Effects of ordered mutations on dynamics in signaling networks

Maulida Mazaya,Yung-Keun Kwon,Hung-Cuong Trinh

doi:10.1186/s12920-019-0651-z

Maulida Mazaya, Yung-Keun Kwon + Show 1 more

Open Access

https://doi.org/10.1186/s12920-019-0651-z

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Abstract

BackgroundMany previous clinical studies have found that accumulated sequential mutations are statistically related to tumorigenesis. However, they are limited in fully elucidating the significance of the ordered-mutation because they did not focus on the network dynamics. Therefore, there is a pressing need to investigate the dynamics characteristics induced by ordered-mutations.MethodsTo quantify the ordered-mutation-inducing dynamics, we defined the mutation-sensitivity and the order-specificity that represent if the network is sensitive against a double knockout mutation and if mutation-sensitivity is specific to the mutation order, respectively, using a Boolean network model.ResultsThrough intensive investigations, we found that a signaling network is more sensitive when a double-mutation occurs in the direction order inducing a longer path and a smaller number of paths than in the reverse order. In addition, feedback loops involving a gene pair decreased both the mutation-sensitivity and the order-specificity. Next, we investigated relationships of functionally important genes with ordered-mutation-inducing dynamics. The network is more sensitive to mutations subject to drug-targets, whereas it is less specific to the mutation order. Both the sensitivity and specificity are increased when different-drug-targeted genes are mutated. Further, we found that tumor suppressors can efficiently suppress the amplification of oncogenes when the former are mutated earlier than the latter.ConclusionTaken together, our results help to understand the importance of the order of mutations with respect to the dynamical effects in complex biological systems.

Highlights

Many previous clinical studies have found that accumulated sequential mutations are statistically related to tumorigenesis
Datasets In this work, we employed datasets of three molecular interaction networks, a human cancer signaling (HCS) network with 1192 genes and 3102 interactions constructed in previous studies [21, 22] to provide a map of human cancer signaling, another large-scale signaling network with 1659 genes and 7964 interactions constructed in previous study [23] which was derived from the Kyoto Encyclopedia of Genes and Genomes database [24] (KEGG) network, and a T-cell large granular lymphocyte survival signaling [16, 25, 26] (TGL) network with 61 genes and 193 interactions about the longterm survival of competent cytotoxic T lymphocytes in humans
Distributions of ordered-mutation-inducing dynamics To see how frequently the network dynamics are affected by ordered mutations, we examined the accumulative distributions of the mutation-sensitivity (δ) and order-specificity (Δ) values of examined gene pairs (Ω) in three signaling networks (Fig. 2) in the case of the largest time gap (i.e., T = 20 for HCS and KEGG, and T = 10 for TGL)

Summary

Introduction

Many previous clinical studies have found that accumulated sequential mutations are statistically related to tumorigenesis. They are limited in fully elucidating the significance of the ordered-mutation because they did not focus on the network dynamics. The accumulated mutations can cause tumorigenesis or cancer development [2, 3]. This process can be affected by the order of genes subject to mutations. It was observed in patients with Myeloproliferative Neoplasms that JAK2 mutation followed by TET2 mutation influenced the clinical features [3]. The mutation order influences the mutagen target size in tumor evolution [6] and results in complications in cancer biology [7]

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