Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 Apr 30;15(4):e0231953.
doi: 10.1371/journal.pone.0231953. eCollection 2020.

Identification of triple-negative breast cancer cell lines classified under the same molecular subtype using different molecular characterization techniques: Implications for translational research

Jose Rodrigo Espinosa Fernandez  1 , Bedrich L Eckhardt  1 , Jangsoon Lee  1 , Bora Lim  1 , Troy Pearson  1 , Rob S Seitz  2 , David R Hout  2 , Brock L Schweitzer  2 , Tyler J Nielsen  2 , O Rayne Lawrence  2 , Ying Wang  3 , Arvind Rao  3 , Naoto T Ueno  1
Affiliations

Identification of triple-negative breast cancer cell lines classified under the same molecular subtype using different molecular characterization techniques: Implications for translational research

Jose Rodrigo Espinosa Fernandez et al. PLoS One. .

Abstract

The original algorithm that classified triple-negative breast cancer (TNBC) into six subtypes has recently been revised. The revised algorithm (TNBCtype-IM) classifies TNBC into five subtypes and a modifier based on immunological (IM) signatures. The molecular signature may differ between cancer cells in vitro and their respective tumor xenografts. We identified cell lines with concordant molecular subtypes regardless of classification algorithm or analysis of cells in vitro or in vivo, to establish a panel of clinically relevant molecularly stable TNBC models for translational research. Gene expression data were used to classify TNBC cell lines using the original and the revised algorithms. Tumor xenografts were established from 17 cell lines and subjected to gene expression profiling with the original 2188-gene algorithm TNBCtype and the revised 101-gene algorithm TNBCtype-IM. A total of six cell lines (SUM149PT (BL2), HCC1806 (BL2), SUM149PT (BL2), BT549 (M), MDA-MB-453 (LAR), and HCC2157 (BL1)) maintained their subtype classification between in vitro and tumor xenograft analyses across both algorithms. For TNBC molecular classification-guided translational research, we recommend using these TNBC cell lines with stable molecular subtypes.

PubMed Disclaimer

Conflict of interest statement

The authors of this paper have read the journal’s policy and the authors of this paper have the following competing interests: NTU has contracted research with Insight Genetics Inc. (http://www.insightgenetics.com/). RSS, DRH, BLS, TJN, ORL are all paid employees of Insight Genetics, Inc. This does not alter our adherence to PLOS ONE policies on sharing data and materials. The authors would like to declare the following patents/patent applications associated with this research: Insight Genetics Inc. has taken an exclusive license to a patent application for the analysis method to categorize TNBCType patients into various subtypes. The patent application is as follows: [US14/358,330]. Gene expression datasets can be uploaded for classification by TNBCType at http://cbc.mc.vanderbilt.edu/tnbc/. TNBCType-IM is a proprietary algorithm of Insight Genetics Inc.

References

    1. Masuda H, Baggerly KA, Wang Y, Zhang Y, Gonzalez-Angulo AM, Meric-Bernstam F, et al. Differential response to neoadjuvant chemotherapy among 7 triple-negative breast cancer molecular subtypes. Clin Cancer Res. 2013;19:5533–40.9. 10.1158/1078-0432.CCR-13-0799 - DOI - PMC - PubMed
    1. Lehmann BD, Bauer JA, Chen X, Sanders ME, Chakravarthy AB, Shyr Y, et al. Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Invest. 2011;121(7):2750–67. 10.1172/JCI45014 - DOI - PMC - PubMed
    1. Lehmann BD, Jovanovic B, Chen X, Estrada MV, Johnson KN, Shyr Y, et al. Refinement of Triple-Negative Breast Cancer Molecular Subtypes: Implications for Neoadjuvant Chemotherapy Selection. PLoS One. 2016;11:e0157368 10.1371/journal.pone.0157368 - DOI - PMC - PubMed
    1. Ring BZ, Hout DR, Morris SW, Lawrence K, Schweitzer BL, Bailey DB, et al. Generation of an algorithm based on minimal gene sets to clinically subtype triple negative breast cancer patients. BMC Cancer. 2016;16:143 10.1186/s12885-016-2198-0 - DOI - PMC - PubMed
    1. Bhatti S, Heldstab J, Lehn C, Tawfik O, Ash RM, Hout DR, et al. Clinical Activity of Pembrolizumab in a Patient With Metastatic Triple-Negative Breast Cancer Without Tumor Programmed Death-Ligand 1 Expression: A Case Report and Correlative Biomarker Analysis. JCO Precision Oncology. 2017:1–6. - PubMed

Publication types