A computational study of hedgehog signalling involved in basal cell carcinoma reveals the potential and limitation of combination therapy

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Abstract

Background

The smoothened (SMO) receptor is an essential component of the Sonic hedgehog (SHH) signalling, which is associated with the development of skin basal cell carcinoma (BCC). SMO inhibitors are indicated for BCC patients when surgical treatment or radiation therapy are not possible. Unfortunately, SMO inhibitors are not always well tolerated due to severe side effects, and their therapeutical success is limited by resistance mutations.

Methods

We investigated how common are resistance-causing mutations in two genomic databases which are not linked to BCC or other cancers, namely 1000 Genomes and ExAC. To examine the potential for combination therapy or other treatments, we further performed knowledge-based simulations of SHH signalling, in the presence or absence of SMO and PI3K/Akt inhibitors.

Results

The database analysis revealed that of 18 known mutations associated with Vismodegib-resistance, three were identified in the databases. Treatment of individuals carrying such mutations is thus liable to fail a priori. Analysis of the simulations suggested that a combined inhibition of SMO and the PI3K/Akt signalling pathway may provide an effective reduction in tumour proliferation. However, the inhibition dosage of SMO and PI3K/Akt depended on the activity of phosphodiesterases (PDEs). Under high PDEs activities, SMO became the most important control node of the network. By applying PDEs inhibition, the control potential of SMO decreased and PI3K appeared as a significant factor in controlling tumour proliferation.

Conclusions

Our systems biology approach employs knowledge-based computer simulations to help interpret the large amount of data available in public databases, and provides application-oriented solutions for improved cancer resistance treatments.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4451-1) contains supplementary material, which is available to authorized users.

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Most cited references 27

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Author and article information

Contributors

Antoine Buetti-Dinh:

ORCID: http://orcid.org/0000-0002-6469-0296

antoine.buetti@lnu.se

Rebecca Jensen: beccjens@gmail.com

Ran Friedman: ran.friedman@lnu.se

Journal

Journal ID (nlm-ta): BMC Cancer

Journal ID (iso-abbrev): BMC Cancer

Title: BMC Cancer

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2407

Publication date (Electronic): 18 May 2018

Publication date PMC-release: 18 May 2018

Publication date Collection: 2018

Volume: 18

Electronic Location Identifier: 569

Affiliations

[1 ]ISNI 0000 0001 2174 3522, GRID grid.8148.5, Department of Chemistry and Biomedical Sciences, , Linnæus University, ; Norra vägen 49, Kalmar, SE-391 82 Sweden

[2 ]ISNI 0000 0001 2174 3522, GRID grid.8148.5, Linnæus University Centre for Biomaterials Chemistry, Linnæus University, ; Norra vägen 49, Kalmar, SE-391 82 Sweden

[3 ]ISNI 0000 0001 2174 3522, GRID grid.8148.5, Centre for Ecology and Evolution in Microbial Model Systems, , Linnæus University, ; Landgången 3, Kalmar, SE-391 82 Sweden

[4 ]ISNI 0000 0001 2203 2861, GRID grid.29078.34, Institute of Computational Science, Faculty of Informatics, Università della Svizzera Italiana, ; Via Giuseppe Buffi 13, Lugano, CH-6900 Switzerland

[5 ]ISNI 0000 0001 2223 3006, GRID grid.419765.8, Swiss Institute of Bioinformatics, ; Quartier Sorge – Batiment Genopode, Lausanne, CH-1015 Switzerland

Author information

Antoine Buetti-Dinh http://orcid.org/0000-0002-6469-0296

Article

Publisher ID: 4451

DOI: 10.1186/s12885-018-4451-1

PMC ID: 5960207

PubMed ID: 29776351

SO-VID: 9b4cefe0-439a-4b89-a2d2-c51117a168d6

License:

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 5 February 2018

Date accepted : 30 April 2018

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100002794, Cancerfonden;

Award ID: CAN 2015/387

Custom metadata

ScienceOpen disciplines: Oncology & Radiotherapy

Keywords: basal cell carcinoma,drug resistance,knowledge-based analysis,vismodegib,sonidegib,erivedge,odozmo

Data availability:

ScienceOpen disciplines: Oncology & Radiotherapy

Keywords: basal cell carcinoma, drug resistance, knowledge-based analysis, vismodegib, sonidegib, erivedge, odozmo

A computational study of hedgehog signalling involved in basal cell carcinoma reveals the potential and limitation of combination therapy

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Abstract

Background

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Results

Conclusions

Electronic supplementary material

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Karger: Dermatology

Most cited references 27

G-protein-coupled receptors and cancer.

Wnt signaling in disease and in development.

Advances in targeting cyclic nucleotide phosphodiesterases.

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