Gene expression profiling of mouse Sertoli cell lines

2004 ◽  
Vol 315 (2) ◽  
pp. 249-257 ◽  
Author(s):  
Kai Strothmann ◽  
Manuela Simoni ◽  
Premendu Mathur ◽  
Susan Siakhamary ◽  
Eberhard Nieschlag ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Sertoli Cell ◽  
Cell Lines ◽  
Expression Profiling

scholarly journals Assessing Various Control Samples for Microarray Gene Expression Profiling of Laryngeal Squamous Cell Carcinoma

Biomolecules ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 588
Author(s):  
Adam Ustaszewski ◽  
Magdalena Kostrzewska-Poczekaj ◽  
Joanna Janiszewska ◽  
Malgorzata Jarmuz-Szymczak ◽  
Malgorzata Wierzbicka ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Epithelial Cells ◽  
Cell Carcinoma ◽  
Gene Expression Profiling ◽  
Cell Lines ◽  
Squamous Cell ◽  
Expression Profiling ◽  
Laryngeal Squamous Cell Carcinoma ◽  
Control Samples

Selection of optimal control samples is crucial in expression profiling tumor samples. To address this issue, we performed microarray expression profiling of control samples routinely used in head and neck squamous cell carcinoma studies: human bronchial and tracheal epithelial cells, squamous cells obtained by laser uvulopalatoplasty and tumor surgical margins. We compared the results using multidimensional scaling and hierarchical clustering versus tumor samples and laryngeal squamous cell carcinoma cell lines. A general observation from our study is that the analyzed cohorts separated according to two dominant factors: “malignancy”, which separated controls from malignant samples and “cell culture-microenvironment” which reflected the differences between cultured and non-cultured samples. In conclusion, we advocate the use of cultured epithelial cells as controls for gene expression profiling of cancer cell lines. In contrast, comparisons of gene expression profiles of cancer cell lines versus surgical margin controls should be treated with caution, whereas fresh frozen surgical margins seem to be appropriate for gene expression profiling of tumor samples.

scholarly journals Gene expression profiling in wild-type and metallothionein mutant fibroblast cell lines

2006 ◽  
Vol 39 (1) ◽  
Author(s):  
ÁNGELA D ARMENDÁRIZ ◽  
FELIPE OLIVARES ◽  
RODRIGO PULGAR ◽  
ALEX LOGUINOV ◽  
VERÓNICA CAMBIAZO ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Cell Lines ◽  
Expression Profiling ◽  
Fibroblast Cell ◽  
Wild Type ◽  
Fibroblast Cell Lines

scholarly journals Gene expression profiling of breast cancer cell lines treated with proton and electron radiations

2018 ◽  
pp. 20170934 ◽  
Author(s):  
Valentina Bravatà ◽  
Luigi Minafra ◽  
Francesco Paolo Cammarata ◽  
Pietro Pisciotta ◽  
Debora Lamia ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Gene Expression Profiling ◽  
Cell Lines ◽  
Cancer Cell ◽  
Breast Cancer Cell ◽  
Expression Profiling ◽  
Cancer Cell Lines ◽  
Breast Cancer Cell Lines

Gene Expression Profiling Reveals a Crucial Role for C/EBPbeta in Proliferation Pathways of ALK+ ALCL Cell Lines

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 2818-2818
Author(s):  
Irina Bonzheim ◽  
Martin Irmler ◽  
Natasa Anastasov ◽  
Margit Klier ◽  
Johannes Beckers ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Statistical Analysis ◽  
Gene Expression Profiling ◽  
Cell Lines ◽  
Expression Profiling ◽  
Leucine Zipper ◽  
Cellular Proliferation ◽  
Kinase Activity ◽  
Large Cell

