Thus, new markers for colorectal cancer stem cells are needed. Here, we show the extensive characterization of CD133+ cells in 5 different colon carcinoma continuous cell lines (HT29, HCT116, Caco2, GEO and LS174T), each representing a different maturation level of colorectal cancer cells. Markers associated with stemness, tumorigenesis and metastatic potential were selected. We identified 6 molecules consistently present on CD133+ cells: CD9, CD29, CD49b, CD59, CD151, and CD326. By contrast, CD24, CD26, CD54, CD66c, CD81, CD90, CD99, CD112, CD164, CD166, and CD200 showed a discontinuous behavior, which led us to identify cell type-specific surface antigen mosaics. Finally, some antigens, e.g. CD227, indicated the possibility of classifying the CD133+ cells into 2 subsets likely exhibiting specific features. This study reports, for the first time, an extended characterization of the CD133+ cells in colon carcinoma cell lines and provides a “dictionary” of antigens to be used in colorectal cancer research.

Characterization of stem cell–like cancer cells in immune-competent mice

Blood ◽  
2006 ◽  
Vol 108 (12) ◽  
pp. 3906-3912 ◽  
Author(s):  
Jorg A. Kruger ◽  
Charles D. Kaplan ◽  
Yunping Luo ◽  
He Zhou ◽  
Dorothy Markowitz ◽  
...  
Keyword(s):  
Stem Cell ◽  
Cancer Cells ◽  
Cell Lines ◽  
Carcinoma Cell ◽  
Side Population ◽  
Carcinoma Cell Lines ◽  
Tumorigenic Potential ◽  
4T1 Cells

AbstractRecently, the cancer stem cell hypothesis has gained significant recognition as the descriptor of tumorigenesis. Although previous studies relied on transplanting human or rat tumor cells into immunecompromised mice, our study used the Hoechst 33342 dye–based side population (SP) technique to isolate and transplant stem cell–like cancer cells (SCLCCs) from the 4T1 and NXS2 murine carcinoma cell lines into the immune-competent microenvironment of syngeneic mice. 4T1 cells displayed an SP of 2% with a Sca-1highc-Kit–CD45– phenotype, whereas NXS2 cells contained an SP of 0.2% with a Sca-1highCD24highc-Kit–CD45–GD high2 phenotype. Reverse transcription–polymerase chain reaction (RT-PCR) further revealed up-regulation in SP cells of ABCG2, Sca-1, Wnt-1, and TGF-β2. Additionally, 4T1 and NXS2 SP cells exhibited increased resistance to chemotherapy, and 4T1 SP cells also showed an increased ability to efflux doxorubicin, which correlated with a selective increase in the percentage of SP cells found in the tumors of doxorubicin-treated mice. Most importantly, SP cells showed a markedly higher repopulation and tumorigenic potential in vivo, which correlated with an increased number of cells in the SP compartment of SP-derived tumors. Taken together, these results show that we successfully characterized SCLCCs from 2 murine carcinoma cell lines in the immune-competent microenvironment of syngeneic mice.

Computational Strategies for Analyzing Data in Gene Expression Microarray Experiments

2003 ◽  
Vol 01 (03) ◽  
pp. 541-586 ◽  
Author(s):  
Tero Aittokallio ◽  
Markus Kurki ◽  
Olli Nevalainen ◽  
Tuomas Nikula ◽  
Anne West ◽  
...  
Keyword(s):  
Gene Expression ◽  
Data Analysis ◽  
Microarray Data ◽  
Microarray Data Analysis ◽  
Biological Research ◽  
Microarray Experiments ◽  
Dna Microarray Data ◽  
Open Questions ◽  
Analysis Technique ◽  
Wide Range

Microarray analysis has become a widely used method for generating gene expression data on a genomic scale. Microarrays have been enthusiastically applied in many fields of biological research, even though several open questions remain about the analysis of such data. A wide range of approaches are available for computational analysis, but no general consensus exists as to standard for microarray data analysis protocol. Consequently, the choice of data analysis technique is a crucial element depending both on the data and on the goals of the experiment. Therefore, basic understanding of bioinformatics is required for optimal experimental design and meaningful interpretation of the results. This review summarizes some of the common themes in DNA microarray data analysis, including data normalization and detection of differential expression. Algorithms are demonstrated by analyzing cDNA microarray data from an experiment monitoring gene expression in T helper cells. Several computational biology strategies, along with their relative merits, are overviewed and potential areas for additional research discussed. The goal of the review is to provide a computational framework for applying and evaluating such bioinformatics strategies. Solid knowledge of microarray informatics contributes to the implementation of more efficient computational protocols for the given data obtained through microarray experiments.

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