Skip to main content
Top
Published in: BMC Cancer 1/2024

Open Access 01-12-2024 | mTOR-Inhibitors | Research

High-content analysis identified synergistic drug interactions between INK128, an mTOR inhibitor, and HDAC inhibitors in a non-small cell lung cancer cell line

Authors: Sijiao Wang, Juliano Oliveira-Silveira, Gang Fang, Jungseog Kang

Published in: BMC Cancer | Issue 1/2024

Login to get access

Abstract

Background

The development of drug resistance is a major cause of cancer therapy failures. To inhibit drug resistance, multiple drugs are often treated together as a combinatorial therapy. In particular, synergistic drug combinations, which kill cancer cells at a lower concentration, guarantee a better prognosis and fewer side effects in cancer patients. Many studies have sought out synergistic combinations by small-scale function-based targeted growth assays or large-scale nontargeted growth assays, but their discoveries are always challenging due to technical problems such as a large number of possible test combinations.

Methods

To address this issue, we carried out a medium-scale optical drug synergy screening in a non-small cell lung cancer cell line and further investigated individual drug interactions in combination drug responses by high-content image analysis. Optical high-content analysis of cellular responses has recently attracted much interest in the field of drug discovery, functional genomics, and toxicology. Here, we adopted a similar approach to study combinatorial drug responses.

Results

By examining all possible combinations of 12 drug compounds in 6 different drug classes, such as mTOR inhibitors, HDAC inhibitors, HSP90 inhibitors, MT inhibitors, DNA inhibitors, and proteasome inhibitors, we successfully identified synergism between INK128, an mTOR inhibitor, and HDAC inhibitors, which has also been reported elsewhere. Our high-content analysis further showed that HDAC inhibitors, HSP90 inhibitors, and proteasome inhibitors played a dominant role in combinatorial drug responses when they were mixed with MT inhibitors, DNA inhibitors, or mTOR inhibitors, suggesting that recessive drugs could be less prioritized as components of multidrug cocktails.

