Abstract
Background: Breast cancer (BC) is a heterogeneous disease for which the commonly used chemotherapeutic agents primarily include the anthracyclines (doxorubicin, epirubicin), microtubule inhibitors (paclitaxel, docetaxel, eribulin), and alkylating agents (cyclophosphamide). While these drugs can be highly effective, metastatic tumours are frequently refractory to treatment or become resistant upon tumour relapse. Methods: We undertook a cell polarity/epithelial mesenchymal plasticity (EMP)-enriched short hairpin RNA (shRNA) screen in MDA-MB-468 breast cancer cells to identify factors underpinning heterogeneous responses to three chemotherapeutic agents used clinically in breast cancer: Doxorubicin, docetaxel, and eribulin. shRNA-transduced cells were treated for 6 weeks with the EC10 of each drug, and shRNA representation assessed by deep sequencing. We first identified candidate genes with depleted shRNA, implying that their silencing could promote a response. Using the Broad Institute’s Connectivity Map (CMap), we identified partner inhibitors targeting the identified gene families that may induce cell death in combination with doxorubicin, and tested them with all three drug treatments. Results: In total, 259 shRNAs were depleted with doxorubicin treatment (at p < 0.01), 66 with docetaxel, and 25 with eribulin. Twenty-four depleted hairpins overlapped between doxorubicin and docetaxel, and shRNAs for TGFB2, RUNX1, CCDC80, and HYOU1 were depleted across all the three drug treatments. Inhibitors of MDM/TP53, TGFBR, and FGFR were identified by CMap as the top pharmaceutical perturbagens and we validated the combinatorial benefits of the TGFBR inhibitor (SB525334) and MDM inhibitor (RITA) with doxorubicin treatment, and also observed synergy between the inhibitor SB525334 and eribulin in MDA-MB-468 cells. Conclusions: Taken together, a cell polarity/EMP-enriched shRNA library screen identified relevant gene products that could be targeted alongside current chemotherapeutic agents for the treatment of invasive BC.
| Original language | English |
|---|---|
| Article number | 1123 |
| Journal | Cancers |
| Volume | 12 |
| Issue number | 5 |
| DOIs | |
| State | Published - 30 Apr 2020 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
Funding
Acknowledgments: This work E.W.T. and I.H. were supported in part by US-DOD IDEA grant BC 084667 and a National Breast Cancer Foundation National Collaborative Research Program grant (CG-10-04) to E.W.T. The Translational Research Institute (TRI) receives support from the Australian Government. We would like to thank the core facility teams based at TRI for their technical assistance and Aleksandra Rajapakse for the validation of an experimental assay. The Victorian Centre for Functional Genomics (K.J.S.) is funded by the Australian Cancer Research Foundation (ACRF), the Australian Phenomics Network (APN) through funding from the Australian Government’s National Collaborative Research Infrastructure Strategy (NCRIS) program, the Peter MacCallum Cancer Centre Foundation and the University of Melbourne Research Collaborative Infrastructure Program. During the course of the study, S.B. was supported by a QUTPRA scholarship. This work E.W.T. and I.H. were supported in part by US-DOD IDEA grant BC 084667 and a National Breast Cancer Foundation National Collaborative Research Program grant (CG-10-04) to E.W.T. The Translational Research Institute (TRI) receives support from the Australian Government. We would like to thank the core facility teams based at TRI for their technical assistance and Aleksandra Rajapakse for the validation of an experimental assay. The Victorian Centre for Functional Genomics (K.J.S.) is funded by the Australian Cancer Research Foundation (ACRF), the Australian Phenomics Network (APN) through funding from the Australian Government?s National Collaborative Research Infrastructure Strategy (NCRIS) program, the Peter MacCallum Cancer Centre Foundation and the University of Melbourne Research Collaborative Infrastructure Program. During the course of the study, S.B. was supported by a QUTPRA scholarship.
| Funders | Funder number |
|---|---|
| Australian Government | |
| Australian Phenomics Network | |
| Peter MacCallum Cancer Centre Foundation | |
| US-DOD IDEA | BC 084667 |
| Australian Government | |
| Australian Cancer Research Foundation | |
| National Breast Cancer Foundation | CG-10-04 |
| University of Melbourne | |
| Peter Maccallum Cancer Centre |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Chemotherapy resistance
- Combination chemotherapy
- Docetaxel
- Doxorubicin
- Eribulin
- FGFR
- MDM
- ShRNA library screening
- TGFBR
- TP53
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