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

Overview of attention for article published in BMC Cancer, May 2018
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Title
A computational study of hedgehog signalling involved in basal cell carcinoma reveals the potential and limitation of combination therapy
Published in
BMC Cancer, May 2018
DOI 10.1186/s12885-018-4451-1
Pubmed ID
Authors

Antoine Buetti-Dinh, Rebecca Jensen, Ran Friedman

Abstract

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. 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. 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. 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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 15%
Researcher 4 15%
Student > Bachelor 2 8%
Other 2 8%
Student > Doctoral Student 1 4%
Other 4 15%
Unknown 9 35%
Readers by discipline Count As %
Medicine and Dentistry 6 23%
Biochemistry, Genetics and Molecular Biology 5 19%
Unspecified 1 4%
Social Sciences 1 4%
Computer Science 1 4%
Other 0 0%
Unknown 12 46%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 May 2018.
All research outputs
#20,497,162
of 23,061,402 outputs
Outputs from BMC Cancer
#6,541
of 8,374 outputs
Outputs of similar age
#289,009
of 329,133 outputs
Outputs of similar age from BMC Cancer
#156
of 192 outputs
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