TY - JOUR
T1 - Identification of triple-negative breast cancer cell lines classified under the same molecular subtype using different molecular characterization techniques
T2 - Implications for translational research
AU - Espinosa Fernandez, Jose Rodrigo
AU - Eckhardt, Bedrich L.
AU - Lee, Jangsoon
AU - Lim, Bora
AU - Pearson, Troy
AU - Seitz, Rob S.
AU - Hout, David R.
AU - Schweitzer, Brock L.
AU - Nielsen, Tyler J.
AU - Rayne Lawrence, O.
AU - Wang, Ying
AU - Rao, Arvind
AU - Ueno, Naoto T.
N1 - Funding Information:
This study was supported by: This study was supported by the Morgan Welch Inflammatory Breast Cancer Research Program, a State of Texas Rare and Aggressive Breast Cancer Research Program grant (N.T. Ueno), and MD Anderson?s Cancer Center Support Grant (P30CA016672, used the Animal Core Facility). Insight Genetics Inc. provided support for this study in the form of salaries for RSS, DRH, BLS, TJN, ORL. The specific roles of these authors are articulated in the ?author contributions? section. All funders in this study provided support in the form of research materials, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Publisher Copyright:
© 2020 Espinosa Fernandez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2020/4/1
Y1 - 2020/4/1
N2 - 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.
AB - 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.
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U2 - 10.1371/journal.pone.0231953
DO - 10.1371/journal.pone.0231953
M3 - Article
C2 - 32353087
AN - SCOPUS:85084901989
SN - 1932-6203
VL - 15
JO - PloS one
JF - PloS one
IS - 4
M1 - e0231953
ER -