Conclusions

In conclusion, our optical drug screening platform efficiently identified synergistic drug combinations in a non-small cell lung cancer cell line, and our high-content analysis further revealed how individual drugs in the drug mix interact with each other to generate combinatorial drug response.
Appendix
Available only for authorised users
Literature
1.
2.
go back to reference Dagogo-Jack I, Shaw AT. Tumour heterogeneity and resistance to cancer therapies. Nat Rev Clin Oncol. 2018;15(2):81–94.CrossRefPubMed Dagogo-Jack I, Shaw AT. Tumour heterogeneity and resistance to cancer therapies. Nat Rev Clin Oncol. 2018;15(2):81–94.CrossRefPubMed
3.
go back to reference Al-Lazikani B, Banerji U, Workman P. Combinatorial drug therapy for cancer in the post-genomic era. Nat Biotechnol. 2012;30(7):679–92.CrossRefPubMed Al-Lazikani B, Banerji U, Workman P. Combinatorial drug therapy for cancer in the post-genomic era. Nat Biotechnol. 2012;30(7):679–92.CrossRefPubMed
4.
go back to reference Lopez JS, Banerji U. Combine and conquer: challenges for targeted therapy combinations in early phase trials. Nat Rev Clin Oncol. 2017;14(1):57–66.CrossRefPubMed Lopez JS, Banerji U. Combine and conquer: challenges for targeted therapy combinations in early phase trials. Nat Rev Clin Oncol. 2017;14(1):57–66.CrossRefPubMed
5.
go back to reference Duarte D, Vale N. Evaluation of synergism in drug combinations and reference models for future orientations in oncology. Curr Res Pharmacol Drug Discov. 2022;3:100110.PubMedCentralCrossRefPubMed Duarte D, Vale N. Evaluation of synergism in drug combinations and reference models for future orientations in oncology. Curr Res Pharmacol Drug Discov. 2022;3:100110.PubMedCentralCrossRefPubMed
6.
10.
go back to reference Flobak Å, et al. A high-throughput drug combination screen of targeted small molecule inhibitors in cancer cell lines. Scientific Data. 2019;6(1):237.PubMedCentralCrossRefPubMed Flobak Å, et al. A high-throughput drug combination screen of targeted small molecule inhibitors in cancer cell lines. Scientific Data. 2019;6(1):237.PubMedCentralCrossRefPubMed
12.
go back to reference Zinner RG, et al. Algorithmic guided screening of drug combinations of arbitrary size for activity against cancer cells. Mol Cancer Ther. 2009;8(3):521–32.CrossRefPubMed Zinner RG, et al. Algorithmic guided screening of drug combinations of arbitrary size for activity against cancer cells. Mol Cancer Ther. 2009;8(3):521–32.CrossRefPubMed
13.
go back to reference Yoon BJ. Enhanced stochastic optimization algorithm for finding effective multi-target therapeutics. BMC Bioinformatics. 2011;12 Suppl 1(Suppl 1):S18.CrossRefPubMed Yoon BJ. Enhanced stochastic optimization algorithm for finding effective multi-target therapeutics. BMC Bioinformatics. 2011;12 Suppl 1(Suppl 1):S18.CrossRefPubMed
14.
15.
18.
go back to reference Bray MA, et al. Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes. Nat Protoc. 2016;11(9):1757–74.PubMedCentralCrossRefPubMed Bray MA, et al. Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes. Nat Protoc. 2016;11(9):1757–74.PubMedCentralCrossRefPubMed
19.
go back to reference Boutros M, Heigwer F, Laufer C. Microscopy-Based High-Content Screening. Cell. 2015;163(6):1314–25.CrossRefPubMed Boutros M, Heigwer F, Laufer C. Microscopy-Based High-Content Screening. Cell. 2015;163(6):1314–25.CrossRefPubMed
20.
go back to reference Kang J, et al. Improving drug discovery with high-content phenotypic screens by systematic selection of reporter cell lines. Nat Biotechnol. 2016;34(1):70–7.CrossRefPubMed Kang J, et al. Improving drug discovery with high-content phenotypic screens by systematic selection of reporter cell lines. Nat Biotechnol. 2016;34(1):70–7.CrossRefPubMed
23.
go back to reference Caicedo JC, Singh S, Carpenter AE. Applications in image-based profiling of perturbations. Curr Opin Biotechnol. 2016;39:134–42.CrossRefPubMed Caicedo JC, Singh S, Carpenter AE. Applications in image-based profiling of perturbations. Curr Opin Biotechnol. 2016;39:134–42.CrossRefPubMed
24.
go back to reference Young DW, et al. Integrating high-content screening and ligand-target prediction to identify mechanism of action. Nat Chem Biol. 2008;4(1):59–68.CrossRefPubMed Young DW, et al. Integrating high-content screening and ligand-target prediction to identify mechanism of action. Nat Chem Biol. 2008;4(1):59–68.CrossRefPubMed
25.
go back to reference Futamura Y, et al. Morphobase, an encyclopedic cell morphology database, and its use for drug target identification. Chem Biol. 2012;19(12):1620–30.CrossRefPubMed Futamura Y, et al. Morphobase, an encyclopedic cell morphology database, and its use for drug target identification. Chem Biol. 2012;19(12):1620–30.CrossRefPubMed
26.
go back to reference Woehrmann MH, et al. Large-scale cytological profiling for functional analysis of bioactive compounds. Mol Biosyst. 2013;9(11):2604–17.CrossRefPubMed Woehrmann MH, et al. Large-scale cytological profiling for functional analysis of bioactive compounds. Mol Biosyst. 2013;9(11):2604–17.CrossRefPubMed
27.
go back to reference Schulze CJ, et al. “Function-first” lead discovery: mode of action profiling of natural product libraries using image-based screening. Chem Biol. 2013;20(2):285–95.PubMedCentralCrossRefPubMed Schulze CJ, et al. “Function-first” lead discovery: mode of action profiling of natural product libraries using image-based screening. Chem Biol. 2013;20(2):285–95.PubMedCentralCrossRefPubMed