Abstract Introduction: ALK+ anaplastic large cell lymphomas (ALCL) overexpress C/EBPβ, as a consequence of NPM-ALK kinase activity. C/EBPβ is a leucine zipper transcription factor, which plays a major role in cellular differentiation, inflammation, proliferation and metabolism control. To determine the role of C/EBPβ in ALK+ ALCL transformation, and to identify its downstream targets, a highly specific C/EBPβ-shRNA was used to knockdown C/EBPβ. The consequences of C/EBPβ gene-silencing were analyzed by gene expression profiling. Materials and Methods: Four ALK+ ALCL cell lines, SUDHL-1, Kijk, Karpas 299 and SUP-M2 were transfected with lentivirus containing the C/EBPβ shRNA or the vector without shRNA in triplicates. Western Blot analysis and qRT-PCR were performed to quantify the knockdown effect. At day three after infection, RNA was extracted and used for Gene Chip expression analysis (Affymetrix). Using Anova software for statistical analysis, we identified genes, which were regulated in all four cell lines. The effect of C/EBPβ knockdown on proliferation, cell cycle, and viability was analyzed by MTT assay and FACS analysis. Results: In all four ALK+ ALCL, efficient C/EBPβ knockdown resulted in profound growth retardation (up to 84%) compared to control cells after 6 days of infection, and a clear shift from the S phase to the G1 phase in the cell cycle was observed. To identify genes regulated by C/EBPβ in all four cell lines, we performed statistical analysis applying a false discovery rate of 20%, and accepted only genes with a >1,1 and <0,9 fold ratio. We identfied 435 genes regulated after C/EBPβ knockdown (117 upregulated, 318 downregulated). Classification of the differentially expressed genes into biological categories revealed overrepresentation of genes involved in the regulation of kinase activity, cell cycle and proliferation, lymphocyte differentiation, and metabolic processes. In particular, kinases involved in the regulation of JNK activity, which have been shown previously to be involved in proliferation of ALCL, were highly affected by C/EBPβ knockdown. Genomatix Bibliosphere Pathway Analysis revealed C/EBPβ to be connected to pathways involving cell cycle (RUNX3, CCNG1, CDKN2A), apoptosis (FAS, PTPRC, BCL2A1, BIRC3) and MAPK cascades (TRIB1 and several MAP3Ks). Several of the genes identified contain known C/EBPβ binding sites. Conclusions: C/EBPβ silencing induces growth arrest in ALK+ALCL, which correlates with differential expression of genes involved in cell cycle, apoptosis and differentiation. This study reveals C/EBPβ as a master transcription regulator of NPM-ALK induced cellular proliferation, and therefore, an ideal candidate for targeted therapeutic intervention.

New Pathogenetic Insights Into Classical Hodgkin Lymphoma Revealed by Gene Expression Profiling of Microdissected Hodgkin/Reed-Sternberg Cells.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 266-266 ◽  
Author(s):  
Enrico Tiacci ◽  
Verena Brune ◽  
Susan Eckerle ◽  
Wolfram Klapper ◽  
Ines Pfeil ◽  
...  
Keyword(s):  
Gene Expression ◽  
B Cells ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Hodgkin Lymphoma ◽  
Cell Lines ◽  
Expression Profiling ◽  
Expression Profiles ◽  
B Cell Lymphoma ◽  
Cell Phenotype

Abstract Abstract 266 Background. Previous gene expression profiling studies on cHL have been performed on whole tissue sections (mainly reflecting the prominent reactive background in which the few HRS cells are embedded), or on cHL cell lines. However, cultured HRS cells do not likely reflect primary HRS cells in all aspects, being derived from end-stage patients and from sites (e.g. pleural effusions or bone marrow) which are not typically involved by cHL and where HRS cells lost their dependence on the inflammatory microenvironment of the lymph node. Methods. ∼1000–2000 neoplastic cells were laser-microdissected from hematoxylin/eosin-stained frozen sections of lymph nodes taken at disease onset from patients with cHL (n=16) or with various B-cell lymphomas (n=35), including primary mediastinal B-cell lymphoma (PMBL) and nodular lymphocyte-predominant Hodgkin lymphoma (nLPHL). After two rounds of in vitro linear amplification, mRNA was hybridized to Affymetrix HG-U133 Plus 2.0 chips. Expression profiles were likewise generated from sorted cHL cell lines and several normal mature B-cell populations. Results. Primary and cultured HRS cells, although sharing hallmark cHL signatures such as high NF-kB transcriptional activity and lost B-cell identity, showed considerable transcriptional divergence in chemokine/chemokine receptor activity, extracellular matrix remodeling and cell adhesion (all enriched in primary HRS cells), as well as in proliferation (enriched in cultured HRS cells). Unsupervised and supervised analyses indicated that microdissected HRS cells of cHL represent a transcriptionally unique lymphoma entity, overall closer to nLPHL than to PMBL but with differential behavior of the cHL histological subtypes, being HRS cells of the lymphocyte-rich and mixed-cellularity subtypes close to nLPHL cells while HRS cells of NS and LD exhibited greater similarity to PMBL cells. HRS cells downregulated a large number of genes involved in cell cycle checkpoints and in the maintenance of genomic integrity and chromosomal stability, while upregulating gene and gene signatures involved in various oncogenic signaling pathways and in cell phenotype reprogramming. Comparisons with normal B cells highlighted the lack of consistent transcriptional similarity of HRS cells to bulk germinal center (GC) B cells or plasma cells and, interestingly, a more pronounced resemblance to CD30+ GC B cells and CD30+ extrafollicular B cells, two previously uncharacterized subsets that are transcriptionally distinct from the other mature B-cell types. Conclusions. Gene expression profiling of primary HRS cells provided several new insights into the biology and pathogenesis of cHL, its relatedness to other lymphomas and normal B cells, and its enigmatic phenotype. Disclosures: No relevant conflicts of interest to declare.

