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Gene expression microarray and CGH array of metabolically adaptable cells derived from SUM149 triple-negative Inflammatory Breast Cancer cell line

ABSTRACT: This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Homo sapiens

PROVIDER: GSE60017 | GEO | 2014/10/03

SECONDARY ACCESSION(S): PRJNA257280

REPOSITORIES: GEO

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Gene expression microarray and CGH array of metabolically adaptable cells derived from SUM149 triple-negative Inflammatory Breast Cancer cell line

Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series

| S-ECPF-GEOD-60017 | biostudies-other

Gene expression microarray and CGH array of metabolically adaptable cells derived from SUM149 triple-negative Inflammatory Breast Cancer cell line

Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series

2014-10-03 | E-GEOD-60017 | biostudies-arrayexpress

aCGH: Human SUM149-Luc triple-negative Inflammatory Breast Cancer cell line versus its metabolically adaptable variants MA1 and MA2

Project description:CGH array of MA1 and MA2 variant cells as compared to the parental SUM149-Luc breast cancer cell line. The MA1 and MA2 variants were isolated based on the ability of rare cancer cells to survive and grow without adding glutamine in culture medium. To gain insight into the characteristic of metabolically adaptable MA cells that enables them to survive severe metabolic challenge, i.e., prolonged lack of glutamine and other challenges [Singh et al., PLoS ONE 7: e36510, 2012], we analyzed CGH array to compare these cells with the parental SUM149-Luc (luciferase-transfected) cells. We analyzed two independently selected cell populations, one from 0.5 million parental cells (designated MA1) and one from 1 million parental cells (designated MA2).

2014-10-03 | GSE60015 | GEO

aCGH: Human SUM149-Luc triple-negative Inflammatory Breast Cancer cell line versus its metabolically adaptable variants MA1 and MA2

2014-10-03 | E-GEOD-60015 | biostudies-arrayexpress

Gene expression of metabolically adaptable triple-negative breast cancer cells

Project description:To gain insight into the characteristic of metabolically adaptable MA cells that enables them to survive severe metabolic challenge, i.e., prolonged lack of glutamine and other challenges [Singh et al., PLoS ONE 7: e36510, 2012], we used gene expression microarrays to compare these cells with the parental SUM149-Luc (luciferase-transfected) cells. We analyzed two independently selected cell populations, one from 0.5 million parental cells (designated MA1) and one from 1 million parental cells (designated MA2). Comparing MA1 and MA2 variants to a common parental cell line SUM149-Luc. One sample each.

| S-ECPF-GEOD-60016 | biostudies-other

Gene expression of metabolically adaptable triple-negative breast cancer cells

2014-10-03 | E-GEOD-60016 | biostudies-arrayexpress

Gene expression of metabolically adaptable triple-negative breast cancer cells

2014-10-03 | GSE60016 | GEO

Matching of array CGH and gene expression microarray features for the purpose of integrative genomic analyses.

Project description:BACKGROUND: An increasing number of genomic studies interrogating more than one molecular level is published. Bioinformatics follows biological practice, and recent years have seen a surge in methodology for the integrative analysis of genomic data. Often such analyses require knowledge of which elements of one platform link to those of another. Although important, many integrative analyses do not or insufficiently detail the matching of the platforms. RESULTS: We describe, illustrate and discuss six matching procedures. They are implemented in the R-package sigaR (available from Bioconductor). The principles underlying the presented matching procedures are generic, and can be combined to form new matching approaches or be applied to the matching of other platforms. Illustration of the matching procedures on a variety of data sets reveals how the procedures differ in the use of the available data, and may even lead to different results for individual genes. CONCLUSIONS: Matching of data from multiple genomics platforms is an important preprocessing step for many integrative bioinformatic analysis, for which we present six generic procedures, both old and new. They have been implemented in the R-package sigaR, available from Bioconductor.

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Genome-wide microarray expression and genomic alterations by array-CGH analysis in neuroblastoma stem-like cells.

Project description:Neuroblastoma has a very diverse clinical behaviour: from spontaneous regression to a very aggressive malignant progression and resistance to chemotherapy. This heterogeneous clinical behaviour might be due to the existence of Cancer Stem Cells (CSC), a subpopulation within the tumor with stem-like cell properties: a significant proliferation capacity, a unique self-renewal capacity, and therefore, a higher ability to form new tumors. We enriched the CSC-like cell population content of two commercial neuroblastoma cell lines by the use of conditioned cell culture media for neurospheres, and compared genomic gains and losses and genome expression by array-CGH and microarray analysis, respectively (in CSC-like versus standard tumor cells culture). Despite the array-CGH did not show significant differences between standard and CSC-like in both analyzed cell lines, the microarray expression analysis highlighted some of the most relevant biological processes and molecular functions that might be responsible for the CSC-like phenotype. Some signalling pathways detected seem to be involved in self-renewal of normal tissues (Wnt, Notch, Hh and TGF-?) and contribute to CSC phenotype. We focused on the aberrant activation of TGF-? and Hh signalling pathways, confirming the inhibition of repressors of TGF-? pathway, as SMAD6 and SMAD7 by RT-qPCR. The analysis of the Sonic Hedgehog pathway showed overexpression of PTCH1, GLI1 and SMO. We found overexpression of CD133 and CD15 in SIMA neurospheres, confirming that this cell line was particularly enriched in stem-like cells. This work shows a cross-talk among different pathways in neuroblastoma and its importance in CSC-like cells.

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Metabolically activated adipose tissue macrophages link obesity to triple-negative breast cancer.

Project description:Obesity is associated with increased incidence and severity of triple-negative breast cancer (TNBC); however, mechanisms underlying this relationship are incompletely understood. Here, we show that obesity reprograms mammary adipose tissue macrophages to a pro-inflammatory metabolically activated phenotype (MMe) that alters the niche to support tumor formation. Unlike pro-inflammatory M1 macrophages that antagonize tumorigenesis, MMe macrophages are pro-tumorigenic and represent the dominant macrophage phenotype in mammary adipose tissue of obese humans and mice. MMe macrophages release IL-6 in an NADPH oxidase 2 (NOX2)-dependent manner, which signals through glycoprotein 130 (GP130) on TNBC cells to promote stem-like properties including tumor formation. Deleting Nox2 in myeloid cells or depleting GP130 in TNBC cells attenuates obesity-augmented TNBC stemness. Moreover, weight loss reverses the effects of obesity on MMe macrophage inflammation and TNBC tumor formation. Our studies implicate MMe macrophage accumulation in mammary adipose tissue as a mechanism for promoting TNBC stemness and tumorigenesis during obesity.

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