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Multiomics of HER2-low triple-negative breast cancer identifies a receptor tyrosine kinase–relevant subgroup with therapeutic prospects
Lie Chen, Cui-Cui Liu, Si-Yuan Zhu, Jing-Yu Ge, Yu-Fei Chen, Ding Ma, Zhi-Ming Shao, Ke-Da Yu
Lie Chen, Cui-Cui Liu, Si-Yuan Zhu, Jing-Yu Ge, Yu-Fei Chen, Ding Ma, Zhi-Ming Shao, Ke-Da Yu
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Research Article Oncology

Multiomics of HER2-low triple-negative breast cancer identifies a receptor tyrosine kinase–relevant subgroup with therapeutic prospects

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Abstract

To provide complementary information and reveal the molecular characteristics and therapeutic insights of HER2-low breast cancer, we performed this multiomics study of hormone receptor–negative (HR–) and HER2-low breast cancer, also known as HER2-low triple-negative breast cancer (TNBC), and identified 3 subgroups: basal-like, receptor tyrosine kinase–relevant (TKR), and mesenchymal stem–like. These 3 subgroups had distinct features and potential therapeutic targets and were validated in external data sets. Interestingly, the TKR subgroup (which exists in both HR+ and HR– breast cancer) had activated HER2 and downstream MAPK signaling. In vitro and in vivo patient-derived xenograft experiments revealed that pretreatment of the TKR subgroup with a tyrosine kinase inhibitor (lapatinib or tucatinib) could inhibit HER2 signaling and induce accumulated expression of nonfunctional HER2, resulting in increased sensitivity to the sequential HER2-targeting, Ab–drug conjugate DS-8201. Our findings identify clinically relevant subgroups and provide potential therapeutic strategies for HER2-low TNBC subtypes.

Authors

Lie Chen, Cui-Cui Liu, Si-Yuan Zhu, Jing-Yu Ge, Yu-Fei Chen, Ding Ma, Zhi-Ming Shao, Ke-Da Yu

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Figure 2

HER2-low TNBC subgroups based on multiomics data have distinct features.

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HER2-low TNBC subgroups based on multiomics data have distinct features....
(A) Specific oncogenes and tumor suppressor genes (TSGs) with top-rank GISTIC peaks. (B) The top 30 genes with the most frequent mutations (at least 3% of the cases; left) and total mutation numbers among the BSL, TKR, and MSL subgroups (right; Kruskal-Wallis test). (C) Radar chart illustrating the proportion of copy number gain (left) and loss (right) of specific oncogenes and TSGs. (D) Genes with the most frequent mutations (at least 3% of the cases). (E) Total mutation numbers between BSL and other groups (Mann-Whitney test). (F) Copy number–based clustering on the basis of GISTIC peaks is shown in the heatmap. (G) Relationships between mRNA subgroups and CNA subtypes (left) and mRNA subgroups and mutation subtypes (right). The samples for the data reported in A, B, F, and G were from FUSCC data set; those for C–E were from TCGA data set. Statistical significance was set at P < 0.05. *P < 0.05, **P < 0.01, ***P < 0.001. CIN, low chromosomal instability; Del, deletion; Ins, insertion; Multi, multiple; Val, value.

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ISSN 2379-3708

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