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IDENTIFICATION OF ABERRANTLY SPLICED GENES AND DEREGULATED PATHWAYS/GENE ONTOLOGY THEMES IN MYELODYSPLASTIC SYNDROME PATIENTS WITH SPLICING FACTOR GENE MUTATIONS
Author(s):
Andrea Pellagatti
,
Andrea Pellagatti
Affiliations:
Nuffield Division of Clinical Laboratory Sciences, Radcliffe Department of Medicine,University of Oxford,Oxford,United Kingdom
Violetta Steeples
,
Violetta Steeples
Affiliations:
Nuffield Division of Clinical Laboratory Sciences, Radcliffe Department of Medicine,University of Oxford,Oxford,United Kingdom
Eshita Sharma
,
Eshita Sharma
Affiliations:
Wellcome Trust Centre for Human Genetics,University of Oxford,Oxford,United Kingdom
Emmanouela Repapi
,
Emmanouela Repapi
Affiliations:
The Computational Biology Research Group, Weatherall Institute of Molecular Medicine,University of Oxford,Oxford,United Kingdom
Aleksandar Radujkovic
,
Aleksandar Radujkovic
Affiliations:
Department of Internal Medicine V,University Hospital Heidelberg,Heidelberg,Germany
Patrick Horn
,
Patrick Horn
Affiliations:
Department of Internal Medicine V,University Hospital Heidelberg,Heidelberg,Germany
Richard N. Armstrong
,
Richard N. Armstrong
Affiliations:
Nuffield Division of Clinical Laboratory Sciences, Radcliffe Department of Medicine,University of Oxford,Oxford,United Kingdom
Hamid Dolatshad
,
Hamid Dolatshad
Affiliations:
Nuffield Division of Clinical Laboratory Sciences, Radcliffe Department of Medicine,University of Oxford,Oxford,United Kingdom
Swagata Roy
,
Swagata Roy
Affiliations:
Nuffield Division of Clinical Laboratory Sciences, Radcliffe Department of Medicine,University of Oxford,Oxford,United Kingdom
Helen Lockstone
,
Helen Lockstone
Affiliations:
Wellcome Trust Centre for Human Genetics,University of Oxford,Oxford,United Kingdom
Stephen Taylor
,
Stephen Taylor
Affiliations:
The Computational Biology Research Group, Weatherall Institute of Molecular Medicine,University of Oxford,Oxford,United Kingdom
Aristoteles Giagounidis
,
Aristoteles Giagounidis
Affiliations:
Clinic for Oncology, Hematology, and Palliative Medicine,Marien Hospital Düsseldorf,Düsseldorf,Germany
Paresh Vyas
,
Paresh Vyas
Affiliations:
Medical Research Council, Molecular Hematology Unit, Weatherall Institute of Molecular Medicine,University of Oxford,Oxford,United Kingdom
Anna Schuh
,
Anna Schuh
Affiliations:
Molecular Diagnostics Centre, and NIHR Biomedical Research Centre,Oxford University Hospitals NHS Foundation Trust,Oxford,United Kingdom
Angela Hamblin
,
Angela Hamblin
Affiliations:
Molecular Diagnostics Centre, and NIHR Biomedical Research Centre,Oxford University Hospitals NHS Foundation Trust,Oxford,United Kingdom
Elli Papaemmanuil
,
Elli Papaemmanuil
Affiliations:
Department of Epidemiology-Biostatistics, Center for Molecular Oncology,Memorial Sloan Kettering Cancer Center,New York,United States
Sally Killick
,
Sally Killick
Affiliations:
Department of Haematology,Royal Bournemouth Hospital,Bournemouth,United Kingdom
Luca Malcovati
,
Luca Malcovati
Affiliations:
Fondazione IRCCS Policlinico San Matteo,University of Pavia,Pavia,Italy
Anne-Claude Gavin
,
Anne-Claude Gavin
Affiliations:
Structural and Computational Biology Unit,European Molecular Biology Laboratory (EMBL),Heidelberg,Germany
Anthony D. Ho
,
Anthony D. Ho
Affiliations:
Department of Internal Medicine V,University Hospital Heidelberg,Heidelberg,Germany
Thomas Luft
,
Thomas Luft
Affiliations:
Department of Internal Medicine V,University Hospital Heidelberg,Heidelberg,Germany
Eva Hellström-Lindberg
,
Eva Hellström-Lindberg
Affiliations:
Center for Hematology and Regenerative Medicine,Karolinska University Hospital Huddinge,Stockholm,Sweden
Mario Cazzola
,
Mario Cazzola
Affiliations:
Fondazione IRCCS Policlinico San Matteo,University of Pavia,Pavia,Italy
Christopher W. J. Smith
,
Christopher W. J. Smith
Affiliations:
Department of Biochemistry, Downing Site,University of Cambridge,Cambridge,United Kingdom
Jacqueline Boultwood
Jacqueline Boultwood
Affiliations:
Nuffield Division of Clinical Laboratory Sciences, Radcliffe Department of Medicine,University of Oxford,Oxford,United Kingdom
(Abstract release date: 05/18/17) EHA Library. Pellagatti A. 06/23/17; 181409; S122
Dr. Andrea Pellagatti
Dr. Andrea Pellagatti
Contributions
PDF Abstract
Abstract

