scholarly journals Molecular Characterization of Putative Chordoma Cell Lines

Sarcoma ◽  
2010 ◽  
Vol 2010 ◽  
pp. 1-14 ◽  
Author(s):  
Silke Brüderlein ◽  
Joshua B. Sommer ◽  
Paul S. Meltzer ◽  
Sufeng Li ◽  
Takuya Osada ◽  
...  

Immortal tumor cell lines are an important model system for cancer research, however, misidentification and cross-contamination of cell lines are a common problem. Seven chordoma cell lines are reported in the literature, but none has been characterized in detail. We analyzed gene expression patterns and genomic copy number variations in five putative chordoma cell lines (U-CH1, CCL3, CCL4, GB60, and CM319). We also created a new chordoma cell line, U-CH2, and provided genotypes for cell lines for identity confirmation. Our analyses revealed that CCL3, CCL4, and GB60 are not chordoma cell lines, and that CM319 is a cancer cell line possibly derived from chordoma, but lacking expression of key chordoma biomarkers. U-CH1 and U-CH2 both have gene expression profiles, copy number aberrations, and morphology consistent with chordoma tumors. These cell lines also harbor genetic changes, such as loss of p16, MTAP, or PTEN, that make them potentially useful models for studying mechanisms of chordoma pathogenesis and for evaluating targeted therapies.

Cells ◽  
2019 ◽  
Vol 8 (7) ◽  
pp. 675 ◽  
Author(s):  
Xia ◽  
Liu ◽  
Zhang ◽  
Guo

High-throughput technologies generate a tremendous amount of expression data on mRNA, miRNA and protein levels. Mining and visualizing the large amount of expression data requires sophisticated computational skills. An easy to use and user-friendly web-server for the visualization of gene expression profiles could greatly facilitate data exploration and hypothesis generation for biologists. Here, we curated and normalized the gene expression data on mRNA, miRNA and protein levels in 23315, 9009 and 9244 samples, respectively, from 40 tissues (The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GETx)) and 1594 cell lines (Cancer Cell Line Encyclopedia (CCLE) and MD Anderson Cell Lines Project (MCLP)). Then, we constructed the Gene Expression Display Server (GEDS), a web-based tool for quantification, comparison and visualization of gene expression data. GEDS integrates multiscale expression data and provides multiple types of figures and tables to satisfy several kinds of user requirements. The comprehensive expression profiles plotted in the one-stop GEDS platform greatly facilitate experimental biologists utilizing big data for better experimental design and analysis. GEDS is freely available on http://bioinfo.life.hust.edu.cn/web/GEDS/.


Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 3360-3360
Author(s):  
Erik Wendlandt ◽  
Guido J. Tricot ◽  
Benjamin Darbro ◽  
Fenghuang Zhan

