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

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Abstract

Human lung cell lines are utilized widely for investigating tumor biology, experimental therapy, anticancer drug screening and biomarkers identification. However, the consistency of drug responses of these established cell lines and non-small cell lung cancer (NSCLC) is uncertain. In this study, we assessed the drug response consistency between lung cell lines and NSCLC tumors in The Cancer Genome Atlas by hierarchical clustering using copy number variations in driver genes, and profiled the molecular patterns and correlations in cell lines. We found that some frequently used cell lines of NSCLC subtypes were not clustered with their matched subtypes of tumor. Mutation profiles in the oxidative stress response and squamous differentiation pathway in lung cell lines were in concordance with lung squamous cell carcinoma. Furthermore, lung cell lines and tumors in the same sub-cluster had very similar responses to certain drugs but some were inconsistent, suggesting that clustering through copy number variation data could capture part of the suitability of lung cell lines. The analysis of these results could aid investigators in evaluating drug response models and eventually enabling personalized treatment recommendations for individual patients with NSCLC.

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The data and material are presented within the manuscript.

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The codes used in this manuscript were conducted in R packages.

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Funding

This work was supported by the grants from the National Natural Science Foundation of China (62102004), the Natural Science Young Foundation of Anhui (2008085QF293), the Natural Science Young Foundation of Anhui Agricultural University (2019zd12), the Introduction and Stabilization of Talent Project of Anhui Agricultural University (yj2019-32), and the Graduate Innovation Fund of Anhui Agricultural University (2021yjs-53).

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Authors and Affiliations

  1. School of Information and Computer, Anhui Agricultural University, Hefei, 230036, Anhui, China

    Yueyue Shen, Ying Xiang, Xiaolong Huang, Youhua Zhang & Zhenyu Yue

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  1. Yueyue Shen
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  2. Ying Xiang
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  3. Xiaolong Huang
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  4. Youhua Zhang
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  5. Zhenyu Yue
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Contributions

YS: conceptualization, data curation, methodology, visualization, and writing-original draft. YX: data curation, software, and methodology. XH: data curation and visualization. YZ: methodology and writing-review and editing. ZY: conceptualization, supervision, writing-review and editing, and funding acquisition. All the authors read and approved the final manuscript.

Corresponding author

Correspondence to Zhenyu Yue.

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On behalf of all authors, the corresponding author states that there is no conflict of interest.

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Shen, Y., Xiang, Y., Huang, X. et al. Pharmacogenomic Cluster Analysis of Lung Cancer Cell Lines Provides Insights into Preclinical Model Selection in NSCLC. Interdiscip Sci Comput Life Sci 14, 712–721 (2022). https://doi.org/10.1007/s12539-022-00517-z

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  • DOI: https://doi.org/10.1007/s12539-022-00517-z

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