HER2-positive breast-cancer cell lines are sensitive to KDM5 inhibition: definition of a gene-expression model for the selection of sensitive cases

Gabriela Paroni, Marco Bolis, Adriana Zanetti, Paolo Ubezio, Kristian Helin, Peter Staller, Lars Ole Gerlach, Maddalena Fratelli, Richard M. Neve, Mineko Terao, Enrico Garattini*

*Corresponding author for this work
10 Citations (Scopus)

Abstract

Targeting of histone methylation has therapeutic potential in oncology. Here, we provide proof-of-principle that pharmacological inhibition of KDM5 histone-demethylases is a new strategy for the personalized treatment of HER2+ breast cancer. The anti-proliferative effects of the prototype of a new class of selective KDM5-inhibitors (KDM5-inh1) are evaluated in 40 cell lines, recapitulating the heterogeneity of breast cancer. This analysis demonstrates that HER2+ cells are particularly sensitive to KDM5 inhibition. The results are confirmed in an appropriate in vivo model with a close structural analog (KDM5-inh1A). RNA-seq data obtained in HER2+BT-474 cells exposed to KDM5-Inh1 indicate that the compound alters expression of numerous genes downstream of the ERBB2 gene-product, HER2. In selected HER2-positive breast-cancer cells, we demonstrate synergistic interactions between KDM5-inh1 and HER2-targeting agents (trastuzumab and lapatinib). In addition, HER2+ cell lines with innate and acquired resistance to trastuzumab show sensitivity to KDM5-inh1. The levels of KDM5A/B/C proteins, which are selectively targeted by the agent, have no significant association with KDM5-inh1 responsiveness across our panel of breast-cancer cell lines, suggesting the existence of other determinants of sensitivity. Using RNA-seq data of the breast-cancer cell lines we generate a gene-expression model that is a robust predictor of KDM5-inh1 sensitivity. In a test set of breast cancers, this model predicts sensitivity to the compound in a large fraction of HER2+ tumors. In conclusion, KDM5 inhibition has potential in the treatment of HER2+ breast cancer and our gene-expression model can be developed into a diagnostic tool for the selection of patients.

Original languageEnglish
JournalOncogene
Volume38
Pages (from-to)2675–2689
ISSN0950-9232
DOIs
Publication statusPublished - 11 Apr 2019

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