Abstract Background: Multiple myeloma is the second most common blood borne neoplasia, accounting for nearly 10% of all diagnosed hematologic malignancies and has a disproportionately high incidence in elderly populations. Here we explored copy number variations using the high fidelity CytoScan HD arrays to develop a detailed map of copy number variations and identify novel mediators of disease progression. The results from CytoScan HD microarrays provide a detailed view of the entire genome with a resolution up to 25kb. Furthermore, 750,000 single-nucleotide polymorphisms are included and the array provides information about loss of heterozygosity and uniparental disomy. Materials and methods: CytoScan HD arrays were performed on 97 myeloma patient samples to identify cytogenetic regions important to the development and progression of the disease. Gene expression profiles from 351 patients were analyzed to identify genes with a change in gene expression of 1.5 fold or more. Data from CytoScan and gene expression arrays was combined to perform chromosomal positional enrichment analysis to identify cytogenetic driver lesions, or lesions that provide a small, but significant growth and survival advantage to the cell. Furthermore, Kaplan-Meier, log-rank test and Hazard ratio analyses were performed to identify gene within the driver lesions that have a significant impact on survival when dysregulated. Results: The results from the CytoScan HD analysis closely mirrored what has been shown by FISH and SNP arrays, with gains to the odd numbered chromosomes, specifically 3, 5, 7, 9, 11, 15 and 17 as well as losses to chromosomes 1p and 13. Interestingly, we identified gains to a small region within chromosome 8p, contrary to published reports demonstrating a large scale loss of this region. We identified numerous genes within this region that are important for survival and their overexpression resulted in a decreased progression free survival. For example, Cathepsin B (CTSB) is encoded for in chromosome 8p22-p21 with an increased gene expression of at least 1.5 fold over normal controls, among others. Furthermore, Cathepsin B, a cysteine protease, has been linked to cancer of the ileum, suggesting that a similar role may be present within myeloma. We then integrated the 97 copy number profiles results with 351 myeloma gene expression profiles to identify cytogenetic driver lesions in myeloma important for disease development, progression and poor clinical outcome. Chromosomal positional enrichment analysis was employed to identify global myeloma cytogenetic driver aneuploidies as well as develop unique cytogenetic copy number profiles. Our results identified portions of chromosomes 1q, 3, 8p, 9, 13q and 16q, among others, as important driver lesions with changes to these regions providing growth advantages to the cell. Furthermore, our analysis identified five unique cytogenetic classifications based on common cytogenetic lesions. We continue to explore these driver regions to identify lesions important for the oncogenic properties of the larger regions. Conclusion: The data presented here represents a novel and highly sensitive approach for the identification of novel copy number variations and driver lesions. Furthermore, correlations between copy number variations and gene expression arrays identified novel targets important for disease progression and patient survival. CytoScan HD arrays in conjunction with gene expression analysis provided a high resolution image of important cytogenetic lesions in myeloma and identified potentially important therapeutic targets for drug development. Further work is needed to validate our findings and determine the therapeutic efficacy of the identified targets. Disclosures No relevant conflicts of interest to declare.


2019 ◽  
Author(s):  
Qiong Zhang ◽  
Mei Luo ◽  
Chun-Jie Liu ◽  
An-Yuan Guo

AbstractCancer cell lines (CCLs) as important model systems play critical roles in cancer researches. The misidentification and contamination of CCLs are serious problems, leading to unreliable results and waste of resources. Current methods for CCL authentication are mainly based on the CCL-specific genetic polymorphisms, whereas no method is available for CCL authentication using gene expression profiles. Here, we developed a novel method and homonymic web server (CCLA, Cancer Cell Line Authentication, http://bioinfo.life.hust.edu.cn/web/CCLA/) to authenticate 1,291 human CCLs of 28 tissues using gene expression profiles. CCLA curated CCL-specific gene signatures and employed machine learning methods to measure overall similarities and distances between the query sample and each reference CCL. CCLA showed an excellent speed advantage and high accuracy with a top 1 accuracy of 96.58% or 92.15% (top 3 accuracy of 100% or 95.11%) for microarray or RNA-Seq validation data (719 samples, 461 CCLs), respectively. To the best of our knowledge, CCLA is the first approach to authenticate CCLs based on gene expression. Users can freely and conveniently authenticate CCLs using gene expression profiles or NCBI GEO accession on CCLA website.


2015 ◽  
Vol 2015 ◽  
pp. 1-17 ◽  
Author(s):  
Shiva Marthandan ◽  
Steffen Priebe ◽  
Mario Baumgart ◽  
Marco Groth ◽  
Alessandro Cellerino ◽  
...  

Replicative senescence is of fundamental importance for the process of cellular aging, since it is a property of most of our somatic cells. Here, we elucidated this process by comparing gene expression changes, measured by RNA-seq, in fibroblasts originating from two different tissues, embryonic lung (MRC-5) and foreskin (HFF), at five different time points during their transition into senescence. Although the expression patterns of both fibroblast cell lines can be clearly distinguished, the similar differential expression of an ensemble of genes was found to correlate well with their transition into senescence, with only a minority of genes being cell line specific. Clustering-based approaches further revealed common signatures between the cell lines. Investigation of the mRNA expression levels at various time points during the lifespan of either of the fibroblasts resulted in a number of monotonically up- and downregulated genes which clearly showed a novel strong link to aging and senescence related processes which might be functional. In terms of expression profiles of differentially expressed genes with age, common genes identified here have the potential to rule the transition into senescence of embryonic lung and foreskin fibroblasts irrespective of their different cellular origin.


Medicine ◽  
2017 ◽  
Vol 96 (28) ◽  
pp. e7264 ◽  
Author(s):  
Yuping Han ◽  
Xuefei Jin ◽  
Hongyan Li ◽  
Kaichen Wang ◽  
Ji Gao ◽  
...  