Loss of KDM6A/UTX Function Is a Common Event in a Mouse Model of Multiple Myeloma, Human Cell Lines and Patients.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 606-606
Author(s):  
Jonathan J Keats ◽  
Marta Chesi ◽  
Esteban Braggio ◽  
Stephan Palmer ◽  
Angela Baker ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Mouse Model ◽  
Gene Expression Profiling ◽  
Cell Lines ◽  
Expression Profiling ◽  
Homozygous Deletion ◽  
Recurrent Event ◽  
Comparative Genomic ◽  
Homozygous Deletions

Abstract Abstract 606 Multiple myeloma is a complex malignancy with multiple underlying genetic events. Our group has spent considerable effort over the last 15 years to elucidate the genetic underpinnings of myeloma. Most recently, we used array-based comparative genomic hybridization (aCGH) as a discovery tool in 62 myeloma patients and 46 myeloma cell lines. In that preliminary screen using the Agilent 44B aCGH platform (∼70kb resolution) we identified a diverse array of abnormalities, which resulted in constitutive activation of the NF-kB pathways. That initial analysis concentrated on the 43 genes we identified as potential targets of the 13 homozygous deletion events detected in the patient samples. A pathway analysis of these genes revealed a single pathway involving TRAF3, TRAF2, BIRC2, BIRC3, and CYLD. This first analysis focused exclusively on abnormalities present in the patient samples as we worried some abnormalities identified exclusively in the cell lines might not be relevant to the pathogenesis of myeloma in patients. However, several abnormalities were equally or more frequent overall but occurred exclusively in cell lines including CDKN2C (14 samples), CDKN1B (4 samples), KDM6A/UTX (4 samples), RB1 (3 samples), TP53 (3 samples). Given the fact that KDM6A/UTX deletions were as frequent as many of the best-described tumor suppressors it seemed like a good candidate but in the absence of patient events or a known function at the time it was not prioritized for further study. Recently, as part of the Multiple Myeloma Research Consortium (MMRC) Genomics Initiative, we have completed the analysis of a cohort of 250 myeloma patient samples by aCGH using the Agilent 244A aCGH platform (∼15kb resolution) and gene expression profiling using the Affymetrix U133Plus2.0 genechip. In this cohort with a significantly improved aCGH platform we identified 17 genes that are recurrently inactivated by homozygous deletions including DIAPH2 (15 samples), CDKN2C (14 samples), TRAF3 (11 samples), CYLD (8 samples), BIRC2/3 (7 samples), KDM6A/UTX (6 samples), and RB1 (5 samples). Based on the significant improvement in resolution and data quality achieved with the Agilent 244A aCGH platform we rescreen all of the cell lines on this improved platform. This significantly changed the frequency of several homozygous deletions in this population with the most frequently targeted genes now being CDKN2C (20 samples), KDM6A/UTX (13 samples), DIAPH2 (7 samples), RB1 (4 samples), TP53 (4 samples), CDKN1B (4 samples), and TRAF3 (4 samples). Moreover, as part of the genomic characterization of a spontaneous myeloma mouse model that we have developed, Vk*-Myc, we have identified recurrent (∼50%) homozygous deletions of Kdm6a/Utx. Therefore, one of the genes most commonly targeted by a homozygous deletion in human and mouse myeloma is KDM6A/UTX. In late 2007 after we had identified the first patients with KDM6A/UTX deletions it was shown that UTX is a functional histone demethylase that removes methyl groups from histone H3 lysine 27 (H3K27me). Given the high incidence of deletions and the fact that MMSET, the overexpressed target gene of t(4;14) in myeloma, is predicted to methylate H3K27, H3K36, and/or H4K20 by evolutionary conservation we developed the hypothesis that myeloma is characterized by abnormalities that result in excessive H3K27me (typically a repressive chromatin mark). Given the extensive whole genome sequencing occurring in the MMRC genomics initiative we elected to focus our resequencing efforts on the cell lines exclusively. These studies identified an additional 4 samples with LOH and an inactivating mutation bringing the total percentage of inactivated cell lines to 33%. Clearly, in the expanded patient and cell line cohorts the inactivation of KDM6A/UTX is not independent of MMSET overexpression suggesting they may act independently or synergistically. We are currently attempting to identify the genes controlled by KDM6A/UTX inactivation to better understand the functional consequences of this highly recurrent event. However, in the mouse model unlike the patient or cell lines, the gene expression profiling has identified a gene expression signature that differentiates UTX inactivated and functional samples suggesting an oncogenic function of inactivation. Disclosures: No relevant conflicts of interest to declare.

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