scholarly journals CCLA: an accurate method and web server for cancer cell line authentication using gene expression profiles

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.

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.


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.


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.


2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Jelle Scholtalbers ◽  
Sebastian Boegel ◽  
Thomas Bukur ◽  
Marius Byl ◽  
Sebastian Goerges ◽  
...  

Oncogene ◽  
2002 ◽  
Vol 21 (42) ◽  
pp. 6549-6556 ◽  
Author(s):  
Jiafu Ji ◽  
Xin Chen ◽  
Suet Yi Leung ◽  
Jen-Tsan A Chi ◽  
Kent Man Chu ◽  
...  

2021 ◽  
Author(s):  
Zeynep Ates-Alagoz ◽  
Mehmet Murat Kisla ◽  
Fikriye Zengin Karadayi ◽  
Sercan Baran ◽  
Tuğba Somay Doğan ◽  
...  

Several indole-thiazolidinedione derivatives (9–24) were designed and synthesized as CDK6 inhibitors, and their anticancer activity was probed on the MCF-7 cell line and the effects on gene expression profiles were elucidated.


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