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 3393-3393
Author(s):  
Pieter Sonneveld ◽  
Eric Kamst ◽  
Yvonne de Knegt ◽  
Naomi Klarenbeek ◽  
Martijn Schoester

Abstract Multiple Myeloma (MM) is a disease of monoclonal plasma cells in the bone marrow which has a transient response to classic chemotherapy. At diagnosis, induction chemotherapy followed by high-dose melphalan (HDM) with stem cell support is used in most patients to achieve a clinical response. Because all patients will ultimately relapse, the treatment of melphalan-refractory disease represents a major clinical challenge and new agents are needed to overcome melphalan resistance. We have investigated the anti-myeloma efficacy of two new classes of targeted agents, i.e. proteasome inhibition and histone deacetylation inhibition alone or in combination in the melphalan sensitive MM1S and the Melphalan refractory MM1MEL2000 cell lines. The IC50 values of Bortezomib (B), Melphalan (M) and LAQ824 (L) in MM1S were 2.1 nM, 1.9 uM and 1.7 nM, respectively and in MM1MEL2000 3.9 nM, 50 uM and 4.0 nM. Using isobologram analysis a synergysm between B and L was observed in the sensitive, however not in the melphalan refractory cell line. These data indicate that B proteasome inhibition and histone deacetylation inhibition may be effective ways to overcome melphalan resistance. However, the previously reported synergism between these drugs does not seem to occur in melphalan resistant cells. The gene expression profiles of these cell lines were analysed using the Affymetrix U133plus 2.0 gene chip before and after treatment with melfaphalan or the proteasome inhibitor B or the histone deacetylation inhibitor L or the combination of B and L. Genes that were highly expressed in the melphalan refractory derivate cell line MM1MEL2000 as compared with wild-type MM1S included GP M6B, ADAM23 and HTPAP. Following melphalan exposure, TMF1, a CEBp glucocorticoid interaction factor, WHSC1L1, a MMSET homologue with EGF like domain and several transcription factors had highly increased expression as compared to MM1S. With exposure to B combined with L, increased expression in MM1MEL2000 over MM1S was observed for GTP exchange factor TIAM1 which interacts with RAS and JNK, and the lymphoid enhancer factor, a notch transcription factor. It is concluded that Bortezomib and the histone deacetylase inhibitor LAQ824 are effective agents to overcome melphalan resistance in multiple myeloma. However, the combination fails to show the synergism observed in melphalan sensitive cells. Gene analysis sofar does not provide a clear explanation for this lack of synergism. A comprehensive summary of the observed shifts of gene expression profiles in melphalan resistant cells following exposure to these agents, will be presented.


2012 ◽  
Vol 30 (5_suppl) ◽  
pp. 377-377
Author(s):  
Brian Shuch ◽  
Christopher Ricketts ◽  
Carole Sourbier ◽  
Shinji Tsutsumi ◽  
Xiu-ying Zhang ◽  
...  

377 Background: Papillary kidney cancer, which occurs in 15% of patients with kidney cancer, can be aggressive and there is currently no effective form of therapy for this disease. To evaluate the metabolic characteristics of sporadic papillary kidney cancer, we have evaluated metabolic parameters of several papillary kidney cancer cell lines and available gene expression profiles. Methods: Established cell lines derived from patients with sporadic papillary kidney cancer (LABAZ, MDACC-55, HRC-86T2) and from a hereditary form of fumarate hydratase-deficient kidney cancer (UOK262) were evaluated. All sporadic lines were initially sequenced for fumarate hydratase (FH). All cell lines were metabolically profiled using the Seahorse Extracellular Flux Analyzer and further evaluated for reactive oxygen species (ROS), mitochondrial membrane potential, and glucose dependence. Finally gene expression profiles of publically available datasets of papillary and HLRCC tumors were downloaded, normalized, and analyzed. Results: Sporadic lines had no alterations in FH and metabolic analysis demonstrated normal oxygen consumption and minimal lactate production, in contrast to highly glycolytic UOK262. Also unlike UOK262, the sporadic papillary kidney cancer lines were not sensitive to glucose withdrawal, had low levels of ROS, and had normal mitochondria membrane potential. Principal component analysis (PCA) demonstrated that HLRCC tumor specimens are very different from sporadic papillary tumors at the molecular level. Conclusions: Our study of established sporadic papillary RCC and fumarate hydratase-deficient HLRCC cell line together with analysis of available gene expression profiles demonstrates that these sporadic papillary kidney cancer cell lines appear to have a distinct metabolic profile from those in the fumarate hydratase deficient kidney cancer cell line. Understanding the metabolic basis of papillary kidney cancer could provide the foundation for the development of targeted approaches to therapy for patients with this disease.


PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0245939
Author(s):  
Keita Fukuyama ◽  
Masataka Asagiri ◽  
Masahiro Sugimoto ◽  
Hiraki Tsushima ◽  
Satoru Seo ◽  
...  

Cancer cell lines are widely used in basic research to study cancer development, growth, invasion, or metastasis. They are also used for the development and screening of anticancer drugs. However, there are no clear criteria for choosing the most suitable cell lines among the wide variety of cancer cell lines commercially available for research, and the choice is often based on previously published reports. Here, we investigated the characteristics of liver cancer cell lines by analyzing the gene expression data available in the Cancer Cell Line Encyclopedia. Unsupervised clustering analysis of 28 liver cancer cell lines yielded two main clusters. One cluster showed a gene expression pattern similar to that of hepatocytes, and the other showed a pattern similar to that of fibroblasts. Analysis of hepatocellular carcinoma gene expression profiles available in The Cancer Genome Atlas showed that the gene expression patterns in most hepatoma tissues were similar to those in the hepatocyte-like cluster. With respect to liver cancer research, our findings may be useful for selecting an appropriate cell line for a specific study objective. Furthermore, our approach of utilizing a public database for comparing the properties of cell lines could be an attractive cell line selection strategy that can be applied to other fields of research.


Author(s):  
Qiong Zhang ◽  
Mei Luo ◽  
Chun-Jie Liu ◽  
An-Yuan Guo

Abstract Cancer cell lines (CCLs) as important model systems play critical roles in cancer research. The misidentification and contamination of CCLs are serious problems, leading to unreliable results and waste of resources. Current methods for CCL authentication are mainly based on the CCL-specific genetic polymorphism, whereas no method is available for CCL authentication using gene expression profiles. Here, we developed a novel method and homonymic web server (CCLA, Cancer Cell Line Authentication, http://bioinfo.life.hust.edu.cn/web/CCLA/) to authenticate 1291 human CCLs of 28 tissues using gene expression profiles. CCLA showed an excellent speed advantage and high accuracy for CCL authentication, a top 1 accuracy of 96.58 or 92.15% (top 3 accuracy of 100 or 95.11%) for microarray or RNA-Seq validation data (719 samples, 461 CCLs), respectively. To the best of our knowledge, CCLA is the first approach to authenticate CCLs using gene expression data. Users can freely and conveniently authenticate CCLs using gene expression profiles or NCBI GEO accession on CCLA website.


2006 ◽  
Vol 53 (3) ◽  
pp. 525-530 ◽  
Author(s):  
Jiayi Zhang ◽  
Jinzhong Chen ◽  
Lingfeng Liu ◽  
Chaoneng Ji ◽  
Shaohua Gu ◽  
...  

Bim is a pro-apoptotic member of the Bcl-2 protein family. Overexpression of Bim proved to be highly cytotoxic for diverse cells. The AD293 cell line is derived directly from the HEK293 cell line but has been transfected with a gene that can improve cell adherence. We found that there was almost no apoptosis seen in Bim L-transfected AD293 cells, but more than half of Bim L-transfected HEK293 cells underwent apoptosis. Suppression subtractive hybridization was used to detect the different gene expression profile between these two cell lines. In 192 sequenced positive clones, there were 30 clones repeating twice or more. Ten genes were selected for identification by semi-quantitative RT-PCR. The transcripts of two adhesion-related genes (actin and parvin) and two apoptosis-related genes (cyclin 2 and protein phosphatase 1G) were up-regulated in AD293 cells. These results suggest that the high expression of cell adhesion-related proteins might be responsible for the different apoptosis status after the transfection of Bim L. Our data provide candidate genes responsible for the different apoptosis sensitivity of these two cell lines. Further investigation on the differential expression profile between AD293 and HEK293 might improve our understanding of cell apoptosis mechanism.


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