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3139 Somatic Changes Prior to the Development of Hyperdiploidy Expose Mutation Accumulation Rate and Activated Processes in Multiple Myeloma

Program: Oral and Poster Abstracts
Session: 651. Multiple Myeloma and Plasma Cell Dyscrasias: Basic and Translational: Poster II
Hematology Disease Topics & Pathways:
Research, Translational Research, Plasma Cell Disorders, genomics, bioinformatics, Diseases, Lymphoid Malignancies, computational biology, Biological Processes, Technology and Procedures
Sunday, December 11, 2022, 6:00 PM-8:00 PM

Thomas C. Smits1,2*, Anil Aktas-Samur, PhD3*, Romain Lannes1*, Mariateresa Fulciniti, PhD4, Masood A. Shammas, PhD5*, Jill Corre6*, Giovanni Parmigiani, PhD4*, Herve Avet-Loiseau, MD, PhD7*, Nikhil C Munshi, MD, PhD8 and Mehmet K. Samur, PhD4

1Department of Data Science, Dana Farber Cancer Institute, Boston, MA
2Department of Biomedical Informatics, Harvard Medical School, Boston
3Department of Medical Oncology, Dana Farber Cancer Institute, Boston, MA
4Dana-Farber Cancer Institute, Boston, MA
5Harvard Medical School At VAMC, West Roxbury, MA
6Toulouse, and CRCT, Toulouse, France, Toulouse, France
7Unite de Genomique du Myelome, IUC-Oncopole, Toulouse, France
8Jerome Lipper Multiple Myeloma Center, Dana-Farber Cancer Institute, Boston, MA

Introduction: In multiple myeloma (MM), 55% of newly diagnosed patients show hyperdiploidy (HMM), a copy number gain of the odd-numbered chromosomes, at diagnosis. Although HMM is considered to be a primary event, as it is observed at precursor stages like SMM and MGUS, the processes leading to hyperdiploidy and post-hyperdiploid oncogenic transformation are still unclear.

Methods: For the discovery dataset, we used WGS data from 214 MM patients, of which 102 were HMM, and validated our findings on 814 additional newly diagnosed patients. We calculated the variant allele frequency (VAF) and cancer cell fraction (CCF) for each mutation. We classified mutations on the hyperdiploid chromosomes into pre-hyperdiploid clonal (selecting a VAF of around 67%), post-hyperdiploid clonal (VAF ~ 33%) and subclonal (CCF < 75% & mutation not in pre or post group) after purity correction. On diploid and deleted chromosomes, we classified mutations into clonal and subclonal. We hypothesized that through the analysis of these mutations, we may ascertain the order of processes in HMM and their accumulation rate.

Results: We identified the pre-HMM and post-HMM clonal mutations at an 80% confidence interval. The ratio of mutations post- and pre-HMM was 3.61 (±0.12 SEM) on the discovery set and 3.04 on the validation set. We found that 24% to 28% of all clonal mutations accumulated before the development of hyperdiploidy. The mutational burden in hyperdiploid regions was 1.8 per Mb compared to 2.3 per Mb in diploid regions from the same patient (p-value 2.1e-5). The same comparison for clonal-only mutations showed no statistical significance and a similar accumulation rate pre-HMM. Similarly, non-HMM patients had a significantly higher mutational load on odd-numbered chromosomes than HMM patients (3.6 vs. 1.8 per Mb, p-value 0.02); however, the mutational load was similar between odd-numbered chromosomes and even-numbered chromosomes from the same patient, suggesting that HMM affected mutation accumulation. We next evaluated mutational signatures in pre- and post-HMM mutations using NMF for all three categories. NMF identified seven mutational processes, and we evaluated their stability with permutation testing. We found high cosine similarity between signatures in each iteration (0.92±0.08 SD), indicating the observed signatures are not dependent on individual samples. Pre-HMM mutations had a high enrichment for AID (35.4%), SBS17b (17.6%) and age/Clock-like signatures (31.5% combined). Post-HMM mutations showed a contribution of DNA damage (15.6%) and APOBEC (18.1%). The number of absolute mutations attributed to AID was similar for pre- and post-mutations (78 vs. 82, p-value 0.67), indicating AID was active before hyperdiploidy. The number of mutations and normalized exposure attributed to APOBEC and DNA damage increased for the post-HMM group (p-value 2.2e-16 and 5.4e-11). Moreover, HMM patients with high-risk features showed more post-HMM mutations (865 vs. 570, p-value 0.009). All of our findings were then validated on an independent dataset from newly diagnosed MM patients.

Conclusion: Our study suggests that one quarter of the mutations pre-dates development of hyperdiploidy possibly even before MGUS since the HMM rate is similar between MGUS and newly diagnosed MM. The dominant presence of AID in pre-HMM mutations suggests that hyperdiploidy happens after the somatic hypermutations process and possibly in the germinal center. Moreover, we have previously shown that HMM patients have a lower mutational load than non-HMM patients. Here, we also found a significantly lower mutational burden mainly observed in subclonal mutations, suggesting that, up to HMM development, the mutational rate was similar between all chromosomes; however, the hyperdiploid chromosome accumulation rate decreased after HMM development. These differences may be the result of an activated DNA repair process which requires further studies. Our data also confirmed the activation of APOBEC and DNA damage processes in the post-hyperdiploid stage. Although similar processes were active for all HMM, high-risk features eventually caused increased mutation accumulation post-transformation. Here, we have begun to decipher the chronology of mutational and copy number alteration in MM.

Disclosures: Munshi: Amgen: Consultancy; Oncopep: Consultancy, Current equity holder in publicly-traded company, Other: scientific founder, Patents & Royalties; Karyopharm: Consultancy; Janssen: Consultancy; Bristol-Myers Squibb: Consultancy; Takeda Oncology: Consultancy; GSK: Consultancy; Legend: Consultancy; Celgene: Consultancy; Abbvie: Consultancy; Novartis: Consultancy; Pfizer: Consultancy; Adaptive Biotechnology: Consultancy.

*signifies non-member of ASH