Mutated genes and driver pathways involved in myelodysplastic syndromes—a transcriptome sequencing based approach. Academic Article uri icon

Overview

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

  • August 1, 2015

Research

keywords

  • Leukemia, Myeloid, Acute
  • Myelodysplastic Syndromes
  • Neoplasm Proteins
  • Transcriptome

Identity

Scopus Document Identifier

  • 84951916774

Digital Object Identifier (DOI)

  • 10.1039/c4mb00663a

PubMed ID

  • 26010722

Additional Document Info

volume

  • 11

issue

  • 8