30.
go back to reference Rohban MH. et al. Systematic morphological profiling of human gene and allele function via cell painting. Elife. 2017;6:e24060. Rohban MH. et al. Systematic morphological profiling of human gene and allele function via cell painting. Elife. 2017;6:e24060.
32.
go back to reference de Sousa VML, Carvalho L. Heterogeneity in lung cancer. Pathobiology. 2018;85(1–2):96–107.PubMed de Sousa VML, Carvalho L. Heterogeneity in lung cancer. Pathobiology. 2018;85(1–2):96–107.PubMed
35.
go back to reference Beagle BR, et al. mTOR kinase inhibitors synergize with histone deacetylase inhibitors to kill B-cell acute lymphoblastic leukemia cells. Oncotarget. 2015;6(4):2088–100.CrossRefPubMed Beagle BR, et al. mTOR kinase inhibitors synergize with histone deacetylase inhibitors to kill B-cell acute lymphoblastic leukemia cells. Oncotarget. 2015;6(4):2088–100.CrossRefPubMed
36.
37.
go back to reference Geva-Zatorsky N, et al. Protein dynamics in drug combinations: a linear superposition of individual-drug responses. Cell. 2010;140(5):643–51.CrossRefPubMed Geva-Zatorsky N, et al. Protein dynamics in drug combinations: a linear superposition of individual-drug responses. Cell. 2010;140(5):643–51.CrossRefPubMed
38.
go back to reference Pritchard JR, et al. Defining principles of combination drug mechanisms of action. Proc Natl Acad Sci U S A. 2013;110(2):E170–9.CrossRefPubMed Pritchard JR, et al. Defining principles of combination drug mechanisms of action. Proc Natl Acad Sci U S A. 2013;110(2):E170–9.CrossRefPubMed
39.
go back to reference Pearson K. On lines and planes of closest fit to systems of points in space. Phil Mag. 1901;2(7–12):559–72.CrossRef Pearson K. On lines and planes of closest fit to systems of points in space. Phil Mag. 1901;2(7–12):559–72.CrossRef
40.
go back to reference Stevens J. Applied multivariate statistical-analysis - Johnson, R, Wichern. D Interfaces. 1984;14(5):116–8. Stevens J. Applied multivariate statistical-analysis - Johnson, R, Wichern. D Interfaces. 1984;14(5):116–8.
41.
go back to reference Sugiyama M. Dimensionality reduction of multimodal labeled data by local fisher discriminant analysis. J Mach Learn Res. 2007;8:1027–61. Sugiyama M. Dimensionality reduction of multimodal labeled data by local fisher discriminant analysis. J Mach Learn Res. 2007;8:1027–61.
42.
go back to reference Palmer AC, Sorger PK. Combination cancer therapy can confer benefit via patient-to-patient variability without drug additivity or synergy. Cell. 2017;171(7):1678–1691.e13.PubMedCentralCrossRefPubMed Palmer AC, Sorger PK. Combination cancer therapy can confer benefit via patient-to-patient variability without drug additivity or synergy. Cell. 2017;171(7):1678–1691.e13.PubMedCentralCrossRefPubMed
43.
go back to reference Millson SH, Piper PW. Insights from yeast into whether the inhibition of heat shock transcription factor (Hsf1) by rapamycin can prevent the Hsf1 activation that results from treatment with an Hsp90 inhibitor. Oncotarget. 2014;5(13):5054–64.PubMedCentralCrossRefPubMed Millson SH, Piper PW. Insights from yeast into whether the inhibition of heat shock transcription factor (Hsf1) by rapamycin can prevent the Hsf1 activation that results from treatment with an Hsp90 inhibitor. Oncotarget. 2014;5(13):5054–64.PubMedCentralCrossRefPubMed
44.
go back to reference Giulino-Roth L, et al. Inhibition of Hsp90 Suppresses PI3K/AKT/mTOR signaling and has antitumor activity in Burkitt lymphoma. Mol Cancer Ther. 2017;16(9):1779–90.PubMedCentralCrossRefPubMed Giulino-Roth L, et al. Inhibition of Hsp90 Suppresses PI3K/AKT/mTOR signaling and has antitumor activity in Burkitt lymphoma. Mol Cancer Ther. 2017;16(9):1779–90.PubMedCentralCrossRefPubMed
45.
go back to reference Kim HJ, et al. Synergistic antitumor effects of combined treatment with HSP90 inhibitor and PI3K/mTOR dual inhibitor in Cisplatin-resistant human bladder cancer cells. Yonsei Med J. 2020;61(7):587–96.PubMedCentralCrossRefPubMed Kim HJ, et al. Synergistic antitumor effects of combined treatment with HSP90 inhibitor and PI3K/mTOR dual inhibitor in Cisplatin-resistant human bladder cancer cells. Yonsei Med J. 2020;61(7):587–96.PubMedCentralCrossRefPubMed
46.
go back to reference Chou TC, Talalay P. Quantitative analysis of dose-effect relationships: the combined effects of multiple drugs or enzyme inhibitors. Adv Enzyme Regul. 1984;22:27–55.CrossRefPubMed Chou TC, Talalay P. Quantitative analysis of dose-effect relationships: the combined effects of multiple drugs or enzyme inhibitors. Adv Enzyme Regul. 1984;22:27–55.CrossRefPubMed
Metadata
Title
High-content analysis identified synergistic drug interactions between INK128, an mTOR inhibitor, and HDAC inhibitors in a non-small cell lung cancer cell line
Authors
Sijiao Wang
Juliano Oliveira-Silveira
Gang Fang
Jungseog Kang
Publication date
01-12-2024
Publisher
BioMed Central
Published in
BMC Cancer / Issue 1/2024
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/s12885-024-12057-4

Other articles of this Issue 1/2024

BMC Cancer 1/2024 Go to the issue
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine