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Evaluating cell lines as models for metastatic breast cancer through integrative analysis of genomic data

Author

Listed:
  • Ke Liu

    (Michigan State University
    Michigan State University)

  • Patrick A. Newbury

    (Michigan State University
    Michigan State University)

  • Benjamin S. Glicksberg

    (University of California San Francisco)

  • William Z. D. Zeng

    (University of California San Francisco)

  • Shreya Paithankar

    (Grand Valley State University)

  • Eran R. Andrechek

    (Michigan State University)

  • Bin Chen

    (Michigan State University
    Michigan State University)

Abstract

Cell lines are widely-used models to study metastatic cancer although the extent to which they recapitulate the disease in patients remains unknown. The recent accumulation of genomic data provides an unprecedented opportunity to evaluate the utility of them for metastatic cancer research. Here, we reveal substantial genomic differences between breast cancer cell lines and metastatic breast cancer patient samples. We also identify cell lines that more closely resemble the different subtypes of metastatic breast cancer seen in the clinic and show that surprisingly, MDA-MB-231 cells bear little genomic similarities to basal-like metastatic breast cancer patient samples. Further comparison suggests that organoids more closely resemble the transcriptome of metastatic breast cancer samples compared to cell lines. Our work provides a guide for cell line selection in the context of breast cancer metastasis and highlights the potential of organoids in these studies.

Suggested Citation

  • Ke Liu & Patrick A. Newbury & Benjamin S. Glicksberg & William Z. D. Zeng & Shreya Paithankar & Eran R. Andrechek & Bin Chen, 2019. "Evaluating cell lines as models for metastatic breast cancer through integrative analysis of genomic data," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-10148-6
    DOI: 10.1038/s41467-019-10148-6
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    Cited by:

    1. G. Gambardella & G. Viscido & B. Tumaini & A. Isacchi & R. Bosotti & D. di Bernardo, 2022. "A single-cell analysis of breast cancer cell lines to study tumour heterogeneity and drug response," Nature Communications, Nature, vol. 13(1), pages 1-12, December.

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