Session: 651. Myeloma: Biology and Pathophysiology, excluding Therapy: Poster III
Hematology Disease Topics & Pathways:
multiple myeloma, Diseases, Plasma Cell Disorders, Lymphoid Malignancies
Methods We analyzed data from whole genome, whole exome, and targeted panel sequencing from 1141 newly diagnosed myeloma patients. Internal samples were selected for whole exome or targeted sequencing based on previous karyotype information, or were identified in the process of other sequencing studies. The CoMMpass dataset was screened for the presence of hyperhaploidy. Hyperhaploid samples without prior karyotype information were identified by conflicting copy number profile and B allele frequency information, where the samples had incorrectly been normalized to a diploid copy number. These samples were re-normalized to a haploid copy number. Copy number, B allele frequency, and mutations of key genes were examined.
Results In the entire dataset 9 hyperhaploid samples were identified, of which 2 came from the CoMMpass dataset. From those with gene expression array data, 5/7 were GEP70 high risk and all belonged to the D1 hyperdiploid gene expression subgroup. Samples had a median of 13 monosomies (range 9-14), which in general were those not associated with trisomies in hyperdiploid samples. The chromosomes traditionally trisomic in hyperdiploid myeloma were disomic in hyperhaploid myeloma. We examined the B allele frequency of these disomic chromosomes and saw that they all retained heterodisomy. Retention of heterodisomy indicates that the method of generating hyperhaploidy is through deletion of the monosomic chromosomes, rather than reverting to a haploid genome followed by duplication of some chromosomes. Retention of heterodisomy was also seen on chromosome 18, which is not normally trisomic in hyperdiploid samples, indicating that heterodisomy of chromosome 18 may be essential for a viable plasma cell clone.
We examined the hyperhaploid samples for frequently mutated genes and found that 8/9 (88.8%) of hyperhaploid samples had a mutation in TP53. This rate of mutation far exceeds the overall rate of mutation in newly diagnosed patients (5.5%), indicating an oncogenic dependency in this group. The sample without mutation of TP53 had only 9 monosomies, fewer than the other samples (12-14 monosomies), indicating there may be a prognostic difference that is dependent on the total chromosome count. All samples with TP53 mutation also had monosomy of chromosome 17, indicating bi-allelic inactivation of TP53. The variant allele frequency of the TP53 mutations was high (median=0.94), indicating that bi-allelic inactivation was a clonal event. No other significant mutations were found, including those that encode chromosome segregation or kinetochore proteins.
Conclusions We have previously described bi-allelic inactivation of TP53 as Double Hit myeloma, and here we identify that hyperhaploid myeloma belongs to this poor prognosis group. The method of generating the hyperhaploid clone is through deletion of chromosomes, which may happen in a way that is similar to gain of chromosomes in hyperdiploid myeloma. These Double Hit patients may be good candidates for new therapies, but using next generation sequencing techniques researchers must be careful when normalizing data to correctly identify them as hyperhaploid rather than hyperdiploid, using copy number and B allele frequency data.
Disclosures: Davies: TRM Oncology: Honoraria; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Consultancy; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; ASH: Honoraria; Janssen: Consultancy, Honoraria; MMRF: Honoraria. Morgan: Takeda: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Janssen: Research Funding; Celgene: Consultancy, Honoraria, Research Funding.
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