Literature DB >> 27694350

Optimization of cell lines as tumour models by integrating multi-omics data.

Ning Zhao, Yongjing Liu, Yunzhen Wei, Zichuang Yan, Qiang Zhang, Cheng Wu, Zhiqiang Chang, Yan Xu.   

Abstract

Cell lines are widely used as in vitro models of tumorigenesis. However, an increasing number of researchers have found that cell lines differ from their sourced tumour samples after long-term cell culture. The application of unsuitable cell lines in experiments will affect the experimental accuracy and the treatment of patients. Therefore, it is imperative to identify optimal cell lines for each cancer type. Here, we review the methods used to evaluate cell lines since 2005. Furthermore, gene expression, copy number and mutation profiles from The Cancer Genome Atlas and the Cancer Cell Line Encyclopedia are used to calculate similarity between tumours and cell lines. Then, the ideal cell lines to use for experiments for eight types of cancers are found by combining the results with Gene Ontology functional similarity. After verification, the optimal cell lines have the same genomic characteristics as their homologous tumour samples. The contaminated cell lines identified in previous research are also determined to be unsuitable in vitro cancer models here. Moreover, our study suggests that some of the commonly used cell lines are not suitable cancer models. In summary, we provide a reference for ideal cell lines to use in in vitro experiments and contribute to improving the accuracy of future cancer research. Furthermore, this research provides a foundation for identifying more effective treatment strategies.
© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  cancer in vitro model; cell line; multi-omics; optimization

Mesh:

Year:  2017        PMID: 27694350     DOI: 10.1093/bib/bbw082

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  8 in total

Review 1.  An Interactive Resource to Probe Genetic Diversity and Estimated Ancestry in Cancer Cell Lines.

Authors:  Julie Dutil; Zhihua Chen; Alvaro N Monteiro; Jamie K Teer; Steven A Eschrich
Journal:  Cancer Res       Date:  2019-03-20       Impact factor: 12.701

2.  Comprehensive Genetic Characterization of Human Thyroid Cancer Cell Lines: A Validated Panel for Preclinical Studies.

Authors:  Iñigo Landa; Nikita Pozdeyev; Christopher Korch; Laura A Marlow; Robert C Smallridge; John A Copland; Ying C Henderson; Stephen Y Lai; Gary L Clayman; Naoyoshi Onoda; Aik Choon Tan; Maria E R Garcia-Rendueles; Jeffrey A Knauf; Bryan R Haugen; James A Fagin; Rebecca E Schweppe
Journal:  Clin Cancer Res       Date:  2019-02-08       Impact factor: 12.531

3.  CNpare: matching DNA copy number profiles.

Authors:  Blas Chaves-Urbano; Barbara Hernando; Maria J Garcia; Geoff Macintyre
Journal:  Bioinformatics       Date:  2022-05-31       Impact factor: 6.931

Review 4.  Computational estimation of quality and clinical relevance of cancer cell lines.

Authors:  Lucia Trastulla; Javad Noorbakhsh; Francisca Vazquez; James McFarland; Francesco Iorio
Journal:  Mol Syst Biol       Date:  2022-07       Impact factor: 13.068

5.  Pharmacogenomic Cluster Analysis of Lung Cancer Cell Lines Provides Insights into Preclinical Model Selection in NSCLC.

Authors:  Yueyue Shen; Ying Xiang; Xiaolong Huang; Youhua Zhang; Zhenyu Yue
Journal:  Interdiscip Sci       Date:  2022-04-27       Impact factor: 3.492

6.  Comparison of Proteomics Profiles Between Xenografts Derived from Cell Lines and Primary Tumors of Thyroid Carcinoma.

Authors:  Luo Fang; Yu-Jia Liu; Yi-Wen Zhang; Zong-Fu Pan; Li-Ke Zhong; Lie-Hao Jiang; Jia-Feng Wang; Xiao-Wei Zheng; Ling-Ya Chen; Ping Huang; Ming-Hua Ge; Zhuo Tan
Journal:  J Cancer       Date:  2021-01-31       Impact factor: 4.207

7.  OGEE v2: an update of the online gene essentiality database with special focus on differentially essential genes in human cancer cell lines.

Authors:  Wei-Hua Chen; Guanting Lu; Xiao Chen; Xing-Ming Zhao; Peer Bork
Journal:  Nucleic Acids Res       Date:  2016-10-30       Impact factor: 16.971

8.  A pan-cancer atlas of cancer hallmark-associated candidate driver lncRNAs.

Authors:  Yulan Deng; Shangyi Luo; Xinxin Zhang; Chaoxia Zou; Huating Yuan; Gaoming Liao; Liwen Xu; Chunyu Deng; Yujia Lan; Tingting Zhao; Xu Gao; Yun Xiao; Xia Li
Journal:  Mol Oncol       Date:  2018-10-02       Impact factor: 6.603

  8 in total

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