Distinct transcriptomic and exomic abnormalities within myelodysplastic syndrome marrow cells

Abstract

To provide biologic insights into mechanisms underlying myelodysplastic syndromes (MDS) we evaluated the CD34⁺ marrow cells transcriptome using high-throughput RNA sequencing (RNA-Seq). We demonstrated significant differential gene expression profiles (GEPs) between MDS and normal and identified 41 disease classifier genes. Additionally, two main clusters of GEPs distinguished patients based on their major clinical features, particularly between those whose disease remained stable versus patients who transformed into acute myeloid leukemia within 12 months. The genes whose expression was associated with disease outcome were involved in functional pathways and biologic processes highly relevant for MDS. Combined with exomic analysis we identified differential isoform usage of genes in MDS mutational subgroups, with consequent dysregulation of distinct biologic functions. This combination of clinical, transcriptomic and exomic findings provides valuable understanding of mechanisms underlying MDS and its progression to a more aggressive stage and also facilitates prognostic characterization of MDS patients.

Keywords:

• Myeloid leukemias and dysplasias
• myeloproliferative disorders
• trancriptomics
• isoform usage

Acknowledgements

An earlier version of the study data was presented at the 56th annual meeting of the American Society of Hematology (San Francisco, CA; 6–9 December 2014), abstract #1894, Blood 2014;124(21):1894. After completion of our manuscript, a multi-center study that also describes the impact of altered gene expression in MDS using RNA-Seq technology has been reported online [52].

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Potential conflict of interest

Disclosure forms provided by the authors are available with the full text of this article online at https://doi.org/10.1080/10428194.2018.1452210.

Additional information

Funding

This work was supported by the Stanford MDS Center Research Fund, the William E. Walsh Leukemia Research Fund, the Eugene, Elizabeth and Christine Cronkite Hematology Fund and the Leukemia and Lymphoma Society MDS SCOR grant 38363. This work used the Genome Sequencing Service Center by Stanford Center for Genomics and Personalized Medicine Sequencing Center, supported by the grant award NIH S10OD02014. G.I.M. is supported by the National Human Genome Research Institute of the National Institutes of Health under Award Number R00 HG007065.