Dataset Information

A high-throughput drug screen reveals means to differentiate triple-negative breast cancer.

ABSTRACT: Plasticity delineates cancer subtypes with more or less favourable outcomes. In breast cancer, the subtype triple-negative lacks expression of major differentiation markers, e.g., estrogen receptor α (ERα), and its high cellular plasticity results in greater aggressiveness and poorer prognosis than other subtypes. Whether plasticity itself represents a potential vulnerability of cancer cells is not clear. However, we show here that cancer cell plasticity can be exploited to differentiate triple-negative breast cancer (TNBC). Using a high-throughput imaging-based reporter drug screen with 9 501 compounds, we have identified three polo-like kinase 1 (PLK1) inhibitors as major inducers of ERα protein expression and downstream activity in TNBC cells. PLK1 inhibition upregulates a cell differentiation program characterized by increased DNA damage, mitotic arrest, and ultimately cell death. Furthermore, cells surviving PLK1 inhibition have decreased tumorigenic potential, and targeting PLK1 in already established tumours reduces tumour growth both in cell line- and patient-derived xenograft models. In addition, the upregulation of genes upon PLK1 inhibition correlates with their expression in normal breast tissue and with better overall survival in breast cancer patients. Our results indicate that differentiation therapy based on PLK1 inhibition is a potential alternative strategy to treat TNBC.

SUBMITTER: Vulin M

PROVIDER: S-EPMC9507968 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Publications

A high-throughput drug screen reveals means to differentiate triple-negative breast cancer.

Vulin Milica M Jehanno Charly C Sethi Atul A Correia Ana Luísa AL Obradović Milan M S MMS Couto Joana Pinto JP Coissieux Marie-May MM Diepenbruck Maren M Preca Bogdan-Tiberius BT Volkmann Katrin K der Maur Priska Auf PA Schmidt Alexander A Münst Simone S Sauteur Loïc L Kloc Michal M Palafox Marta M Britschgi Adrian A Unterreiner Vincent V Galuba Olaf O Claerr Isabelle I Lopez-Romero Sandra S Galli Giorgio G GG Baeschlin Daniel D Okamoto Ryoko R Soysal Savas D SD Mechera Robert R Weber Walter P WP Radimerski Thomas T Bentires-Alj Mohamed M

Oncogene 20220825 39

Plasticity delineates cancer subtypes with more or less favourable outcomes. In breast cancer, the subtype triple-negative lacks expression of major differentiation markers, e.g., estrogen receptor α (ERα), and its high cellular plasticity results in greater aggressiveness and poorer prognosis than other subtypes. Whether plasticity itself represents a potential vulnerability of cancer cells is not clear. However, we show here that cancer cell plasticity can be exploited to differentiate triple- ...[more]

PMID: 36008466

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Project description:While high-throughput drug screening offers possibilities to profile phenotypic responses of hundreds of compounds, elucidation of the cell context-specific mechanisms of drug action requires additional analyses. To that end, we developed a computational target deconvolution pipeline that identifies the key target dependencies based on collective drug response patterns in each cell line separately. The pipeline combines quantitative drug-cell line responses with drug-target interaction networks among both intended on- and potent off-targets to identify pharmaceutically actionable and selective therapeutic targets. To demonstrate its performance, the target deconvolution pipeline was applied to 310 small molecules tested on 20 genetically and phenotypically heterogeneous triple-negative breast cancer (TNBC) cell lines to identify cell line-specific target mechanisms in terms of cytotoxic and cytostatic drug target vulnerabilities. The functional essentiality of each protein target was quantified with a target addiction score (TAS), as a measure of dependency of the cell line on the therapeutic target. The target dependency profiling was shown to capture inhibitory information that is complementary to that obtained from the structure or sensitivity of the drugs. Comparison of the TAS profiles and gene essentiality scores from CRISPR-Cas9 knockout screens revealed that certain proteins with low gene essentiality showed high target addictions, suggesting that they might be functioning as protein groups, and therefore be resistant to single gene knock-out. The comparative analysis discovered protein groups of potential multi-target synthetic lethal interactions, for instance, among histone deacetylases (HDACs). Our integrated approach also recovered a number of well-established TNBC cell line-specific drivers and known TNBC therapeutic targets, such as HDACs and cyclin-dependent kinases (CDKs). The present work provides novel insights into druggable vulnerabilities for TNBC, and opportunities to identify multi-target synthetic lethal interactions for further studies.

Dataset Information

A high-throughput drug screen reveals means to differentiate triple-negative breast cancer.

Publications

A high-throughput drug screen reveals means to differentiate triple-negative breast cancer.

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