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Comprehensive transcriptomic analysis of cell lines as models of primary tumors across 22 tumor types

Author

Listed:
  • K. Yu

    (University of California San Francisco
    University of California, San Francisco)

  • B. Chen

    (Michigan State University
    Michigan State University)

  • D. Aran

    (University of California San Francisco)

  • J. Charalel

    (Stanford University)

  • C. Yau

    (Buck Institute for Research on Aging
    University of California, San Francisco)

  • D. M. Wolf

    (University of California, San Francisco)

  • L. J. ‘t Veer

    (University of California, San Francisco)

  • A. J. Butte

    (University of California San Francisco
    University of California, San Francisco)

  • T. Goldstein

    (University of California San Francisco)

  • M. Sirota

    (University of California San Francisco
    University of California, San Francisco)

Abstract

Cancer cell lines are a cornerstone of cancer research but previous studies have shown that not all cell lines are equal in their ability to model primary tumors. Here we present a comprehensive pan-cancer analysis utilizing transcriptomic profiles from The Cancer Genome Atlas and the Cancer Cell Line Encyclopedia to evaluate cell lines as models of primary tumors across 22 tumor types. We perform correlation analysis and gene set enrichment analysis to understand the differences between cell lines and primary tumors. Additionally, we classify cell lines into tumor subtypes in 9 tumor types. We present our pancreatic cancer results as a case study and find that the commonly used cell line MIA PaCa-2 is transcriptionally unrepresentative of primary pancreatic adenocarcinomas. Lastly, we propose a new cell line panel, the TCGA-110-CL, for pan-cancer studies. This study provides a resource to help researchers select more representative cell line models.

Suggested Citation

  • K. Yu & B. Chen & D. Aran & J. Charalel & C. Yau & D. M. Wolf & L. J. ‘t Veer & A. J. Butte & T. Goldstein & M. Sirota, 2019. "Comprehensive transcriptomic analysis of cell lines as models of primary tumors across 22 tumor types," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-11415-2
    DOI: 10.1038/s41467-019-11415-2
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    Cited by:

    1. Han Jin & Cheng Zhang & Martin Zwahlen & Kalle Feilitzen & Max Karlsson & Mengnan Shi & Meng Yuan & Xiya Song & Xiangyu Li & Hong Yang & Hasan Turkez & Linn Fagerberg & Mathias Uhlén & Adil Mardinoglu, 2023. "Systematic transcriptional analysis of human cell lines for gene expression landscape and tumor representation," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    2. Yuchen Bai & Carolin Gotz & Ginevra Chincarini & Zixuan Zhao & Clare Slaney & Jarryd Boath & Luc Furic & Christopher Angel & Stephen M. Jane & Wayne A. Phillips & Steven A. Stacker & Camile S. Farah &, 2023. "YBX1 integration of oncogenic PI3K/mTOR signalling regulates the fitness of malignant epithelial cells," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    3. Yeo-Jun Yoon & Donghyun Kim & Kwon Yong Tak & Seungyeon Hwang & Jisun Kim & Nam Suk Sim & Jae-Min Cho & Dojin Choi & Youngmi Ji & Junho K. Hur & Hyunki Kim & Jong-Eun Park & Jae-Yol Lim, 2022. "Salivary gland organoid culture maintains distinct glandular properties of murine and human major salivary glands," Nature Communications, Nature, vol. 13(1), pages 1-16, December.

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