EXOME SEQUENCING POINTS TO DIFFERENCES IN GENETIC INSTABILITY LEVEL IN MGUS COMPARED TO MM
Author(s): ,
Aneta Mikulasova
Affiliations:
Department of Experimental Biology, Faculty of Science,Masaryk University,Brno,Czech Republic;Department of Pathological Physiology, Faculty of Medicine,Masaryk University,Brno,Czech Republic
,
Brian A. Walker
Affiliations:
Centre for Molecular Pathology,Royal Marsden Hospital,London,United Kingdom
,
Christopher P. Wardell
Affiliations:
Laboratory for Genome Sequencing Analysis,RIKEN Centre for Integrative Medical Sciences,Tokyo,Japan
,
Eileen M. Boyle
Affiliations:
Division of Molecular Pathology,Institute of Cancer Research,London,United Kingdom
,
Marketa Wayhelova
Affiliations:
Department of Experimental Biology, Faculty of Science,Masaryk University,Brno,Czech Republic
,
Jan Smetana
Affiliations:
Department of Experimental Biology, Faculty of Science,Masaryk University,Brno,Czech Republic
,
Ludek Pour
Affiliations:
Department of Internal Medicine, Hematology and Oncology,University Hospital Brno,Brno,Czech Republic
,
Petr Kuglik
Affiliations:
Department of Experimental Biology, Faculty of Science,Masaryk University,Brno,Czech Republic;Department of Pathological Physiology, Faculty of Medicine,Masaryk University,Brno,Czech Republic
,
Roman Hajek
Affiliations:
Department of Haematooncology,University Hospital Ostrava,Ostrava,Czech Republic;Faculty of Medicine,University of Ostrava,Ostrava,Czech Republic
Gareth J. Morgan
Affiliations:
Myeloma Institute for Research and Therapy,University of Arkansas Medical School,Little Rock, Arkansas,United States
EHA Learning Center. Mikulasova A. Jun 13, 2015; 103212
Disclosure(s): Masaryk University
Department of Experimental Biology, Faculty of Science
Aneta Mikulasova
Aneta Mikulasova

Access to EHA Members only content is an EHA membership benefit. Click here to join EHA or renew your membership here.


Abstract
Discussion Forum (0)
Rate & Comment (0)
Abstract: S476

Type: Oral Presentation + travel grant

Presentation during EHA20: From 13.06.2015 15:45 to 13.06.2015 16:00

Location: Room A2+3

Background
Malignant transformation of normal to tumour cells is a multistep process followed by sequential aggregation of hits at different molecular levels. Genetic events including single nucleotide variants (SNVs), insertion-deletion changes (indels) as well as copy number alterations (CNAs) affect the phenotype of the tumour population and consequently patient prognosis. Transformation from a symptomless state, monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM) can be used as a unique model for cancer development studies. To date, there is very little data regarding the mechanisms leading to disease progression at molecular level.

Aims

To perform exome sequencing together with SNP array analysis in MGUS patients to describe the premalignant phenotype and compared these to advanced tumour cells at the DNA level.



Methods
Overall, 33 and 69 MGUS patients were included in a WES and SNP array study, respectively. Plasma cells (PC) were isolated from bone marrow by FACSAria (BD Biosciences) system using CD138, CD19 and CD56 markers to obtain a pure abnormal PC population with a purity >90%. For WES, NEBNext kit and SureSelect Human All Exon V5 (Agilent) were used, samples were sequenced by HiSeq2000 (Illumina). Copy number alterations (CNAs) were tested by SurePrint G3 CGH+SNP, 4x180K (Agilent). Results were compared to 463 and 91 MM patients analysed by WES and SNP arrays, respectively.

Results
CNAs and acquired somatic gene mutations (SNVs) were detected in 68% (47/69) and 100% (33/33) of MGUS patients in comparison to 100% (91/91, p<10-4) and 100% (463/463) of MM patients, respectively. However, the overall number of both CNAs and SNVs per patient was significantly lower in MGUS (CNAs: median 2, range 0-15; SNVs: median 89, range 9-315) than in MM (CNAs: median 16, range 2-49, p<10-18; SNVs median 123, range 1-897, p<10-4). Non-synonymous SNVs (NS-SNVs) were present in 97% (32/33) cases with a median 19 (range 0–70) NS-SNVs per patient. Overall, 42 genes were recurrently mutated in at least 2 patients and 2 non-large protein coding genes were mutated in at least 3 cases including KLHL6 and NPIPL2. We identified 7 genes which were significantly mutated in MM in our previous study including KRAS (n=2), HIST1H1E (n=2) and NRAS, DIS3, EGR1, LTB, PRKD2 (all n=1). IGH translocations were identified in 27% (9/33) of patients: t(11;14) in 12% (4/33), t(4;14) in 9% (3/33), t(14;16) in 3% (1/33) and t(14;20) in 3% (1/33). As previously described in MM, only one type of IGH translocation was found per patient and all 9 cases with IGH translocation did not have additional hyperdiploidy. We did not find any translocations involving MYC (8q24.21) or the light chain loci IGK (2p12) and IGL (22q11.2) and any mutations in TP53, ATM, ATR and ZNFH4 genes involved in DNA repair pathway alterations which were identified as unfavourable factors to MM patients survival.

Summary
We have performed the first comprehensive analysis of MGUS patients using exome sequencing together with SNP arrays and described the main genetic events that are already present in this premalignant state. We proved that complex genetic instability is formed before clinical manifestation first at the gene level then at the chromosome level. Then, a number of random genetic hits increases to form a landscape for significant oncogenic hits driving the transition to a malignant state. This study was supported by grants IGA MHCZ NT13492, OPVK CZ.1.07/2.3.00/20.0183.

Keyword(s): MGUS, Mutation analysis

Session topic: Multiple myeloma - Biology
Code of conduct/disclaimer available in General Terms & Conditions
Anonymous User Privacy Preferences

Strictly Necessary Cookies (Always Active)

MULTILEARNING platforms and tools hereinafter referred as “MLG SOFTWARE” are provided to you as pure educational platforms/services requiring cookies to operate. In the case of the MLG SOFTWARE, cookies are essential for the Platform to function properly for the provision of education. If these cookies are disabled, a large subset of the functionality provided by the Platform will either be unavailable or cease to work as expected. The MLG SOFTWARE do not capture non-essential activities such as menu items and listings you click on or pages viewed.


Performance Cookies

Performance cookies are used to analyse how visitors use a website in order to provide a better user experience.



Google Analytics is used for user behavior tracking/reporting. Google Analytics works in parallel and independently from MLG’s features. Google Analytics relies on cookies and these cookies can be used by Google to track users across different platforms/services.


Save Settings