Abstract: S122

Type: Oral Presentation

Presentation during EHA22: On Friday, June 23, 2017 from 12:15 - 12:30

Location: Hall E

Background
The myelodysplastic syndromes (MDS) are disorders of the hematopoietic stem cell (HSC) and patients suffer from anemia and other cytopenias and show increasing bone marrow blasts over time. Mutations in spliceosomal genes (including SF3B1, SRSF2 and U2AF1) occur in >50% of MDS patients.

Aims
We aimed to identify the deregulated pathways and gene ontology (GO) categories associated with aberrantly spliced genes in CD34+ cells and in differentiated cells of MDS-affected lineages isolated from the bone marrow of MDS patients harboring spliceosome mutations.

Methods
Transcriptome data were generated using RNA sequencing (RNA-seq) and splicing factor mutant cases were compared to wildtype cases and to healthy controls. Aberrant (including cryptic) splicing events were identified using rMATS. Deregulated pathways and GO themes were identified using Ingenuity Pathway Analysis and GOseq.

Results

RNA-Seq was performed on CD34+ cells obtained from the bone marrow of 91 MDS patients (including 28, 8 and 6 cases with SF3B1, SRSF2 or U2AF1 mutations, respectively) and 8 healthy controls. The aberrant splicing events associated with each mutated splicing factor tended to affect different sets of genes, although some overlap was observed. GO analysis of the aberrantly spliced genes associated with SF3B1, SRSF2 or U2AF1 mutations showed a marked convergence of significantly enriched ontology themes: 26 of the top 30 most significant GO categories, including ‘RNA splicing’ and ‘translation’, in the comparison of mutant cases for each splicing factor gene to healthy controls (18 of 30 in the comparison to wildtype cases) were common to all three mutated splicing factor genes. Pathway analysis revealed deregulated pathways (e.g. ‘oxidative phosphorylation’ and ‘mitochondrial dysfunction’) that were common to more than one mutated gene (i.e. SF3B1 and SRSF2), and pathways specific for one mutated splicing factor gene (e.g. ‘protein ubiquitination’ in SF3B1 mutant cases). An analysis of upstream transcriptional regulators showed a significant overlap between the aberrantly spliced genes associated with each mutant splicing factor gene (in the comparison to both wildtype cases and to healthy controls) and genes regulated by several transcription factors, including E2F1.
RNA-Seq was also performed on CD34+ cells and on differentiated erythroid, granulocytic and monocytic cell populations isolated from the bone marrow of each of 7 SF3B1 mutant MDS cases, 7 wildtype cases and 5 healthy controls, in order to explore similarities/differences between aberrantly spliced genes and deregulated pathways and GO themes in cells of different lineages. There were many aberrantly spliced genes in one cell population that did not overlap with aberrantly spliced genes in other populations. A small proportion (i.e. <5%) of aberrantly spliced genes were common to all four cell populations. GO analysis of the aberrantly spliced genes identified showed that 6 of the top 30 most significant categories (including ‘RNA binding’ and ‘translation’) in the comparison of SF3B1 mutant cases to healthy controls (4 of 30 in the comparison to wildtype cases) were common to all four cell populations studied. Pathway analysis revealed that several pathways were deregulated in specific cell populations (e.g. ‘mTOR signaling’ in erythroid cells), and some pathways (e.g. ‘EIF2 signaling’, involved in protein synthesis initiation) were deregulated in all four cell populations studied.

