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Cited by 429

The DOI matches its Crossref record; 65 of the 65 references it cites were found in a registry or an index.

The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer

Open access
Wander, Seth A., Cohen, Ofir, Gong, Xueqian, Johnson, Gabriela N., Buendia-Buendia, Jorge E., Lloyd, Maxwell R., Kim, Dewey, Luo, Flora, Mao, Pingping, Helvie, Karla, Kowalski, Kailey J., Nayar, Utthara, Waks, Adrienne G., Parsons, Stephen H., Martinez, Ricardo, Litchfield, Lacey M., Ye, Xiang S., Yu, Chunping, Jansen, Valerie M., Stille, John R., Smith, Patricia S., Oakley, Gerard J., Chu, Quincy S., Batist, Gerald, Hughes, Melissa E., Kremer, Jill D., Garraway, Levi A., Winer, Eric P., Tolaney, Sara M., Lin, Nancy U., Buchanan, Sean G., Wagle, Nikhil·2020·Cancer Discovery
DOI 10.1158/2159-8290.cd-19-1390
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Abstract

Mechanisms driving resistance to cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) in hormone receptor–positive (HR+) breast cancer have not been clearly defined. Whole-exome sequencing of 59 tumors with CDK4/6i exposure revealed multiple candidate resistance mechanisms including RB1 loss, activating alterations in AKT1, RAS, AURKA, CCNE2, ERBB2, and FGFR2, and loss of estrogen receptor expression. In vitro experiments confirmed that these alterations conferred CDK4/6i resistance. Cancer cells cultured to resistance with CDK4/6i also acquired RB1, KRAS, AURKA, or CCNE2 alterations, which conferred sensitivity to AURKA, ERK, or CHEK1 inhibition. Three of these activating alterations—in AKT1, RAS, and AURKA—have not, to our knowledge, been previously demonstrated as mechanisms of resistance to CDK4/6i in breast cancer preclinically or in patient samples. Together, these eight mechanisms were present in 66% of resistant tumors profiled and may define therapeutic opportunities in patients. Significance: We identified eight distinct mechanisms of resistance to CDK4/6i present in 66% of resistant tumors profiled. Most of these have a therapeutic strategy to overcome or prevent resistance in these tumors. Taken together, these findings have critical implications related to the potential utility of precision-based approaches to overcome resistance in many patients with HR+ metastatic breast cancer. This article is highlighted in the In This Issue feature, p. 1079

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Metadata

Authors
Wander, S. A., Cohen, O., Gong, X., Johnson, G. N., Buendia-Buendia, J. E., Lloyd, M. R., Kim, D., Luo, F., Mao, P., Helvie, K., Kowalski, K. J., Nayar, U., Waks, A. G., Parsons, S. H., Martinez, R., Litchfield, L. M., Ye, X. S., Yu, C., Jansen, V. M., Stille, J. R., Smith, P. S., Oakley, G. J., Chu, Q. S., Batist, G., Hughes, M. E., Kremer, J. D., Garraway, L. A., Winer, E. P., Tolaney, S. M., Lin, N. U., Buchanan, S. G., & Wagle, N.
Venue
Cancer Discovery
Publisher
American Association for Cancer Research (AACR)
Published
2020-08-01
Volume
10
Issue
8
Pages
1174-1193
ISSN
  • 2159-8274 (ISSN-L)
  • 2159-8290
DOI
10.1158/2159-8290.cd-19-1390
OpenAlex
W3024684302
Cited by
429
References
65
FWCI
25.49
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer. https://app.cochat.ai/papers/10.1158/2159-8290.cd-19-1390
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Wander, S. A., Cohen, O., Gong, X., Johnson, G. N., Buendia-Buendia, J. E., Lloyd, M. R., Kim, D., Luo, F., Mao, P., Helvie, K., Kowalski, K. J., Nayar, U., Waks, A. G., Parsons, S. H., Martinez, R., Litchfield, L. M., Ye, X. S., Yu, C., Jansen, V. M., . . . Wagle, N. (2020). The Genomic Landscape of Intrinsic and Acquired Resistance to Cyclin-Dependent Kinase 4/6 Inhibitors in Patients with Hormone Receptor–Positive Metastatic Breast Cancer. Cancer Discovery. https://doi.org/10.1158/2159-8290.cd-19-1390

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.