Oncotarget

Research Papers:

Targeted drug combination therapy design based on driver genes

Lilian Zsákai _, Anna Sipos, Judit Dobos, Dániel Erős, Csaba Szántai-Kis, Péter Bánhegyi, János Pató, László Őrfi, Zsolt Matula, Gábor Mikala, György Kéri, István Peták and István Vályi-Nagy

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Oncotarget. 2019; 10:5255-5266. https://doi.org/10.18632/oncotarget.26985

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Abstract

Lilian Zsákai1,3,*, Anna Sipos1,4,*, Judit Dobos1, Dániel Erős1, Csaba Szántai-Kis1, Péter Bánhegyi1, János Pató1, László Őrfi1,2, Zsolt Matula3, Gábor Mikala3, György Kéri1,6,#, István Peták4,5 and István Vályi-Nagy3

1 Vichem Chemie Research Ltd., Budapest, Hungary

2 Department of Pharmaceutical Chemistry, Semmelweis University, Budapest, Hungary

3 Department of Hematology and Stem Cell Transplantation, Central Hospital of Southern Pest National Institute of Hematology and Infectious Diseases, Budapest, Hungary

4 Oncompass Medicine Hungary Ltd., Budapest, Hungary

5 Department of Pharmacology, Semmelweis University, Budapest, Hungary

6 MTA-SE Patho-Biochemistry Research Group, Department of Medical Chemistry, Semmelweis University, Budapest, Hungary

# Author deceased

* These authors contributed equally to this work

Correspondence to:

Lilian Zsákai,email: lilianzsakai@gmail.com,
zsakai.lilian@eszszk.hu

Keywords: combination therapy; cancer driver gene; primary culture; small molecule compound; multiple myeloma

Received: October 06, 2017     Accepted: June 25, 2018     Published: September 03, 2019

ABSTRACT

Targeted therapies against cancer types with more than one driver gene hold bright but elusive promise, since approved drugs are not available for all driver mutations and monotherapies often result in resistance. Targeting multiple driver genes in different pathways at the same time may provide an impact extensive enough to fight resistance. Our goal was to find synergistic drug combinations based on the availability of targeted drugs and their biological activity profiles and created an associated compound library based on driver gene-related protein targets. In this study, we would like to show that driver gene pattern based customized combination therapies are more effective than monotherapies on six cell lines and patient-derived primary cell cultures.

We tested 55–102 drug combinations targeting driver genes and driver pathways for each cell line and found 25–85% of these combinations highly synergistic. Blocking 2–5 cancer pathways using only 2–3 targeted drugs was sufficient to reach high rates of tumor cell eradication at remarkably low concentrations.

Our results demonstrate that the efficiency of cancer treatment may be significantly improved by combining drugs against multiple tumor specific drivers.


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