Conclusion
Our study has identified aberrantly spliced genes and deregulated pathways associated with spliceosome mutations in the HSCs and the major cell lineages affected in MDS, providing new insights into how these mutations impact cellular processes in this disorder.

Session topic: 9. Myelodysplastic syndromes - Biology

Keyword(s): CD34+ cells, Myelodysplasia, Mutation, Expression profiling

Abstract: S122

Type: Oral Presentation

Presentation during EHA22: On Friday, June 23, 2017 from 12:15 - 12:30

Location: Hall E

Background
The myelodysplastic syndromes (MDS) are disorders of the hematopoietic stem cell (HSC) and patients suffer from anemia and other cytopenias and show increasing bone marrow blasts over time. Mutations in spliceosomal genes (including SF3B1, SRSF2 and U2AF1) occur in >50% of MDS patients.

Aims
We aimed to identify the deregulated pathways and gene ontology (GO) categories associated with aberrantly spliced genes in CD34+ cells and in differentiated cells of MDS-affected lineages isolated from the bone marrow of MDS patients harboring spliceosome mutations.

Methods
Transcriptome data were generated using RNA sequencing (RNA-seq) and splicing factor mutant cases were compared to wildtype cases and to healthy controls. Aberrant (including cryptic) splicing events were identified using rMATS. Deregulated pathways and GO themes were identified using Ingenuity Pathway Analysis and GOseq.

Results

RNA-Seq was performed on CD34+ cells obtained from the bone marrow of 91 MDS patients (including 28, 8 and 6 cases with SF3B1, SRSF2 or U2AF1 mutations, respectively) and 8 healthy controls. The aberrant splicing events associated with each mutated splicing factor tended to affect different sets of genes, although some overlap was observed. GO analysis of the aberrantly spliced genes associated with SF3B1, SRSF2 or U2AF1 mutations showed a marked convergence of significantly enriched ontology themes: 26 of the top 30 most significant GO categories, including ‘RNA splicing’ and ‘translation’, in the comparison of mutant cases for each splicing factor gene to healthy controls (18 of 30 in the comparison to wildtype cases) were common to all three mutated splicing factor genes. Pathway analysis revealed deregulated pathways (e.g. ‘oxidative phosphorylation’ and ‘mitochondrial dysfunction’) that were common to more than one mutated gene (i.e. SF3B1 and SRSF2), and pathways specific for one mutated splicing factor gene (e.g. ‘protein ubiquitination’ in SF3B1 mutant cases). An analysis of upstream transcriptional regulators showed a significant overlap between the aberrantly spliced genes associated with each mutant splicing factor gene (in the comparison to both wildtype cases and to healthy controls) and genes regulated by several transcription factors, including E2F1.
RNA-Seq was also performed on CD34+ cells and on differentiated erythroid, granulocytic and monocytic cell populations isolated from the bone marrow of each of 7 SF3B1 mutant MDS cases, 7 wildtype cases and 5 healthy controls, in order to explore similarities/differences between aberrantly spliced genes and deregulated pathways and GO themes in cells of different lineages. There were many aberrantly spliced genes in one cell population that did not overlap with aberrantly spliced genes in other populations. A small proportion (i.e. <5%) of aberrantly spliced genes were common to all four cell populations. GO analysis of the aberrantly spliced genes identified showed that 6 of the top 30 most significant categories (including ‘RNA binding’ and ‘translation’) in the comparison of SF3B1 mutant cases to healthy controls (4 of 30 in the comparison to wildtype cases) were common to all four cell populations studied. Pathway analysis revealed that several pathways were deregulated in specific cell populations (e.g. ‘mTOR signaling’ in erythroid cells), and some pathways (e.g. ‘EIF2 signaling’, involved in protein synthesis initiation) were deregulated in all four cell populations studied.

Conclusion
Our study has identified aberrantly spliced genes and deregulated pathways associated with spliceosome mutations in the HSCs and the major cell lineages affected in MDS, providing new insights into how these mutations impact cellular processes in this disorder.

Session topic: 9. Myelodysplastic syndromes - Biology

Keyword(s): CD34+ cells, Myelodysplasia, Mutation, Expression profiling

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