Mutated Genes And Driver Pathways Involved In Myelodysplastic Syndromes - A Transcriptome Sequencing Based Approach

Abstract

Myelodysplastic syndromes are a heterogeneous group of clonal disorders of hematopoietic progenitors and have potentiality to progress into acute myelogenous leukemia. Development of effective treatments has been impeded by limited insight into pathogenic pathways. In this study, we applied RNA-seq technology to study the transcriptome on 20 MDS patients and 5 age-matched controls, and developed a pipeline for analyzing this data. After analysis, we identified 38 mutated genes contributing to MDS pathogenesis. 37 out of 38 genes have not been reported previously, suggesting our pipeline is critical for identifying novel mutated genes in MDS. The most recurrent mutation happened in gene IFRD1, which involved 30% of patient samples. Biological relationships among these mutated genes were mined using Ingenuity Pathway Analysis, and the results demonstrated that top two networks with highest scores were highly associated with cancer and hematological diseases, indicating that the mutated genes identified by our method were highly relevant to MDS. We then integrated the pathways in KEGG database and the identified mutated genes using our novel rule-based mutated driver pathway scoring approach for detecting mutated driver pathways. The results indicated two mutated driver pathways are important for the pathogenesis of MDS: pathway in cancer and in regulation of actin cytoskeleton. The latter, which likely contributes to the hallmark morphologic dysplasia observed in MDS, has not been reported, to the best of our knowledge. These results provide us new insights into the pathogenesis of MDS, which, in turn, may lead to novel therapeutics for this disease.

Publication Date

5-14-2015

Publication Title

Molecular BioSystems

Volume

11

Issue

8

Number of Pages

2158-2166

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1039/c4mb00663a

Socpus ID

84951916774 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84951916774

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