Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

Genetic clonal heterogeneity is common in multiple myeloma (MM). However, the specific drivers of subclonal evolution associated with disease progression under therapeutic selection has not been fully characterized with the resource of sequential samples to accurately observe changes in relation to drug exposures. To address this gap, we generated whole-genome sequencing data for 2-4 sequential samples of 50 UK relapsed/refractory MM (rrMM) patients taken before, during and after acquisition of therapy resistance. These patients were exposed to a real-world range of multi-agent therapy combinations between 2011 and 2020 all of which included IMiDs. We undertook high-resolution subclonal heterogeneity analysis using Battenberg and multi-dimensional DPClust as gold-standard methods [Salcedo et al. 2020, PMID: 31919445] and implemented the Plackett-Luce model of partial rankings to time genomic events based on their cancer cell fraction and identify alternative evolutionary trajectories [Ansari-Pour et al. 2021, PMID: 34836952]. This approach enabled the identification and tracking of recurrent genomic aberrations gaining dominance amongst the evolving subclones of the disease in relation to therapeutic exposure and resistance acquisition, and to our knowledge is the first time that has been applied to analyze multi-timepoint myeloma WGS datasets. We observed recurrent selection of subclones harbouring 17p loss of heterozygosity (LOH) or 1pLOH with disease progression and therapy resistance acquisition in tumour phylogenies. In addition, clonal timing analysis of the longitudinal dataset suggested that sequential acquisition of 1pLOH and 1qGain in the same clone was a common selected trajectory (22% of cases). To validate this finding, the same trajectory analysis was undertaken in a much larger IMiD-refractory rrMM WGS as a validation dataset (N=386, Myeloma Genome Project), albeit with single time-point samples and compared with a set of unrelated newly diagnosed WGS dataset (N=198, IFM 2009) [Ansari-Pour et al. 2023, PMID: 36223594]. Strikingly, 1pLOH was found to be the only event that showed evidence for clonal selection in this case-control analysis (timing rank fold-change = 3.7, P<2.2x10 -16). Interestingly, the 1pLOH-1qGain trajectory (27% of cases; co-occurrence OR = 2.3 (95% CI 1.5-3.8), P=2x10 -4) was also identified in the validation dataset, corroborating the potential driverness of the dual chromosome 1 copy number events in subclonal expansion during therapy resistance acquisition. While this WGS-based analysis of selected evolutionary trajectories in relapsed/refractory myeloma patient tumours needs further confirmation with sequential WGS datasets from uniformly treated cohorts, these findings suggest potential collaborative genetic interaction between 1pLOH and 1qGain in the same cell as emerging co-drivers of resistance/disease progression, conferring a greater selective advantage under therapeutic exposure than either event on its own. If confirmed, these biomarkers may define a new ‘double hit’ in relapsed/refractory myeloma, with biological consequences that will require novel and directed therapeutic approaches.

More information Original publication

DOI

10.1182/blood-2023-190584

Type

Journal article

Publisher

American Society of Hematology

Publication Date

2023-11-02T00:00:00+00:00

Volume

142

Pages

1999 - 1999

Total pages

0